diff --git a/.DS_Store b/.DS_Store new file mode 100644 index 0000000000000000000000000000000000000000..8875e4948659e0d1f9f2c3561fe26909563b8b19 Binary files /dev/null and b/.DS_Store differ diff --git a/032_Employee_Attrition/all.parquet b/032_Employee_Attrition/all.parquet deleted file mode 100644 index 8435571a715ad3a3cc8edb56fad09d086120ee08..0000000000000000000000000000000000000000 --- a/032_Employee_Attrition/all.parquet +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:1c7093c5e20f64abadb9478f4861ec535b3c077f135244bb8f7f372c5429f8af -size 102128 diff --git a/032_Employee_Attrition/sample.csv b/032_Employee_Attrition/sample.csv deleted file mode 100644 index 047d2ee8cd98a1094e9c87eecafd0ecb3d3c2d68..0000000000000000000000000000000000000000 --- a/032_Employee_Attrition/sample.csv +++ /dev/null @@ -1,21 +0,0 @@ -Left,Satisfaction Level,Work Accident,Average Monthly Hours,Last Evaluation,Years in the Company,salary,Department,Number of Projects,Promoted in the last 5 years?,Date Hired -No,0.24,No,142,0.89,4,medium,support,5,No,2016-06-04 -No,0.28,No,124,0.51,3,low,technical,3,No,2017-06-06 -No,0.91,No,255,0.67,4,low,accounting,2,No,2016-11-17 -No,0.34,Yes,116,0.81,3,low,sales,4,No,2017-11-19 -No,0.55,No,179,0.5,3,low,technical,4,No,2017-10-25 -No,0.36,No,162,0.93,5,low,support,3,No,2015-02-22 -Yes,0.78,No,256,0.87,5,medium,support,5,No,2015-04-01 -Yes,0.37,No,140,0.51,3,medium,support,2,No,2017-10-04 -No,0.73,No,174,0.63,3,low,accounting,4,No,2017-05-09 -Yes,0.84,No,249,0.85,6,low,marketing,4,No,2014-03-20 -No,0.98,Yes,265,0.61,2,medium,technical,4,No,2018-09-30 -No,0.93,No,137,0.97,4,low,RandD,5,No,2016-08-04 -No,0.57,No,235,0.67,2,low,product_mng,5,No,2018-11-23 -No,0.84,No,125,0.47,4,low,RandD,3,No,2016-01-26 -No,0.22,No,180,0.62,3,low,support,3,No,2017-01-03 -No,0.14,No,162,0.88,4,medium,marketing,3,No,2016-02-04 -No,0.5,No,267,0.77,2,high,management,3,No,2018-05-27 -No,0.69,No,174,0.76,3,low,marketing,5,No,2017-12-21 -No,0.93,No,276,0.48,3,low,IT,3,No,2017-05-08 -No,0.6,No,145,0.97,2,medium,technical,5,No,2018-10-06 diff --git a/README.md b/README.md index 32897cd3e640101ba184f8c4ccd896981de3804a..4e9239137c82a661e4a881cdc904cd333447d483 100644 --- a/README.md +++ b/README.md @@ -1,3 +1,110 @@ +# 💾🏋️💾 DataBench 💾🏋️💾 + +This repository contains the original 65 datasets used for the paper Question Answering over Tabular Data with DataBench: +A Large-Scale Empirical Evaluation of LLMs. + +Large Language Models (LLMs) are showing emerging abilities, and one of the latest recognized ones is tabular +reasoning in question answering on tabular data. Although there are some available datasets to assess question +answering systems on tabular data, they are not large and diverse enough to evaluate this new ability of LLMs. +To this end, we provide a corpus of 65 real world datasets, with 3,269,975 and 1615 columns in total, and 1300 questions to evaluate your models for the task of QA over Tabular Data. +By clicking on each in the table below, you will be able to explore each dataset. + +| | Name | Rows | Cols | Domain | Source (Reference) | +|---:|:-------------------------------|-------:|-------:|:---------------------------|:-----------------------------------------------------------------------------------------------------------------------------------| +| 1 | [Forbes](https://public.graphext.com/0b211530c7e213d3/index.html?section=data) | 2668 | 17 | Business | [Forbes](https://www.forbes.com/billionaires/)| +| 2 | [Titanic](https://public.graphext.com/8577225c5ffd88fd/index.html) | 887 | 8 | Travel and Locations | [Kaggle](https://www.kaggle.com/competitions/titanic/data)| +| 3 | [Love](https://public.graphext.com/be7a566b0c485916/index.html) | 373 | 35 | Social Networks and Surveys | [Graphext](https://public.graphext.com/1de78f6820cfd5ba/index.html) | +| 4 | [Taxi](https://public.graphext.com/bcee13c23070f333/index.html) | 100000 | 20 | Travel and Locations | [Kaggle](https://www.kaggle.com/competitions/nyc-taxi-trip-duration/overview) | +| 5 | [NYC Calls](https://public.graphext.com/1ce2f5fae408621e/index.html) | 100000 | 46 | Business | [City of New York](https://data.cityofnewyork.us/Social-Services/NYC-311-Data/jrb2-thup) | +| 6 | [London Airbnbs](https://public.graphext.com/6bbf4bbd3ff279c0/index.html) | 75241 | 74 | Travel and Locations | [Kaggle](https://www.kaggle.com/datasets/labdmitriy/airbnb) | +| 7 | [Fifa](https://public.graphext.com/37bca51494c10a79/index.html) | 14620 | 59 | Sports and Entertainment | [Kaggle](https://www.kaggle.com/datasets/stefanoleone992/fifa-21-complete-player-dataset) | +| 8 | [Tornados](https://public.graphext.com/4be9872e031199c3/index.html) | 67558 | 14 | Health | [Kaggle](https://www.kaggle.com/datasets/danbraswell/us-tornado-dataset-1950-2021) | +| 9 | [Central Park](https://public.graphext.com/7b3d3a4d7bf1e9b5/index.html) | 56245 | 6 | Travel and Locations | [Kaggle](https://www.kaggle.com/datasets/danbraswell/new-york-city-weather-18692022) | +| 10 | [ECommerce Reviews](https://public.graphext.com/a5b8911b215958ad/index.html) | 23486 | 10 | Business | [Kaggle](https://www.kaggle.com/datasets/nicapotato/womens-ecommerce-clothing-reviews) | +| 11 | [SF Police](https://public.graphext.com/ab815ab14f88115c/index.html) | 713107 | 35 | Social Networks and Surveys | [US Gov](https://catalog.data.gov/dataset/police-department-incident-reports-2018-to-present) | +| 12 | [Heart Failure](https://public.graphext.com/245cec64075f5542/index.html) | 918 | 12 | Health | [Kaggle](https://www.kaggle.com/datasets/fedesoriano/heart-failure-prediction) | +| 13 | [Roller Coasters](https://public.graphext.com/1e550e6c24fc1930/index.html) | 1087 | 56 | Sports and Entertainment | [Kaggle](https://www.kaggle.com/datasets/robikscube/rollercoaster-database) | +| 14 | [Madrid Airbnbs](https://public.graphext.com/77265ea3a63e650f/index.html) | 20776 | 75 | Travel and Locations | [Inside Airbnb](http://data.insideairbnb.com/spain/comunidad-de-madrid/madrid/2023-09-07/data/listings.csv.gz) | +| 15 | [Food Names](https://public.graphext.com/5aad4c5d6ef140b3/index.html) | 906 | 4 | Business | [Data World](https://data.world/alexandra/generic-food-database) | +| 16 | [Holiday Package Sales](https://public.graphext.com/fbc34d3f24282e46/index.html) | 4888 | 20 | Travel and Locations | [Kaggle](https://www.kaggle.com/datasets/susant4learning/holiday-package-purchase-prediction) | +| 17 | [Hacker News](https://public.graphext.com/f20501a9d616b5a5/index.html) | 9429 | 20 | Social Networks and Surveys | [Kaggle](https://www.kaggle.com/datasets/hacker-news/hacker-news) | +| 18 | [Staff Satisfaction](https://public.graphext.com/6822ac1ce6307fec/index.html) | 14999 | 11 | Business | [Kaggle](https://www.kaggle.com/datasets/mohamedharris/employee-satisfaction-index-dataset) | +| 19 | [Aircraft Accidents](https://public.graphext.com/1802117b1b14f5c5/index.html) | 23519 | 23 | Health | [Kaggle](https://www.kaggle.com/datasets/ramjasmaurya/aviation-accidents-history1919-april-2022) | +| 20 | [Real Estate Madrid](https://public.graphext.com/5f83ec219a7ea84f/index.html) | 26026 | 59 | Business | [Idealista](https://public.graphext.com/5f83ec219a7ea84f/index.html) | +| 21 | [Telco Customer Churn](https://public.graphext.com/362cd8e3e96f70d4/index.html) | 7043 | 21 | Business | [Kaggle](https://www.kaggle.com/datasets/blastchar/telco-customer-churn) | +| 22 | [Airbnbs Listings NY](https://public.graphext.com/77265ea3a63e650f/index.html) | 37012 | 33 | Travel and Locations | [Kaggle](https://www.kaggle.com/datasets/dgomonov/new-york-city-airbnb-open-data) | +| 23 | [Climate in Madrid](https://public.graphext.com/83a75b4f1cea8df4/index.html?section=data) | 36858 | 26 | Travel and Locations | [AEMET](https://public.graphext.com/83a75b4f1cea8df4/index.html?section=data) | +| 24 | [Salary Survey Spain 2018](https://public.graphext.com/24d1e717ba01aa3d/index.html) | 216726 | 29 | Business | [INE](ine.es) | +| 25 | [Data Driven SEO ](https://public.graphext.com/4e5b1cac9ebdfa44/index.html) | 62 | 5 | Business | [Graphext](https://www.graphext.com/post/data-driven-seo-a-keyword-optimization-guide-using-web-scraping-co-occurrence-analysis-graphext-deepnote-adwords) | +| 26 | [Predicting Wine Quality](https://public.graphext.com/de04acf5d18a9aea/index.html) | 1599 | 12 | Business | [Kaggle](https://www.kaggle.com/datasets/yasserh/wine-quality-dataset) | +| 27 | [Supermarket Sales](https://public.graphext.com/9a6742da6a8d8f7f/index.html) | 1000 | 17 | Business | [Kaggle](https://www.kaggle.com/datasets/aungpyaeap/supermarket-sales) | +| 28 | [Predict Diabetes](https://public.graphext.com/def4bada27af324c/index.html) | 768 | 9 | Health | [Kaggle](https://www.kaggle.com/datasets/iammustafatz/diabetes-prediction-dataset) | +| 29 | [NYTimes World In 2021](https://public.graphext.com/af4c8eef1757973c/index.html?section=data) | 52588 | 5 | Travel and Locations | [New York Times](https://public.graphext.com/af4c8eef1757973c/index.html) | +| 30 | [Professionals Kaggle Survey](https://public.graphext.com/3a2e87f90363a85d/index.html) | 19169 | 64 | Business | [Kaggle](https://www.kaggle.com/c/kaggle-survey-2021/data) | +| 31 | [Trustpilot Reviews](https://public.graphext.com/367e29432331fbfd/index.html?section=data) | 8020 | 6 | Business | [TrustPilot](https://public.graphext.com/367e29432331fbfd/index.html?section=data) | +| 32 | [Delicatessen Customers](https://public.graphext.com/a1687589fbde07bc/index.html) | 2240 | 29 | Business | [Kaggle](https://www.kaggle.com/datasets/rodsaldanha/arketing-campaign) | +| 33 | [Employee Attrition](https://public.graphext.com/07a91a15ecf2b8f6/index.html) | 14999 | 11 | Business | [Kaggle(modified)](https://www.kaggle.com/datasets/pavan9065/predicting-employee-attrition) | +| 34 | [World Happiness Report 2020](https://public.graphext.com/754c83ff0a7ba087/index.html) | 153 | 20 | Social Networks and Surveys | [World Happiness](https://worldhappiness.report/data/) | +| 35 | [Billboard Lyrics](https://public.graphext.com/7e0b009e8d0af719/index.html) | 5100 | 6 | Sports and Entertainment | [Brown University](https://cs.brown.edu/courses/cs100/students/project11/) | +| 36 | [US Migrations 2012-2016](https://public.graphext.com/dbdadf87a5c21695/index.html) | 288300 | 9 | Social Networks and Surveys | [US Census](https://www.census.gov/topics/population/migration/guidance/county-to-county-migration-flows.html) | +| 37 | [Ted Talks](https://public.graphext.com/07e48466fb670904/index.html) | 4005 | 19 | Social Networks and Surveys | [Kaggle](https://www.kaggle.com/datasets/ashishjangra27/ted-talks) | +| 38 | [Stroke Likelihood](https://public.graphext.com/20ccfee9e84948e3/index.html) | 5110 | 12 | Health | [Kaggle](https://www.kaggle.com/datasets/kamilpytlak/personal-key-indicators-of-heart-disease) | +| 39 | [Happy Moments](https://public.graphext.com/9b86efff48989701/index.html) | 100535 | 11 | Social Networks and Surveys | [Kaggle](https://www.kaggle.com/datasets/ritresearch/happydb) | +| 40 | [Speed Dating](https://public.graphext.com/f1912daad7870be0/index.html) | 8378 | 123 | Social Networks and Surveys | [Kaggle](https://www.kaggle.com/datasets/ulrikthygepedersen/speed-dating) | +| 41 | [Airline Mentions X (former Twitter)](https://public.graphext.com/29cb7f73f6e17a38/index.html) | 14640 | 15 | Social Networks and Surveys | [X (former Twitter)](https://public.graphext.com/7e6999327d1f83fd/index.html) | +| 42 | [Predict Student Performance](https://public.graphext.com/def4bada27af324c/index.html) | 395 | 33 | Business | [Kaggle](https://www.kaggle.com/datasets/impapan/student-performance-data-set) | +| 43 | [Loan Defaults](https://public.graphext.com/0c7fb68ab8071a1f/index.html) | 83656 | 20 | Business | [SBA](https://www.kaggle.com/datasets/mirbektoktogaraev/should-this-loan-be-approved-or-denied) | +| 44 | [IMDb Movies](https://public.graphext.com/e23e33774872c496/index.html) | 85855 | 22 | Sports and Entertainment | [Kaggle](https://www.kaggle.com/datasets/harshitshankhdhar/imdb-dataset-of-top-1000-movies-and-tv-shows) | +| 45 | [Spotify Song Popularity](https://public.graphext.com/def4bada27af324c/index.html) | 21000 | 19 | Sports and Entertainment | [Spotify](https://www.kaggle.com/datasets/tomigelo/spotify-audio-features) | +| 46 | [120 Years Olympics](https://public.graphext.com/e57d5e2f172c9a99/index.html) | 271116 | 15 | Sports and Entertainment | [Kaggle](https://www.kaggle.com/datasets/heesoo37/120-years-of-olympic-history-athletes-and-results) | +| 47 | [Bank Customer Churn](https://public.graphext.com/e8f7aeacd209f74a/index.html) | 7088 | 15 | Business | [Kaggle](https://www.kaggle.com/datasets/mathchi/churn-for-bank-customers) | +| 48 | [Data Science Salary Data](https://public.graphext.com/4e5b1cac9ebdfa44/index.html) | 742 | 28 | Business | [Kaggle](https://www.kaggle.com/datasets/ruchi798/data-science-job-salaries) | +| 49 | [Boris Johnson UK PM Tweets](https://public.graphext.com/f6623a1ca0f41c8e/index.html) | 3220 | 34 | Social Networks and Surveys | [X (former Twitter)](https://public.graphext.com/f6623a1ca0f41c8e/index.html) | +| 50 | [ING 2019 X Mentions](https://public.graphext.com/075030310aa702c6/index.html) | 7244 | 22 | Social Networks and Surveys | [X (former Twitter)](https://public.graphext.com/075030310aa702c6/index.html) | +| 51 | [Pokemon Features](https://public.graphext.com/f30d4d863a2e6b01/index.html) | 1072 | 13 | Business | [Kaggle](https://www.kaggle.com/datasets/rounakbanik/pokemon) | +| 52 | [Professional Map](https://public.graphext.com/70af2240cb751968/index.html) | 1227 | 12 | Business | [Kern et al, PNAS'20](https://github.com/behavioral-ds/VocationMap) | +| 53 | [Google Patents](https://public.graphext.com/a262300e31874716/index.html) | 9999 | 20 | Business | [BigQuery](https://www.kaggle.com/datasets/bigquery/patents/data) | +| 54 | [Joe Biden Tweets](https://public.graphext.com/33fa2efa41541ab1/index.html) | 491 | 34 | Social Networks and Surveys | [X (former Twitter)](https://public.graphext.com/339cee259f0a9b32/index.html?section=data) | +55 | [German Loans](https://public.graphext.com/d3f5e425e9d4b0a1/index.html) | 1000 | 18 | Business | [Kaggle](https://www.kaggle.com/datasets/uciml/german-credit/data) | +| 56 | [Emoji Diet](https://public.graphext.com/e721cc7d790c06d4/index.html) | 58 | 35 | Health | [Kaggle](https://www.kaggle.com/datasets/ofrancisco/emoji-diet-nutritional-data-sr28) | +| 57 | [Spain Survey 2015](https://public.graphext.com/90ca7539b160fdfa/index.html?section=data) | 20000 | 45 | Social Networks and Surveys | [CIS](https://public.graphext.com/90ca7539b160fdfa/index.html?section=data) | +| 58 | [US Polls 2020](https://public.graphext.com/dbdadf87a5c21695/index.html) | 3523 | 52 | Social Networks and Surveys | [Brandwatch](https://www.brandwatch.com/p/us-election-raw-polling-data/) | +| 59 | [Second Hand Cars](https://public.graphext.com/543d0c49d7120ca0/index.html) | 50000 | 21 | Business | [DataMarket](https://www.kaggle.com/datasets/datamarket/venta-de-coches) | +| 60 | [Bakery Purchases](https://public.graphext.com/6f2102e80f47a192/index.html) | 20507 | 5 | Business | [Kaggle](https://www.kaggle.com/code/xvivancos/market-basket-analysis/report) | +| 61 | [Disneyland Customer Reviews](https://public.graphext.com/b1037bb566b7b316/index.html) | 42656 | 6 | Travel and Locations | [Kaggle](https://www.kaggle.com/datasets/arushchillar/disneyland-reviews) | +| 62 | [Trump Tweets](https://public.graphext.com/7aff94c3b7f159fc/index.html) | 15039 | 20 | Social Networks and Surveys | [X (former Twitter)](https://public.graphext.com/be903c098a90e46f/index.html?section=data) | +| 63 | [Influencers](https://public.graphext.com/e097f1ea03d761a9/index.html) | 1039 | 14 | Social Networks and Surveys | [X (former Twitter)](https://public.graphext.com/e097f1ea03d761a9/index.html) | +| 64 | [Clustering Zoo Animals](https://public.graphext.com/d1b66902e46a712a/index.html) | 101 | 18 | Health | [Kaggle](https://www.kaggle.com/datasets/jirkadaberger/zoo-animals) | +| 65 | [RFM Analysis](https://public.graphext.com/4db2e54e29006a21/index.html) | 541909 | 8 | Business | [UCI ML](https://www.kaggle.com/datasets/carrie1/ecommerce-data) | + +## Folder structure +Each folder represents one dataset. You will find the following files within: + +* all.parquet: the processed data, with each column tagged with our typing system, in [parquet](https://arrow.apache.org/docs/python/parquet.html). +* qa.csv: contains the human-made set of questions, tagged by type and columns used, for the dataset. +* sample.csv: sample containing 20 rows of the original dataset +* info.yml: additional information about the dataset + +## Column typing system +In an effort to map the stage for later analysis, we have categorized the columns by type. This information allows us to segment different kinds of data so that we can subsequently analyze the model's behavior on each column type separately. All parquet files have been casted to their smallest viable data type using the open source [Lector](https://github.com/graphext/lector) reader. + +What this means is that in the data types we have more granular information that allows us to know if the column contains NaNs or not (following panda’s convention of Int vs int), as well as whether small numerical values contain negatives (Uint vs int) and their range. We also have dates with potential timezone information (although for now they’re all UTC), as well as information about categories’ cardinality coming from the arrow types. + +In the table below you can see all the data types assigned to each column, as well as the number of columns for each type. The most common data types are numbers and categories with 1336 columns of the total of 1615 included in DataBench. These are followed by some other more rare types as urls, booleans, dates or lists of elements. + +| Type | Columns | Example | +| -------------- | ------- | ----------------------- | +| number | 788 | 55 | +| category | 548 | apple | +| date | 50 | 1970-01-01 | +| text | 46 | A red fox ran... | +| url | 31 | google.com | +| boolean | 18 | True | +| list[number] | 14 | [1,2,3] | +| list[category] | 112 | [apple, orange, banana] | +| list[url] | 8 | [google.com, apple.com] | + + --- license: mit --- diff --git a/000_Forbes/all.parquet b/data/001_Forbes/all.parquet similarity index 100% rename from 000_Forbes/all.parquet rename to data/001_Forbes/all.parquet diff --git a/000_Forbes/info.yml b/data/001_Forbes/info.yml similarity index 100% rename from 000_Forbes/info.yml rename to data/001_Forbes/info.yml diff --git a/data/001_Forbes/qa.csv b/data/001_Forbes/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..ceaddd6c0ee9ee6b3581bcc771230c8596b72952 --- /dev/null +++ b/data/001_Forbes/qa.csv @@ -0,0 +1,26 @@ +question,answer,type,columns_used,column_types,sample_answer +Is the person with the highest net worth self-made?,True,boolean,"['finalWorth', 'selfMade']","['number[uint32]', 'boolean']",False +Does the youngest billionaire identify as male?,True,boolean,"['age', 'gender']","['number[UInt8]', 'category']",True +Is the city with the most billionaires in the United States?,True,boolean,"['city', 'country']","['category', 'category']",True +Is there a non-self-made billionaire in the top 5 ranks?,True,boolean,"['rank', 'selfMade']","['number[uint16]', 'boolean']",False +Does the oldest billionaire have a philanthropy score of 5?,False,boolean,"['age', 'philanthropyScore']","['number[UInt8]', 'number[UInt8]']",False +What is the age of the youngest billionaire?,19.0,number,['age'],['number[UInt8]'],32.0 +How many billionaires are there from the 'Technology' category?,343,number,['category'],['category'],0 +What's the total worth of billionaires in the 'Automotive' category?,583600,number,"['category', 'finalWorth']","['category', 'number[uint32]']",0 +How many billionaires have a philanthropy score above 3?,25,number,['philanthropyScore'],['number[UInt8]'],0 +What's the rank of the wealthiest non-self-made billionaire?,3,number,"['selfMade', 'rank']","['boolean', 'number[uint16]']",288 +Which category does the richest billionaire belong to?,Automotive,category,"['finalWorth', 'category']","['number[uint32]', 'category']",Food & Beverage +What's the country of origin of the oldest billionaire?,United States,category,"['age', 'country']","['number[UInt8]', 'category']",United Kingdom +What's the gender of the billionaire with the highest philanthropy score?,M,category,"['philanthropyScore', 'gender']","['number[UInt8]', 'category']",M +What's the source of wealth for the youngest billionaire?,drugstores,category,"['age', 'source']","['number[UInt8]', 'category']",fintech +What is the title of the billionaire with the lowest rank?,,category,"['rank', 'title']","['number[uint16]', 'category']", +List the top 3 countries with the most billionaires.,"['United States', 'China', 'India']",list[category],['country'],['category'],"['United States', 'China', 'Brazil']" +List the top 5 sources of wealth for billionaires.,"['real estate', 'investments', 'pharmaceuticals', 'diversified', 'software']",list[category],['source'],['category'],"['diversified', 'media, automotive', 'Semiconductor materials', 'WeWork', 'beverages']" +List the top 4 cities where the youngest billionaires live.,"[nan, 'Los Angeles', 'Jiaozuo', 'Oslo']",list[category],"['age', 'city']","['number[UInt8]', 'category']","['San Francisco', 'New York', 'Wuhan', 'Bangalore']" +List the bottom 3 categories with the fewest billionaires.,"['Logistics', 'Sports', 'Gambling & Casinos']",list[category],['category'],['category'],"['Service', 'Fashion & Retail', 'Manufacturing']" +List the bottom 2 countries with the least number of billionaires.,"['Colombia', 'Andorra']",list[category],['country'],['category'],"['Canada', 'Egypt']" +List the top 5 ranks of billionaires who are not self-made.,"[3, 10, 14, 16, 18]",list[number],"['selfMade', 'rank']","['boolean', 'number[uint16]']","[288, 296, 509, 523, 601]" +List the bottom 3 ages of billionaires who have a philanthropy score of 5.,"[48.0, 83.0, 83.0]",list[number],"['philanthropyScore', 'age']","['number[UInt8]', 'number[UInt8]']",[] +List the top 6 final worth values of billionaires in the 'Technology' category.,"[171000, 129000, 111000, 107000, 106000, 91400]",list[number],"['category', 'finalWorth']","['category', 'number[uint32]']",[] +List the bottom 4 ranks of female billionaires.,"[14, 18, 21, 30]",list[number],"['gender', 'rank']","['category', 'number[uint16]']",[] +List the top 2 final worth values of billionaires in the 'Automotive' category.,"[219000, 44800]",list[number],"['category', 'finalWorth']","['category', 'number[uint32]']",[] diff --git a/000_Forbes/sample.csv b/data/001_Forbes/sample.csv similarity index 100% rename from 000_Forbes/sample.csv rename to data/001_Forbes/sample.csv diff --git a/001_Titanic/all.parquet b/data/002_Titanic/all.parquet similarity index 100% rename from 001_Titanic/all.parquet rename to data/002_Titanic/all.parquet diff --git a/001_Titanic/info.yml b/data/002_Titanic/info.yml similarity index 100% rename from 001_Titanic/info.yml rename to data/002_Titanic/info.yml diff --git a/data/002_Titanic/qa.csv b/data/002_Titanic/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..99895f00e75cbc2a7ade6fe59c80ec113686d0b0 --- /dev/null +++ b/data/002_Titanic/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Did any children below the age of 18 survive?,True,boolean,"[Age, Survived]","['number[UInt8]', 'boolean']",True +Were there any passengers who paid a fare of more than $500?,True,boolean,[Fare],['number[double]'],False +Is every passenger's name unique?,True,boolean,[Name],['text'],True +Were there any female passengers in the 3rd class who survived?,True,boolean,"[Sex, Pclass, Survived]","['category', 'number[uint8]', 'boolean']",True +How many unique passenger classes are present in the dataset?,3,number,[Pclass],['number[uint8]'],3 +What's the maximum age of the passengers?,80.0,number,[Age],['number[UInt8]'],69.0 +How many passengers boarded without any siblings or spouses?,604,number,[Siblings_Spouses Aboard],['number[uint8]'],12 +"On average, how much fare did the passengers pay?",32.31,number,[Fare],['number[double]'],23.096459999999997 +Which passenger class has the highest number of survivors?,1,category,"[Pclass, Survived]","['number[uint8]', 'boolean']",3 +What's the most common gender among the survivors?,female,category,"[Sex, Survived]","['category', 'boolean']",female +"Among those who survived, which fare range was the most common: (0-50, 50-100, 100-150, 150+)?",0-50,category,"[Fare, Survived]","['number[double]', 'boolean']",0-50 +"What's the most common age range among passengers: (0-18, 18-30, 30-50, 50+)?",18-30,category,[Age],['number[UInt8]'],18-30 +Name the top 3 passenger classes by survival rate.,"[1, 2, 3]",list[category],"[Pclass, Survived]","['number[uint8]', 'boolean']","[1, 3, 2]" +"Could you list the bottom 3 fare ranges by number of survivors: (0-50, 50-100, 100-150, 150+)?","['50-100', '150+', '100-150']",list[category],"[Fare, Survived]","['number[double]', 'boolean']","[50-100, 150+, 100-150]" +"What is the top 4 age ranges('30-50', '18-30', '0-18', '50+') with the highest number of survivors?","['30-50', '18-30', '0-18', '50+']",list[category],"[Age, Survived]","['number[UInt8]', 'boolean']","[30-50, 18-30, 0-18, 50+]" +What are the top 2 genders by average fare paid?,"['female', 'male']",list[category],"[Sex, Fare]","['category', 'number[double]']","[female, male]" +What are the oldest 3 ages among the survivors?,"[24.0, 22.0, 27.0]",list[number],"[Age, Survived]","['number[UInt8]', 'boolean']","[56.0, 47.0, 42.0]" +Which are the top 4 fares paid by survivors?,"[13.0, 26.0, 7.75, 10.5]",list[number],"[Fare, Survived]","['number[double]', 'boolean']","[133.65, 39.0, 35.5, 30.5]" +Could you list the youngest 3 ages among the survivors?,"[53.0, 55.0, 11.0]",list[number],"[Age, Survived]","['number[UInt8]', 'boolean']","[14.0, 24.0, 28.0]" +Which are the bottom 4 fares among those who didn't survive?,"[90.0, 12.275, 9.35, 10.5167]",list[number],"[Fare, Survived]","['number[double]', 'boolean']","[13.0, 7.75, 11.5, 10.1708]" diff --git a/001_Titanic/sample.csv b/data/002_Titanic/sample.csv similarity index 100% rename from 001_Titanic/sample.csv rename to data/002_Titanic/sample.csv diff --git a/002_Love/all.parquet b/data/003_Love/all.parquet similarity index 100% rename from 002_Love/all.parquet rename to data/003_Love/all.parquet diff --git a/002_Love/info.yml b/data/003_Love/info.yml similarity index 100% rename from 002_Love/info.yml rename to data/003_Love/info.yml diff --git a/data/003_Love/qa.csv b/data/003_Love/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..df6fc1ebee24d2f24de89a58067d89e673f4a425 --- /dev/null +++ b/data/003_Love/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Is the average age of the respondents above 30?,True,boolean,['What is your age? 👶🏻👵🏻'],['number[uint8]'],True +Are there more single individuals than married ones in the dataset?,True,boolean,['What is your civil status? 💍'],['category'],False +Do the majority of respondents have a height greater than 170 cm?,True,boolean,[What's your height? in cm 📏],['number[uint8]'],True +Is the most frequent hair color black?,False,boolean,['What is your hair color? 👩🦰👱🏽'],['category'],False +How many unique nationalities are present in the dataset?,13,number,"[What's your nationality?""]""",['category'],1 +What is the average gross annual salary?,56332.81720430108,number,['Gross annual salary (in euros) 💸'],['number[UInt32]'],62710.0 +How many respondents wear glasses all the time?,0,number,['How often do you wear glasses? 👓'],['category'],0 +What's the median age of the respondents?,33.0,number,['What is your age? 👶🏻👵🏻'],['number[uint8]'],32.5 +What is the most common level of studies achieved?,Master,category,['What is the maximum level of studies you have achieved? 🎓'],['category'],Master +Which body complexity has the least number of respondents?,Very thin,category,['What is your body complexity? 🏋️'],['category'],Obese +What's the most frequent eye color?,Brown,category,['What is your eye color? 👁️'],['category'],Brown +Which sexual orientation has the highest representation?,Heterosexual,category,"[What's your sexual orientation?""]""",['category'],Heterosexual +List the top 3 most common areas of knowledge.,"['[Computer Science]', '[Business]', '[Enginering & Architecture]']",list[category],['What area of knowledge is closer to you?'],['list[category]'],"['[Computer Science]', '[Business]', '[Enginering & Architecture]']" +List the bottom 3 hair lengths in terms of frequency.,"['Medium', 'Long', 'Bald']",list[category],['How long is your hair? 💇🏻♀️💇🏽♂️'],['category'],"['Short', 'Medium', 'Long']" +Name the top 5 civil statuses represented in the dataset.,"['Single', 'Married', 'In a Relationship', 'In a Relationship Cohabiting', 'Divorced']",list[category],['What is your civil status? 💍'],['category'],"['Married', 'In a Relationship', 'In a Relationship Cohabiting', 'Single', 'Divorced']" +What are the 4 least common hair colors?,"['Red', 'Other', 'White', 'Blue']",list[category],['What is your hair color? 👩🦰👱🏽'],['category'],"['Brown', 'Black']" +What are the top 4 maximum gross annual salaries?,"[500000.0, 360000.0, 300000.0, 300000.0]",list[number],['Gross annual salary (in euros) 💸'],['number[UInt32]'],"[150000.0, 130000.0, 125000.0, 120000.0]" +Name the bottom 3 values for the happiness scale.,"[2, 2, 2]",list[number],['Happiness scale'],['number[uint8]'],"[7, 10, 6]" +What are the 5 highest ages present in the dataset?,"[65, 62, 60, 60, 59]",list[number],['What is your age? 👶🏻👵🏻'],['number[uint8]'],"[65, 60, 51, 50, 50]" +List the bottom 6 skin tone values based on frequency.,"[2, 1, 6, 0, 7, 8]",list[number],['What is your skin tone?'],['number[uint8]'],"[3, 1, 6, 2, 7, 0]" diff --git a/002_Love/sample.csv b/data/003_Love/sample.csv similarity index 100% rename from 002_Love/sample.csv rename to data/003_Love/sample.csv diff --git a/003_Taxi/all.parquet b/data/004_Taxi/all.parquet similarity index 100% rename from 003_Taxi/all.parquet rename to data/004_Taxi/all.parquet diff --git a/003_Taxi/info.yml b/data/004_Taxi/info.yml similarity index 100% rename from 003_Taxi/info.yml rename to data/004_Taxi/info.yml diff --git a/data/004_Taxi/qa.csv b/data/004_Taxi/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..9088c21ae16753785feaf6b3cc5546097880131c --- /dev/null +++ b/data/004_Taxi/qa.csv @@ -0,0 +1,32 @@ +question,answer,type,columns_used,column_types,sample_answer +Are there any trips with a total distance greater than 30 miles?,False,boolean,['trip_distance'],['number[double]'],False +Were there any trips that cost more than $100 in total?,False,boolean,['total_amount'],['number[double]'],False +Is there any trip with more than 6 passengers?,False,boolean,['passenger_count'],['number[uint8]'],False +Did all the trips use a payment type of either 1 or 2?,False,boolean,['payment_type'],['number[uint8]'],True +What is the maximum fare amount charged for a trip?,75.25,number,['fare_amount'],['number[double]'],85.0 +How many unique pickup locations are in the dataset?,96,number,['PULocationID'],['number[uint16]'],193 +What is the average tip amount given by passengers?,2.74,number,['tip_amount'],['number[double]'],1.5 +How many trips took place in the airport area?,99807,number,['Airport_fee'],['number[UInt8]'],194 +Which payment type is the most common in the dataset?,1,category,['payment_type'],['number[uint8]'],1 +Which vendor has the most trips recorded?,2,category,['VendorID'],['number[uint8]'],2 +What is the most common drop-off location?,236,category,['DOLocationID'],['number[uint16]'],161 +On which date did the first recorded trip occur?,2023-01-31,category,['tpep_pickup_datetime'],"['date[ns, UTC]']",2019-01-01 00:46:40 +Which are the top 3 most frequent pickup locations?,"[161, 237, 236]",list[category],['PULocationID'],['number[uint16]'],"[237, 236, 161]" +Name the 4 most common rate codes used.,"[1, 2, 5, 4]",list[category],['RatecodeID'],['number[uint8]'],"[1, 2, 5, 3]" +list the 2 most frequent store and forward flags.,"['N', 'Y']",list[category],['store_and_fwd_flag'],['category'],"['N', 'Y']" +Identify the top 4 payment types used by frequency,"[1, 2, 4, 3]",list[category],['payment_type'],['number[uint8]'],"[1, 2, 3]" +Report the 4 highest toll amounts paid.,"[0, 0, 0, 0]",list[number],['tolls_amount'],['number[uint8]'],"[0, 0, 0, 0]" +list the top 3 longest trip distances,"[19.83, 19.74, 19.68]",list[number],['trip_distance'],['number[double]'],"[8.32, +5.93, +2.8]" +Identify the 5 largest total amounts paid for trips.,"[80.0, 80.0, 80.0, 80.0, 79.55]",list[number],['total_amount'],['number[double]'],"[45.8, +39.9, +33.2, +25.2, +24.87]" +Report the 6 highest fare amounts charged.,"[75.25, 74.4, 73.0, 73.0, 73.0, 73.0]",list[number],['fare_amount'],['number[double]'],"[40.8, +28.9, +21.2, +17.0, +14.9, +13.5]" diff --git a/003_Taxi/sample.csv b/data/004_Taxi/sample.csv similarity index 100% rename from 003_Taxi/sample.csv rename to data/004_Taxi/sample.csv index b05bc8830c6e07f2ab48117a4158ee24de54a417..d67af56f82655b5249d7b86b007b706f30d3835a 100644 --- a/003_Taxi/sample.csv +++ b/data/004_Taxi/sample.csv @@ -1,21 +1,21 @@ store_and_fwd_flag,payment_type,tpep_pickup_datetime,fare_amount,VendorID,DOLocationID,tolls_amount,tip_amount,PULocationID,Airport_fee,trip_distance,RatecodeID,total_amount,passenger_count -N,1,2023-02-01T20:33:05Z,10.7,2,90,0,4.71,246,0.0,1.59,1,20.41,2 -N,1,2023-02-01T21:17:13Z,6.5,1,50,0,1.75,143,0.0,0.8,1,13.25,2 -N,1,2023-02-01T10:17:39Z,17.0,2,170,0,4.2,43,0.0,2.44,1,25.2,2 +Y,1,2023-02-01T16:42:37Z,12.8,1,48,0,3.85,100,0.0,0.9,1,23.15,1 +N,1,2023-02-01T02:59:27Z,5.8,2,141,0,1.51,263,0.0,0.79,1,12.31,1 N,2,2023-02-01T20:33:36Z,40.8,2,238,0,0.0,13,0.0,8.32,1,45.8,2 +N,1,2023-02-01T20:33:05Z,10.7,2,90,0,4.71,246,0.0,1.59,1,20.41,2 +N,1,2023-02-01T21:33:10Z,14.9,2,90,0,4.97,231,0.0,2.64,1,24.87,1 +N,1,2023-02-01T10:34:53Z,7.9,1,75,0,2.95,237,0.0,1.3,1,14.85,1 +N,1,2023-02-01T10:29:39Z,12.8,2,234,0,3.36,161,0.0,1.74,1,20.16,4 N,1,2023-02-02T01:48:49Z,12.8,2,163,0,3.56,68,0.0,2.29,1,21.36,1 -N,1,2023-02-01T20:20:43Z,9.3,1,170,0,2.15,113,0.0,1.1,1,16.45,1 +N,1,2023-02-01T10:17:39Z,17.0,2,170,0,4.2,43,0.0,2.44,1,25.2,2 N,1,2023-02-01T22:29:07Z,8.6,2,90,0,2.72,230,0.0,1.37,1,16.32,2 -N,1,2023-02-01T21:33:10Z,14.9,2,90,0,4.97,231,0.0,2.64,1,24.87,1 +N,2,2023-02-01T18:40:29Z,10.7,2,236,0,0.0,163,0.0,1.35,1,17.2,1 N,1,2023-02-01T18:47:54Z,21.2,1,137,0,5.5,142,0.0,2.8,1,33.2,1 -Y,1,2023-02-01T16:42:37Z,12.8,1,48,0,3.85,100,0.0,0.9,1,23.15,1 +N,1,2023-02-01T00:00:34Z,28.9,2,181,0,6.0,234,0.0,5.93,1,39.9,1 +N,1,2023-02-01T23:21:43Z,11.4,2,13,0,1.64,125,0.0,1.86,1,18.04,2 N,3,2023-02-01T12:42:04Z,8.6,1,162,0,0.0,161,0.0,0.6,1,12.6,1 N,1,2023-02-01T15:46:37Z,13.5,1,144,0,3.5,170,0.0,2.0,1,21.0,1 -N,1,2023-02-01T15:53:16Z,7.2,1,230,0,2.2,186,0.0,0.6,1,13.4,2 -N,1,2023-02-01T10:34:53Z,7.9,1,75,0,2.95,237,0.0,1.3,1,14.85,1 -N,1,2023-02-01T10:29:39Z,12.8,2,234,0,3.36,161,0.0,1.74,1,20.16,4 -N,1,2023-02-01T23:21:43Z,11.4,2,13,0,1.64,125,0.0,1.86,1,18.04,2 -N,1,2023-02-01T00:00:34Z,28.9,2,181,0,6.0,234,0.0,5.93,1,39.9,1 -N,1,2023-02-01T02:59:27Z,5.8,2,141,0,1.51,263,0.0,0.79,1,12.31,1 -N,2,2023-02-01T18:40:29Z,10.7,2,236,0,0.0,163,0.0,1.35,1,17.2,1 +N,1,2023-02-01T21:17:13Z,6.5,1,50,0,1.75,143,0.0,0.8,1,13.25,2 N,1,2023-02-01T19:26:30Z,13.5,2,43,0,4.0,163,0.0,2.15,1,24.0,1 +N,1,2023-02-01T15:53:16Z,7.2,1,230,0,2.2,186,0.0,0.6,1,13.4,2 +N,1,2023-02-01T20:20:43Z,9.3,1,170,0,2.15,113,0.0,1.1,1,16.45,1 diff --git a/004_NYC_Calls/all.parquet b/data/005_NYC/all.parquet similarity index 100% rename from 004_NYC_Calls/all.parquet rename to data/005_NYC/all.parquet diff --git a/004_NYC_Calls/info.yml b/data/005_NYC/info.yml similarity index 100% rename from 004_NYC_Calls/info.yml rename to data/005_NYC/info.yml diff --git a/data/005_NYC/qa.csv b/data/005_NYC/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..b1e9f7e0560ae5408fa5b399e14bfa11490857f9 --- /dev/null +++ b/data/005_NYC/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Are there any complaints made in Brooklyn?,True,boolean,['borough'],['category'],True +Do any complaints have 'Dog' as a descriptor?,True,boolean,['descriptor'],['category'],False +Were there any complaints raised in April?,True,boolean,['month_name'],['category'],True +Is the Mayor's office of special enforcement one of the agencies handling complaints?,True,boolean,['agency'],['category'],False +How many complaints have been made in Queens?,23110,number,['borough'],['category'],0 +What's the total number of unique agencies handling complaints?,22,number,['agency'],['category'],7 +How many complaints were raised at midnight?,14811,number,['hour'],['number[uint8]'],2 +How many unique descriptors are present in the dataset?,1131,number,['descriptor'],['category'],16 +Which borough has the most complaints?,BROOKLYN,category,['borough'],['category'],QUEENS +Which month sees the highest number of complaints?,July,category,['month_name'],['category'],January +Which weekday has the least complaints?,Sunday,category,['weekday_name'],['category'],Thursday +Which agency is least frequently handling complaints?,ACS,category,['agency'],['category'],DOHMH +List the top 5 most frequent complaint types.,"['Noise - Residential', 'HEAT/HOT WATER', 'Illegal Parking', 'Blocked Driveway', 'Street Condition']",list[category],['complaint_type'],['category'],"[HEAT/HOT WATER, Building/Use, Noise - Residential, General Construction/Plumbing, Air Quality]" +Which 4 agencies handle the most complaints?,"['NYPD', 'HPD', 'DOT', 'DSNY']",list[category],['agency'],['category'],"[NYPD, HPD, DOB, DSNY]" +Name the 3 least frequent descriptors for complaints.,"['Booting Company', 'Ready NY - Businesses', 'Animal']",list[category],['descriptor'],['category'],"[Structure - Outdoors, Air: Odor/Fumes, Restaurant (AD2), 12 Dead Animals]" +Mention the 2 most common weekdays for complaints.,"['Tuesday', 'Monday']",list[category],['weekday_name'],['category'],"[Monday, Wednesday]" +What are the top 4 hours with the most complaints?,"[0, 12, 10, 11]",list[number],['hour'],['number[uint8]'],"[18, 21, 0, 16]" +State the 3 lowest unique complaint keys.,"[15628852, 15634748, 15634996]",list[number],['unique_key'],['number[uint32]'],"[18311800, 22322205, 25369019]" +Which 5 hours see the least complaints?,"[6, 2, 3, 5, 4]",list[number],['hour'],['number[uint8]'],"[22, 7, 14, 23, 8]" +List 6 unique complaint numbers from the dataset.,"[33629705, 46718634, 51900343, 53128216, 34575561, 46015340]",list[number],['unique_key'],['number[uint32]'],"[51990440, 43655624, 35414182, 43260648, 28084067, 50082845]" diff --git a/004_NYC_Calls/sample.csv b/data/005_NYC/sample.csv similarity index 100% rename from 004_NYC_Calls/sample.csv rename to data/005_NYC/sample.csv diff --git a/005_London_Airbnbs/all.parquet b/data/006_London/all.parquet similarity index 100% rename from 005_London_Airbnbs/all.parquet rename to data/006_London/all.parquet diff --git a/005_London_Airbnbs/info.yml b/data/006_London/info.yml similarity index 100% rename from 005_London_Airbnbs/info.yml rename to data/006_London/info.yml diff --git a/data/006_London/qa.csv b/data/006_London/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..7c8ab47f3bef5a5eb8b2dff3a88c0ec1b7dff099 --- /dev/null +++ b/data/006_London/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Are all properties in the dataset located in the same neighbourhood?,False,boolean,['neighbourhood_cleansed'],['category'],False +Do all hosts verify their identity?,False,boolean,['host_identity_verified'],['category'],False +Are all reviews_per_month values greater than 5?,False,boolean,['reviews_per_month'],['number[double]'],False +Are there any listings without a specified room type?,False,boolean,['room_type'],['category'],False +How many unique hosts are there in the dataset?,563,number,['host_neighbourhood'],['category'],20 +How many listings have a valid price?,0,number,['price'],['category'],0 +How many properties have received a perfect review score for communication?,0,number,['review_scores_communication'],['number[double]'],0 +What is the maximum number of bedrooms a property has in this dataset?,22.0,number,['bedrooms'],['number[UInt8]'],3.0 +Which neighbourhood has the most listings?,Westminster,category,['neighbourhood_cleansed'],['category'],Hammersmith and Fulham +What is the most common room type in the listings?,Entire home/apt,category,['room_type'],['category'],Private room +What property type has the least listings?,Hut,category,['property_type'],['category'],Entire condo +Which host verification method is the least used?,photographer],category,['host_verifications'],['list[category]'],[phone] +List the top 3 neighbourhoods with the most listings.,"['Westminster', 'Tower Hamlets', 'Hackney']",list[category],['neighbourhood_cleansed'],['category'],"['Hammersmith and Fulham', 'Hackney', 'Westminster']" +Which are the top 5 most common property types?,"['Entire rental unit', 'Private room in rental unit', 'Private room in home', 'Entire condo', 'Entire home']",list[category],['property_type'],['category'],"['Private room in rental unit', 'Entire rental unit', 'Entire home', 'Private room in home', 'Entire condo']" +List the 4 least common host verification methods.,"['[email]', '[]', '[None]', ' photographer']",list[category],['host_verifications'],['list[category]'],"['[phone]', ' phone', ' work_email', ' phone']" +Which are the 2 most preferred room types?,"['Entire home/apt', 'Private room']",list[category],['room_type'],['category'],"['Private room', 'Entire home/apt']" +What are the top 3 highest review scores for location?,"[5.0, 5.0, 5.0]",list[number],['review_scores_location'],['number[double]'],"[5.0, 4.0, 4.89]" +What are the 4 most common number of bedrooms in properties?,"[1.0, 2.0, 3.0, 4.0]",list[number],['bedrooms'],['number[UInt8]'],"[1.0, 2.0, 3.0]" +What are the 5 highest counts of listings by a single host for entire homes?,"[288, 288, 288, 288, 288]",list[number],['calculated_host_listings_count_entire_homes'],['number[uint16]'],"[1, 1, 1, 1, 1]" +List the 6 lowest review scores for communication.,"[0.0, 0.0, 0.0, 0.0, 0.0, 0.0]",list[number],['review_scores_communication'],['number[double]'],"[4.4, 4.89, 4.95, 4.5, 4.75, 4.94]" diff --git a/005_London_Airbnbs/sample.csv b/data/006_London/sample.csv similarity index 100% rename from 005_London_Airbnbs/sample.csv rename to data/006_London/sample.csv diff --git a/006_Fifa/all.parquet b/data/007_Fifa/all.parquet similarity index 100% rename from 006_Fifa/all.parquet rename to data/007_Fifa/all.parquet diff --git a/006_Fifa/info.yml b/data/007_Fifa/info.yml similarity index 100% rename from 006_Fifa/info.yml rename to data/007_Fifa/info.yml diff --git a/data/007_Fifa/qa.csv b/data/007_Fifa/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..e602f54e5f552eb85c7b7a77f368409b46c73a64 --- /dev/null +++ b/data/007_Fifa/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Are there players who have a greater overall score than their potential score?,False,boolean,"['Overall', 'Potential']","['number[uint8]', 'number[uint8]']",False +Are there any players who joined their current club before they were 18 years old?,True,boolean,"['Joined', 'Age']","['category', 'number[uint8]']",True +Are there any players whose preferred foot is left and are from a nationality that starts with 'B'?,True,boolean,"['Preferred Foot', 'Nationality']","['category', 'category']",False +Are there any players who are taller than 6 feet and have an agility score above 90?,False,boolean,"['Height_ft', 'Agility']","['number[double]', 'number[uint8]']",False +What is the average overall score of players from France?,67.861432,number,"['Nationality', 'Overall']","['category', 'number[uint8]']", +How many unique clubs are there in the dataset?,683,number,['Club'],['category'],19 +What is the highest value (in €) of a player in the dataset?,105500000,number,['Value_€'],['number[uint32]'],13500000 +How many players have the position 'ST'?,414,number,['Position'],['category'],1 +What is the most common nationality in the dataset?,England,category,['Nationality'],['category'],Ghana +What is the most common preferred foot amongst players?,Right,category,['Preferred Foot'],['category'],Right +Which club has the most players in the dataset?,Crystal Palace,category,['Club'],['category'],Lech Poznań +What is the most common position of players in the dataset?,SUB,category,['Position'],['category'],SUB +Which are the top 5 nationalities in terms of the average overall score of their players?,"['Tanzania', 'Syria', 'Mozambique', 'Chad', 'Central African Rep.']",list[category],"['Nationality', 'Overall']","['category', 'number[uint8]']","['Portugal', 'Ivory Coast', 'Brazil', 'United States', 'Ghana']" +Which are the top 3 clubs in terms of the total value (in €) of their players?,"['Liverpool', 'Manchester City', 'Real Madrid']",list[category],"['Club', 'Value_€']","['category', 'number[uint32]']","['Sassuolo', 'Atalanta', 'DC United']" +Which are the bottom 4 nationalities in terms of the average agility of their players?,"['Macau', 'Andorra', 'Moldova', 'Liechtenstein']",list[category],"['Nationality', 'Agility']","['category', 'number[uint8]']","['United States', 'Guyana', 'Saudi Arabia', 'Poland']" +Which are the top 6 clubs in terms of the average potential score of their players?,"['FC Bayern München', 'Real Madrid', 'FC Barcelona', 'Paris Saint-Germain', 'Juventus', 'Manchester City']",list[category],"['Club', 'Potential']","['category', 'number[uint8]']","['Sassuolo', 'Inter', 'Sporting CP', '1. FSV Mainz 05', 'Atalanta', 'DC United']" +What are the top 3 overall scores in the dataset?,"[93, 92, 91]",list[number],['Overall'],['number[uint8]'],"[79, 77, 77]" +What are the bottom 5 potential scores in the dataset?,"[48, 48, 49, 50, 50]",list[number],['Potential'],['number[uint8]'],"[60, 65, 66, 67, 68]" +What are the top 4 values (in €) of players in the dataset?,"[105500000, 90000000, 87000000, 80000000]",list[number],['Value_€'],['number[uint32]'],"[13500000, 7500000, 5500000, 5500000]" +What are the top 2 wages (in €) of players in the dataset?,"[560000, 370000]",list[number],['Wage_€'],['number[uint32]'],"[47000, 29000]" diff --git a/006_Fifa/sample.csv b/data/007_Fifa/sample.csv similarity index 100% rename from 006_Fifa/sample.csv rename to data/007_Fifa/sample.csv diff --git a/007_Tornados/all.parquet b/data/008_Tornados/all.parquet similarity index 100% rename from 007_Tornados/all.parquet rename to data/008_Tornados/all.parquet diff --git a/007_Tornados/info.yml b/data/008_Tornados/info.yml similarity index 100% rename from 007_Tornados/info.yml rename to data/008_Tornados/info.yml diff --git a/data/008_Tornados/qa.csv b/data/008_Tornados/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..c34732cb42816b1a24ad70b3b6f6dbfdd8ecf664 --- /dev/null +++ b/data/008_Tornados/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +There are no tornadoes that resulted in more than 500 injuries.,True,boolean,[inj],['number[uint16]'],True +All tornadoes in the dataset occurred in the 21st century.,False,boolean,[yr],['number[uint16]'],False +No tornado has a length greater than 100 miles.,True,boolean,[len],['number[double]'],True +There are no tornadoes that resulted in more than 100 fatalities.,True,boolean,[fat],['number[uint8]'],True +How many unique states are represented in the dataset?,53,number,[st],['category'],12 +What is the highest magnitude of tornado recorded in the dataset?,5,number,[mag],['number[int8]'],2 +What is the longest length of a tornado path in the dataset?,234.7,number,[len],['number[double]'],72.2 +What is the maximum number of injuries caused by a single tornado?,1740,number,[inj],['number[uint16]'],3 +Which state has experienced the most tornadoes?,TX,category,[st],['category'],IL +In which month do most tornadoes occur?,5,category,[mo],['number[uint8]'],6 +On what date did the most destructive tornado (by injuries) occur?,1979-04-10 00:00:00,category,"[date, inj]","['date[ns, UTC]', 'number[uint16]']",1973-03-15 +On what date did the longest tornado (by path length) occur?,1953-03-22 00:00:00,category,"[date, len]","['date[ns, UTC]', 'number[double]']",1955-06-04 +Which are the top 5 states with the highest average tornado magnitude?,"[AR, KY, VT, TN, MS]",list[category],"[st, mag]","['category', 'number[int8]']","['TN', 'GA', 'IN', 'OK', 'TX']" +Which are the top 3 states with the most tornado-related injuries?,"[TX, AL, MS]",list[category],"[st, inj]","['category', 'number[uint16]']","['TN', 'IL', 'AR']" +Which are the top 4 states with the most tornado-related fatalities?,"[AL, TX, MS, OK]",list[category],"[st, fat]","['category', 'number[uint8]']","['TN', 'AR', 'FL', 'GA']" +Which are the bottom 2 states in terms of the average tornado path length?,"[AK, VI]",list[category],"[st, len]","['category', 'number[double]']","['TN', 'WY']" +What are the top 3 number of injuries caused by tornadoes in the dataset?,"[1740, 1500, 1228]",list[number],[inj],['number[uint16]'],"[3, 1, 0]" +What are the top 5 magnitudes of tornadoes in the dataset?,"[5, 5, 5, 5, 5]",list[number],[mag],['number[int8]'],"[2, 2, 1, 1, 1]" +What are the top 4 path lengths of tornadoes in the dataset?,"[234.7, 217.8, 202.5, 202.1]",list[number],[len],['number[double]'],"[72.2, 4.7, 4.3, 3.2]" +What are the top 6 number of fatalities caused by tornadoes in the dataset?,"[158, 116, 114, 94, 80, 72]",list[number],[fat],['number[uint8]'],"[1, 0, 0, 0, 0, 0]" diff --git a/007_Tornados/sample.csv b/data/008_Tornados/sample.csv similarity index 100% rename from 007_Tornados/sample.csv rename to data/008_Tornados/sample.csv diff --git a/008_Central_Park/all.parquet b/data/009_Central/all.parquet similarity index 100% rename from 008_Central_Park/all.parquet rename to data/009_Central/all.parquet diff --git a/008_Central_Park/info.yml b/data/009_Central/info.yml similarity index 100% rename from 008_Central_Park/info.yml rename to data/009_Central/info.yml diff --git a/data/009_Central/qa.csv b/data/009_Central/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..00fa14e03323df87aa3427b15a5f8841488418e9 --- /dev/null +++ b/data/009_Central/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +There were no days when the precipitation was greater than 5 inches.,True,boolean,[PRCP],['number[double]'],True +All recorded temperatures are above freezing point.,False,boolean,"[TMIN, TMAX]","['number[Int8]', 'number[UInt8]']",False +There were no days when the snow depth was more than 10 inches.,True,boolean,[SNWD],['number[UInt8]'],True +There were no days when the maximum temperature was below freezing point.,False,boolean,[TMAX],['number[UInt8]'],False +What is the highest recorded precipitation in inches?,8.28,number,[PRCP],['number[double]'],0.66 +What is the lowest minimum temperature recorded?,-15.0,number,[TMIN],['number[Int8]'],-13.0 +What is the highest maximum temperature recorded?,106.0,number,[TMAX],['number[UInt8]'],81.0 +What is the deepest recorded snow depth in inches?,26.0,number,[SNWD],['number[UInt8]'],4.0 +On which date was the highest precipitation recorded?,1882-09-23 00:00:00,category,"[DATE, PRCP]","['date[ns, UTC]', 'number[double]']",1891-07-24 +On which date was the lowest minimum temperature recorded?,1934-02-09 00:00:00,category,"[DATE, TMIN]","['date[ns, UTC]', 'number[Int8]']",1917-12-30 +On which date was the highest maximum temperature recorded?,1936-07-09 00:00:00,category,"[DATE, TMAX]","['date[ns, UTC]', 'number[UInt8]']",1891-07-24 +On which date was the deepest snow depth recorded?,1947-12-27 00:00:00,category,"[DATE, SNWD]","['date[ns, UTC]', 'number[UInt8]']",1945-02-03 +What are the dates of the top 5 highest recorded precipitation events?,"[1882-09-23 00:00:00, 2007-04-15 00:00:00, 1977-11-08 00:00:00, 1903-10-09 00:00:00, 2021-09-01 00:00:00]",list[category],"[DATE, PRCP]","['date[ns, UTC]', 'number[double]']","['1891-07-24', '1966-10-16', '1945-09-27', '1999-05-18', '1898-09-15']" +What are the dates of the top 3 lowest minimum temperatures recorded?,"[1934-02-09 00:00:00, 1917-12-30 00:00:00, 1943-02-15 00:00:00]",list[category],"[DATE, TMIN]","['date[ns, UTC]', 'number[Int8]']","['1917-12-30', '1945-02-03', '1892-03-21']" +What are the dates of the top 4 highest maximum temperatures recorded?,"[1936-07-09 00:00:00, 1918-08-07 00:00:00, 1977-07-21 00:00:00, 2011-07-22 00:00:00]",list[category],"[DATE, TMAX]","['date[ns, UTC]', 'number[UInt8]']","['1891-07-24', '1903-06-03', '1982-07-02', '1960-08-26']" +What are the dates of the top 2 deepest snow depth recorded?,"[1947-12-27 00:00:00, 1947-12-28 00:00:00]",list[category],"[DATE, SNWD]","['date[ns, UTC]', 'number[UInt8]']","['1945-02-03', '1917-12-30']" +What are the top 3 highest recorded precipitation events in inches?,"[8.28, 7.57, 7.4]",list[number],[PRCP],['number[double]'],"[0.66, 0.26, 0.1]" +What are the top 5 lowest minimum temperatures recorded?,"[-15.0, -13.0, -8.0, -7.0, -7.0]",list[number],[TMIN],['number[Int8]'],"[-13.0, 18.0, 19.0, 29.0, 32.0]" +What are the top 4 highest maximum temperatures recorded?,"[106.0, 104.0, 104.0, 104.0]",list[number],[TMAX],['number[UInt8]'],"[81.0, 81.0, 80.0, 79.0]" +What are the top 2 deepest snow depth recorded in inches?,"[26.0, 25.0]",list[number],[SNWD],['number[UInt8]'],"[4.0, 3.0]" diff --git a/008_Central_Park/sample.csv b/data/009_Central/sample.csv similarity index 100% rename from 008_Central_Park/sample.csv rename to data/009_Central/sample.csv diff --git a/009_ECommerce_Reviews/all.parquet b/data/010_ECommerce/all.parquet similarity index 100% rename from 009_ECommerce_Reviews/all.parquet rename to data/010_ECommerce/all.parquet diff --git a/009_ECommerce_Reviews/info.yml b/data/010_ECommerce/info.yml similarity index 100% rename from 009_ECommerce_Reviews/info.yml rename to data/010_ECommerce/info.yml diff --git a/data/010_ECommerce/qa.csv b/data/010_ECommerce/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..9873fe8dcd26eebc9d88a3bbcacf83919ab0afcb --- /dev/null +++ b/data/010_ECommerce/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Are there more than 20 unique clothing items in the dataset?,True,boolean,[Clothing ID],['number[uint16]'],False +Is the age of the reviewers above 50 years on average?,False,boolean,[Age],['number[uint8]'],False +Do all reviews come from the same department?,False,boolean,[Department Name],['category'],False +Are all products recommended?,False,boolean,[Recommended IND],['number[uint8]'],False +What is the average age of the reviewers?,43.198543813335604,number,[Age],['number[uint8]'],39.65 +What's the highest number of positive feedback received for a review?,122,number,[Positive Feedback Count],['number[uint8]'],19 +What is the most common rating given by reviewers?,5,number,[Rating],['number[uint8]'],5 +How many unique clothing items are there in the dataset?,1206,number,[Clothing ID],['number[uint16]'],20 +Which department has the most reviews?,Tops,category,['Department Name'],['category'],Dresses +Which class of clothing is most commonly reviewed?,Dresses,category,['Class Name'],['category'],Dresses +Which division is most commonly mentioned in the reviews?,General,category,['Division Name'],['category'],General +What is the most frequently reviewed clothing item?,1078,category,['Clothing ID'],['number[uint16]'],1095 +Which are the top 6 most reviewed categories in Department Name?,"['Tops', 'Dresses', 'Bottoms', 'Intimate', 'Jackets', 'Trend']",list[category],[Department Name],['category'],"[Dresses, Tops, Bottoms, Intimate]" +Which are the top 2 most reviewed categories in Class Name?,"['Dresses', 'Knits']",list[category],[Class Name],['category'],"[Dresses, Blouses]" +Which are the top 2 most reviewed categories in Division Name?,"['General', 'General Petite']",list[category],[Division Name],['category'],"[General, General Petite]" +What are the 4 most common ratings given by reviewers?,"[5, 4, 3, 2]",list[category],[Rating],['number[uint8]'],"[5, 4, 3, 2]" +What are the 5 most common Ages of reviewers?,"[39, 35, 36, 34, 38]",list[number],[Age],['number[uint8]'],"[36, 30, 56, 33, 34]" +What are the 6 most common Positive Feedback Counts of reviewers?,"[0, 1, 2, 3, 4, 5]",list[number],[Positive Feedback Count],['number[uint8]'],"[0, 3, 5, 1, 19, 11]" +What are the 4 most common values for recommendation indicator?,"[1, 0]",list[number],[Recommended IND],['number[uint8]'],"[1, 0]" +What are the 2 most common clothing IDs in the reviews?,"[1078, 862]",list[number],[Clothing ID],['number[uint16]'],"[1095, 903]" diff --git a/009_ECommerce_Reviews/sample.csv b/data/010_ECommerce/sample.csv similarity index 100% rename from 009_ECommerce_Reviews/sample.csv rename to data/010_ECommerce/sample.csv diff --git a/010_SF_Police/all.parquet b/data/011_SF/all.parquet similarity index 100% rename from 010_SF_Police/all.parquet rename to data/011_SF/all.parquet diff --git a/010_SF_Police/info.yml b/data/011_SF/info.yml similarity index 100% rename from 010_SF_Police/info.yml rename to data/011_SF/info.yml diff --git a/data/011_SF/qa.csv b/data/011_SF/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..4036f965de64361aec4fb711570a5b8cdde6596e --- /dev/null +++ b/data/011_SF/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Was the highest reported incident in the year 2023 filed online?,False,boolean,"[Incident Year, Filed Online, Incident Number]","['number[uint16]', 'boolean', 'number[uint32]']",False +Are all incidents reported on Mondays resolved?,False,boolean,"[Incident Day of Week, Resolution]","['category', 'category']",False +Do any incidents reported in Police District 'Central' fall in Supervisor District 5?,False,boolean,"[Police District, Supervisor District]","['category', 'number[UInt8]']",False +Are there any incidents that occurred at the same latitude and longitude more than once?,True,boolean,"[Latitude, Longitude]","['number[double]', 'number[double]']",False +How many unique types of incident categories are there in the dataset?,49,number,[Incident Category],['category'],11 +What's the total number of incidents reported online?,144099,number,[Filed Online],['boolean'],1 +How many different police districts are there in the dataset?,11,number,[Police District],['category'],9 +What is the average incident count per year?,118851.16666666667,number,[Incident Year],['number[uint16]'],3.3333333333333335 +What is the most common incident category?,Larceny Theft,category,[Incident Category],['category'],Larceny Theft +Which day of the week has the highest number of incidents?,Friday,category,[Incident Day of Week],['category'],Saturday +What is the most common resolution for incidents reported online?,Open or Active,category,"[Filed Online, Resolution]","['boolean', 'category']",Open or Active +What is the Police District with the most incidents?,Central,category,[Police District],['category'],Northern +What are the top 5 most common incident descriptions?,"[Theft, From Locked Vehicle, >$950, [Malicious Mischief], Vandalism to Property, Battery, Lost Property, Vehicle, Recovered, Auto]",list[category],[Incident Description],['category'],"['Investigative Detention', 'Theft, From Locked Vehicle, $200-$950', 'Assault, Aggravated, W/ Other Weapon', 'Theft, From Locked Vehicle, >$950', 'Theft, From Unlocked Vehicle, >$950']" +Name the 4 most frequently occurring police districts.,"[Central, Northern, Mission, Southern]",list[category],[Police District],['category'],"['Northern', 'Central', 'Mission', 'Bayview']" +List the 3 most common incident categories on Fridays.,"[Larceny Theft, Malicious Mischief, Other Miscellaneous]",list[category],"[Incident Day of Week, Incident Category]","['category', 'category']","['Other Miscellaneous', 'Larceny Theft', 'Assault']" +Give the 6 most common resolutions for incidents.,"[Open or Active, Cite or Arrest Adult, Unfounded, Exceptional Adult]",list[category],[Resolution],['category'],"['Open or Active', 'Cite or Arrest Adult']" +List the years with the top 4 highest incident counts.,"[2018, 2019, 2022, 2021]",list[number],[Incident Year],['number[uint16]'],"[2018, 2019, 2021, 2022]" +Which 3 incident years have the lowest number of online filed reports?,"[2023, 2020, 2021]",list[number],"[Incident Year, Filed Online]","['number[uint16]', 'boolean']","[2018, 2020, 2021]" +Provide the 5 most frequently repeated latitude-longitude pairs.,"[(37.784560141211806, -122.40733704162238), (37.7751608100771, -122.40363551943442), (37.78640961281089, -122.40803623744476), (37.7839325760642, -122.4125952775858), (37.77871942789032, -122.4147412230519)]",list[number],"[Latitude, Longitude]","['number[double]', 'number[double]']","[(37.72344678051801, -122.40007300242718), (37.724004908138426, -122.4353125712072), (37.73078874215092, -122.42838994658086), (37.73132568595012, -122.46129211000152), (37.7430966136643, -122.47462383026864)]" +Name the 6 years with the most number of unique incident categories.,"[2018, 2019, 2020, 2021, 2022, 2023]",list[number],"[Incident Year, Incident Category]","['number[uint16]', 'category']","[2018, 2019, 2021, 2022, 2020, 2023]" diff --git a/010_SF_Police/sample.csv b/data/011_SF/sample.csv similarity index 100% rename from 010_SF_Police/sample.csv rename to data/011_SF/sample.csv diff --git a/011_Heart_Failure/all.parquet b/data/012_Heart/all.parquet similarity index 100% rename from 011_Heart_Failure/all.parquet rename to data/012_Heart/all.parquet diff --git a/011_Heart_Failure/info.yml b/data/012_Heart/info.yml similarity index 100% rename from 011_Heart_Failure/info.yml rename to data/012_Heart/info.yml diff --git a/data/012_Heart/qa.csv b/data/012_Heart/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..cce2dad1acb791b90d0519494e43a596e6b2e186 --- /dev/null +++ b/data/012_Heart/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Do all patients experience exercise-induced angina?,False,boolean,['ExerciseAngina'],['category'],False +Does any patient have a resting blood pressure above 200?,False,boolean,['RestingBP'],['number[uint8]'],False +Are there patients without heart disease?,True,boolean,['HeartDisease'],['number[uint8]'],True +Does everyone have normal resting electrocardiographic results?,False,boolean,['RestingECG'],['category'],False +What is the maximum age of patients in the dataset?,77,number,['Age'],['number[uint8]'],69 +What is the minimum resting blood pressure among the patients?,0,number,['RestingBP'],['number[uint8]'],95 +What is the average cholesterol level in the dataset?,198.7995642701525,number,['Cholesterol'],['number[uint16]'],207.8 +What is the standard deviation of maximum heart rate among the patients?,25.4603341382503,number,['MaxHR'],['number[uint8]'],27.360170821258063 +What is the most common chest pain type among patients?,ASY,category,['ChestPainType'],['category'],ASY +What is the least common resting electrocardiographic result?,ST,category,['RestingECG'],['category'],ST +What is the most common ST slope among patients with heart disease?,Flat,category,"['ST_Slope', 'HeartDisease']","['category', 'number[uint8]']",Flat +What is the least common chest pain type among male patients?,TA,category,"['ChestPainType', 'Sex']","['category', 'category']",TA +What are the top 3 most common chest pain types?,"['ASY', 'NAP', 'ATA']",list[category],['ChestPainType'],['category'],"['ASY', 'NAP', 'ATA']" +Which 4 resting electrocardiographic results are least common?,"['ST', 'LVH', 'Normal']",list[category],['RestingECG'],['category'],"['ST', 'LVH', 'Normal']" +What are the 2 most common ST slopes among patients with heart disease?,"['Flat', 'Up']",list[category],"['ST_Slope', 'HeartDisease']","['category', 'number[uint8]']","['Flat', 'Down']" +What are the 4 most common chest pain types among male patients?,"['TA', 'ATA', 'NAP', 'ASY']",list[category],"['ChestPainType', 'Sex']","['category', 'category']","['TA', 'ATA', 'NAP', 'ASY']" +What are the top 5 ages of patients in the dataset?,"[54, 58, 55, 56, 57]",list[number],['Age'],['number[uint8]'],"[56, 67, 64, 57, 63]" +What are the 4 least common resting blood pressures among the patients?,"[101, 174, 192, 129]",list[number],['RestingBP'],['number[uint8]'],"[145, 160, 108, 142]" +What are the 6 most common cholesterol levels in the dataset?,"[0, 254, 223, 220, 230, 211]",list[number],['Cholesterol'],['number[uint16]'],"[0, 195, 518, 309, 254, 271]" +What are the 3 least common maximum heart rates among the patients?,"[177, 187, 194]",list[number],['MaxHR'],['number[uint8]'],"[179, 86, 140]" diff --git a/011_Heart_Failure/sample.csv b/data/012_Heart/sample.csv similarity index 100% rename from 011_Heart_Failure/sample.csv rename to data/012_Heart/sample.csv diff --git a/012_Roller_Coasters/all.parquet b/data/013_Roller/all.parquet similarity index 100% rename from 012_Roller_Coasters/all.parquet rename to data/013_Roller/all.parquet diff --git a/012_Roller_Coasters/info.yml b/data/013_Roller/info.yml similarity index 100% rename from 012_Roller_Coasters/info.yml rename to data/013_Roller/info.yml diff --git a/data/013_Roller/qa.csv b/data/013_Roller/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..a68e94fd1ed4dc288298189238270928dd5fefaa --- /dev/null +++ b/data/013_Roller/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Did the oldest roller coaster in the dataset still operate?,True,boolean,"[year_introduced, Status]","['category', 'category']",True +Is there a roller coaster in the dataset that operates at a speed more than 100 mph?,True,boolean,[speed_mph],['number[double]'],False +Are all roller coasters in the dataset designed by 'Werner Stengel' removed?,False,boolean,"[Designer, Status]","['category', 'category']",False +Does every roller coaster have a G-force value?,False,boolean,[Gforce_clean],['number[double]'],False +What is the maximum speed (in mph) for roller coasters in the dataset?,149.1,number,[speed_mph],['number[double]'],62.0 +How many roller coasters were introduced in the year 2000?,47,number,[year_introduced],['number[uint16]'],0 +What is the average G-force across all roller coasters in the dataset?,3.8240055248618785,number,[Gforce_clean],['number[double]'],3.62 +What is the total number of roller coasters designed by 'Edwin Madeupname' in the dataset?,0,number,[Designer],['category'],0 +Which manufacturer has built the fastest roller coaster?,Intamin,category,"[Manufacturer, speed_mph]","['category', 'number[double]']",Bolliger & Mabillard +What is the status of the roller coaster with the highest G-force?,Removed,category,"[Status, Gforce_clean]","['category', 'number[double]']", +What type of the roller coaster is the oldest in the dataset?,Wood,category,"[Type, Opening date]","['category', 'category']",Other +What is the location of the roller coaster with the highest number of inversions?,Alton Towers,category,"[Location, Inversions_clean]","['category', 'number[uint8]']",Busch Gardens Tampa Bay +What are the names of the top 3 fastest roller coasters?,"[Formula Rossa, Kingda Ka, Top Thrill Dragster]",list[category],"[coaster_name, speed_mph]","['category', 'number[double]']","[\'Afterburn (roller coaster)\', \'Hades 360\', \'Montu (roller coaster)\']" +Which 2 roller coasters have the highest number of inversions?,"[The Smiler, Colossus (Thorpe Park)]",list[category],"[coaster_name, Inversions_clean]","['category', 'number[uint8]']","[\'Montu (roller coaster)\', \'Wipeout (roller coaster)\']" +What are the locations of the top 5 roller coasters with the highest G-force?,"[Sea Lion Park, Fuji-Q Highland, Six Flags Over Texas, Nürburgring, Morey's Piers]",list[category],"[Location, Gforce_clean]","['category', 'number[double]']","[\'Other\', \'Busch Gardens Tampa Bay\', \'Mt. Olympus Water & Theme Park\', \'Adventuredome\', \'Other\']" +Name the 4 oldest roller coasters in the dataset.,"[Switchback Railway, Flip Flap Railway, Loop the Loop (Coney Island), Loop the Loop (Young's Pier)]",list[category],"[coaster_name, Opening date]","['category', 'category']","[\'Zipper Dipper\', \'Runaway Mine Train (Six Flags Over Texas)\', \'The Bush Beast\', \'Canyon Blaster (Adventuredome)\']" +What are the top 3 speeds (in mph) of roller coasters in the dataset?,"[149.1, 128.0, 120.0]",list[number],[speed_mph],['number[double]'],"[62.0, 60.0, 60.0]" +List the G-force values of the 2 roller coasters with the highest G-force.,"[12.0, 6.5]",list[number],[Gforce_clean],['number[double]'],"[4.3, 3.8]" +What are the heights (in ft) of the top 4 tallest roller coasters?,"[377.3, 367.5, 318.2, 306.1]",list[number],[height_ft],['number[double]'],"[98.4, 90.2, 82.0, 78.7]" +Name the introduction years of the 6 oldest roller coasters in the dataset.,"[1884, 1895, 1901, 1901, 1902, 1902]",list[number],"[year_introduced, Opening date]","['number[uint16]', 'category']","[1934, 1966, 1985, 1993, 1996, 1999]" diff --git a/012_Roller_Coasters/sample.csv b/data/013_Roller/sample.csv similarity index 100% rename from 012_Roller_Coasters/sample.csv rename to data/013_Roller/sample.csv diff --git a/013_Airbnb_Madrid/all.parquet b/data/014_Airbnb/all.parquet similarity index 100% rename from 013_Airbnb_Madrid/all.parquet rename to data/014_Airbnb/all.parquet diff --git a/013_Airbnb_Madrid/info.yml b/data/014_Airbnb/info.yml similarity index 100% rename from 013_Airbnb_Madrid/info.yml rename to data/014_Airbnb/info.yml diff --git a/data/014_Airbnb/qa.csv b/data/014_Airbnb/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..fa89152f4ade1df2c14d5f307d773c6bcacdf1bb --- /dev/null +++ b/data/014_Airbnb/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Is there a rental property with exactly 5 bedrooms?,True,boolean,['bedrooms'],['number[UInt8]'],False +Is there a rental property listed by a superhost that is instantly bookable?,True,boolean,"['host_is_superhost', 'instant_bookable']","['category', 'category']",True +Are there any rental properties that can accommodate more than 10 guests?,True,boolean,['accommodates'],['number[uint8]'],False +Is there a rental property that has received a perfect review score?,False,boolean,['review_scores_rating'],['number[double]'],False +How many rental properties are there in the dataset?,20776,number,[],[],20.0 +What is the maximum number of bedrooms in a property?,18.0,number,['bedrooms'],['number[UInt8]'],0 +What is the highest price per night for a rental property?,95150.0,number,['price'],['category'],3.62 +What is the maximum number of reviews a property has received?,870,number,['number_of_reviews'],['number[uint16]'],0 +Which neighbourhood is the property with the highest number of bedrooms located in?,Universidad,category,"['bedrooms', 'neighbourhood_cleansed']","['number[UInt8]', 'category']",Bolliger & Mabillard +What type of room is the most expensive property?,Entire home/apt,category,"['price', 'room_type']","['category', 'category']", +What is the property type of the listing with the most reviews?,Entire rental unit,category,"['number_of_reviews', 'property_type']","['number[uint16]', 'category']",Other +What is the neighbourhood of the property that can accommodate the most number of guests?,Unknown,category,"['accommodates', 'neighbourhood']","['number[uint8]', 'category']",Busch Gardens Tampa Bay +Which are the top 3 neighbourhoods with the most number of listings?,"['Madrid, Comunidad de Madrid, Spain', 'Madrid, Community of Madrid, Spain', 'Madrid, Spain']",list[category],['neighbourhood'],['category'],"[\'Afterburn (roller coaster)\', \'Hades 360\', \'Montu (roller coaster)\']" +Which are the top 2 property types that have received the most reviews?,"['Entire rental unit', 'Private room in rental unit']",list[category],"['property_type', 'number_of_reviews']","['category', 'number[uint16]']","[\'Montu (roller coaster)\', \'Wipeout (roller coaster)\']" +Which are the bottom 4 neighbourhoods with the least number of listings?,"['madrid, Comunidad de Madrid, Spain', 'Madrid, madrid, Spain', 'Lavapies, Comunidad de Madrid, Spain', 'Madrid, Comunidad de Madrid, España, Spain']",list[category],['neighbourhood'],['category'],"[\'Other\', \'Busch Gardens Tampa Bay\', \'Mt. Olympus Water & Theme Park\', \'Adventuredome\', \'Other\']" +What are the bottom 2 room types that are least available?,"['Shared room', 'Hotel room']",list[category],['room_type'],['category'],"[\'Zipper Dipper\', \'Runaway Mine Train (Six Flags Over Texas)\', \'The Bush Beast\', \'Canyon Blaster (Adventuredome)\']" +What are the top 3 prices of the most expensive properties?,"[95150.0, 90130.0, 64430.0]",list[number],['price'],['category'],"[62.0, 60.0, 60.0]" +What are the bottom 4 prices of the least expensive properties?,"[0.0, 0.0, 0.0, 0.0]",list[number],['price'],['category'],"[4.3, 3.8]" +What are the top 2 numbers of reviews received by the most reviewed properties?,"[870, 822]",list[number],['number_of_reviews'],['number[uint16]'],"[98.4, 90.2, 82.0, 78.7]" +What are the top 5 numbers of guests accommodated by the properties that can accommodate the most guests?,"[16, 16, 16, 16, 16]",list[number],['accommodates'],['number[uint8]'],"[1934, 1966, 1985, 1993, 1996, 1999]" diff --git a/013_Airbnb_Madrid/sample.csv b/data/014_Airbnb/sample.csv similarity index 100% rename from 013_Airbnb_Madrid/sample.csv rename to data/014_Airbnb/sample.csv diff --git a/014_Food_Names_Embeddings/all.parquet b/data/015_Food/all.parquet similarity index 100% rename from 014_Food_Names_Embeddings/all.parquet rename to data/015_Food/all.parquet diff --git a/014_Food_Names_Embeddings/info.yml b/data/015_Food/info.yml similarity index 100% rename from 014_Food_Names_Embeddings/info.yml rename to data/015_Food/info.yml diff --git a/data/015_Food/qa.csv b/data/015_Food/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..a03c10957dcea5c725a26c9fc0b9fe8fae1560f7 --- /dev/null +++ b/data/015_Food/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Is there a food item with 'Fruits' as its group?,True,boolean,['GROUP'],['category'],False +Are there food items with 'Nuts' as their sub group?,True,boolean,['SUB GROUP'],['category'],True +Is there a food item with scientific name 'Tilia argentea'?,True,boolean,['SCIENTIFIC NAME'],['category'],False +Is 'Angelica' listed as a food name in the dataset?,True,boolean,['FOOD NAME'],['category'],False +How many food items are there in the dataset?,906,number,[],[],20 +How many unique food groups are there in the dataset?,24,number,['GROUP'],['category'],8 +How many unique sub groups are there in the dataset?,123,number,['SUB GROUP'],['category'],14 +How many unique food items are there in the dataset?,906,number,['FOOD NAME'],['category'],20 +What is the group of the food named 'Kiwi'?,Fruits,category,"['FOOD NAME', 'GROUP']","['category', 'category']", +What is the sub group of the food with scientific name 'Tilia argentea'?,Herbs,category,"['SCIENTIFIC NAME', 'SUB GROUP']","['category', 'category']", +What is the scientific name of the food named 'Kiwi'?,Actinidia chinensis,category,"['FOOD NAME', 'SCIENTIFIC NAME']","['category', 'category']", +What is the food name of the item with scientific name 'Tilia argentea'?,Silver linden,category,"['SCIENTIFIC NAME', 'FOOD NAME']","['category', 'category']", +What are the top 3 most common food groups?,"['Aquatic foods', 'Vegetables', 'Fruits']",list[category],['GROUP'],['category'],"['Aquatic foods', 'Herbs and Spices', 'Vegetables']" +What are the top 2 most common sub groups?,"['Fishes', 'Herbs']",list[category],['SUB GROUP'],['category'],"['Nuts', 'Mollusks']" +What are the bottom 4 least common food groups?,"['Eggs', 'Baby foods', 'Unclassified', 'Herbs and spices']",list[category],['GROUP'],['category'],"['Nuts', 'Animal foods', 'Snack foods', 'Soy']" +What are the bottom 2 least common sub groups?,"['Soy', 'Green vegetables']",list[category],['SUB GROUP'],['category'],"['Soy products', 'Venison']" +What are the top 3 most common food name lengths?,"[9, 6, 7]",list[number],['FOOD NAME'],['category'],"[15, 13, 8]" +What are the bottom 4 least common food name lengths?,"[39, 30, 45, 33]",list[number],['FOOD NAME'],['category'],"[7, 31, 6, 12]" +What are the top 2 most common scientific name lengths?,"[17.0, 19.0]",list[number],['SCIENTIFIC NAME'],['category'],"[12.0, 14.0]" +What are the top 5 most common group name lengths?,"[6.0, 13.0, 10.0, 16.0, 12.0]",list[number],['GROUP'],['category'],"[13.0, 16.0, 10.0, 9.0, 4.0]" diff --git a/014_Food_Names_Embeddings/sample.csv b/data/015_Food/sample.csv similarity index 100% rename from 014_Food_Names_Embeddings/sample.csv rename to data/015_Food/sample.csv diff --git a/015_Holiday_Package_Sales/all.parquet b/data/016_Holiday/all.parquet similarity index 100% rename from 015_Holiday_Package_Sales/all.parquet rename to data/016_Holiday/all.parquet diff --git a/015_Holiday_Package_Sales/info.yml b/data/016_Holiday/info.yml similarity index 100% rename from 015_Holiday_Package_Sales/info.yml rename to data/016_Holiday/info.yml diff --git a/data/016_Holiday/qa.csv b/data/016_Holiday/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..bc96303fa9886f72da352ed188af8e88ca35eac8 --- /dev/null +++ b/data/016_Holiday/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Is there a customer with 'Large Business' as their occupation?,True,boolean,['Occupation'],['category'],True +Are there customers with 'King' as their pitched product?,True,boolean,['ProductPitched'],['category'],True +Is there a customer with designation 'VP'?,True,boolean,['Designation'],['category'],True +Is 'Unmarried' listed as a marital status in the dataset?,True,boolean,['MaritalStatus'],['category'],True +How many customers are there in the dataset?,4888,number,,[],20 +How many unique occupations are there in the dataset?,4,number,['Occupation'],['category'],3 +How many unique designations are there in the dataset?,5,number,['Designation'],['category'],4 +How many unique marital statuses are there in the dataset?,4,number,['MaritalStatus'],['category'],4 +What is the occupation of the customer with ID 200000?,Salaried,category,"['CustomerID', 'Occupation']","['number[uint32]', 'category']", +What is the product pitched to the customer with ID 200001?,Deluxe,category,"['CustomerID', 'ProductPitched']","['number[uint32]', 'category']", +What is the designation of the customer with ID 200002?,Executive,category,"['CustomerID', 'Designation']","['number[uint32]', 'category']", +What is the marital status of the customer with ID 200003?,Divorced,category,"['CustomerID', 'MaritalStatus']","['number[uint32]', 'category']", +What are the top 3 most common occupations?,"['Salaried', 'Small Business', 'Large Business']",list[category],['Occupation'],['category'],"['Small Business', 'Salaried', 'Large Business']" +What are the top 2 most common pitched products?,"['Basic', 'Deluxe']",list[category],['ProductPitched'],['category'],"['Basic', 'Deluxe']" +What are the bottom 4 least common occupations?,"['Salaried', 'Small Business', 'Large Business', 'Free Lancer']",list[category],['Occupation'],['category'],"['Small Business', 'Salaried', 'Large Business']" +What are the bottom 2 least common pitched products?,"['Super Deluxe', 'King']",list[category],['ProductPitched'],['category'],"['Standard', 'King']" +What are the top 3 most common ages of the customers?,"[35.0, 36.0, 34.0]",list[number],['Age'],['number[UInt8]'],"[37.0, 40.0, 55.0]" +What are the bottom 4 least common ages of the customers?,"[57.0, 60.0, 18.0, 61.0]",list[number],['Age'],['number[UInt8]'],"[30.0, 52.0, 20.0, 31.0]" +What are the top 2 most common monthly incomes of the customers?,"[20855.0, 21288.0]",list[number],['MonthlyIncome'],['number[UInt32]'],"[19668.0, 20021.0]" +What are the top 5 most common duration of pitch?,"[9.0, 7.0, 8.0, 6.0, 16.0]",list[number],['DurationOfPitch'],['number[UInt8]'],"[7.0, 9.0, 22.0, 17.0, 11.0]" diff --git a/015_Holiday_Package_Sales/sample.csv b/data/016_Holiday/sample.csv similarity index 100% rename from 015_Holiday_Package_Sales/sample.csv rename to data/016_Holiday/sample.csv diff --git a/016_Hacker_News/all.parquet b/data/017_Hacker/all.parquet similarity index 100% rename from 016_Hacker_News/all.parquet rename to data/017_Hacker/all.parquet diff --git a/016_Hacker_News/info.yml b/data/017_Hacker/info.yml similarity index 100% rename from 016_Hacker_News/info.yml rename to data/017_Hacker/info.yml diff --git a/data/017_Hacker/qa.csv b/data/017_Hacker/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..19b9375cfb708d961d1862491b7d7067d85fc07e --- /dev/null +++ b/data/017_Hacker/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Is there any entry posted on a weekend?,True,boolean,['weekday_name'],['category'],True +Are there titles with more than 100 characters?,False,boolean,['title'],['text'],False +Do any entries have a negative sentiment according to the Cardiff NLP model?,False,boolean,['title_gx_cardiff_nlp_sentiment'],['category'],False +"Is the term 'linux' mentioned in the ""Clusters II"" column?",True,boolean,['Clusters II'],['category'],True +How many entries were posted in the morning?,1516,number,['partofday'],['category'],1 +What's the highest score received by an entry?,6015,number,['score'],['number[uint16]'],2517 +"On average, how many descendants does an entry have?",339.2486205432937,number,['descendants'],['number[UInt16]'],558.0 +How many entries are in the Autumn season?,2301,number,['season'],['category'],8 +Which day of the week has the most entries?,Tuesday,category,['weekday_name'],['category'],Wednesday +What is the predominant language used in titles?,en,category,['title_gx_lang'],['category'],en +In which season was the entry with the highest score posted?,Spring,category,"['score', 'season']","['number[uint16]', 'category']",Summer +On which part of the day are most entries posted?,afternoon,category,['partofday'],['category'],afternoon +"List the top 4 most frequent terms in the ""Clusters II"" column.","['year, work, new', 'google, web, firefox, open', 'apple, linux, rust, iphone', 'facebook, twitter, die, account']",list[category],['Clusters II'],['category'],"['year, work, new', 'google, web, firefox, open', 'apple, linux, rust, iphone', 'amazon, database, sqlite, sql']" +Name the bottom 3 month names in terms of entry frequency.,"['August', 'December', 'July']",list[category],['month_name'],['category'],"['December', 'June', 'January']" +Identify the top 5 weekdays based on entry frequency.,"['Tuesday', 'Wednesday', 'Thursday', 'Monday', 'Friday']",list[category],['weekday_name'],['category'],"['Wednesday', 'Friday', 'Tuesday', 'Monday', 'Sunday']" +Provide the bottom 4 seasons in terms of entry count.,"['Spring', 'Winter', 'Autumn', 'Summer']",list[category],['season'],['category'],"['Autumn', 'Summer', 'Winter', 'Spring']" +List the top 3 scores in the dataset.,"[6015, 5771, 4338]",list[number],['score'],['number[uint16]'],"[2517, 1181, 1070]" +Name the bottom 5 title text lengths.,"[1.0, 2.0, 2.0, 2.0, 2.0]",list[number],['title_gx_text_length'],['number[UInt8]'],"[16.0, 20.0, 22.0, 30.0, 31.0]" +Identify the top 4 numbers of descendants.,"[4576.0, 3678.0, 3676.0, 3463.0]",list[number],['descendants'],['number[UInt16]'],"[3676.0, 1609.0, 524.0, 512.0]" +Provide the bottom 6 scores in the dataset.,"[501, 501, 501, 501, 501, 501]",list[number],['score'],['number[uint16]'],"[501, 516, 526, 534, 544, 583]" diff --git a/016_Hacker_News/sample.csv b/data/017_Hacker/sample.csv similarity index 100% rename from 016_Hacker_News/sample.csv rename to data/017_Hacker/sample.csv diff --git a/017_Staff_Satisfaction/all.parquet b/data/018_Staff/all.parquet similarity index 100% rename from 017_Staff_Satisfaction/all.parquet rename to data/018_Staff/all.parquet diff --git a/017_Staff_Satisfaction/info.yml b/data/018_Staff/info.yml similarity index 100% rename from 017_Staff_Satisfaction/info.yml rename to data/018_Staff/info.yml diff --git a/data/018_Staff/qa.csv b/data/018_Staff/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..0b82fbd8e6ebfc29abd87ae2d9f34ce1be1e3c56 --- /dev/null +++ b/data/018_Staff/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Are there any employees with more than 7 projects?,False,boolean,[Number of Projects],['number[uint8]'],False +Has any employee worked for more than 300 hours on average per month?,True,boolean,[Average Monthly Hours],['number[uint16]'],False +Are all satisfaction levels above 0.5?,False,boolean,[Satisfaction Level],['number[double]'],False +Were there any employees hired in 2019?,True,boolean,[Date Hired],"['date[ns, UTC]']",False +How many unique departments are there?,10,number,[Department],['category'],9 +What's the maximum number of years an employee has been in the company?,10,number,[Years in the Company],['number[uint8]'],6 +How many employees have been promoted in the last 5 years?,319,number,[Promoted in the last 5 years?],['category'],0 +"On average, how many hours do employees work monthly?",201.05,number,[Average Monthly Hours],['number[uint16]'],188.15 +Which department has the highest number of employees?,sales,category,[Department],['category'],support +What's the most common salary level among employees?,low,category,[salary],['category'],low +Which year had the highest number of employees hired?,2017,category,[Date Hired],"['date[ns, UTC]']",2017 +Which salary level has the least number of employees who had an accident at work?,high,category,"[salary, Work Accident]","['category', 'category']",Not found +Name the top 4 departments with the most employees.,"['sales', 'technical', 'support', 'IT']",list[category],[Department],['category'],"['support', 'technical', 'marketing', 'accounting']" +List the bottom 3 departments by the number of promotions in the last 5 years.,"['hr', 'accounting', 'IT']",list[category],"[Department, Promoted in the last 5 years?]","['category', 'category']",['Not found'] +Identify the top 5 departments with the highest average satisfaction levels.,"['management', 'RandD', 'product_mng', 'marketing', 'support']",list[category],"[Department, Satisfaction Level]","['category', 'number[double]']","['IT', 'RandD', 'accounting', 'technical', 'product_mng']" +What are the bottom 2 departments by average monthly hours worked?,"['hr', 'marketing']",list[category],"[Department, Average Monthly Hours]","['category', 'number[uint16]']","['sales', 'RandD']" +Identify the top 3 years with the highest employee hiring.,"['2017', '2018', '2016']",list[number],[Date Hired],"['date[ns, UTC]']","[2017, 2016, 2018]" +Which are the top 4 satisfaction levels among employees who left?,"[0.1, 0.11, 0.09, 0.37]",list[number],"[Satisfaction Level, Left]","['number[double]', 'category']",[] +List the bottom 5 average monthly hours among employees who were promoted in the last 5 years.,"[215, 133, 159, 241, 247]",list[number],"[Average Monthly Hours, Promoted in the last 5 years?]","['number[uint16]', 'category']",[0] +Which are the top 6 years based on the last evaluation scores?,"[0.55, 0.5, 0.54, 0.51, 0.57, 0.49]",list[number],[Last Evaluation],['number[double]'],"[2015, 2014, 2016, 2018, 2017]" diff --git a/017_Staff_Satisfaction/sample.csv b/data/018_Staff/sample.csv similarity index 100% rename from 017_Staff_Satisfaction/sample.csv rename to data/018_Staff/sample.csv diff --git a/018_Aircraft_Accidents/all.parquet b/data/019_Aircraft/all.parquet similarity index 100% rename from 018_Aircraft_Accidents/all.parquet rename to data/019_Aircraft/all.parquet diff --git a/018_Aircraft_Accidents/info.yml b/data/019_Aircraft/info.yml similarity index 100% rename from 018_Aircraft_Accidents/info.yml rename to data/019_Aircraft/info.yml diff --git a/data/019_Aircraft/qa.csv b/data/019_Aircraft/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..b155c4b7d0d172d935590c3951a5755339f6c4f8 --- /dev/null +++ b/data/019_Aircraft/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Did any incident result in the total destruction of the aircraft?,True,boolean,['Aircaft_Damage_Type'],['category'],False +Have there been any incidents where the cause was related to the undercarriage of the aircraft?,True,boolean,['Incident_Cause(es)'],['category'],False +Has there been any instance where the ground casualties were non-zero?,True,boolean,['Ground_Casualties'],['category'],True +Are there incidents where the aircraft was involved in a collision?,True,boolean,"['Incident_Category', 'Incident_Cause(es)']","['category', 'category']",True +How many unique aircraft models are in the dataset?,3523,number,['Aircaft_Model'],['category'],20 +What's the highest number of occupants recorded in an incident?,524.0,number,['Onboard_Total'],['category'],86 +How many incidents occurred in January 2022?,7,number,['Date'],"['date[ns, UTC]']",0 +How many incidents resulted in non-zero fatalities?,0,number,['Fatalities'],['number[uint16]'],10 +Which aircraft model was involved in the most incidents?,Junkers Ju-52/3m,category,['Aircaft_Model'],['category'],Antonov An-2V +What was the cause of the incident that resulted in the most fatalities?,"Airplane - Pressurization, Airplane - Pressurization - Bulkhead failure, Airplane - Pressurization - Explosive decompression, Maintenance - (repair of) previous damage, Result - Loss of control",category,"['Incident_Cause(es)', 'Fatalities']","['category', 'number[uint16]']","Result - Loss of control, Security - Sabotage (bomb)" +What is the most common phase of aircraft during incidents?,En route (ENR),category,['Aircraft_Phase'],['category'],Landing (LDG) +What is the location of the incident with the highest number of onboard occupants?,near Ueno Village...,category,"['Incident_Location', 'Onboard_Total']","['category', 'category']", +What are the top 3 most common causes of incidents?,"['Info-Unavailable', 'Result - Runway excursion', 'Result - Damaged on the ground']",list[category],['Incident_Cause(es)'],['category'],"['Info-Unavailable', 'Result - Damaged on the ground', 'Result - Loss of control']" +List the top 5 locations where the most incidents have occurred.,"['unknown', 'Havana-José Martí International Airport (HAV)', 'Miami International Airport, FL (MIA)', 'Rio de Janeiro-Galeão International Airport, RJ (GIG)', 'Beirut International Airport (BEY)']",list[category],['Incident_Location'],['category'],"['near Loukhi', 'Arnhem', 'Glasgow-Preswick Airport', 'near Olpoi', 'Sioux Falls-Joe Foss Field Airport']" +Name the 4 most frequently occurring aircraft operators in the dataset.,"['USAAF', 'USAF', 'RAF', 'US Navy']",list[category],['Aircaft_Operator'],['category'],"['USAAF', 'Aeroflot, Northern', 'United Airlines', 'British Aerospace']" +What are the top 2 most common types of aircraft damage?,"['Damaged beyond repair', 'Substantial']",list[category],['Aircaft_Damage_Type'],['category'],"['Damaged beyond repair', 'Substantial']" +What are the 5 highest numbers of onboard passengers in incidents?,"[509.0, 503.0, 497.0, 451.0, 440.0]",list[number],['Onboard_Passengers'],['category'],"[81, 39, 14, 11, 8]" +List the 3 highest numbers of onboard crew in incidents.,"[32.0, 31.0, 29.0]",list[number],['Onboard_Crew'],['category'],"[5, 4, 3]" +Identify the 4 highest numbers of total onboard occupants in incidents.,"[524.0, 521.0, 517.0, 469.0]",list[number],['Onboard_Total'],['category'],"[86, 44, 19, 15]" +What are the 6 highest numbers of ground casualties in incidents?,"[1600, 900, 237, 107, 88, 87]",list[number],['Ground_Casualties'],['category'],"[9, 1]" diff --git a/018_Aircraft_Accidents/sample.csv b/data/019_Aircraft/sample.csv similarity index 100% rename from 018_Aircraft_Accidents/sample.csv rename to data/019_Aircraft/sample.csv diff --git a/019_Real_Estate_Madrid/all.parquet b/data/020_Real/all.parquet similarity index 100% rename from 019_Real_Estate_Madrid/all.parquet rename to data/020_Real/all.parquet diff --git a/019_Real_Estate_Madrid/info.yml b/data/020_Real/info.yml similarity index 100% rename from 019_Real_Estate_Madrid/info.yml rename to data/020_Real/info.yml diff --git a/data/020_Real/qa.csv b/data/020_Real/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..e690a09f1b3d79cab80088e4039295f3048efe11 --- /dev/null +++ b/data/020_Real/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +"Are there any properties with a price over 1,000,000?",True,boolean,['Precio'],['number[uint32]'],True +Any property with more than 10 bedrooms?,True,boolean,['Habitaciones'],['number[uint8]'],False +Are there properties with zero bathrooms?,False,boolean,['Baños'],['number[uint8]'],False +Has any property been listed for more than 100 days?,True,boolean,['Duración'],['number[uint16]'],True +What's the highest price in the dataset?,17000000.0,number,['Precio'],['number[uint32]'],1245000.0 +What's the total number of properties listed?,26026,number,[],[],20 +What's the longest duration a property has been listed?,2535.0,number,['Duración'],['number[uint16]'],300.0 +What's the largest property (by surface area) listed?,5504.0,number,['Superficie'],['number[uint16]'],350.0 +What's the most common type of property listed?,Piso,category,['Tipo'],['category'],Piso +Which advertiser has listed the most properties?,housell,category,['Anunciante'],['category'],gilmar_villalba +Which property has the highest price?,GM31-121816,category,"['Referencia', 'Precio']","['category', 'number[uint32]']",14075097 +Which property has the largest surface area?,IF5563-FINCA VALLE LOZOYA,category,"['Referencia', 'Superficie']","['category', 'number[uint16]']",2126-002573 +What are the top 5 types of properties listed?,"['Piso', 'Chalet', 'Apartamento', 'Chalet adosado', 'Chalet unifamiliar']",list[category],['Tipo'],['category'],"['Piso', 'Chalet', 'Apartamento', 'Chalet adosado', 'Chalet pareado']" +Name the 3 advertisers who have listed the most properties.,"['housell', 'servihabitat_central', 'pradesa_proyectos_inmobiliarios']",list[category],['Anunciante'],['category'],"['gilmar_villalba', 'consulting_parque_de_los_estados', 'vivantial_okuant']" +What are the 4 most common localities for properties listed?,"['Madrid Capital', 'Torrejón de Ardoz', 'Alcalá de Henares', 'Móstoles']",list[category],['Localidad'],['category'],"['Madrid Capital', 'Alpedrete', 'Fuenlabrada', 'Valdemorillo']" +What are the 2 most common districts for properties listed?,"['Centro', 'Salamanca']",list[category],['Distrito'],['category'],"['San Blas', 'Centro']" +What are the 5 highest property prices listed?,"[17000000.0, 13600000.0, 13250000.0, 13000000.0, 12000000.0]",list[number],['Precio'],['number[uint32]'],"[1245000.0, 950000.0, 590000.0, 555000.0, 550000.0]" +List the 3 longest durations properties have been listed.,"[2535.0, 2534.0, 2285.0]",list[number],['Duración'],['number[uint16]'],"[300.0, 146.0, 129.0]" +Identify the 4 largest properties (by surface area) listed.,"[5504.0, 3957.0, 2974.0, 2927.0]",list[number],['Superficie'],['number[uint16]'],"[350.0, 311.0, 300.0, 250.0]" +What are the 6 highest numbers of bedrooms in properties listed?,"[20, 20, 20, 20, 20, 20]",list[number],['Habitaciones'],['number[uint8]'],"[9, 5, 5, 4, 4, 3]" diff --git a/019_Real_Estate_Madrid/sample.csv b/data/020_Real/sample.csv similarity index 100% rename from 019_Real_Estate_Madrid/sample.csv rename to data/020_Real/sample.csv diff --git a/020_Telco_Customer_Churn/all.parquet b/data/021_Telco/all.parquet similarity index 100% rename from 020_Telco_Customer_Churn/all.parquet rename to data/021_Telco/all.parquet diff --git a/020_Telco_Customer_Churn/info.yml b/data/021_Telco/info.yml similarity index 100% rename from 020_Telco_Customer_Churn/info.yml rename to data/021_Telco/info.yml diff --git a/data/021_Telco/qa.csv b/data/021_Telco/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..6c11a534ab125686b79bfe60dd07fb7981442e1a --- /dev/null +++ b/data/021_Telco/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Are there more than 2000 customers with a monthly charge higher than $80?,True,boolean,['MonthlyCharges'],['number[double]'],False +Do all customers have phone service?,True,boolean,['PhoneService'],['category'],False +Are there any customers with no internet service?,True,boolean,['InternetService'],['category'],True +Are there any customers who are senior citizens and have dependents?,True,boolean,"['SeniorCitizen', 'Dependents']","['number[uint8]', 'category']",True +How many unique customers are there in the dataset?,7043,number,['customerID'],['category'],20 +What's the highest monthly charge?,118.75,number,['MonthlyCharges'],['number[double]'],104.0 +What's the total number of customers?,7043,number,[],[],20 +What's the longest tenure?,72,number,['tenure'],['number[uint8]'],72 +What's the most common payment method?,Electronic check,category,['PaymentMethod'],['category'],Electronic check +What's the most common contract type?,Month-to-month,category,['Contract'],['category'],Month-to-month +Which customer has the highest total charge?,2889-FPWRM,category,"['customerID', 'TotalCharges']","['category', 'number[double]']",4853-RULSV +Which customer has the highest monthly charge?,7569-NMZYQ,category,"['customerID', 'MonthlyCharges']","['category', 'number[double]']",4853-RULSV +What are the top 3 most common internet services?,"['Fiber optic', 'DSL', 'No']",list[category],['InternetService'],['category'],"['Fiber optic', 'DSL', 'No']" +Name the 4 most common payment methods.,"['Electronic check', 'Mailed check', 'Bank transfer (automatic)', 'Credit card (automatic)']",list[category],['PaymentMethod'],['category'],"['Electronic check', 'Bank transfer (automatic)', 'Mailed check', 'Credit card (automatic)']" +What are the 2 most common types of contract?,"['Month-to-month', 'Two year']",list[category],['Contract'],['category'],"['Month-to-month', 'Two year']" +What are the 5 most common services for which customers have multiple lines?,"['No', 'Yes', 'No phone service']",list[category],['MultipleLines'],['category'],"['Yes', 'No phone service']" +What are the 5 highest total charges?,"[8684.8, 8672.45, 8670.1, 8594.4, 8564.75]",list[number],['TotalCharges'],['number[double]'],"[7250.15, 6127.6, 5016.65, 3340.55, 3260.1]" +What are the 4 highest monthly charges?,"[118.75, 118.65, 118.6, 118.6]",list[number],['MonthlyCharges'],['number[double]'],"[104.0, 95.15, 89.6, 89.4]" +What are the 6 longest tenures?,"[72, 72, 72, 72, 72, 72]",list[number],['tenure'],['number[uint8]'],"[72, 70, 68, 67, 52, 41]" +What are the 3 shortest tenures?,"[0, 0, 0]",list[number],['tenure'],['number[uint8]'],"[1, 1, 1]" diff --git a/020_Telco_Customer_Churn/sample.csv b/data/021_Telco/sample.csv similarity index 100% rename from 020_Telco_Customer_Churn/sample.csv rename to data/021_Telco/sample.csv diff --git a/021_Airbnbs_Listings_NY/all.parquet b/data/022_Airbnbs/all.parquet similarity index 100% rename from 021_Airbnbs_Listings_NY/all.parquet rename to data/022_Airbnbs/all.parquet diff --git a/021_Airbnbs_Listings_NY/info.yml b/data/022_Airbnbs/info.yml similarity index 100% rename from 021_Airbnbs_Listings_NY/info.yml rename to data/022_Airbnbs/info.yml diff --git a/data/022_Airbnbs/qa.csv b/data/022_Airbnbs/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..a523fcefa89b89995462f354cfb6dda57c14b044 --- /dev/null +++ b/data/022_Airbnbs/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Is there a listing with a review score rating of 100?,True,boolean,['review_scores_rating'],['number[UInt8]'],True +Are there any hosts who have listed more than 10 properties?,True,boolean,['host_total_listings_count'],['number[UInt16]'],True +Are all listings instantly bookable?,False,boolean,['instant_bookable'],['category'],True +Is there a listing that requires a minimum of 365 nights?,True,boolean,['minimum_nights'],['number[uint16]'],False +How many unique hosts are there in the dataset?,26765,number,['host_id'],['number[uint32]'],20 +What is the highest number of listings a single host has?,2739.0,number,['host_total_listings_count'],['number[UInt16]'],38.0 +How many unique locations are listed by the hosts?,1316,number,['host_location'],['category'],6 +What is the average review score rating across all listings?,93.767188,number,['review_scores_rating'],['number[UInt8]'],95.33333333333333 +What is the most common host location?,"New York, New York, United States",category,['host_location'],['category'],"New York, New York, United States" +What is the name of the listing with the most bedrooms?,"Walk to UN, Macy's & Empire State B",category,"['bedrooms', 'name']","['number[UInt8]', 'text']",Historic Gem Close to SI Ferry +Which location has the highest number of listings?,"New York, New York, United States",category,['host_location'],['category'],"New York, New York, United States" +What is the most common property type?,Entire apartment,category,['property_type'],['category'],Entire apartment +What are the top 5 unique host locations with the most listings?,"['New York, New York, United States', 'US', 'Brooklyn, New York, United States', 'Queens, New York, United States', 'Bronx, New York, United States']",list[category],['host_location'],['category'],"['New York, New York, United States', 'US', 'Brooklyn, New York, United States', 'FR', 'Sydney, New South Wales, Australia']" +Name the 3 listings with the lowest review score ratings.,"['Studio Apartment in East Williamsburg', 'Spacious Artist Loft Williamsburg', 'Cute 1 BR in the Lower East Side']",list[category],"['review_scores_rating', 'name']","['number[UInt8]', 'text']","['Historic Gem Close to SI Ferry', 'A+ Location Studio Apartment (Queen Bed & Futon)', 'Private Room in Heart of East Village!']" +List the 4 most common property types.,"['Entire apartment', 'Private room in apartment', 'Entire condominium', 'Entire house']",list[category],['property_type'],['category'],"['Entire apartment', 'Private room in apartment', 'Entire guest suite', 'Entire condominium']" +Who are the top 6 hosts with the most listings?,"['107434423', '305240193', '137358866', '51501835', '6168257', '22541573']",list[category],"['host_id', 'listing_id']","['number[uint32]', 'number[uint32]']","[62803, 1385157, 1898675, 3734323, 14295824, 14707270]" +What are the top 3 listing ids with the highest review score ratings?,"['4370230', '10166986', '14218173']",list[number],"['review_scores_rating', 'listing_id']","['number[UInt8]', 'number[uint32]']","[9334365, 8385447, 4016121]" +What are the 5 listing ids with the lowest number of minimum nights required?,"['4659046', '13192217', '17441150', '22058411', '28389772']",list[number],"['minimum_nights', 'listing_id']","['number[uint16]', 'number[uint32]']","[12584072, 44505052, 39727144, 45912795, 47406985]" +List the 4 listing ids of the properties with the highest number of bedrooms.,"['8536270', '2261367', '41552433', '23124338']",list[number],"['bedrooms', 'listing_id']","['number[UInt8]', 'number[uint32]']","[12584072, 27570074, 8385447, 31898478]" +What are the 6 listing ids with the lowest review score location?,"['18972792', '30422813', '30929071', '40777675', '45217842', '45217978']",list[number],"['review_scores_location', 'listing_id']","['number[UInt8]', 'number[uint32]']","[9334365, 31898478, 12584072, 33156370, 44505052, 25939748]" diff --git a/021_Airbnbs_Listings_NY/sample.csv b/data/022_Airbnbs/sample.csv similarity index 100% rename from 021_Airbnbs_Listings_NY/sample.csv rename to data/022_Airbnbs/sample.csv diff --git a/022_Climate_Madrid/all.parquet b/data/023_Climate/all.parquet similarity index 100% rename from 022_Climate_Madrid/all.parquet rename to data/023_Climate/all.parquet diff --git a/022_Climate_Madrid/info.yml b/data/023_Climate/info.yml similarity index 70% rename from 022_Climate_Madrid/info.yml rename to data/023_Climate/info.yml index 31a7cc96c99385b33445687476295e03b29945ef..3fb0a67864d03eb2e67417d9373d7aac6cdf308b 100644 --- a/022_Climate_Madrid/info.yml +++ b/data/023_Climate/info.yml @@ -1,4 +1,4 @@ -Explore: https://app.graphext.com/projects/UHJvamVjdC00NzM4Mw==/v/data +Explore: https://public.graphext.com/83a75b4f1cea8df4/index.html?section=data Source: https://public.graphext.com/83a75b4f1cea8df4/index.html?section=data Title: 🌡 The Climate in Madrid 1920-2020 tags: diff --git a/data/023_Climate/qa.csv b/data/023_Climate/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..137379ad598cad0c52f257734a4c99bb2a26dc53 --- /dev/null +++ b/data/023_Climate/qa.csv @@ -0,0 +1,21 @@ +question,answer,columns_used,type,column_types,sample_answer +Was there a day when the minimum temperature was below zero and it didn't rain?,True,"[tmin, prec]",boolean,"['number[double]', 'number[double]']",True +Are there records where the solar radiation exceeds 10 but the maximum temperature was below 20?,True,"[sol, tmax]",boolean,"['number[double]', 'number[double]']",True +Did any day with maximum wind speed above 15 also have average wind speed below 5?,True,"[racha, velmedia]",boolean,"['number[double]', 'number[double]']",False +Were there days in the summer where the minimum temperature dropped below 10?,True,"[season, tmin]",boolean,"['category', 'number[double]']",False +How many days had a maximum temperature above 30 degrees?,5500,[tmax],number,['number[double]'],3 +"On average, what's the minimum temperature during winters?",2.7196082770831027,"[season, tmin]",number,"['category', 'number[double]']", +How many unique days had solar radiation measurements?,28615,[sol],number,['number[double]'],15 +What's the highest wind speed ever recorded?,32.2,[racha],number,['number[double]'],14.4 +On which weekday did the highest temperature ever occur?,Friday,"[tmax, weekday_name]",category,"['number[double]', 'category']",Thursday +In which season do we find the highest average solar radiation?,Summer,"[season, sol]",category,"['category', 'number[double]']",Summer +Which month had the lowest average wind speed?,October,"[month_name, velmedia]",category,"['category', 'number[double]']",February +On what date was the highest pressure ever recorded?,2016-12-22T00:00:00Z,"[presMax, fecha]",category,"['number[double]', 'date[ns, UTC]']",1950-02-14T00:00:00Z +What are the top 3 months with the highest average maximum temperatures?,"['July', 'August', 'June']","[month_name, tmax]",list[category],"['category', 'number[double]']","['July', 'August', 'September']" +"Which are the 5 weekdays with the most rain, ranked from highest to lowest?","['Friday', 'Sunday', 'Saturday', 'Thursday', 'Wednesday']","[weekday_name, prec]",list[category],"['category', 'number[double]']","['Saturday', 'Sunday', 'Wednesday', 'Thursday', 'Tuesday']" +"List the 4 seasons ranked by average solar radiation, from highest to lowest.","['Summer', 'Spring', 'Autumn', 'Winter']","[season, sol]",list[category],"['category', 'number[double]']","['Summer', 'Autumn', 'Spring', 'Winter']" +Which 2 months recorded the lowest average minimum temperatures?,"['January', 'December']","[month_name, tmin]",list[category],"['category', 'number[double]']","['February', 'December']" +List the top 5 recorded maximum temperatures.,"[40.7, 40.6, 40.0, 40.0, 40.0]",[tmax],list[number],['number[double]'],"[37.5, 36.0, 33.3, 28.6, 26.6]" +What are the 4 lowest wind speeds ever recorded?,"[0.0, 0.0, 0.0, 0.0]",[velmedia],list[number],['number[double]'],"[0.3, 0.3, 0.3, 0.8]" +Rank the highest 3 solar radiation measurements.,"[14.9, 14.8, 14.7]",[sol],list[number],['number[double]'],"[13.0, 12.7, 12.3]" +Which 6 days of the year (numbered from 1 to 365/366) had the highest average temperatures?,"[209, 210, 208, 207, 211, 205]","[dayofyear, tmed]",list[number],"['number[uint16]', 'number[double]']","[208, 206, 205, 235, 260, 103]" diff --git a/022_Climate_Madrid/sample.csv b/data/023_Climate/sample.csv similarity index 100% rename from 022_Climate_Madrid/sample.csv rename to data/023_Climate/sample.csv diff --git a/023_Salary_Survey_Spain/all.parquet b/data/024_Salary/all.parquet similarity index 100% rename from 023_Salary_Survey_Spain/all.parquet rename to data/024_Salary/all.parquet diff --git a/023_Salary_Survey_Spain/info.yml b/data/024_Salary/info.yml similarity index 100% rename from 023_Salary_Survey_Spain/info.yml rename to data/024_Salary/info.yml diff --git a/data/024_Salary/qa.csv b/data/024_Salary/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..81cba1a049947b5a335a530e98cc624ff9a14ce9 --- /dev/null +++ b/data/024_Salary/qa.csv @@ -0,0 +1,21 @@ +question,answer,columns_used,type,column_types,sample_answer +"Are there records where the RETRINOIN_xRZI exceeds 10,000?",True,[RETRINOIN_xRZI],boolean,['number[double]'],True +Are there any female respondents who belong to the ESTE NUTS1 region?,True,"[SEXO, NUTS1]",boolean,"['category', 'category']",True +Do we have respondents who fall under both PRIVADO control and NACIONAL market?,True,"[CONTROL, MERCADO]",boolean,"['category', 'category']",True +"Are there records with RETRINOIN_WwQk less than 5,000?",True,[RETRINOIN_WwQk],boolean,['number[double]'],False +How many unique respondents belong to the ESTE NUTS1 region?,58852,[NUTS1],number,['category'],2 +"On average, what's the RETRINOIN value for male respondents?",29370.243704368546,"[SEXO, RETRINOIN]",number,"['category', 'number[double]']",26024.9957143 +What's the highest value for RETRINOIN_ac1q in the dataset?,199496.34,[RETRINOIN_ac1q],number,['number[double]'],59117.54 +How many unique clusters are present in the 'umap_cluster' column?,73,[umap_cluster],number,['category'],15 +Which 'ANOS2' category has the most number of respondents?,DE 40 A 49,[ANOS2],category,['category'],DE 40 A 49 +In which 'NUTS1' region do we find the highest average RETRINOIN?,COMUNIDAD DE MADRID,"[NUTS1, RETRINOIN]",category,"['category', 'number[double]']",CENTRO +Which 'MERCADO' category is the least common in the dataset?,UNIÓN EUROPEA,[MERCADO],category,['category'],UNIÓN EUROPEA +Which 'umap_cluster' is the most dominant in the dataset?,Cluster 1,[umap_cluster],category,['category'],Cluster 7 +What are the top 4 'CNACE' categories with the highest frequency?,"['Actividades administrativas y servicios auxliares: actividad', 'Actividades sanitarias y de servicios sociales: actividades', 'Comercio al por mayor y al por menor; reparación de vehículo', 'Actividades profesionales, científicas y técnicas: actividad']",[CNACE],list[category],['category'],"[\'Industria manufacturera: industria de la alimentación, fabri\', \'Actividades administrativas y servicios auxliares: actividad\', \'Actividades profesionales, científicas y técnicas: actividad\', \'Actividades artísticas, recreativas y de entrenimiento: acti\']" +Which are the 3 least common 'ANOS2' categories in the dataset?,"['MENOS 19 AÑOS', 'MÁS DE 59', 'DE 20 A 29']",[ANOS2],list[category],['category'],"[\'DE 50 A 59\', \'DE 20 A 29\', \'DE 30 A 39\']" +List the top 5 'NUTS1' regions by frequency.,"['ESTE', 'COMUNIDAD DE MADRID', 'NORESTE', 'SUR', 'CENTRO']",[NUTS1],list[category],['category'],"[\'ESTE\', \'NOROESTE\', \'NORESTE\', \'CENTRO\', \'SUR\']" +Which 2 'umap_cluster' categories are the least represented?,"['Cluster 71', 'Cluster 73']",[umap_cluster],list[category],['category'],"[\'Cluster 20\', \'Cluster 10\']" +List the top 5 recorded RETRINOIN values.,"[4225998.36, 4153877.05, 4021902.63, 3903390.45, 2192967.2]",[RETRINOIN],list[number],['number[double]'],"[59117.54, 50502.32, 35417.81, 30993.25, 29699.05]" +What are the 4 lowest x values in the dataset?,"[-23714.217, -23706.5, -23698.271, -23697.166]",[x],list[number],['number[double]'],"[-19757.53, -16221.655, -10021.664, -5854.7065]" +Rank the highest 3 y values in the dataset.,"[28352.02, 28313.926, 28283.78]",[y],list[number],['number[double]'],"[22543.754, 21725.412, 15036.662]" +Which 6 RETRINOIN_ac1q values are the most frequent in the dataset?,"[0.0, 10302.6, 18000.0, 30000.0, 12000.0, 21000.0]",[RETRINOIN_ac1q],list[number],['number[double]'],"[29699.05, 13871.31, 50502.32, 27320.4, 26262.3, 20237.57]" diff --git a/023_Salary_Survey_Spain/sample.csv b/data/024_Salary/sample.csv similarity index 100% rename from 023_Salary_Survey_Spain/sample.csv rename to data/024_Salary/sample.csv diff --git a/024_Data_Driven_SEO/all.parquet b/data/025_Data/all.parquet similarity index 100% rename from 024_Data_Driven_SEO/all.parquet rename to data/025_Data/all.parquet diff --git a/024_Data_Driven_SEO/info.yml b/data/025_Data/info.yml similarity index 100% rename from 024_Data_Driven_SEO/info.yml rename to data/025_Data/info.yml diff --git a/data/025_Data/qa.csv b/data/025_Data/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..f85e0a39a6c87bcf5964b5917feb66ebb67aa7a7 --- /dev/null +++ b/data/025_Data/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Is the most visited URL related to 'no code data science'?,True,boolean,"['URLs', 'Keyword', 'Ranking']","['url', 'category', 'number[uint8]']",True +Does any URL have a competition level of 'Low'?,True,boolean,"['URLs', 'Competition']","['url', 'category']",True +Are there any URLs with an average monthly searches above 1000?,False,boolean,"['URLs', 'Avg. monthly searches']","['url', 'number[uint8]']",False +Is the URL with the highest ranking also the one with the highest monthly searches?,True,boolean,"['URLs', 'Ranking', 'Avg. monthly searches']","['url', 'number[uint8]', 'number[uint8]']",True +How many unique URLs are in the dataset?,28,number,['URLs'],['url'],13 +What is the highest ranking value in the dataset?,11,number,['Ranking'],['number[uint8]'],11 +What is the minimum average monthly searches in the dataset?,50,number,['Avg. monthly searches'],['number[uint8]'],50 +How many unique keywords are present in the dataset?,6,number,['Keyword'],['category'],6 +What is the competition level of the highest-ranked URL?,Medium,category,"['Ranking', 'Competition']","['number[uint8]', 'category']",Low +What keyword has the highest average monthly searches?,no code data science,category,"['Avg. monthly searches', 'Keyword']","['number[uint8]', 'category']",no code analytics platform +What is the competition level for the URL with the lowest ranking?,Low,category,"['Ranking', 'Competition']","['number[uint8]', 'category']",Medium +What keyword is associated with the URL with the highest ranking?,no code data science,category,"['Ranking', 'Keyword']","['number[uint8]', 'category']",no code analytics +What are the top 3 URLs with the highest average monthly searches?,"['https://www.obviously.ai/', 'https://venturebeat.com/2021/10/12/no-code-ai-startup-obviously-ai-raises-4-7m/', 'https://hbr.org/2021/11/how-no-code-platforms-could-disrupt-the-it-industry']",list[category],"['URLs', 'Avg. monthly searches']","['url', 'number[uint8]']","[https://towardsdatascience.com/top-8-no-code-machine-learning-platforms-you-should-use-in-2020-1d1801300dd0, https://hbr.org/2021/11/how-no-code-platforms-can-bring-ai-to-small-and-midsize-businesses, https://www.obviously.ai/]" +List the bottom 2 competition levels of URLs with ranking less than 5.,"['Medium', 'Unknown']",list[category],"['Ranking', 'Competition']","['number[uint8]', 'category']","[High, High]" +Which are the top 4 keywords associated with the URLs of highest rankings?,"['no code data science', 'no code data analytics', 'no code data science', 'no code data science']",list[category],"['Ranking', 'Keyword']","['number[uint8]', 'category']","[no code analytics, no code data science, no code analytics platform, no code data science]" +Enumerate the bottom 3 URLs with the lowest rankings.,"['https://www.obviously.ai/', 'https://www.obviously.ai/', 'https://venturebeat.com/2021/10/12/no-code-ai-startup-obviously-ai-raises-4-7m/']",list[category],"['Ranking', 'URLs']","['number[uint8]', 'url']","[https://www.obviously.ai/, https://hbr.org/2021/11/how-no-code-platforms-can-bring-ai-to-small-and-midsize-businesses, https://analyticsindiamag.com/top-12-no-code-machine-learning-platforms-in-2021/]" +What are the top 4 rankings associated with the keyword 'no code data science'?,"[10, 9, 8, 7]",list[number],"['Keyword', 'Ranking']","['category', 'number[uint8]']","[10, 9, 6, 4]" +List the bottom 3 average monthly searches for URLs with medium competition.,"[50, 50, 50]",list[number],"['Competition', 'Avg. monthly searches']","['category', 'number[uint8]']","[50, 50, 50]" +Provide the top 5 rankings of URLs with low competition (if any).,"[11, 10, 10, 9, 9]",list[number],"['Competition', 'Ranking']","['category', 'number[uint8]']","[11, 8, 6, 6, 5]" +Specify the bottom 2 average monthly searches for URLs with the highest rankings.,"[50, 50]",list[number],"['Ranking', 'Avg. monthly searches']","['number[uint8]', 'number[uint8]']","[50, 50]" diff --git a/024_Data_Driven_SEO/sample.csv b/data/025_Data/sample.csv similarity index 100% rename from 024_Data_Driven_SEO/sample.csv rename to data/025_Data/sample.csv diff --git a/025_Predicting_Wine_Quality/all.parquet b/data/026_Predicting/all.parquet similarity index 100% rename from 025_Predicting_Wine_Quality/all.parquet rename to data/026_Predicting/all.parquet diff --git a/025_Predicting_Wine_Quality/info.yml b/data/026_Predicting/info.yml similarity index 100% rename from 025_Predicting_Wine_Quality/info.yml rename to data/026_Predicting/info.yml diff --git a/data/026_Predicting/qa.csv b/data/026_Predicting/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..3b27b1ed185bb7fbd10152898696033ff39d9080 --- /dev/null +++ b/data/026_Predicting/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Is there any wine with a quality rating of 10?,False,boolean,['quality'],['number[uint8]'],False +Are there any wines with residual sugar above 15g/dm^3?,True,boolean,['residual sugar'],['number[double]'],False +Is the highest alcohol content wine also the one with the highest quality rating?,False,boolean,"['alcohol', 'quality']","['number[double]', 'number[uint8]']",False +Does any wine have a pH level below 2.5?,False,boolean,['pH'],['number[double]'],False +How many unique quality ratings are there in the dataset?,6,number,['quality'],['number[uint8]'],5 +What is the maximum fixed acidity level found in the dataset?,15.9,number,['fixed acidity'],['number[double]'],10.7 +What is the minimum volatile acidity level in the dataset?,0.12,number,['volatile acidity'],['number[double]'],0.28 +How many wines have free sulfur dioxide above 50 mg/dm^3?,16,number,['free sulfur dioxide'],['number[UInt8]'],0 +What is the quality rating of the wine with the highest alcohol content?,5,category,"['alcohol', 'quality']","['number[double]', 'number[uint8]']",7.0 +What is the quality rating of the wine with the highest fixed acidity?,5,category,"['fixed acidity', 'quality']","['number[double]', 'number[uint8]']",6.0 +What is the quality rating of the wine with the lowest volatile acidity?,7,category,"['volatile acidity', 'quality']","['number[double]', 'number[uint8]']",7.0 +What is the quality rating of the wine with the highest pH level?,6,category,"['pH', 'quality']","['number[double]', 'number[uint8]']",6.0 +List the quality ratings of the top 3 wines with the highest alcohol content.,"['5', '6', '6']",list[category],"['alcohol', 'quality']","['number[double]', 'number[uint8]']","[7, 7, 8]" +Enumerate the quality ratings of the bottom 2 wines with the lowest residual sugar.,"['6', '6']",list[category],"['residual sugar', 'quality']","['number[double]', 'number[uint8]']","[5, 5]" +Which are the quality ratings of the top 5 wines with the highest density?,"['6', '6', '7', '5', '5']",list[category],"['density', 'quality']","['number[double]', 'number[uint8]']","[6, 7, 5, 7, 6]" +List the quality ratings of the bottom 4 wines with the lowest pH level.,"['4', '6', '6', '8']",list[category],"['pH', 'quality']","['number[double]', 'number[uint8]']","[7, 8, 5, 7]" +What are the alcohol contents of the top 4 wines with the highest quality ratings?,"['12.8', '12.6', '12.9', '9.8']",list[number],"['quality', 'alcohol']","['number[uint8]', 'number[double]']","[11.7, 11.8, 12.3, 10.0]" +List the volatile acidity levels of the bottom 3 wines with the lowest quality ratings.,"['0.58', '0.61', '1.185']",list[number],"['quality', 'volatile acidity']","['number[uint8]', 'number[double]']","[0.76, 0.5, 0.46]" +Enumerate the fixed acidity levels of the top 5 wines with the highest quality ratings.,"['7.9', '10.3', '5.6', '12.6', '11.3']",list[number],"['quality', 'fixed acidity']","['number[uint8]', 'number[double]']","[9.4, 10.5, 8.9, 10.1, 7.7]" +Provide the residual sugar levels of the bottom 2 wines with the lowest quality ratings.,"['2.2', '2.1']",list[number],"['quality', 'residual sugar']","['number[uint8]', 'number[double]']","[1.8, 1.6]" diff --git a/025_Predicting_Wine_Quality/sample.csv b/data/026_Predicting/sample.csv similarity index 100% rename from 025_Predicting_Wine_Quality/sample.csv rename to data/026_Predicting/sample.csv diff --git a/026_Supermarket_Sales/all.parquet b/data/027_Supermarket/all.parquet similarity index 100% rename from 026_Supermarket_Sales/all.parquet rename to data/027_Supermarket/all.parquet diff --git a/026_Supermarket_Sales/info.yml b/data/027_Supermarket/info.yml similarity index 100% rename from 026_Supermarket_Sales/info.yml rename to data/027_Supermarket/info.yml diff --git a/data/027_Supermarket/qa.csv b/data/027_Supermarket/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..c2fc9b47174c00cf6bbf0ffc54a0ad6458606351 --- /dev/null +++ b/data/027_Supermarket/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Is there any purchase with a total cost above 1000?,True,boolean,['Total'],['number[double]'],False +Are there any customers who made a purchase using cash?,True,boolean,['Payment'],['category'],True +Is the customer with the highest total purchase cost a 'Member'?,True,boolean,"['Total', 'Customer type']","['number[double]', 'category']",False +Does any customer with a rating strictly above 9 use 'Ewallet' as their payment method?,True,boolean,"['Rating', 'Payment']","['number[double]', 'category']",False +How many unique branches are there in the dataset?,3,number,['Branch'],['category'],3 +What is the maximum quantity of products bought in a single purchase?,10,number,['Quantity'],['number[uint8]'],10 +What is the minimum total cost of a purchase in the dataset?,10.6785,number,['Total'],['number[double]'],45.927 +How many purchases were made in Yangon city?,340,number,['City'],['category'],11 +What is the payment method used for the purchase with the highest total cost?,Credit card,category,"['Total', 'Payment']","['number[double]', 'category']",Credit card +What is the product line of the purchase with the highest total cost?,Fashion accessories,category,"['Total', 'Product line']","['number[double]', 'category']",Electronic accessories +What is the customer type of the purchase with the lowest total cost?,Member,category,"['Total', 'Customer type']","['number[double]', 'category']",Normal +What is the gender of the customer with the highest total purchase cost?,Female,category,"['Total', 'Gender']","['number[double]', 'category']",Male +List the payment methods of the top 3 purchases with the highest total cost.,"['Credit card', 'Credit card', 'Ewallet']",list[category],"['Total', 'Payment']","['number[double]', 'category']","['Credit card', 'Cash', 'Ewallet']" +Enumerate the product lines of the bottom 2 purchases with the lowest total cost.,"['Sports and travel', 'Fashion accessories']",list[category],"['Total', 'Product line']","['number[double]', 'category']","['Sports and travel', 'Sports and travel']" +Which are the customer types of the top 5 purchases with the highest total cost?,"['Member', 'Normal', 'Member', 'Normal', 'Normal']",list[category],"['Total', 'Customer type']","['number[double]', 'category']","['Normal', 'Normal', 'Normal', 'Normal', 'Normal']" +List the genders of the bottom 4 purchases with the lowest total cost.,"['Male', 'Female', 'Female', 'Male']",list[category],"['Total', 'Gender']","['number[double]', 'category']","['Male', 'Male', 'Female', 'Female']" +What are the quantities of products bought in the top 4 purchases with the highest total cost?,"[10, 10, 10, 10]",list[number],"['Total', 'Quantity']","['number[double]', 'number[uint8]']","[10, 7, 10, 10]" +List the unit prices of the bottom 3 purchases with the lowest total cost.,"[10.17, 12.09, 12.54]",list[number],"['Total', 'Unit price']","['number[double]', 'number[double]']","[21.87, 60.87, 42.97]" +Enumerate the ratings of the top 5 purchases with the highest total cost.,"[6.6, 8.7, 4.5, 8.0, 4.4]",list[number],"['Total', 'Rating']","['number[double]', 'number[double]']","[4.2, 7.6, 8.1, 9.0, 6.4]" +Provide the gross incomes of the bottom 2 purchases with the lowest total cost.,"[0.5085, 0.6045]",list[number],"['Total', 'gross income']","['number[double]', 'number[double]']","[2.187, 6.087]" diff --git a/026_Supermarket_Sales/sample.csv b/data/027_Supermarket/sample.csv similarity index 100% rename from 026_Supermarket_Sales/sample.csv rename to data/027_Supermarket/sample.csv diff --git a/027_Predict_Diabetes/all.parquet b/data/028_Predict/all.parquet similarity index 100% rename from 027_Predict_Diabetes/all.parquet rename to data/028_Predict/all.parquet diff --git a/027_Predict_Diabetes/info.yml b/data/028_Predict/info.yml similarity index 100% rename from 027_Predict_Diabetes/info.yml rename to data/028_Predict/info.yml diff --git a/data/028_Predict/qa.csv b/data/028_Predict/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..16df3a999b0be8ffd2e679c56b00efd1160aca4a --- /dev/null +++ b/data/028_Predict/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Are there any individuals in the dataset who are above 60 years of age?,False,boolean,['Age'],['number[uint8]'],True +Does anyone have a Diabetes Pedigree Function score above 2.5?,True,boolean,['DiabetesPedigreeFunction'],['number[double]'],False +Does the person with the highest glucose level also have diabetes?,True,boolean,"['Glucose', 'Outcome']","['number[uint8]', 'number[uint8]']",True +Is there anyone who has zero pregnancies and is diabetic?,True,boolean,"['Pregnancies', 'Outcome']","['number[uint8]', 'number[uint8]']",True +What is the maximum number of pregnancies recorded in the dataset?,17,number,['Pregnancies'],['number[uint8]'],10 +What is the minimum blood pressure level recorded in the dataset?,0,number,['BloodPressure'],['number[uint8]'],0 +What is the average BMI recorded in the dataset?,31.992578124999998,number,['BMI'],['number[double]'],31.910000000000004 +How many individuals have an insulin level above 150?,187,number,['Insulin'],['number[uint16]'],4 +What is the diabetes outcome for the person with the highest BMI?,1,category,"['BMI', 'Outcome']","['number[double]', 'number[uint8]']",1 +What is the diabetes outcome for the person with the lowest blood pressure?,0,category,"['BloodPressure', 'Outcome']","['number[uint8]', 'number[uint8]']",0 +What is the diabetes outcome for the person with the highest insulin level?,1,category,"['Insulin', 'Outcome']","['number[uint16]', 'number[uint8]']",1 +What is the diabetes outcome for the person with the lowest glucose level?,0,category,"['Glucose', 'Outcome']","['number[uint8]', 'number[uint8]']",0 +List the diabetes outcomes of the top 3 individuals with the highest number of pregnancies.,"[1, 1, 1]",list[category],"['Pregnancies', 'Outcome']","['number[uint8]', 'number[uint8]']","[1, 0, 0]" +List the diabetes outcomes of the bottom 2 individuals with the lowest BMI.,"[0, 0]",list[category],"['BMI', 'Outcome']","['number[double]', 'number[uint8]']","[0, 0]" +List the diabetes outcomes of the top 5 individuals with the highest insulin levels.,"[1, 1, 1, 1, 1]",list[category],"['Insulin', 'Outcome']","['number[uint16]', 'number[uint8]']","[1, 0, 0, 1, 1]" +List the diabetes outcomes of the bottom 4 individuals with the lowest blood pressure.,"[0, 0, 0, 0]",list[category],"['BloodPressure', 'Outcome']","['number[uint8]', 'number[uint8]']","[0, 1, 0, 1]" +What are the ages of the top 4 individuals with the highest number of pregnancies?,"[51, 67, 67, 67]",list[number],"['Pregnancies', 'Age']","['number[uint8]', 'number[uint8]']","[40, 34, 50, 60]" +List the BMI of the bottom 3 individuals with the lowest glucose levels.,"[32.0, 32.0, 32.0]",list[number],"['Glucose', 'BMI']","['number[uint8]', 'number[double]']","[20.4, 37.2, 30.2]" +Enumerate the blood pressure levels of the top 5 individuals with the highest Diabetes Pedigree Function scores.,"[0, 0, 0, 0, 0]",list[number],"['DiabetesPedigreeFunction', 'BloodPressure']","['number[double]', 'number[uint8]']","[74, 50, 0, 80, 58]" +Provide the glucose levels of the bottom 2 individuals with the lowest insulin levels.,"[117, 111]",list[number],"['Insulin', 'Glucose']","['number[uint16]', 'number[uint8]']","[112, 108]" diff --git a/027_Predict_Diabetes/sample.csv b/data/028_Predict/sample.csv similarity index 100% rename from 027_Predict_Diabetes/sample.csv rename to data/028_Predict/sample.csv diff --git a/028_NYTimes_World_In_2021/all.parquet b/data/029_NYTimes/all.parquet similarity index 100% rename from 028_NYTimes_World_In_2021/all.parquet rename to data/029_NYTimes/all.parquet diff --git a/028_NYTimes_World_In_2021/info.yml b/data/029_NYTimes/info.yml similarity index 100% rename from 028_NYTimes_World_In_2021/info.yml rename to data/029_NYTimes/info.yml diff --git a/data/029_NYTimes/qa.csv b/data/029_NYTimes/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..186f419e75eeb37e6b62841162a5d8304395d4d4 --- /dev/null +++ b/data/029_NYTimes/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Are there any articles that have the material type 'Op-Ed'?,False,boolean,['material_type'],['category'],False +Does the article with the longest headline contain the keyword 'United States Politics and Government'?,False,boolean,"['headline', 'keywords']","['text', 'list[category]']",False +Is there any article published on '2021-01-05'?,False,boolean,['date'],"['date[ns, UTC]']",False +Does any article contain more than 10 keywords?,True,boolean,['keywords'],['list[category]'],False +How many unique material types are there in the dataset?,4,number,['material_type'],['category'],5 +What is the longest length of a headline in the dataset?,96,number,['headline'],['text'],110 +How many articles were published on '2021-01-02'?,52,number,['date'],"['date[ns, UTC]']",0 +What is the highest number of keywords associated with a single article?,8,number,['keywords'],['list[category]'],8 +What is the material type of the article with the longest headline?,News,category,"['headline', 'material_type']","['text', 'category']",News +What is the material type of the article with the shortest headline?,News,category,"['headline', 'material_type']","['text', 'category']",Editorial +What is the material type of the article with the most number of keywords?,News,category,"['keywords', 'material_type']","['list[category]', 'category']",News +What is the material type of the article with the least number of keywords?,News,category,"['keywords', 'material_type']","['list[category]', 'category']",News +List the material types of the top 3 articles with the longest headlines.,"['News', 'News', 'News']",list[category],"['headline', 'material_type']","['text', 'category']","['News', 'Interactive Feature', 'News']" +List the material types of the bottom 2 articles with the shortest headlines.,"['News', 'News']",list[category],"['headline', 'material_type']","['text', 'category']","['Editorial', 'News']" +List the material types of the top 5 articles with the most number of keywords.,"['News', 'News', 'News', 'News', 'News']",list[category],"['keywords', 'material_type']","['list[category]', 'category']","['News', 'Editorial', 'News', 'Review', 'News']" +List the material types of the bottom 4 articles with the least number of keywords.,"['News', 'News', 'News', 'News']",list[category],"['keywords', 'material_type']","['list[category]', 'category']","['News', 'Interactive Feature', 'News', 'News']" +What are the lengths of the headlines of the top 4 articles with the most number of keywords?,"[86, 85, 84, 84]",list[number],"['keywords', 'headline']","['list[category]', 'text']","[73, 20, 69, 62]" +List the number of keywords in the bottom 3 articles with the shortest headlines.,"[1, 1, 1]",list[number],"['headline', 'keywords']","['text', 'list[category]']","[8, 1, 2]" +Enumerate the lengths of the headlines of the top 5 articles with the longest headlines.,"[96, 96, 95, 95, 95]",list[number],['headline'],['text'],"[110, 94, 92, 73, 73]" +Provide the number of keywords in the bottom 2 articles with the least number of keywords.,"[1, 1]",list[number],['keywords'],['list[category]'],"[1, 2]" diff --git a/028_NYTimes_World_In_2021/sample.csv b/data/029_NYTimes/sample.csv similarity index 100% rename from 028_NYTimes_World_In_2021/sample.csv rename to data/029_NYTimes/sample.csv diff --git a/029_Professionals_Kaggle_Survey/all.parquet b/data/030_Professionals/all.parquet similarity index 100% rename from 029_Professionals_Kaggle_Survey/all.parquet rename to data/030_Professionals/all.parquet diff --git a/029_Professionals_Kaggle_Survey/info.yml b/data/030_Professionals/info.yml similarity index 100% rename from 029_Professionals_Kaggle_Survey/info.yml rename to data/030_Professionals/info.yml diff --git a/data/030_Professionals/qa.csv b/data/030_Professionals/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..7adc029556187f46128d408ea520809c0b913865 --- /dev/null +++ b/data/030_Professionals/qa.csv @@ -0,0 +1,27 @@ +question,answer,type,columns_used,column_types,sample_answer +Is the 'USA' the most common entry in the 'Geographies' column?,False,boolean,['Geographies'],['list[category]'],True +Are there any participants who are unemployed with a bachelor's degree from Africa?,False,boolean,"['Labeled Clusters', 'Geographies']","['category', 'list[category]']",False +Do all participants recommend Python as the first programming language?,False,boolean,['What programming language would you recommend an aspiring data scientist to learn first?'],['category'],False +Are there more than 1000 participants who hope to become familiar with AWS in the next 2 years?,False,boolean,['Which of the following cloud computing platforms do you hope to become more familiar with in the next 2 years?'],['list[category]'],False +How many unique job titles are represented in the dataset?,14,number,['Select the title most similar to your current role (or most recent title if retired)'],['category'],7 +What's the median number of years participants have used machine learning methods?,1.5,number,['(Average) For how many years have you used machine learning methods?'],['number[double]'],0.5 +How many participants are from the United Kingdom?,450,number,['In which country do you currently reside?'],['category'],1 +What is the most common number of programming languages used by participants on a regular basis?,2,number,['What programming languages do you use on a regular basis?'],['list[category]'],3.0 +What's the most common computing platform used for data science projects?,A laptop,category,['What type of computing platform do you use most often for your data science projects?'],['category'],A laptop +What's the most common programming language used on a regular basis?,Python,category,['What programming languages do you use on a regular basis?'],['list[category]'],Python +Which country has the second highest number of participants?,United States of America,category,['In which country do you currently reside?'],['category'],India +Which title is the least common among participants?,Developer Relations/Advocacy,category,['Select the title most similar to your current role (or most recent title if retired)'],['category'],Business Analyst +What are the top 4 geographies represented in the dataset?,"['India', 'USA', 'Western Europe', 'China - Japan - Korea']",list[category],['Geographies'],['list[category]'],"['USA', 'India', 'Other', 'Russia']" +Name the top 3 general segments of participants.,"['Analysts', 'Data Scientists', 'Academics']",list[category],['General Segments'],['list[category]'],"['Student', 'Data Scientist', 'Data Analyst']" +list the top 5 most common job titles.,"['Data Scientist', 'Software Engineer', 'Other', 'Data Analyst', 'Currently not employed']",list[category],['Select the title most similar to your current role (or most recent title if retired)'],['category'],"['Student', 'Data Scientist', 'Software Engineer', 'Other', 'Data Analyst']" +Identify the top 6 programming languages used regularly.,"['Python', 'SQL', 'R', 'Javascript', 'C++', 'Java']",list[category],['What programming languages do you use on a regular basis?'],['list[category]'],"['Python', 'SQL', 'R', 'Java', 'C++', 'Javascript']" +Report the top 4 age ranges of participants by frequency,"['25-29', '30-34', '22-24', '35-39']",list[number],['What is your age (years)?'],['category'],"['25-29', '22-24', '30-34', '35-39']" +list the highest 3 years of machine learning experience.,"[19.83, 19.74, 19.68]",list[number],['(Average) For how many years have you used machine learning methods?'],['number[double]'],"[7.5, +4.5, +3.5]" +Identify the 5 highest yearly compensations.,"[1000000, 1000000, 1000000, 1000000, 1000000]",list[number],['(Average) What is your current yearly compensation (approximate $USD)?'],['number[double]'],"[174999.5, +174999.5, +137499.5, +84999.5, +34999.5]" +Report the 6 most common sizes of the company where participants work.,"[75.25, 74.4, 73.0, 73.0, 73.0, 73.0]",list[number],['What is the size of the company where you are employed?'],['category'],"['0-49 employees', '> 10,000 employees', '50-249 employees', '1000-9,999 employees', '250-999 employees', 'I am a student']" diff --git a/029_Professionals_Kaggle_Survey/sample.csv b/data/030_Professionals/sample.csv similarity index 100% rename from 029_Professionals_Kaggle_Survey/sample.csv rename to data/030_Professionals/sample.csv diff --git a/030_Trustpilot_Reviews/all.parquet b/data/031_Trustpilot/all.parquet similarity index 100% rename from 030_Trustpilot_Reviews/all.parquet rename to data/031_Trustpilot/all.parquet diff --git a/030_Trustpilot_Reviews/info.yml b/data/031_Trustpilot/info.yml similarity index 100% rename from 030_Trustpilot_Reviews/info.yml rename to data/031_Trustpilot/info.yml diff --git a/data/031_Trustpilot/qa.csv b/data/031_Trustpilot/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..ae1a7bda6b1e307303a6a4ff08d3ed614f328bf6 --- /dev/null +++ b/data/031_Trustpilot/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Are there more reviews with rating 5 from 'GB' than 'US'?,True,boolean,"['country_code', 'rating']","['category', 'number[uint8]']",True +Is the average rating for 'Wise' in 'GB' above 4?,True,boolean,"['rating', 'Company', 'country_code']","['number[uint8]', 'category', 'category']",True +Do any reviews originate from 'AO'?,True,boolean,['country_code'],['category'],False +Did any reviews receive a rating of 1?,True,boolean,['rating'],['number[uint8]'],True +What's the total number of reviews for 'Wise'?,3840,number,['Company'],['category'],20 +How many unique countries gave 'Wise' a rating of 5?,120,number,"['country_code', 'Company', 'rating']","['category', 'category', 'number[uint8]']",8 +What is the highest rating received?,5,number,['rating'],['number[uint8]'],5 +What's the average rating across all reviews?,4.097755610972569,number,['rating'],['number[uint8]'],4.15 +Which company received the most 5-star reviews?,Wise,category,"['Company', 'rating']","['category', 'number[uint8]']",Wise +From which country did 'Wise' receive the most reviews?,GB,category,"['country_code', 'Company']","['category', 'category']",ES +Which country had the lowest representation in the reviews?,CW,category,['country_code'],['category'],PL +Which company received the lowest rating?,N26,category,"['rating', 'Company']","['number[uint8]', 'category']",N26 +Which are the top 3 countries with the most 5-star reviews for 'Wise'?,"['GB', 'US', 'ES']",list[category],"['country_code', 'Company', 'rating']","['category', 'category', 'number[uint8]']","['PL', 'DE', 'ES']" +Which are the 2 companies represented in the dataset?,"['Wise', 'N26']",list[category],['Company'],['category'],"['Wise', 'N26']" +Which are the bottom 4 countries in terms of review count?,"['CW', 'FO', 'KZ', 'NE']",list[category],['country_code'],['category'],"['IT', 'HU', 'US', 'AU']" +What are the top 5 most common countries?,"['GB', 'DE', 'FR']",list[category],['country_code'],['category'],"['GB', 'ES', 'FR']" +What are the top 3 most common ratings?,"[5, 1, 4]",list[number],['rating'],['number[uint8]'],"[5, 4, 1]" +What are the bottom 2 least common ratings?,"[3, 2]",list[number],['rating'],['number[uint8]'],"[3, 2]" +What are the top 4 ratings given to 'Wise'?,"[5, 1, 4, 2]",list[number],"['rating', 'Company']","['number[uint8]', 'category']","[5, 4, 2]" +What are the bottom 5 ratings given to 'N26'?,"[3, 2, 4, 1, 5]",list[number],"['rating', 'Company']","['number[uint8]', 'category']","[5, 4, 1, 3]" diff --git a/030_Trustpilot_Reviews/sample.csv b/data/031_Trustpilot/sample.csv similarity index 100% rename from 030_Trustpilot_Reviews/sample.csv rename to data/031_Trustpilot/sample.csv index 9e56feb1604ca8cc8a1e6b6f0306b38d83a95f26..09d3de195fe038e90092e7fd3494fe4ad0237616 100644 --- a/030_Trustpilot_Reviews/sample.csv +++ b/data/031_Trustpilot/sample.csv @@ -1,21 +1,21 @@ rating,country_code,Company +2,US,Wise 5,PT,N26 5,PL,Wise 5,IT,Wise +4,IE,Wise 5,HU,Wise 5,GB,Wise 5,GB,N26 5,GB,N26 +4,GB,N26 +1,GB,N26 +1,GB,N26 5,FR,N26 5,FR,Wise 5,ES,Wise -5,DE,Wise -5,AU,Wise -4,IE,Wise -4,GB,N26 4,ES,Wise -4,DE,N26 3,ES,N26 -2,US,Wise -1,GB,N26 -1,GB,N26 +5,DE,Wise +4,DE,N26 +5,AU,Wise diff --git a/031_Delicatessen_Customer_Segmentation/all.parquet b/data/032_Delicatessen/all.parquet similarity index 100% rename from 031_Delicatessen_Customer_Segmentation/all.parquet rename to data/032_Delicatessen/all.parquet diff --git a/031_Delicatessen_Customer_Segmentation/info.yml b/data/032_Delicatessen/info.yml similarity index 100% rename from 031_Delicatessen_Customer_Segmentation/info.yml rename to data/032_Delicatessen/info.yml diff --git a/data/032_Delicatessen/qa.csv b/data/032_Delicatessen/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..c468a6ce1558a9b3f538fdf8d527a5bea4c903a7 --- /dev/null +++ b/data/032_Delicatessen/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Is there any customer with a PhD education level?,True,boolean,['Education'],['category'],True +Do we have any customers who are married?,True,boolean,['Marital_Status'],['category'],True +Is there any customer with income higher than 100000?,True,boolean,['Income'],['number[UInt32]'],False +Has any customer made more than 10 web purchases?,True,boolean,['NumWebPurchases'],['number[uint8]'],False +How many customers do we have in the dataset?,2240,number,['ID'],['number[uint16]'],20 +What's the average income of our customers?,52247.25135379061,number,['Income'],['number[UInt32]'],51873.7 +What's the maximum number of web purchases made by a customer?,27,number,['NumWebPurchases'],['number[uint8]'],8 +What's the minimum recency of purchase among the customers?,0,number,['Recency'],['number[uint8]'],16 +What's the most common education level among our customers?,Graduation,category,['Education'],['category'],Graduation +What's the most common marital status among our customers?,Married,category,['Marital_Status'],['category'],Married +Who is the customer with the highest income?,9432,category,"['ID', 'Income']","['number[uint16]', 'number[UInt32]']",10742 +Who is the customer with the most recent purchase?,4047,category,"['ID', 'Recency']","['number[uint16]', 'number[uint8]']",10779 +Who are the top 3 customers with the highest income?,"[9432, 1503, 1501]",list[category],"['ID', 'Income']","['number[uint16]', 'number[UInt32]']","[10742, 6935, 5831]" +What are the top 2 most common education levels among our customers?,"['Graduation', 'PhD']",list[category],['Education'],['category'],"['Graduation', 'Master']" +What are the top 3 most common marital statuses among our customers?,"['Married', 'Together', 'Single']",list[category],['Marital_Status'],['category'],"['Married', 'Together', 'Single']" +Who are the 4 customers with the most web purchases?,"[5255, 4619, 10311, 6237]",list[category],"['ID', 'NumWebPurchases']","['number[uint16]', 'number[uint8]']","[2607, 7247, 3759, 2579]" +What are the top 3 income values among our customers?,"[666666.0, 162397.0, 160803.0]",list[number],['Income'],['number[UInt32]'],"[86580, 78497, 77870]" +What are the top 2 recency values among our customers?,"[99, 99]",list[number],['Recency'],['number[uint8]'],"[95, 93]" +What are the bottom 3 income values among our customers?,"[1730.0, 2447.0, 3502.0]",list[number],['Income'],['number[UInt32]'],"[14188, 21645, 22148]" +What are the bottom 2 recency values among our customers?,"[0, 0]",list[number],['Recency'],['number[uint8]'],"[16, 21]" diff --git a/031_Delicatessen_Customer_Segmentation/sample.csv b/data/032_Delicatessen/sample.csv similarity index 100% rename from 031_Delicatessen_Customer_Segmentation/sample.csv rename to data/032_Delicatessen/sample.csv diff --git a/data/033_Employee/all.parquet b/data/033_Employee/all.parquet new file mode 100644 index 0000000000000000000000000000000000000000..16741f6c492ec6910c291e133721cee2c983379d --- /dev/null +++ b/data/033_Employee/all.parquet @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:fa9ee6f5570c0fafc75a42a519546cffe69d60c87ee62b89527084cec5a8e514 +size 107195 diff --git a/032_Employee_Attrition/info.yml b/data/033_Employee/info.yml similarity index 72% rename from 032_Employee_Attrition/info.yml rename to data/033_Employee/info.yml index 2ce75f01cc7966e16c7657b8996dfe36dd49bde1..0f04934734e48727332e643630112d9a6551c288 100644 --- a/032_Employee_Attrition/info.yml +++ b/data/033_Employee/info.yml @@ -1,4 +1,4 @@ -Explore: https://app.graphext.com/projects/UHJvamVjdC0zNDUyOA==/v/data +Explore: https://public.graphext.com/07a91a15ecf2b8f6/index.html Source: https://www.kaggle.com/datasets/pavan9065/predicting-employee-attrition Title: 👨‍💼 Predict Employee Attrition tags: diff --git a/data/033_Employee/qa.csv b/data/033_Employee/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..d5acdb93a48a55adda18e1d9c58d6ebab6b42a7d --- /dev/null +++ b/data/033_Employee/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Is there any customer with a high salaryl?,True,boolean,['salary'],['category'],True +Do we have any employees who suffered a work accident?,True,boolean,['Work Accident'],['category'],True +Is there any employee with more than 100 hours per month on average?,True,boolean,['Average Monthly Hours'],['number'],True +Does any employee have a satisfaction level above 0.9?,True,boolean,['Satisfaction Level'],['number'],True +How many employees do we have in the dataset?,14999,number,['Number of Projects'],['category'],20 +What's the median satisfaction level of our employees?,0.64,number,['Satisfaction Level'],['number'],0.645 +What's the maximum number of web purchases made by a customer?,27,number,['Marital_Status'],['category'],8 +What's the most common marital status among the employees?,Together,number,['Marital_Status'],['number'],16 +What's the most common education level among our employees?,Graduation,category,['Education'],['category'],Graduation +What's the most common marital status among our employees?,Married,category,['Marital_Status'],['category'],Married +"Among the employees who have left the company in sales, what's the most common salary level?",low,category,"['Left', 'Department', 'salary']","['category', 'category', 'category']", +"Among the employees who have had a work accident in sales, what's the most common salary level?",low,category,"['Work Accident', 'Department', 'salary']","['category', 'category', 'category']",low +Who are the top 3 satisfaction levels?,"[1, 1, 1]",list[number],['Satisfaction Level'],['number'],"[0.98,0.93,0.93]" +What are the top 2 most common Work Accident statuses among our employees?,"['No', 'Yes']",list[category],['Work Accident'],['category'],"['No', 'Yes']" +What are the top 3 most common marital statuses among our employees?,"['Together', 'Single', 'Married']",list[category],['Marital_Status'],['category'],"['Married', 'Together', 'Single']" +What are the highest 3 years spent in the company? ,"[10, 10, 10]",list[number],['Years in the Company'],['number'],"[6, 5, 5]" +What are the top 3 departments with a 'low' salary level?,"['sales', 'technical', 'support']",list[category],"['Department', 'salary']","['category', 'category']","[95, 93]" +"For the 2 employees with the top satisfaction levels who belong to the sales department, what are their salary levels?","['low', 'low']",list[category],"['Satisfaction Level', 'Department', 'salary']","['number', 'category', 'category']","['low', 'low']" +What are the top 3 average monthly hours worked among the employees in the top 3 departments with the most employees?,"[200.91135265700484, 202.49742647058824, 200.75818752803949]",list[number],"['Department', 'Average Monthly Hours']","['category', 'number']","[265, 256, 249]" +What are the lowest 2 satisfaction levels among the employees who have not had a work accident?,"[0.09, 0.09]",list[number],"['Work Accident', 'Satisfaction Level']","['category', 'number']","[0.14, 0.22]" diff --git a/data/033_Employee/sample.csv b/data/033_Employee/sample.csv new file mode 100644 index 0000000000000000000000000000000000000000..7206db6c2515ef47c80e509b89c70b0fc4c0214c --- /dev/null +++ b/data/033_Employee/sample.csv @@ -0,0 +1,21 @@ +Left,Satisfaction Level,Work Accident,Average Monthly Hours,Last Evaluation,Years in the Company,salary,Department,Number of Projects,Promoted in the last 5 years?,Date Hired,Marital_Status +No,0.73,No,174,0.63,3,low,accounting,4,No,2017-05-09, Married +No,0.93,No,276,0.48,3,low,IT,3,No,2017-05-08, Married +No,0.5,No,267,0.77,2,high,management,3,No,2018-05-27, Together +No,0.91,No,255,0.67,4,low,accounting,2,No,2016-11-17, Together +No,0.57,No,235,0.67,2,low,product_mng,5,No,2018-11-23, Single +No,0.36,No,162,0.93,5,low,support,3,No,2015-02-22, Together +No,0.69,No,174,0.76,3,low,marketing,5,No,2017-12-21, Single +No,0.34,Yes,116,0.81,3,low,sales,4,No,2017-11-19, Married +No,0.98,Yes,265,0.61,2,medium,technical,4,No,2018-09-30, Married +No,0.55,No,179,0.5,3,low,technical,4,No,2017-10-25, Single +No,0.14,No,162,0.88,4,medium,marketing,3,No,2016-02-04, Married +No,0.28,No,124,0.51,3,low,technical,3,No,2017-06-06, Married +Yes,0.37,No,140,0.51,3,medium,support,2,No,2017-10-04, Together +No,0.22,No,180,0.62,3,low,support,3,No,2017-01-03, Together +No,0.6,No,145,0.97,2,medium,technical,5,No,2018-10-06, Together +No,0.24,No,142,0.89,4,medium,support,5,No,2016-06-04, Single +No,0.93,No,137,0.97,4,low,RandD,5,No,2016-08-04, Married +Yes,0.84,No,249,0.85,6,low,marketing,4,No,2014-03-20, Together +Yes,0.78,No,256,0.87,5,medium,support,5,No,2015-04-01, Together +No,0.84,No,125,0.47,4,low,RandD,3,No,2016-01-26, Married diff --git a/033_World_Happiness_Report/all.parquet b/data/034_World/all.parquet similarity index 100% rename from 033_World_Happiness_Report/all.parquet rename to data/034_World/all.parquet diff --git a/033_World_Happiness_Report/info.yml b/data/034_World/info.yml similarity index 100% rename from 033_World_Happiness_Report/info.yml rename to data/034_World/info.yml diff --git a/data/034_World/qa.csv b/data/034_World/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..ba5e9ddcb52609af077575f9c627073c1885f814 --- /dev/null +++ b/data/034_World/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +"Is there any country with a Ladder score above 7.5, a Generosity score above 0.2, and a Social support score above 0.7?",True,boolean,"['Ladder score', 'Generosity', 'Social support']","['number[double]', 'number[double]', 'number[double]']",False +"Are there any countries in Western Europe with a Perceptions of corruption score above 0.5, a Ladder score above 7, and a Social support score above 0.7?",True,boolean,"['Regional indicator', 'Perceptions of corruption', 'Ladder score', 'Social support']","['category', 'number[double]', 'number[double]', 'number[double]']",False +Are there any countries in Western Europe with a Perceptions of corruption score above 0.5?,True,boolean,"['Social support', 'Generosity']","['number[double]', 'number[double]']",False +Is there any country with a Social support score below 0.5?,True,boolean,"['Regional indicator', 'Ladder score']","['category', 'number[double]']",False +What's the average Ladder score among the countries in Western Europe with a Generosity score above 0.2 and a Social support score above 0.7?,7.222675085250001,number,"['Regional indicator', 'Ladder score', 'Generosity', 'Social support']","['category', 'number[double]', 'number[double]', 'number[double]']",7.213750000000001 +What's the average Perceptions of corruption score among the countries in Sub-Saharan Africa with a Ladder score below 5 and a Social support score below 0.5?,0.7493706045,number,"['Regional indicator', 'Perceptions of corruption', 'Ladder score', 'Social support']","['category', 'number[double]', 'number[double]', 'number[double]']",0.871 +What's the maximum Generosity score among the countries?,0.560663998,number,"['Regional indicator', 'Generosity']","['category', 'number[double]']",0.302 +What's the minimum Social support score among the countries?,0.319459856,number,"['Regional indicator', 'Social support']","['category', 'number[double]']",0.288 +Which region has the highest number of countries with a Ladder score above 7 and a Generosity score above 0.2?,Western Europe,category,"['Ladder score', 'Generosity', 'Regional indicator']","['number[double]', 'number[double]', 'category']",North America and ANZ +Which region accounts for the most countries with a Generosity score above 0.2?,Western Europe,category,"['Generosity', 'Regional indicator']","['number[double]', 'category']",Western Europe +In which region are the majority of countries with a Perceptions of corruption score below 0.5 located?,Western Europe,category,"['Perceptions of corruption', 'Regional indicator']","['number[double]', 'category']",Sub-Saharan Africa +In which region can you find the majority of countries with a Social support score above 0.7?,Western Europe,category,"['Social support', 'Regional indicator']","['number[double]', 'category']",Western Europe +Can you name the three regions that have the most countries with a Ladder score above 7 and a Generosity score above 0.2?,['Western Europe'],list[category],"['Ladder score', 'Generosity', 'Regional indicator']","['number[double]', 'number[double]', 'category']","['North America and ANZ', 'Western Europe', 'Latin America and Caribbean']" +What are the top 3 regions with the most countries with a Generosity score above 0.2?,"['Western Europe', 'Southeast Asia', 'Sub-Saharan Africa']",list[category],"['Generosity', 'Regional indicator']","['number[double]', 'category']","['Western Europe', 'Sub-Saharan Africa', 'Central and Eastern Europe']" +Identify the three highest Ladder scores from countries in Western Europe that have a Generosity score above 0.2 and a Social support score above 0.7.,"[7.504499912, 7.448900223, 7.164500237]",list[number],"['Ladder score', 'Generosity', 'Social support', 'Regional indicator']","['number[double]', 'number[double]', 'number[double]', 'category']","[7.5599, 7.5045, 7.487]" +What are the top 3 Perceptions of corruption scores among the countries in Sub-Saharan Africa?,"[0.891806662, 0.861874342, 0.861330688]",list[number],"['Perceptions of corruption', 'Regional indicator']","['number[double]', 'category']","[0.933, 0.916, 0.915]" +What are the top 3 Generosity scores among the countries in Western Europe?,"[0.263732493, 0.246944219, 0.214965805]",list[number],"['Generosity', 'Regional indicator']","['number[double]', 'category']","[0.302, 0.275, 0.263]" +What are the top 3 Social support scores among the countries in Sub-Saharan Africa?,"[0.910357833, 0.852532268, 0.846880972]",list[number],"['Social support', 'Regional indicator']","['number[double]', 'category']","[0.983, 0.942, 0.941]" +Which are the three lowest Ladder scores in Western Europe?,"[5.514999866, 5.53550005, 5.910900116]",list[number],"['Ladder score', 'Regional indicator']","['number[double]', 'category']","[4.784, 4.956, 5.094]" +Which are the three lowest Perceptions of corruption scores in Sub-Saharan Africa?,"[0.183541179, 0.606934547, 0.619799435]",list[number],"['Perceptions of corruption', 'Regional indicator']","['number[double]', 'category']","[0.167, 0.179, 0.183]" diff --git a/033_World_Happiness_Report/sample.csv b/data/034_World/sample.csv similarity index 100% rename from 033_World_Happiness_Report/sample.csv rename to data/034_World/sample.csv diff --git a/034_Billboard_Lyrics/all.parquet b/data/035_Billboard/all.parquet similarity index 100% rename from 034_Billboard_Lyrics/all.parquet rename to data/035_Billboard/all.parquet diff --git a/034_Billboard_Lyrics/info.yml b/data/035_Billboard/info.yml similarity index 100% rename from 034_Billboard_Lyrics/info.yml rename to data/035_Billboard/info.yml diff --git a/data/035_Billboard/qa.csv b/data/035_Billboard/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..874041c37b8efb299af5187ac1cf2fd45f1eb895 --- /dev/null +++ b/data/035_Billboard/qa.csv @@ -0,0 +1,25 @@ +question,answer,type,columns_used,column_types,sample_answer +Is the song with the highest rank from 1965?,True,boolean,"['Rank', 'Year']","['number[uint8]', 'number[uint16]']",False +Does the song with the lowest rank contain the word 'love' in its lyrics?,True,boolean,"['Rank', 'Lyrics']","['number[uint8]', 'text']",False +Is the artist of the song with the highest rank the same as the artist of the song with the lowest rank?,False,boolean,"['Rank', 'Artist']","['number[uint8]', 'category']",False +Are there songs without lyrics?,True,boolean,['Lyrics'],['text'],False +How many songs were produced in 1965?,100,number,['Year'],['number[uint16]'],2 +In which year was the song with the highest rank produced?,1965,number,"['Rank', 'Year']","['number[uint8]', 'number[uint16]']",2008 +What's the rank of the song with the longest lyrics?,19,number,"['Rank', 'Lyrics']","['number[uint8]', 'text']",64 +How many unique artists are there in the dataset?,2473,number,['Artist'],['category'],20 +Who is the artist of the song with the highest rank?,sam the sham and the pharaohs,category,"['Rank', 'Artist']","['number[uint8]', 'category']",alicia keys +What is the title of the song with the lowest rank?,how sweet it is to be loved by you,category,"['Rank', 'Song']","['number[uint8]', 'category']",the end of the innocence +Which song's lyrics contain the word 'love' the most times?,the way you love me,category,"['Song', 'Lyrics']","['category', 'text']",game of love +What is the title of the song produced in the earliest year?,wooly bully,category,"['Song', 'Year']","['category', 'number[uint16]']",i like it like that +Who are the artists of the top 5 ranked songs?,"['sam the sham and the pharaohs', 'ssgt barry sadler', 'the beach boys', 'the beatles', 'the beatles']",list[category],"['Rank', 'Artist']","['number[uint8]', 'category']","['alicia keys', 'christina aguilera', 'mariah carey', 'wayne fontana the mindbenders', 'fall out boy']" +What are the titles of the 3 songs with the shortest lyrics?,"['girl youll be a woman soon', 'papa dont preach', 'breathe']",list[category],"['Song', 'Lyrics']","['category', 'text']","['all the small things', 'days go by', 'hurting each other']" +Which 4 songs were produced in the most recent year?,"['uptown funk', 'thinking out loud', 'see you again', 'trap queen']",list[category],"['Song', 'Year']","['category', 'number[uint16]']",['i cry'] +Who are the artists of the bottom 5 ranked songs?,"['marvin gaye', 'wilson pickett', 'neil diamond', 'jerry butler', 'the beatles']",list[category],"['Rank', 'Artist']","['number[uint8]', 'category']","['don henley', 'lady antebellum', 'the who', 'aerosmith', 'the dave clark five']" +What are the ranks of the top 3 songs with the most occurrences of the word 'love' in their lyrics?,"[64, 41, 28]",list[number],"['Rank', 'Lyrics']","['number[uint8]', 'text']","[11, 2, 5]" +What are the years of production of the bottom 4 ranked songs?,"[1965, 1966, 1967, 1968]",list[number],"['Rank', 'Year']","['number[uint8]', 'number[uint16]']","[1989, 2010, 1971, 1989]" +What are the ranks of the 2 songs produced in the earliest year?,"[1, 2]",list[number],"['Rank', 'Year']","['number[uint8]', 'number[uint16]']","[80, 34]" +What are the years of production of the top 5 songs with the longest lyrics?,"[1998, 2009, 2010, 2007, 2002]",list[number],"['Year', 'Lyrics']","['number[uint16]', 'text']","[2013, 1973, 1988, 1994, 2005]" +Is the song with the highest rank from 1965 by the Beatles?,False,boolean,"['Rank', 'Year', 'Artist']","['number[uint8]', 'number[uint16]', 'category']",False +Which artist has the song with the highest rank in 1965?,sam the sham and the pharaohs,category,"['Rank', 'Year', 'Artist']","['number[uint8]', 'number[uint16]', 'category']",wayne fontana the mindbenders +Who are the artists of the top 3 songs in 1965?,"['sam the sham and the pharaohs', 'four tops', 'the beach boys']",list[category],"['Rank', 'Year', 'Artist']","['number[uint8]', 'number[uint16]', 'category']","['wayne fontana the mindbenders', 'the dave clark five']" +What are the years of production of the top 3 songs with the word 'love' in their lyrics by the Beatles?,"[1967, 1965, 1966]",list[number],"['Year', 'Lyrics', 'Artist']","['number[uint16]', 'text', 'category']",[] diff --git a/034_Billboard_Lyrics/sample.csv b/data/035_Billboard/sample.csv similarity index 100% rename from 034_Billboard_Lyrics/sample.csv rename to data/035_Billboard/sample.csv diff --git a/035_US_County_To_County/all.parquet b/data/036_US/all.parquet similarity index 100% rename from 035_US_County_To_County/all.parquet rename to data/036_US/all.parquet diff --git a/035_US_County_To_County/info.yml b/data/036_US/info.yml similarity index 76% rename from 035_US_County_To_County/info.yml rename to data/036_US/info.yml index 2fff17992dd14183de68d36d730c3a41c8162da1..7f1d608f618dd6544f80b2fbef76fc4602cd5bcc 100644 --- a/035_US_County_To_County/info.yml +++ b/data/036_US/info.yml @@ -1,4 +1,4 @@ -Explore: https://public.graphext.com/c3c706a523601058/index.html +Explore: https://public.graphext.com/9ff1f94ddab25962/index.html Source: https://www.census.gov/topics/population/migration/guidance/county-to-county-migration-flows.html Title: 🇺🇸 US County-to-County Migration 2012-2016 ACS tags: diff --git a/data/036_US/qa.csv b/data/036_US/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..43001e623485970844d48229ddbcad3537fbc38c --- /dev/null +++ b/data/036_US/qa.csv @@ -0,0 +1,21 @@ +question,answer,columns_used,type,column_types,sample_answer +"Are there records where the 'count' exceeds 20,000?",True,['count'],boolean,['number[uint16]'],False +Do we have any records originating from 'Jefferson'?,True,['name_origin'],boolean,['category'],True +Are there destinations with the name 'Baldwin'?,True,['name_dest'],boolean,['category'],False +Are there records where the latitude of the destination is greater than 60?,True,['lat_dest'],boolean,['number[double]'],False +How many unique destinations are there in the dataset?,3219,['dest'],number,['number[uint32]'],20 +"On average, how many times is each origin-destination pair reported?",67.7453798126951,['count'],number,['number[uint16]'],17.55 +What's the highest count value in the dataset?,40580,['count'],number,['number[uint16]'],66 +How many unique origin names are there in the dataset?,1904,['name_origin'],number,['category'],17 +From which origin do we have the highest 'count' recorded?,,"['count', 'name_origin']",category,"['number[uint16]', 'category']",18077 +To which destination do we find the highest 'count' reported?,Los Angeles,"['count', 'name_dest']",category,"['number[uint16]', 'category']",6001 +Which origin has the lowest latitude?,Guáanica,"['lat_origin', 'name_origin']",category,"['number[double]', 'category']",Okaloosa +Which destination has the highest longitude?,Fajardo,"['lon_dest', 'name_dest']",category,"['number[double]', 'category']",Montgomery +What are the top 3 origins with the highest average count?,"['Los Angeles', 'New York', 'San Francisco']","['name_origin', 'count']",list[category],"['category', 'number[uint16]']","['18077', '48439', '36123']" +Which are the 4 destinations with the lowest average count?,"['Kalawao', 'Loving', 'Kenedy', 'Wheatland']","['name_dest', 'count']",list[category],"['category', 'number[uint16]']","[48113, 12127, 37115, 39041]" +List the 5 origins with the highest average latitude values.,"['North Slope', 'Northwest Arctic', 'Yukon-Koyukuk', 'Nome', 'Fairbanks North Star']","['name_origin', 'lat_origin']",list[category],"['category', 'number[double]']","['53063', '53033', '53045', '55097', '36045']" +Which 2 origins have the lowest average longitude values?,"['Aleutians West', 'Nome']","['name_origin', 'lon_origin']",list[category],"['category', 'number[double]']","['53045', '6013']" +List the top 5 recorded count values.,"[40580, 39899, 38430, 28524, 24452]",['count'],list[number],['number[uint16]'],"[66, 35, 32, 30, 25]" +What are the 3 highest latitude values for destinations?,"[69.42718361, 69.42718361, 69.42718361]",['lat_dest'],list[number],['number[double]'],"[46.39399576, 46.27467409, 43.15268452]" +Rank the lowest 4 longitude values for origins.,"[-167.08526, -167.08526, -167.08526, -167.08526]",['lon_origin'],list[number],['number[double]'],"[-123.1229957, -121.8986791, -121.7629538, -119.6502747]" +Which 6 destination IDs have the highest average counts?,"[6037, 36061, 48201, 6059, 6071, 6085]","['dest', 'count']",list[number],"['number[uint32]', 'number[uint16]']","[6001, 20045, 36055, 13035, 26103, 55003]" diff --git a/035_US_County_To_County/sample.csv b/data/036_US/sample.csv similarity index 100% rename from 035_US_County_To_County/sample.csv rename to data/036_US/sample.csv diff --git a/036_Ted_Talks/all.parquet b/data/037_Ted/all.parquet similarity index 100% rename from 036_Ted_Talks/all.parquet rename to data/037_Ted/all.parquet diff --git a/036_Ted_Talks/info.yml b/data/037_Ted/info.yml similarity index 100% rename from 036_Ted_Talks/info.yml rename to data/037_Ted/info.yml diff --git a/data/037_Ted/qa.csv b/data/037_Ted/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..bb48100b1cb78e0bd4436da0cce7b216b24a7e26 --- /dev/null +++ b/data/037_Ted/qa.csv @@ -0,0 +1,21 @@ +question,answer,columns_used,type,column_types,sample_answer +Are there talks with more than a million views?,True,['views'],boolean,['number[uint32]'],True +Is there a talk by 'Elon Musk'?,True,['speaker_1'],boolean,['category'],False +Are there any TEDx events included?,True,['event'],boolean,['category'],True +Are there talks available in more than 10 languages?,True,['available_lang'],boolean,['list[category]'],True +How many unique speakers are there in the dataset?,3274,['speaker_1'],number,['category'],20 +What's the average number of views for the talks?,2148005.5737827714,['views'],number,['number[uint32]'],1502352.85 +What's the maximum duration of a talk (in seconds)?,3922,['duration'],number,['number[uint16]'],1523 +How many talks have more than 500 comments?,186,['comments'],number,['number[UInt16]'],2 +Which event has the highest average views?,TEDxPuget Sound,"['event', 'views']",category,"['category', 'number[uint32]']",TEDxRainier +Which speaker's talk has the most comments?,Richard Dawkins,"['speaker_1', 'comments']",category,"['category', 'number[UInt16]']",{0: 'Suzana Herculano-Houzel'} +Which talk's title has the least views?,Por qué necesitamos proteger el alta mar,"['title', 'views']",category,"['text', 'number[uint32]']",Online predators spread fake porn of me. Here's how I fought back +In which event was the longest talk held?,Countdown,"['event', 'duration']",category,"['category', 'number[uint16]']",TED1984 +Which are the top 4 events with the highest average number of comments?,"['TEDxPuget Sound', 'TEDxHouston', 'TEDxFiDiWomen', 'TEDxUW']","['event', 'comments']",list[category],"['category', 'number[UInt16]']","['TEDGlobal 2013', 'TED2016', 'TEDxRainier', 'TEDIndia 2009']" +List the top 3 most frequent speakers in the dataset.,"['Alex Gendler', 'Iseult Gillespie', 'Emma Bryce']",'speaker_1',list[category],['category'],"[""{0: 'Miwa Matreyek'}"", ""{0: 'Thomas Pogge'}"", ""{0: 'Asher Hasan'}""]" +Which 5 events have the shortest average talk durations?,"['TEDxConcorde', 'Small Thing Big Idea', 'The TED Interview', 'TEDxConcordiaUPortland', 'The Way We Work']","['event', 'duration']",list[category],"['category', 'number[uint16]']","['TEDIndia 2009', 'TED2007', 'TED-Ed', 'TEDGlobal 2017', 'TEDxRainier']" +List 2 events with the most number of talks.,"['TED-Ed', 'TED2018']",'event',list[category],['category'],"['TEDGlobal 2010', 'TEDxCanberra']" +What are the top 4 most viewed talks' view counts?,"[65051954, 57074270, 56932551, 49730580]",['views'],list[number],['number[uint32]'],"[3492293, 3082440, 2478498, 2438526]" +List the 3 shortest talk durations in the dataset.,"[60, 78, 78]",['duration'],list[number],['number[uint16]'],"[268, 279, 287]" +Which 5 talks have the highest number of comments?,"[6449.0, 4931.0, 3424.0, 3006.0, 2984.0]",['comments'],list[number],['number[UInt16]'],"['What is so special about the human brain?', 'The case for optimism on climate change', 'The linguistic genius of babies', 'My message of peace from Pakistan', 'Glorious visions in animation and performance']" +List the view counts of the 6 least viewed talks.,"[0, 0, 0, 0, 0, 0]",['views'],list[number],['number[uint32]'],"[195172, 310677, 451421, 477710, 779329, 887739]" diff --git a/036_Ted_Talks/sample.csv b/data/037_Ted/sample.csv similarity index 100% rename from 036_Ted_Talks/sample.csv rename to data/037_Ted/sample.csv diff --git a/037_Stroke_Likelihood/all.parquet b/data/038_Stroke/all.parquet similarity index 100% rename from 037_Stroke_Likelihood/all.parquet rename to data/038_Stroke/all.parquet diff --git a/037_Stroke_Likelihood/info.yml b/data/038_Stroke/info.yml similarity index 100% rename from 037_Stroke_Likelihood/info.yml rename to data/038_Stroke/info.yml diff --git a/data/038_Stroke/qa.csv b/data/038_Stroke/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..217bca0388ed563be4d0e5a1ffc34adea33bb760 --- /dev/null +++ b/data/038_Stroke/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Is it true that the oldest person in the dataset has a stroke?,True,boolean,"['age', 'stroke']","['number[UInt8]', 'number[uint8]']",False +Do all smokers have hypertension?,False,boolean,"['smoking_status', 'hypertension']","['category', 'number[uint8]']",False +Are all people with heart diseases married?,False,boolean,"['heart_disease', 'ever_married']","['number[uint8]', 'category']",True +Is the average glucose level higher for males than females?,True,boolean,"['gender', 'avg_glucose_level']","['category', 'number[double]']",False +How many people in the dataset have a stroke?,249,number,['stroke'],['number[uint8]'],1 +What is the average age of people who smoke?,47.09632446134347,number,"['smoking_status', 'age']","['category', 'number[UInt8]']",50.333333333333336 +What is the highest glucose level recorded in the dataset?,271.74,number,['avg_glucose_level'],['number[double]'],143.43 +How many unique 'work_type' categories are there in the dataset?,5,number,['work_type'],['category'],4 +What is the most common work type among stroke patients?,Private,category,"['stroke', 'work_type']","['number[uint8]', 'category']",Self-employed +What is the smoking status of the youngest person in the dataset?,Unknown,category,"['age', 'smoking_status']","['number[UInt8]', 'category']",Unknown +What is the residence type of the person with the highest BMI?,Rural,category,"['bmi', 'Residence_type']","['number[double]', 'category']",Urban +What is the gender of the person with the lowest glucose level?,Female,category,"['avg_glucose_level', 'gender']","['number[double]', 'category']",Female +What are the top 3 work types among people with heart diseases?,"['Private', 'Self-employed', 'Govt_job']",list[category],"['heart_disease', 'work_type']","['number[uint8]', 'category']",['Private'] +What are the 5 most common smoking statuses among people with a stroke?,"['never smoked', 'formerly smoked', 'Unknown', 'smokes']",list[category],"['stroke', 'smoking_status']","['number[uint8]', 'category']",['Unknown'] +What are the top 4 residence types of people with hypertension?,"['Rural', 'Urban']",list[category],"['hypertension', 'Residence_type']","['number[uint8]', 'category']",['Rural'] +What are the top 2 work types among people who have never married?,"['Private', 'children']",list[category],"['ever_married', 'work_type']","['category', 'category']","['children', 'Self-employed']" +What are the top 5 ages of people with strokes?,"[82.0, 82.0, 82.0, 82.0, 82.0]",list[number],"['stroke', 'age']","['number[uint8]', 'number[UInt8]']",[43.0] +What are the 3 lowest BMIs among people who smoke?,"[15.7, 16.7, 16.7]",list[number],"['smoking_status', 'bmi']","['category', 'number[double]']","[26.8, 34.1, 35.6]" +What are the top 4 glucose levels of people who have heart diseases?,"[271.74, 254.63, 254.6, 252.72]",list[number],"['heart_disease', 'avg_glucose_level']","['number[uint8]', 'number[double]']",[62.2] +What are the 6 highest ages of people who have never married?,"[82.0, 82.0, 82.0, 82.0, 82.0, 82.0]",list[number],"['ever_married', 'age']","['category', 'number[UInt8]']","[51.0, 42.0, 31.0, 26.0, 10.0, 8.0]" diff --git a/037_Stroke_Likelihood/sample.csv b/data/038_Stroke/sample.csv similarity index 100% rename from 037_Stroke_Likelihood/sample.csv rename to data/038_Stroke/sample.csv diff --git a/038_Happy_Moments/all.parquet b/data/039_Happy/all.parquet similarity index 100% rename from 038_Happy_Moments/all.parquet rename to data/039_Happy/all.parquet diff --git a/038_Happy_Moments/info.yml b/data/039_Happy/info.yml similarity index 67% rename from 038_Happy_Moments/info.yml rename to data/039_Happy/info.yml index 92b0b488a20d537685ea988f152302b80d8d307b..717d15c51ceccf30d0e5ea86cd4a90f68198dadb 100644 --- a/038_Happy_Moments/info.yml +++ b/data/039_Happy/info.yml @@ -1,4 +1,4 @@ -Explore: https://app.graphext.com/projects/UHJvamVjdC0zMzg0OA==/view +Explore: https://public.graphext.com/9b86efff48989701/index.html Source: https://www.kaggle.com/datasets/ritresearch/happydb Title: 😊 Happy Moments tags: diff --git a/data/039_Happy/qa.csv b/data/039_Happy/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..a6062157bffe2e54ca53d6b375483237dcc3c544 --- /dev/null +++ b/data/039_Happy/qa.csv @@ -0,0 +1,21 @@ +question,answer,columns_used,type,column_types,sample_answer +Are there any reflections with more than 10 sentences?,True,['num_sentence'],boolean,['number[uint8]'],False +Is there a reflection from 'USA' with over 5 sentences?,True,"['country', 'num_sentence']",boolean,"['category', 'number[uint8]']",False +Are there any reflections categorized as 'affection'?,True,['predicted_category'],boolean,['category'],True +Are there any married individuals who reflected on 'exercise'?,True,"['marital', 'predicted_category']",boolean,"['category', 'category']",False +How many unique reflection periods are there?,2,['reflection_period'],number,['category'],2 +"On average, how many sentences are there in the reflections?",1.3407668971005122,['num_sentence'],number,['number[uint8]'],1.05 +What's the highest age of an individual in the dataset?,233.0,['age'],number,['number[UInt8]'],54.0 +How many reflections are from 'IND'?,16729,['country'],number,['category'],2 +Which country has the highest average number of sentences in their reflections?,UKR,"['country', 'num_sentence']",category,"['category', 'number[uint8]']",USA +Which gender has the most reflections categorized as 'affection'?,f,"['gender', 'predicted_category']",category,"['category', 'category']",f +From which country is the oldest individual who reflected?,USA,"['country', 'age']",category,"['category', 'number[UInt8]']",USA +Which marital status has the most reflections on 'bonding'?,single,"['marital', 'predicted_category']",category,"['category', 'category']",single +Which are the top 3 countries with the highest average number of sentences in their reflections?,"['UKR', 'CRI', 'HKG']","['country', 'num_sentence']",list[category],"['category', 'number[uint8]']","['USA', 'IND']" +List the 4 most common predicted categories in the dataset.,"['affection', 'achievement', 'enjoy_the_moment', 'bonding']",['predicted_category'],list[category],['category'],"['affection', 'achievement', 'enjoy_the_moment', 'nature']" +Which 5 countries have the youngest average age of reflectors?,"['KAZ', 'ALB', 'LKA', 'MAR', 'SLV']","['country', 'age']",list[category],"['category', 'number[UInt8]']","['IND', 'USA']" +List 2 genders with the most number of reflections.,"['m', 'f']",['gender'],list[category],['category'],"['f', 'm']" +What are the top 4 reflection IDs with the most number of sentences?,"[455, 455, 508, 455]","['wid', 'num_sentence']",list[number],"['number[uint16]', 'number[uint8]']","[5032, 8129, 2634, 645]" +List the 3 highest ages in the dataset.,"[233.0, 233.0, 233.0]",['age'],list[number],['number[UInt8]'],"[54.0, 49.0, 48.0]" +Which 5 reflection IDs have the least number of sentences?,"[2053, 2, 1936, 6227, 45]","['wid', 'num_sentence']",list[number],"['number[uint16]', 'number[uint8]']","[8129, 2634, 645, 783, 13285]" +List the age of the 6 youngest individuals in the dataset.,"[2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0]",['age'],list[number],['number[UInt8]'],"[22.0, 22.0, 24.0, 24.0, 24.0, 26.0]" diff --git a/038_Happy_Moments/sample.csv b/data/039_Happy/sample.csv similarity index 100% rename from 038_Happy_Moments/sample.csv rename to data/039_Happy/sample.csv diff --git a/039_Speed_Dating/all.parquet b/data/040_Speed/all.parquet similarity index 100% rename from 039_Speed_Dating/all.parquet rename to data/040_Speed/all.parquet diff --git a/039_Speed_Dating/info.yml b/data/040_Speed/info.yml similarity index 100% rename from 039_Speed_Dating/info.yml rename to data/040_Speed/info.yml diff --git a/data/040_Speed/qa.csv b/data/040_Speed/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..372ae8d4c5eb340898f3b26c2ea6d00a0c1d68a4 --- /dev/null +++ b/data/040_Speed/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Is it true that the youngest participant has met their match?,False,boolean,"['age', 'match']","['number[UInt8]', 'number[uint8]']",False +Do all people who got a match have the same race as their partner?,False,boolean,"['match', 'samerace']","['number[uint8]', 'number[uint8]']",False +Are all participants who expected more than 5 matches male?,True,boolean,"['expected_num_matches', 'gender']","['number[UInt8]', 'category']",True +Is the average age of participants who got a match higher than those who didn't?,False,boolean,"['match', 'age']","['number[uint8]', 'number[UInt8]']",True +How many participants had a match?,1380,number,['match'],['number[uint8]'],4 +What is the average age of participants who have the same race as their partner?,26.390236506973924,number,"['samerace', 'age']","['number[uint8]', 'number[UInt8]']",28.0 +What is the highest number of matches expected by any participant in the dataset?,18.0,number,['expected_num_matches'],['number[UInt8]'],9.0 +How many unique 'race' categories are there in the dataset?,5,number,['race'],['category'],3 +What is the most common race among participants who got a match?,european/caucasian-american,category,"['match', 'race']","['number[uint8]', 'category']",european/caucasian-american +What is the gender of the youngest participant in the dataset?,male,category,"['age', 'gender']","['number[UInt8]', 'category']",female +What is the race of the participant with the highest number of expected matches?,other,category,"['expected_num_matches', 'race']","['number[UInt8]', 'category']",asian/pacific islander/asian-american +What is the wave of the participant with the youngest age?,5,category,"['age', 'wave']","['number[UInt8]', 'number[uint8]']",13 +What are the top 3 waves among people who got a match?,"[21, 4, 11]",list[category],"['match', 'wave']","['number[uint8]', 'number[uint8]']","[21, 7, 7]" +What are the 5 most common races among people who expected more than 5 matches?,"['european/caucasian-american', 'asian/pacific islander/asian-american', 'black/african american', 'latino/hispanic american', 'other']",list[category],"['expected_num_matches', 'race']","['number[UInt8]', 'category']","['european/caucasian-american', 'asian/pacific islander/asian-american']" +What are the top 4 waves of people who have the same race as their partner?,"[15, 9, 21, 11]",list[category],"['samerace', 'wave']","['number[uint8]', 'number[uint8]']","[7, 4, 15, 11]" +What are the top 2 genders among people who expected no match?,"['female', 'male']",list[category],"['expected_num_matches', 'gender']","['number[UInt8]', 'category']",['female'] +What are the top 5 ages of participants who got a match?,"[42.0, 42.0, 42.0, 42.0, 39.0]",list[number],"['match', 'age']","['number[uint8]', 'number[UInt8]']","[31.0, 28.0, 27.0, 23.0]" +What are the 3 lowest numbers of matches expected by people who got a match?,"[0.0, 0.0, 0.0]",list[number],"['match', 'expected_num_matches']","['number[uint8]', 'number[UInt8]']","[1.0, 1.0, 1.0]" +What are the top 4 ages of people who have the same race as their partner?,"[55.0, 55.0, 55.0, 42.0]",list[number],"['samerace', 'age']","['number[uint8]', 'number[UInt8]']","[34.0, 31.0, 28.0, 24.0]" +What are the 6 youngest ages of participants who expected no match?,"[18.0, 18.0, 18.0, 18.0, 18.0, 18.0]",list[number],"['expected_num_matches', 'age']","['number[UInt8]', 'number[UInt8]']",[23.0] diff --git a/039_Speed_Dating/sample.csv b/data/040_Speed/sample.csv similarity index 100% rename from 039_Speed_Dating/sample.csv rename to data/040_Speed/sample.csv diff --git a/040_Airline_Twitter_topics_and_sentiment/all.parquet b/data/041_Airline/all.parquet similarity index 100% rename from 040_Airline_Twitter_topics_and_sentiment/all.parquet rename to data/041_Airline/all.parquet diff --git a/040_Airline_Twitter_topics_and_sentiment/info.yml b/data/041_Airline/info.yml similarity index 100% rename from 040_Airline_Twitter_topics_and_sentiment/info.yml rename to data/041_Airline/info.yml diff --git a/data/041_Airline/qa.csv b/data/041_Airline/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..ba0e5dfd10f6da18534a0d0e71e2ee857e5ee87a --- /dev/null +++ b/data/041_Airline/qa.csv @@ -0,0 +1,21 @@ +question,answer,columns_used,type,column_types,sample_answer +Are there any tweets with more than 10 retweets?,True,['retweet_count'],boolean,['number[uint8]'],False +Is there a negative sentiment tweet from 'United' airline?,True,"['airline', 'airline_sentiment']",boolean,"['category', 'category']",True +Are there any tweets categorized with 'Late Flight' as the negative reason?,True,['negativereason'],boolean,['category'],True +Are there any tweets from 'Eastern Time (US & Canada)' timezone with positive sentiment?,True,"['user_timezone', 'airline_sentiment']",boolean,"['category', 'category']",True +How many unique user timezones are there in the dataset?,85,['user_timezone'],number,['category'],6 +"On average, what is the sentiment confidence of the tweets?",0.9001688524590163,['airline_sentiment_confidence'],number,['number[double]'],0.887105 +What's the maximum number of retweets a tweet has received?,44,['retweet_count'],number,['number[uint8]'],1 +How many tweets are from 'Virgin America' airline?,504,['airline'],number,['category'],0 +Which airline has the highest average sentiment confidence?,US Airways,"['airline', 'airline_sentiment_confidence']",category,"['category', 'number[double]']",American +Which negative reason is most commonly associated with 'American' airline?,Customer Service Issue,"['airline', 'negativereason']",category,"['category', 'category']",Lost Luggage +From which timezone is the tweet with the highest sentiment confidence?,Eastern Time (US & Canada),"['user_timezone', 'airline_sentiment_confidence']",category,"['category', 'number[double]']",Eastern Time (US & Canada) +Which airline has the most tweets with negative sentiment?,United,"['airline', 'airline_sentiment']",category,"['category', 'category']",Delta +Which are the top 3 airlines with the highest average sentiment confidence?,"['US Airways', 'American', 'United']","['airline', 'airline_sentiment_confidence']",list[category],"['category', 'number[double]']","['American', 'Delta', 'United']" +List the 4 most common negative reasons in the dataset.,"['Customer Service Issue', 'Late Flight', 'Can't Tell', 'Cancelled Flight']",'negativereason',list[category],['category'],"[""Can't Tell"", 'Cancelled Flight', 'Customer Service Issue', 'Late Flight']" +Which 5 user timezones have the most number of tweets?,"['Eastern Time (US & Canada)', 'Central Time (US & Canada)', 'Pacific Time (US & Canada)', 'Quito', 'Atlantic Time (Canada)']",['user_timezone'],list[category],['category'],"['Eastern Time (US & Canada)', 'Pacific Time (US & Canada)', 'Alaska', 'Atlantic Time (Canada)', 'Amsterdam']" +List 2 airlines with the least number of tweets in the dataset.,"['Virgin America', 'Delta']",['airline'],list[category],['category'],"['American', 'United']" +What are the top 4 tweet IDs with the highest sentiment confidence?,"[570306133677760513, 570301031407624196, 570300817074462722, 570300767074181121]","['tweet_id', 'airline_sentiment_confidence']",list[number],"['number[int64]', 'number[double]']","[569731104070115329, 569263373092823040, 568818669024907264, 567775864679456768]" +List the 3 highest retweet counts in the dataset.,"[44, 32, 31]",['retweet_count'],list[number],['number[uint8]'],"[1, 0, 0]" +Which 5 tweet IDs have the lowest sentiment confidence?,"[569972097453137920, 568092537786748928, 568028183267639297, 568993773277069312, 569227372223811584]","['tweet_id', 'airline_sentiment_confidence']",list[number],"['number[int64]', 'number[double]']","[569332237138841600, 568975192615223296, 568526521910079488, 569184833361936387, 568884344221081600]" +List the sentiment confidence of the 6 most retweeted tweets in the dataset.,"[1.0, 1.0, 1.0, 0.6593, 1.0, 0.6940000000000001]","['airline_sentiment_confidence', 'retweet_count']",list[number],"['number[double]', 'number[uint8]']","[1.0, 1.0, 1.0, 1.0, 0.6625, 1.0]" diff --git a/040_Airline_Twitter_topics_and_sentiment/sample.csv b/data/041_Airline/sample.csv similarity index 100% rename from 040_Airline_Twitter_topics_and_sentiment/sample.csv rename to data/041_Airline/sample.csv diff --git a/041_Predict_Student_Performance/all.parquet b/data/042_Predict/all.parquet similarity index 100% rename from 041_Predict_Student_Performance/all.parquet rename to data/042_Predict/all.parquet diff --git a/041_Predict_Student_Performance/info.yml b/data/042_Predict/info.yml similarity index 100% rename from 041_Predict_Student_Performance/info.yml rename to data/042_Predict/info.yml diff --git a/data/042_Predict/qa.csv b/data/042_Predict/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..8acf94f8d11d387f1b44db8830dbb63782bf1576 --- /dev/null +++ b/data/042_Predict/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Is it true that the student with the highest number of absences is from a rural area?,True,boolean,"['absences', 'address']","['number[uint8]', 'category']",False +Are all students who are in a romantic relationship older than 17?,False,boolean,"['romantic', 'age']","['category', 'number[uint8]']",False +Is the average final grade (G3) of students who consume a lot of alcohol (Dalc > 2) lower than those who don't?,True,boolean,"['Dalc', 'G3']","['number[uint8]', 'number[uint8]']",False +Do all students who have both parents at home (Pstatus = 'T') have more than 3 free time after school (freetime > 3)?,False,boolean,"['Pstatus', 'freetime']","['category', 'number[uint8]']",False +How many students have their mother's education (Medu) level above 3?,131,number,['Medu'],['number[uint8]'],3 +What is the average age of students who want to take higher education (higher = 'yes')?,16.634666666666668,number,"['higher', 'age']","['category', 'number[uint8]']",16.944444444444443 +What is the highest number of absences among students?,75,number,['absences'],['number[uint8]'],18 +How many unique schools are there in the dataset?,2,number,['school'],['category'],2 +What is the most common mother's job among students who want to take higher education?,other,category,"['higher', 'Mjob']","['category', 'category']",other +What is the gender of the student with the highest final grade (G3)?,M,category,"['G3', 'sex']","['number[uint8]', 'category']",M +What is the school of the student with the highest number of absences?,GP,category,"['absences', 'school']","['number[uint8]', 'category']",GP +What is the family size of the student with the highest final grade (G3)?,GT3,category,"['G3', 'famsize']","['number[uint8]', 'category']",GT3 +What are the top 3 reasons for choosing a school among students who want to take higher education?,"['course', 'home', 'reputation']",list[category],"['higher', 'reason']","['category', 'category']","['course', 'home', 'reputation']" +What are the 5 most common mother's jobs among students with a final grade above 10?,"['other', 'services', 'teacher', 'health', 'at_home']",list[category],"['G3', 'Mjob']","['number[uint8]', 'category']","['other', 'at_home', 'services']" +What are the top 4 schools among students with absences above 10?,"['GP', 'MS']",list[category],"['absences', 'school']","['number[uint8]', 'category']","['MS', 'GP']" +What are the top 2 family relations among students with a final grade below 10?,"[4, 5]",list[category],"['G3', 'famrel']","['number[uint8]', 'number[uint8]']","[4, 5]" +What are the top 5 ages of students who want to take higher education?,"[16, 17, 15, 18, 19]",list[number],"['higher', 'age']","['category', 'number[uint8]']","[18, 15, 16, 17, 20]" +What are the 3 lowest final grades of students who have more than 10 absences?,"[4, 14, 17]",list[number],"['absences', 'G3']","['number[uint8]', 'number[uint8]']","[6, 9]" +What are the top 4 ages of students whose mother's education level is above 3?,"[15, 16, 18, 17]",list[number],"['Medu', 'age']","['number[uint8]', 'number[uint8]']","[15, 17]" +What are the 6 lowest final grades of students who don't want to take higher education?,"[8, 10, 12, 9, 7, 13]",list[number],"['higher', 'G3']","['category', 'number[uint8]']","[10, 12]" diff --git a/041_Predict_Student_Performance/sample.csv b/data/042_Predict/sample.csv similarity index 100% rename from 041_Predict_Student_Performance/sample.csv rename to data/042_Predict/sample.csv diff --git a/042_Predict_Loan_Default/all.parquet b/data/043_Predict/all.parquet similarity index 100% rename from 042_Predict_Loan_Default/all.parquet rename to data/043_Predict/all.parquet diff --git a/042_Predict_Loan_Default/info.yml b/data/043_Predict/info.yml similarity index 100% rename from 042_Predict_Loan_Default/info.yml rename to data/043_Predict/info.yml diff --git a/data/043_Predict/qa.csv b/data/043_Predict/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..d208836042c6be0690d36d7feea72db9c898f9eb --- /dev/null +++ b/data/043_Predict/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Is it true that the oldest company (based on approval year) is from an urban (UrbanRural=1) area?,False,boolean,"['ApprovalFY', 'UrbanRural']","['number[uint16]', 'number[uint8]']",False +Are all companies with more than 10 employees located in an urban (UrbanRural=1) area?,False,boolean,"['NoEmp', 'UrbanRural']","['number[uint16]', 'number[uint8]']",True +"Are all companies with a default amount greater than $250,000 in the food sector?",False,boolean,"['default_amount', 'Sector']","['number[uint32]', 'category']",False +Is the average number of retained jobs higher for companies located in urban (UrbanRural=1) areas than those in rural (UrbanRural=0) areas?,True,boolean,"['UrbanRural', 'RetainedJob']","['number[uint8]', 'number[uint16]']",True +How many companies have a franchise code of 1?,57340,number,['FranchiseCode'],['number[uint32]'],14 +What is the average disbursement gross for companies in the retail sector?,164636.4123068934,number,"['Sector', 'DisbursementGross']","['category', 'number[uint32]']", +What is the highest approval year in the dataset?,2010,number,['ApprovalFY'],['number[uint16]'],2008 +How many unique sectors are there in the dataset?,20,number,['Sector'],['category'],8 +What is the most common sector among companies with a franchise code of 1?,Retail trade,category,"['FranchiseCode', 'Sector']","['number[uint32]', 'category']",Other services (except public administration) +What is the state of the company with the highest disbursement gross?,ME,category,"['DisbursementGross', 'State']","['number[uint32]', 'category']",FL +What is the bank for the company with the highest default amount?,COMMUNITY BANK & TRUST,category,"['default_amount', 'Bank']","['number[uint32]', 'category']","READYCAP LENDING, LLC" +What is the sector of the company with the most number of employees?,Health care and social assistance,category,"['NoEmp', 'Sector']","['number[uint16]', 'category']",Construction +What are the top 3 sectors among companies with a franchise code of 1?,"['Retail trade', 'Other services (except public administration)', 'Manufacturing']",list[category],"['FranchiseCode', 'Sector']","['number[uint32]', 'category']","['Other services (except public administration)', 'Construction', 'Manufacturing']" +What are the 5 most common banks among companies with an approval year earlier than 2000?,"['WELLS FARGO BANK NATL ASSOC', 'BANK OF AMERICA NATL ASSOC', 'U.S. BANK NATIONAL ASSOCIATION', 'JPMORGAN CHASE BANK NATL ASSOC', 'PNC BANK, NATIONAL ASSOCIATION']",list[category],"['ApprovalFY', 'Bank']","['number[uint16]', 'category']","['TRUSTMARK NATIONAL BANK', 'KEYBANK NATIONAL ASSOCIATION']" +"What are the top 4 states among companies with a disbursement gross greater than $1,000,000?","['CA', 'TX', 'FL', 'AZ']",list[category],"['DisbursementGross', 'State']","['number[uint32]', 'category']",[] +"What are the top 2 sectors among companies with a default amount greater than $500,000?","['Retail trade', 'Accommodation and food services']",list[category],"['default_amount', 'Sector']","['number[uint32]', 'category']",[] +What are the top 5 approval years for companies in the retail sector?,"[2005, 2004, 2006, 2007, 2003]",list[number],"['Sector', 'ApprovalFY']","['category', 'number[uint16]']",[] +What are the 3 highest disbursement gross for companies with a franchise code of 1?,"[50000.0, 100000.0, 10000.0]",list[number],"['FranchiseCode', 'DisbursementGross']","['number[uint32]', 'number[uint32]']","[249719.0, 136000.0, 125000.0]" +What are the top 4 approval years for companies in the state of CA?,"[2007, 2004, 2006, 2003]",list[number],"['State', 'ApprovalFY']","['category', 'number[uint16]']","[2006, 2004, 2003]" +What are the 6 highest default amounts among companies in the state of NY?,"[0.0, 50000.0, 25000.0, 100000.0, 35000.0, 10000.0]",list[number],"['State', 'default_amount']","['category', 'number[uint32]']","[49996.0, 12942.0]" diff --git a/042_Predict_Loan_Default/sample.csv b/data/043_Predict/sample.csv similarity index 100% rename from 042_Predict_Loan_Default/sample.csv rename to data/043_Predict/sample.csv diff --git a/043_IMDb_Movies/all.parquet b/data/044_IMDb/all.parquet similarity index 100% rename from 043_IMDb_Movies/all.parquet rename to data/044_IMDb/all.parquet diff --git a/043_IMDb_Movies/info.yml b/data/044_IMDb/info.yml similarity index 100% rename from 043_IMDb_Movies/info.yml rename to data/044_IMDb/info.yml diff --git a/data/044_IMDb/qa.csv b/data/044_IMDb/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..6c8dd462804a5d29657e4b01b390a14afe3cdc9f --- /dev/null +++ b/data/044_IMDb/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Is it true that the oldest movie (based on year) in the drama genre is from the USA?,False,boolean,"['year', 'genre', 'country']","['number[UInt16]', 'category', 'category']",False +"Are all movies from the USA, with more than 80 minutes duration in the drama genre, in English?",False,boolean,"['duration', 'genre', 'country', 'language']","['number[uint16]', 'category', 'category', 'category']",False +Are all movies with votes greater than 90 from the USA in English?,True,boolean,"['votes', 'country', 'language']","['number[UInt8]', 'category', 'category']",False +Is the average duration of English language movies from the USA longer than those from non-USA countries?,False,boolean,"['country', 'language', 'duration']","['category', 'category', 'number[uint16]']",False +"How many movies from the USA, in the drama genre, have a metascore of 100?",6,number,"['metascore', 'genre', 'country']","['number[UInt8]', 'category', 'category']",0 +"What is the average duration for movies in the drama genre, from the USA, in English?",96.07926963408374,number,"['genre', 'country', 'language', 'duration']","['category', 'category', 'category', 'number[uint16]']",100.0 +What is the latest year for English language movies from the USA in the dataset?,2020.0,number,"['country', 'language', 'year']","['category', 'category', 'number[UInt16]']",1994 +How many unique languages are there in the dataset for movies from the USA?,650,number,"['country', 'language']","['category', 'category']",3 +What is the most common genre among English language movies from the USA with a metascore of 100?,"Adventure, Family, Fantasy",category,"['metascore', 'country', 'language', 'genre']","['number[UInt8]', 'category', 'category', 'category']",0 +What is the country of the English language movie with the longest duration?,Argentina,category,"['duration', 'language', 'country']","['number[uint16]', 'category', 'category']",USA +What is the language of the movie from the USA with the highest metascore?,English,category,"['metascore', 'country', 'language']","['number[UInt8]', 'category', 'category']",0 +What is the genre of the English language movie from the USA with the most votes?,Drama,category,"['votes', 'country', 'language', 'genre']","['number[uint32]', 'category', 'category', 'category']","Romance, Western" +What are the top 3 genres among English language movies from the USA with a metascore of 100?,"['Adventure, Family, Fantasy', 'Drama, Mystery', 'Drama, Romance, War']",list[category],"['metascore', 'country', 'language', 'genre']","['number[UInt8]', 'category', 'category', 'category']",[] +What are the 5 most common countries among English language movies with a year earlier than 2000?,"['USA', 'UK', 'Canada', 'UK, USA', 'Australia']",list[category],"['year', 'language', 'country']","['number[UInt16]', 'category', 'category']",['USA'] +What are the top 4 languages among movies from the USA with a duration greater than 180 minutes?,"['English', 'English, Spanish', 'English, Russian', 'English, Hungarian']",list[category],"['duration', 'country', 'language']","['number[uint16]', 'category', 'category']",[] +What are the top 2 genres among English language movies from the USA with a metascore greater than 90?,"['Drama', 'Crime, Drama']",list[category],"['metascore', 'country', 'language', 'genre']","['number[UInt8]', 'category', 'category', 'category']",[] +What are the top 5 years for English language movies from the USA in the drama genre?,"[2017.0, 2016.0, 2015.0, 2013.0, 2018.0]",list[number],"['genre', 'country', 'language', 'year']","['category', 'category', 'category', 'number[UInt16]']",[1994] +What are the 3 longest durations for English language movies from the USA with a metascore of 100?,"[102, 119, 112]",list[number],"['metascore', 'country', 'language', 'duration']","['number[UInt8]', 'category', 'category', 'number[uint16]']",[] +What are the four years with more English language movies from the USA?,"[2017.0, 2016.0, 2018.0, 2013.0]",list[number],"['country', 'language', 'year']","['category', 'category', 'number[UInt16]']","[1994, 1942, 1951, 1964]" +Can you show the 6 highest metascores among English language movies from the USA?,"[49.0, 55.0, 57.0, 48.0, 54.0, 52.0]",list[number],"['country', 'language', 'metascore']","['category', 'category', 'number[UInt8]']",[] diff --git a/043_IMDb_Movies/sample.csv b/data/044_IMDb/sample.csv similarity index 100% rename from 043_IMDb_Movies/sample.csv rename to data/044_IMDb/sample.csv diff --git a/044_Predict_Spotify_Songs_Popularity/all.parquet b/data/045_Predict/all.parquet similarity index 100% rename from 044_Predict_Spotify_Songs_Popularity/all.parquet rename to data/045_Predict/all.parquet diff --git a/044_Predict_Spotify_Songs_Popularity/info.yml b/data/045_Predict/info.yml similarity index 100% rename from 044_Predict_Spotify_Songs_Popularity/info.yml rename to data/045_Predict/info.yml diff --git a/data/045_Predict/qa.csv b/data/045_Predict/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..43b2a574856851ebf5c113e2b1ec9815a1b60134 --- /dev/null +++ b/data/045_Predict/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Is it true that the song with the lowest popularity in the dataset is longer than 300000 ms?,True,boolean,"[popularity, duration_ms]","['number[uint8]', 'number[UInt32]']",False +Did any song released in the year 2020 in the dataset achieve the maximum popularity?,False,boolean,"[release_year, popularity]","['number[uint16]', 'number[uint8]']",False +Does the song with the longest duration also have the highest energy?,False,boolean,"[duration_ms, energy]","['number[UInt32]', 'number[double]']",False +Does the song with the highest energy also have the highest popularity?,False,boolean,"[energy, popularity]","['number[double]', 'number[uint8]']",True +How many unique artists are there in the dataset?,13056,number,[artists],['list[category]'],20 +What's the average song duration in the dataset?,228998.0798095238,number,[duration_ms],['number[UInt32]'],256381.1 +What's the maximum popularity score in the dataset?,94,number,[popularity],['number[uint8]'],59 +How many songs were released in the year with the most releases?,489,number,[release_year],['number[uint16]'],2 +Who is the artist with the highest popularity score?,['Giveon'],category,"[popularity, artists]","['number[uint8]', 'list[category]']","['Victorious Cast', 'Elizabeth Gillies', 'Ariana Grande']" +In which month was the most popular song released?,3.0,category,"[popularity, release_month]","['number[uint8]', 'number[UInt8]']",8.0 +What's the name of the longest duration song?,Monster Tunes Yearmix 2011 - Mixed by Mark Eteson,category,"[duration_ms, name]","['number[UInt32]', 'category']",Ölmez Bu Hareket / Çileli Müjde +What's the name of the song with the most energy?,Marathon (Mix Cut) - Simon O'Shine Mix,category,"[energy, name]","['number[double]', 'category']",Give It Up (feat. Elizabeth Gillies & Ariana Grande) +What are the top 5 most common artist names in the dataset?,"['Die drei ???', 'Benjamin Blümchen', 'TKKG Retro-Archiv', 'Bibi Blocksberg', 'Lata Mangeshkar']",list[category],[artists],['list[category]'],"[""['Victorious Cast', 'Elizabeth Gillies', 'Ariana Grande']"", ""['Julio Iglesias']"", ""['Ari Lasso']"", ""['Romeo Santos', 'Mala Rodríguez']"", ""['Funkmaster Flex', 'Big Kap', 'Eminem', 'Dr. Dre']""]" +What are the names of the top 3 most popular songs?,"[Heartbreak Anniversary, Good Days, Paradise (feat. Dermot Kennedy)]",list[category],"[popularity, name]","['number[uint8]', 'category']","['Give It Up (feat. Elizabeth Gillies & Ariana Grande)', 'Lächeln', 'Winter Winds']" +What are the top 3 artists who released songs with the longest durations?,"['Mark Eteson', 'Various Artists', 'Serge Reggiani']",list[category],"[duration_ms, artists]","['number[UInt32]', 'list[category]']","[""['Ozan Arif']"", ""['環球演奏團']"", ""['Andrew E.']""]" +What are the names of the top 2 songs with the most energy?,"[Marathon (Mix Cut) - Simon O'Shine Mix, Applause; Martha Tilton Returns to Stage - Live]",list[category],"[energy, name]","['number[double]', 'category']","['Give It Up (feat. Elizabeth Gillies & Ariana Grande)', 'Rahasia Perempuan']" +What are the top 5 most popular scores?,"[0, 35, 23, 1, 26]",list[number],[popularity],['number[uint8]'],"[52, 59, 27, 47, 46]" +What are the 3 longest song durations?,"[4792587.0, 4658245.0, 4585640.0]",list[number],[duration_ms],['number[UInt32]'],"[698880.0, 496600.0, 324587.0]" +What are the 4 latest release years in the dataset?,"[2021, 2021, 2021, 2021]",list[number],[release_year],['number[uint16]'],"[2020, 2017, 2013, 2012]" +What are the top 3 energy scores in the dataset?,"[1.0, 1.0, 1.0]",list[number],[energy],['number[double]'],"[0.944, 0.908, 0.822]" diff --git a/044_Predict_Spotify_Songs_Popularity/sample.csv b/data/045_Predict/sample.csv similarity index 100% rename from 044_Predict_Spotify_Songs_Popularity/sample.csv rename to data/045_Predict/sample.csv diff --git a/045_120_Years_Olympics/all.parquet b/data/046_120/all.parquet similarity index 100% rename from 045_120_Years_Olympics/all.parquet rename to data/046_120/all.parquet diff --git a/045_120_Years_Olympics/info.yml b/data/046_120/info.yml similarity index 100% rename from 045_120_Years_Olympics/info.yml rename to data/046_120/info.yml diff --git a/data/046_120/qa.csv b/data/046_120/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..7d45a7b6d7f4b80270d127a50819a5952285f2c0 --- /dev/null +++ b/data/046_120/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Is it true that the athlete with the lowest ID is older than 30 years?,True,boolean,"[ID, Age]","['number[uint32]', 'number[UInt8]']",True +Did any athlete from the team with the most participants win two gold medals?,False,boolean,"[Team, Medal]","['category', 'category']",False +Does the athlete with the highest weight also participate in the sport with the most athletes?,False,boolean,"[Weight, Sport]","['number[UInt8]', 'category']",False +Does the athlete with the highest height also have a medal?,False,boolean,"[Height, Medal]","['number[UInt8]', 'category']",False +How many unique teams are there in the dataset?,230,number,[Team],['category'],15 +What's the average age of athletes in the dataset?,25.556898357297374,number,[Age],['number[UInt8]'],27.15 +What's the maximum weight of athletes in the dataset?,214.0,number,[Weight],['number[UInt8]'],92.0 +How many athletes participated in the year with the most participants?,2536,number,[Year],['number[uint16]'],2 +Who is the athlete with the highest weight?,Ricardo Blas Jr.,category,"[Weight, Name]","['number[UInt8]', 'category']",Martin Laumann Ylven +In which city did the athlete with the highest height participate?,London,category,"[Height, City]","['number[UInt8]', 'category']",Vancouver +What's the name of the athlete who participated in the most number of games?,Robert Tait McKenzie,category,[Name],['category'],Khalid Raghib +What's the sport of the athlete with the most medals?,Art Competitions,category,"[Medal, Sport, Name]","['category', 'category', 'category']",Rowing +What are the top 5 most common team names in the dataset?,"[United States, France, Great Britain, Italy, Germany]",list[category],[Team],['category'],"['Morocco', 'Romania', 'Germany', 'Japan', 'Italy']" +What are the names of the top 3 athletes with the highest weights?,"[Ricardo Blas Jr., Shinichi Shinohara, Emmanuel Yarborough]",list[category],"[Weight, Name]","['number[UInt8]', 'category']","['Martin Laumann Ylven', 'Juri Takayama', 'Graziano Mancinelli']" +What are the 3 teams with the most number of athletes?,"[United States, France, Great Britain]",list[category],[Team],['category'],"['Morocco', 'Romania', 'Germany']" +What are the names of the top 2 athletes who participated in the most number of games?,"[Robert Tait McKenzie, Heikki Ilmari Savolainen]",list[category],[Name],['category'],"['Khalid Raghib', 'Mrioara Trac (-Curelea)']" +What are the top five most common ages of athletes?,"[23.0, 24.0, 22.0, 25.0, 21.0]",list[number],[Age],['number[UInt8]'],"[27.0, 22.0, 21.0, 19.0, 25.0]" +What are the three highest weights of athletes?,"[214.0, 198.0, 190.0]",list[number],[Weight],['number[UInt8]'],"[92.0, 85.0, 77.0]" +What are the 4 most common years of participation?,"[1992, 1988, 2000, 1996]",list[number],[Year],['number[uint16]'],"[1912, 2000, 1956, 1964]" +What are the three most common heights of athletes?,"[180.0, 170.0, 178.0]",list[number],[Height],['number[UInt8]'],"[172.0, 175.0, 174.0]" diff --git a/045_120_Years_Olympics/sample.csv b/data/046_120/sample.csv similarity index 100% rename from 045_120_Years_Olympics/sample.csv rename to data/046_120/sample.csv diff --git a/046_Bank_Customer_Churn/all.parquet b/data/047_Bank/all.parquet similarity index 100% rename from 046_Bank_Customer_Churn/all.parquet rename to data/047_Bank/all.parquet diff --git a/046_Bank_Customer_Churn/info.yml b/data/047_Bank/info.yml similarity index 100% rename from 046_Bank_Customer_Churn/info.yml rename to data/047_Bank/info.yml diff --git a/data/047_Bank/qa.csv b/data/047_Bank/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..9c33cf509c2054bc1d1cd24c5e1a18fcd93e2e4b --- /dev/null +++ b/data/047_Bank/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Does the dataset contain customers who are under the age of 18?,False,boolean,['customer_age'],['number[uint8]'],False +Are there any customers with a total transaction amount of zero?,False,boolean,['total_trans_amt'],['number[uint16]'],False +"Does the dataset include customers with a credit limit exceeding $50,000?",False,boolean,['credit_limit'],['number[UInt16]'],False +Are there any customers in the dataset who are inactive for more than 12 months?,False,boolean,['months_inactive_12_mon'],['number[uint8]'],False +What is the highest credit limit in the dataset?,34516.0,number,['credit_limit'],['number[UInt16]'],34516.0 +What is the maximum total transaction amount recorded?,18484,number,['total_trans_amt'],['number[uint16]'],5149 +What is the largest total revolving balance in the dataset?,2517,number,['total_revolving_bal'],['number[uint16]'],2517 +What is the highest customer age in the dataset?,73,number,['customer_age'],['number[uint8]'],58 +What is the most common level of education among the customers?,Graduate,category,['education_level'],['category'],Graduate +What is the most common income category of the customers?,Less than $40K,category,['income_category'],['category'],Less than $40K +Which gender is most represented among the customers?,F,category,['gender'],['category'],F +What is the most common attrition flag value?,0,category,['attrition_flag'],['category'],0 +What are the top 3 most common education levels among the customers?,"['Graduate', 'High School', 'Unknown']",list[category],['education_level'],['category'],"['Graduate', 'Unknown', 'Post-Graduate']" +Which are the 4 most frequent income categories?,"['Less than $40K', '$40K - $60K', '$80K - $120K', '$60K - $80K']",list[category],['income_category'],['category'],"['Less than $40K', 'Unknown', '$80K - $120K', '$40K - $60K']" +Which are the top 3 most frequent income categories?,"['Less than $40K', '$40K - $60K', '$80K - $120K']",list[category],['income_category'],['category'],"['Less than $40K', 'Unknown', '$80K - $120K']" +Which are the two most frequent income categories?,"['Less than $40K', '$40K - $60K']",list[category],['income_category'],['category'],"['Less than $40K', 'Unknown']" +Who are the top 5 oldest customers in the dataset?,"[73, 70, 68, 67, 67]",list[number],"['customer_age', 'id']","['number[uint8]', 'number[uint16]']","[5024, 7430, 8918, 3002, 7360]" +Who are the five customers with the highest credit limit?,"[34516.0, 34516.0, 34516.0, 34516.0, 34516.0]",list[number],"['credit_limit', 'id']","['number[UInt16]', 'number[uint16]']","[3782, 8260, 8918, 8055, 3002]" +Who are the 6 customers with the highest total transaction amount?,"[18484, 17744, 17634, 17498, 17437, 17350]",list[number],"['total_trans_amt', 'id']","['number[uint16]', 'number[uint16]']","[2000, 2418, 10093, 3782, 9612, 7951]" +Who are the top six customers with the highest total revolving balance?,"[2517, 2517, 2517, 2517, 2517, 2517]",list[number],"['total_revolving_bal', 'id']","['number[uint16]', 'number[uint16]']","[10093, 7430, 6400, 3782, 9612, 7360]" diff --git a/046_Bank_Customer_Churn/sample.csv b/data/047_Bank/sample.csv similarity index 100% rename from 046_Bank_Customer_Churn/sample.csv rename to data/047_Bank/sample.csv diff --git a/047_Data_Science_Salary_Data/all.parquet b/data/048_Data/all.parquet similarity index 100% rename from 047_Data_Science_Salary_Data/all.parquet rename to data/048_Data/all.parquet diff --git a/047_Data_Science_Salary_Data/info.yml b/data/048_Data/info.yml similarity index 100% rename from 047_Data_Science_Salary_Data/info.yml rename to data/048_Data/info.yml diff --git a/data/048_Data/qa.csv b/data/048_Data/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..e46709e33f4dd73d7bc5dcca636f73de7db77471 --- /dev/null +++ b/data/048_Data/qa.csv @@ -0,0 +1,21 @@ +question,answer,columns_used,type,column_types,sample_answer +"Are there any job positions available in 'New York, NY'?",True,['Location'],boolean,['category'],True +Are there any job listings from companies founded before 1900?,True,['Founded'],boolean,['number[int16]'],False +Are there any job listings that require Python skills?,True,['python_yn'],boolean,['number[uint8]'],True +Is there a job listing for a 'Data Engineer' role?,True,['Job Title'],boolean,['category'],True +How many unique job titles are listed?,264,['Job Title'],number,['category'],19 +"On average, how old are the companies that have job listings?",46.591644204851754,['age'],number,['number[int16]'],1885.25 +What's the highest rating a company has received?,5.0,['Rating'],number,['number[double]'],4.7 +How many job listings are there from 'Government' type of ownership?,15,['Type of ownership'],number,['category'],0 +Which job title has the highest average salary?,"Director II, Data Science - GRM Actuarial","['Job Title', 'avg_salary']",category,"['category', 'number[double]']",Lead Big Data Engineer +Which state has the most number of job listings?, CA,['job_state'],category,['category'], CA +From which sector is the job listing with the highest salary?,Insurance,"['Sector', 'avg_salary']",category,"['category', 'number[double]']",Information Technology +Which company size has the most job listings?,1001 to 5000 employees,['Size'],category,['category'],1001 to 5000 employees +Which are the top 3 sectors with the most job listings?,"['Information Technology', 'Biotech & Pharmaceuticals', 'Business Services']",['Sector'],list[category],['category'],"['Information Technology', 'Insurance', 'Business Services']" +List the 4 most common industries in the dataset.,"['Biotech & Pharmaceuticals', 'Insurance Carriers', 'Computer Hardware & Software', 'IT Services']",['Industry'],list[category],['category'],"['Computer Hardware & Software', 'Insurance Carriers', 'Enterprise Software & Network Solutions', 'Internet']" +Which 5 states have the most number of job listings?,"[' CA', ' MA', ' NY', ' VA', ' IL']",['job_state'],list[category],['category'],"[' CA', ' MA', ' NY', ' IL', ' TN']" +List 2 company sizes with the least number of job listings.,"['1 to 50 employees', '5001 to 10000 employees']",['Size'],list[category],['category'],"['10000+ employees', 'Unknown']" +What are the top 4 average salaries for job titles in the dataset?,"[254.0, 232.5, 225.0, 205.0]","['Job Title', 'avg_salary']",list[number],"['category', 'number[double]']","[162.0, 161.5, 154.5, 150.5]" +List the year the 3 oldest companies that have job listings were founded.,"[1744, 1781, 1781]",['Founded'],list[number],['number[int16]'],"[1784, 1912, 1928]" +Which are the highest 5 ratings?,"[5.0, 5.0, 5.0, 5.0, 5.0]",['Rating'],list[number],['number[double]'],"[4.7, 4.4, 4.3]" +List the average salaries of the 6 most recent companies.,"[78.0, 88.5, 110.0, 40.5, 132.5, 20.5]","['Founded', 'avg_salary']",list[number],"['number[int16]', 'number[double]']","[122.0, 150.5, 154.5, 162.0, 59.5, 102.5]" diff --git a/047_Data_Science_Salary_Data/sample.csv b/data/048_Data/sample.csv similarity index 95% rename from 047_Data_Science_Salary_Data/sample.csv rename to data/048_Data/sample.csv index 7f3296c2d677c353be0f5e1106d84010ec3b1a45..e95aa379e4b6214d457bc8a123e6edcdadd2962e 100644 --- a/047_Data_Science_Salary_Data/sample.csv +++ b/data/048_Data/sample.csv @@ -12,7 +12,7 @@ Founded,Rating,Sector,Industry,age,Type of ownership,Size,avg_salary,python_yn,L 1989,3.6,Business Services,Advertising & Marketing,31,Company - Private,1001 to 5000 employees,161.5,1,"Fort Lee, NJ", NJ,Director Data Science 1928,3.7,Information Technology,Computer Hardware & Software,92,Company - Public,10000+ employees,61.0,1,"Chicago, IL", IL,Information Security Data Analyst 2006,4.4,Information Technology,Internet,14,Company - Public,1001 to 5000 employees,102.5,1,"Nashville, TN", TN,Senior Data Engineer --1,-1.0,-1,-1,-1,Company - Private,Unknown,120.0,0,"Cambridge, MA", MA,"Senior Scientist, Cell Pharmacology/Assay Development" +1784,-1.0,-1,-1,-1,Company - Private,Unknown,120.0,0,"Cambridge, MA", MA,"Senior Scientist, Cell Pharmacology/Assay Development" 1945,3.8,Insurance,Insurance Carriers,75,Nonprofit Organization,5001 to 10000 employees,106.5,0,"Chattanooga, TN", TN,MongoDB Data Engineer II 1968,3.9,Finance,Financial Analytics & Research,52,Company - Public,5001 to 10000 employees,140.0,1,"Chicago, IL", IL,Senior Insurance Data Scientist 1997,4.7,Business Services,Advertising & Marketing,23,Company - Private,201 to 500 employees,56.5,0,"Harrisburg, PA", PA,Jr. Business Data Analyst diff --git a/048_Boris_Johnson_UK_PM_Tweets/all.parquet b/data/049_Boris/all.parquet similarity index 100% rename from 048_Boris_Johnson_UK_PM_Tweets/all.parquet rename to data/049_Boris/all.parquet diff --git a/048_Boris_Johnson_UK_PM_Tweets/info.yml b/data/049_Boris/info.yml similarity index 100% rename from 048_Boris_Johnson_UK_PM_Tweets/info.yml rename to data/049_Boris/info.yml diff --git a/data/049_Boris/qa.csv b/data/049_Boris/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..38b6a4098215f3cb8f782a409f644d804fc5f702 --- /dev/null +++ b/data/049_Boris/qa.csv @@ -0,0 +1,20 @@ +question,answer,type,columns_used,column_types,sample_answer +Are there any authors in the dataset who have more followers than people they are following?,True,boolean,"['user_followers_count', 'user_following_count']","['number[uint32]', 'number[uint16]']",True +Is there any tweet in the dataset that has more replies than retweets?,True,boolean,"['replies', 'retweets']","['number[uint16]', 'number[uint32]']",True +Are there any verified users who have tweeted in a language other than English?,True,boolean,"['user_verified', 'lang']","['boolean', 'category']",False +Does the dataset contain any tweets that include image links?,True,boolean,[image_links],['list[url]'],True +How many unique authors are present in the dataset?,1,number,['author_id'],['number[uint32]'],1 +What is the highest number of retweets a single tweet has received?,117386,number,['retweets'],['number[uint32]'],5939 +What is the average number of favorites per tweet?,5081.805590062112,number,['favorites'],['number[uint32]'],7154.5 +What's the total number of tweets from verified users?,3220,number,['user_verified'],['boolean'],20 +Which author has the most tweets in the dataset?,3131144855,category,['author_id'],['number[uint32]'],3131144855 +Which language is most commonly used in the tweets?,en,category,['lang'],['category'],en +What is the most common source of tweets?,"Twitter for iPhone",category,['source'],['category'],Twitter for iPhone +"Which type of tweet (e.g., original, retweet, quote) is most common in the dataset?",original,category,['type'],['category'],original +Who are the top three authors (by ID) with the most followers?,[3131144855],list[category],"['author_id', 'user_followers_count']","['number[uint32]', 'number[uint32]']",[3131144855] +What are the top five most frequently mentioned names in the tweets?,"['G7', 'foreignoffice', 'UN', 'Conservatives', 'COP26']",list[category],['mention_names'],['list[category]'],"['[]', '[Hillingdon_Tory]', '[UN]', '[CyrilRamaphosa]', '[JoeMurphyLondon]']" +List the top four most commonly used languages in the tweets.,"['en', 'und', 'fr', 'es']",list[category],['lang'],['category'],['en'] +What are the highest three numbers of followers count present in the dataset?,"[3543402, 3543402, 3543402]",list[number],['user_followers_count'],['number[uint32]'],"[3543402, 3543402, 3543402]" +What are the bottom four numbers of favorites count?,"[7, 7, 8, 9]",list[number],['favorites'],['number[uint32]'],"[137, 198, 202, 210]" +List the top six numbers of retweets.,"[117386, 53527, 35698, 31449, 24824, 19982]",list[number],['retweets'],['number[uint32]'],"[5939, 4233, 2075, 1901, 1259, 1087]" +What are the bottom five numbers of replies?,"[2, 2, 3, 3, 4]",list[number],['replies'],['number[uint16]'],"[19, 38, 41, 49, 49]" diff --git a/048_Boris_Johnson_UK_PM_Tweets/sample.csv b/data/049_Boris/sample.csv similarity index 100% rename from 048_Boris_Johnson_UK_PM_Tweets/sample.csv rename to data/049_Boris/sample.csv diff --git a/049_ING_2019_Twitter_Mentions/all.parquet b/data/050_ING/all.parquet similarity index 100% rename from 049_ING_2019_Twitter_Mentions/all.parquet rename to data/050_ING/all.parquet diff --git a/049_ING_2019_Twitter_Mentions/info.yml b/data/050_ING/info.yml similarity index 100% rename from 049_ING_2019_Twitter_Mentions/info.yml rename to data/050_ING/info.yml diff --git a/data/050_ING/qa.csv b/data/050_ING/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..4bee0363de2bc324e5129e8c3e94b33e261b886c --- /dev/null +++ b/data/050_ING/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Is the most favorited author mainly communicating in Spanish?,True,boolean,"['favorites', 'lang']","['category', 'category']",True +Does the author with the longest name post mainly original content?,True,boolean,"['author_name', 'type']","['category', 'category']",False +Is there an author who received no retweets for any of their posts?,True,boolean,"['author_name', 'retweets']","['category', 'number[uint8]']",True +Are there any posts that do not contain any links?,True,boolean,['links'],['list[url]'],True +How many unique authors are in the dataset?,3765,number,['author_name'],['category'],20 +What is the length of the longest post (based on the number of words)?,61,number,['text'],['text'],49 +What is the total number of retweets received by all authors in the dataset?,1243,number,['retweets'],['number[uint8]'],2 +How many posts do not contain any mentions of other users?,0,number,['mention_ids'],['list[number[int64]]'],0 +What is the name of the most retweeted author?,ING España,category,"['author_name', 'retweets']","['category', 'number[uint8]']",ING enfurecido 🦁 +What is the language of the most favorited post?,es,category,"['lang', 'favorites']","['category', 'number[uint8]']",es +Who is the author of the post with the most words?,juan prin,category,"['author_name', 'text']","['category', 'text']",🇪🇸 Bearded.LocutusBorg 🇮🇪🏳️‍🌈 +"What type of post (original, reply, or other) is the most common in the dataset?",reply,category,['type'],['category'],reply +Who are the authors of the top 3 most retweeted posts?,"['Lavincompae', '#NI UNA MENOS \xa0♐\xa0✊\xa0🚺', 'SFC The World']",list[category],"['author_name', 'retweets']","['category', 'number[uint8]']","[Manuel, ING enfurecido 🦁, Albert Navarro]" +What are the languages of the 5 least favorited posts?,"['es', 'es', 'es', 'es', 'es']",list[category],"['lang', 'favorites']","['category', 'number[uint8]']","[es, es, es, es, es]" +Who are the authors of the 4 shortest posts (based on the number of words)?,"['Correctorada', 'El Joker', 'Xenia Viladas', 'DrJaus \xa0🇪🇸']",list[category],"['author_name', 'text']","['category', 'text']","[Vito!!, Albert Navarro, JEEVES, Leo Tarda]" +What types of posts are the 6 most common in the dataset?,"['reply', 'original']",list[category],['type'],['category'],"[reply, original]" +What are the retweet counts for the top 5 most favorited posts?,"[0, 0, 0, 0, 3]",list[number],"['retweets', 'favorites']","['number[uint8]', 'number[uint8]']","[0, 1, 0, 1, 0]" +What are the word counts of the 3 longest posts?,"[61, 60, 59]",list[number],['text'],['text'],"[49, 44, 41]" +What are the retweet counts of the 4 least favorited posts?,"[0, 0, 1, 0]",list[number],"['retweets', 'favorites']","['number[uint8]', 'number[uint8]']","[0, 0, 0, 0]" +What are the word counts for the 6 shortest posts?,"[1, 1, 1, 1, 1, 1]",list[number],['text'],['text'],"[2, 3, 4, 6, 12, 13]" diff --git a/049_ING_2019_Twitter_Mentions/sample.csv b/data/050_ING/sample.csv similarity index 100% rename from 049_ING_2019_Twitter_Mentions/sample.csv rename to data/050_ING/sample.csv diff --git a/050_Pokemon_Feature_Correlation/all.parquet b/data/051_Pokemon/all.parquet similarity index 100% rename from 050_Pokemon_Feature_Correlation/all.parquet rename to data/051_Pokemon/all.parquet diff --git a/050_Pokemon_Feature_Correlation/info.yml b/data/051_Pokemon/info.yml similarity index 100% rename from 050_Pokemon_Feature_Correlation/info.yml rename to data/051_Pokemon/info.yml diff --git a/data/051_Pokemon/qa.csv b/data/051_Pokemon/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..9405bc64c9f2f557440b635e1f51e1d0f61fa645 --- /dev/null +++ b/data/051_Pokemon/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Is there a Pokémon named 'Pikachu' in the dataset?,True,boolean,['name'],['category'],False +Are there any Pokémon with a total stat greater than 700?,True,boolean,['total'],['number[uint16]'],False +Are all Pokémon in the first generation legendary?,False,boolean,"['generation', 'legendary']","['number[uint8]', 'boolean']",False +Is there any Pokémon with a speed greater than 150?,True,boolean,['speed'],['number[uint8]'],False +How many unique Pokémon types are there in the 'type1' column?,20,number,['type1'],['category'],20 +What's the highest total stat value found in the dataset?,1125,number,['total'],['number[uint16]'],1125 +How many Pokémon are there in the third generation?,160,number,['generation'],['number[uint8]'],160 +What is the average attack stat for all Pokémon?,80.94,number,['attack'],['number[uint8]'],80.94 +What is the primary type of the Pokémon with the highest defense stat?,Poison,category,"['defense', 'type1']","['number[uint8]', 'category']",Poison +Which Pokémon has the lowest speed stat?,Shuckle,category,"['speed', 'name']","['number[uint8]', 'category']",Shuckle +What secondary type is the most common among legendary Pokémon?,Flying,category,"['legendary', 'type2']","['boolean', 'category']",Flying +Which Pokémon has the highest special attack and what is its primary type?,Mega Mewtwo Y (Psychic),category,"['sp_attack', 'name', 'type1']","['number[uint8]', 'category', 'category']",Mega Mewtwo Y (Psychic) +Name the top 3 Pokémon with the highest total stats.,"['Eternamax Eternatus', 'Mega Mewtwo X', 'Mega Mewtwo Y']",list[category],"['total', 'name']","['number[uint16]', 'category']","['Eternamax Eternatus', 'Mega Mewtwo X', 'Mega Mewtwo Y']" +Which 5 Pokémon have the lowest hp stats?,"['Shedinja', 'Diglett', 'Alolan Diglett', 'Magikarp', 'Pichu']",list[category],"['hp', 'name']","['number[uint8]', 'category']","['Shedinja', 'Diglett', 'Alolan Diglett', 'Magikarp', 'Pichu']" +Name the top 4 primary categories that have the most Pokémon.,"['Water', 'Normal', 'Grass', 'Bug']",list[category],['type1'],['category'],"['Water', 'Normal', 'Grass', 'Bug']" +Which 6 Pokémon from the second generation have the highest attack stats?,"['Mega Heracross', 'Mega Tyranitar', 'Mega Scizor', 'Tyranitar', 'Scizor', 'Ursaring']",list[category],"['generation', 'attack', 'name']","['number[uint8]', 'number[uint8]', 'category']","['Mega Heracross', 'Mega Tyranitar', 'Mega Scizor', 'Tyranitar', 'Scizor', 'Ursaring']" +What are the top 5 special defense stats in the dataset?,"[250, 230, 200, 160, 160]",list[number],['sp_defense'],['number[uint8]'],"[250, 230, 200, 160, 160]" +list the bottom 3 defense stats of legendary Pokémon.,"[20, 31, 50]",list[number],"['legendary', 'defense']","['boolean', 'number[uint8]']","[20, 31, 50]" +What are the 4 highest speed stats of Pokémon in the fourth generation?,"[135, 127, 125, 125]",list[number],"['generation', 'speed']","['number[uint8]', 'number[uint8]']","[135, 127, 125, 125]" +list the 6 lowest total stats of non-legendary Pokémon.,"[175, 180, 180, 185, 190, 194]",list[number],"['legendary', 'total']","['boolean', 'number[uint16]']","[175, 180, 180, 185, 190, 194]" diff --git a/050_Pokemon_Feature_Correlation/sample.csv b/data/051_Pokemon/sample.csv similarity index 100% rename from 050_Pokemon_Feature_Correlation/sample.csv rename to data/051_Pokemon/sample.csv diff --git a/051_Professional_Map/all.parquet b/data/052_Professional/all.parquet similarity index 100% rename from 051_Professional_Map/all.parquet rename to data/052_Professional/all.parquet diff --git a/051_Professional_Map/info.yml b/data/052_Professional/info.yml similarity index 100% rename from 051_Professional_Map/info.yml rename to data/052_Professional/info.yml diff --git a/data/052_Professional/qa.csv b/data/052_Professional/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..1c9bbaa93fc09f6b61ecb28f5b19551bcead1660 --- /dev/null +++ b/data/052_Professional/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Is the maximum level of Extraversion greater than the maximum level of Agreeableness?,True,boolean,"['Extraversion', 'Agreeableness']","['number[double]', 'number[double]']",True +Is the profession with the highest Openness the same as the profession with the highest Conscientousness?,False,boolean,"['Profession', 'Openness', 'Conscientousness']","['category', 'number[double]', 'number[double]']",False +Does the profession with the lowest Emotional_Range also have the lowest level of Conversation?,False,boolean,"['Profession', 'Emotional_Range', 'Conversation']","['category', 'number[double]', 'number[double]']",False +Is the average level of Openness to Change higher than the average level of Hedonism?,True,boolean,"['Openness to Change', 'Hedonism']","['number[double]', 'number[double]']",True +What is the maximum value of Self-enhancement across all professions?,0.7826336180787501,number,['Self-enhancement'],['number[double]'],0.6291001325102317 +How many professions have an Emotional_Range above 0.5?,1002,number,['Emotional_Range'],['number[double]'],18 +What is the average Extraversion level for the profession with the highest number of records (n)?,0.373214039767641,number,"['Profession', 'Extraversion', 'n']","['category', 'number[double]', 'number[uint16]']",0.3521943338191243 +What is the minimum level of Self-transcendence?,0.0353641396193574,number,['Self-transcendence'],['number[double]'],0.0355792960526332 +What profession has the highest level of Conscientiousness?,Policy Officer,category,"['Profession', 'Conscientousness']","['category', 'number[double]']",U.S. Representative +What is the profession with the lowest level of Hedonism?,Governor,category,"['Profession', 'Hedonism']","['category', 'number[double]']",U.S. Representative +Which profession has the highest Emotional_Range?,Mortgage Banker,category,"['Profession', 'Emotional_Range']","['category', 'number[double]']",U.S. Representative +What is the profession with the highest number of records (n)?,Program Manager,category,"['Profession', 'n']","['category', 'number[uint16]']",Data Analyst +What are the top 3 professions with the highest Openness?,"['Book Publisher', 'Bureau Chief', 'Publisher']",list[category],"['Profession', 'Openness']","['category', 'number[double]']","['User Experience Designer (UX Designer)', 'Sustainability Coach', 'Insurance Writer']" +Which are the bottom 4 professions in terms of Agreeableness?,"['.Net Architect', 'Android Developer', 'Principal Engineer', 'Game Engineer']",list[category],"['Profession', 'Agreeableness']","['category', 'number[double]']","['Automation Engineer', 'Stock Trader', 'Data Analyst', 'User Experience Designer (UX Designer)']" +List the top 5 professions with the highest Conversation levels.,"['Director of Athletics', 'Recruiting Coordinator', 'Athletic Coordinator', 'Director of Personnel', 'Skills Trainer']",list[category],"['Profession', 'Conversation']","['category', 'number[double]']","['U.S. Representative', 'Media Executive', 'Bookkeeper', 'Music Promoter', 'Director of Sales Marketing']" +Name the bottom 2 professions in terms of Self-enhancement.,"['U.S. Senator', 'Congressman']",list[category],"['Profession', 'Self-enhancement']","['category', 'number[double]']","['U.S. Representative', 'Examiner']" +What are the top 3 values of Openness to Change across all professions?,"[0.7557249985959847, 0.7413189187628788, 0.7034528053640179]",list[number],['Openness to Change'],['number[double]'],"[0.5907415983292473, 0.5853143224995465, 0.5741970926130652]" +List the bottom 4 Emotional_Range values.,"[0.1652381569664056, 0.2005428064324122, 0.2215546116855247, 0.2506791678499942]",list[number],['Emotional_Range'],['number[double]'],"[0.3282629326553239, 0.3454430761347227, 0.5168284093531004, 0.5454469457823092]" +What are the highest 5 levels of Extraversion?,"[0.9794365922809228, 0.9723660656030668, 0.954299437125917, 0.9362989453985364, 0.9307917067583288]",list[number],['Extraversion'],['number[double]'],"[0.7997301042051191, 0.7874815418605556, 0.786896532913159, 0.7780772474605324, 0.7595518653914357]" +Name the lowest 6 levels of Self-transcendence.,"[0.0353641396193574, 0.0355792960526332, 0.0399752446723049, 0.0573280662585624, 0.0591099063085338, 0.0592781792571762]",list[number],['Self-transcendence'],['number[double]'],"[0.0355792960526332, 0.1108088371055385, 0.1436964701751416, 0.1772058461581069, 0.2179965189872425, 0.2289998631350671]" diff --git a/051_Professional_Map/sample.csv b/data/052_Professional/sample.csv similarity index 100% rename from 051_Professional_Map/sample.csv rename to data/052_Professional/sample.csv diff --git a/052_Patents_Clustered/all.parquet b/data/053_Patents/all.parquet similarity index 100% rename from 052_Patents_Clustered/all.parquet rename to data/053_Patents/all.parquet diff --git a/052_Patents_Clustered/info.yml b/data/053_Patents/info.yml similarity index 100% rename from 052_Patents_Clustered/info.yml rename to data/053_Patents/info.yml diff --git a/data/053_Patents/qa.csv b/data/053_Patents/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..ef8439d22e8a1d725241b4dbd4f497a23626c747 --- /dev/null +++ b/data/053_Patents/qa.csv @@ -0,0 +1,21 @@ +question,answer,columns_used,type,column_types,sample_answer +Is there a patent related to 'communication' in the title?,False,['title'],boolean,['text'],True +Are there patents associated with the organization 'IBM'?,False,['organization'],boolean,['category'],False +Is there a patent abstract that mentions 'software'?,True,['abstract'],boolean,['text'],False +Are there patents of the 'design' type?,True,['type'],boolean,['category'],True +How many unique organizations have patents listed?,3574,['organization'],number,['category'],18 +"On average, how many claims do the patents have?",14.745974597459746,['num_claims'],number,['number[uint8]'],17.65 +What's the highest number of claims a patent has?,100,['num_claims'],number,['number[uint8]'],41 +How many patents are of 'utility' type?,8848,['type'],number,['category'],19 +Which organization has the patent with the highest number of claims?,Massachusetts Institute of Technology,"['organization', 'num_claims']",category,"['category', 'number[uint8]']","Samsung Electronics Co., Ltd." +Which kind of patent is the most common?,B2,['kind'],category,['category'],B2 +In which language are the patents written?,en,['lang'],category,['category'],en +Which graphext cluster is the most common among the patents?,"member, portion, body, end",['graphext_cluster'],category,['category'],"video, display, mobile, content" +Which are the top 3 organizations with the most patents?,"['International Business Machines Corporation', 'Samsung Electronics Co., Ltd.', 'Google Inc.']",['organization'],list[category],['category'],"['Samsung Electronics Co., Ltd.', 'HYUNDAI MOBIS CO., LTD.', 'Children's Hospital Medical Center']" +List the 4 most common types of patents in the dataset.,"['utility', 'design', 'plant', 'reissue']",['type'],list[category],['category'],"['utility', 'design']" +Which 5 kinds of patents are the most prevalent?,"['B2', 'S1', 'B1', 'P2', 'P3']",['kind'],list[category],['category'],"['B2', 'S1']" +List 2 least common graphext clusters among the patents.,"['habit, plant, foliage, flowers', 'soybean, plant, cultivar, soybean cultivar']",['graphext_cluster'],list[category],['category'],"['+, +1, -based, -based crystal', 'voltage, power, current, circuit']" +What are the top 4 numbers of claims in the patents?,"[20, 1, 18, 19]",['num_claims'],list[number],['number[uint8]'],"[12, 18, 7, 13]" +List the 3 patents (by ID) with the most number of claims.,"[9479771.0, 9325365.0, 9323284.0]","['id', 'num_claims']",list[number],"['number[UInt32]', 'number[uint8]']","[9479911.0, 9323438.0, 9480043.0]" +Which 5 patents (by ID) have the most targets associated?,"[29, 30, 46, 51, 70]","['id', 'target']",list[number],"['number[UInt32]', 'list[number[uint16]]']","[932136912.0, 9480043.0, 9323438.0, 9246982.0, 9323057.0]" +List the 6 most recent patents by their ID.,"[9479476.0, 9479477.0, 9479478.0, 9479479.0, 9479480.0, 9479481.0]","['id', 'date']",list[number],"['number[UInt32]', 'date[ns, UTC]']","[9480043.0, 9479911.0, 9480049.0, 9321442.0, 9323438.0, 9324689.0]" diff --git a/052_Patents_Clustered/sample.csv b/data/053_Patents/sample.csv similarity index 97% rename from 052_Patents_Clustered/sample.csv rename to data/053_Patents/sample.csv index 6603723b233b06bbbe460cf17f8cc935863e9d41..75036ca718357d6c5f543089035472fc97dd81ab 100644 --- a/052_Patents_Clustered/sample.csv +++ b/data/053_Patents/sample.csv @@ -13,7 +13,7 @@ B2,12,Reducing network usage of computing device,2016-01-26T00:00:00Z,en,9246982 B2,7,Compositions and methods for inhibiting norovirus infection,2016-04-26T00:00:00Z,en,9321803.0,"A composition for use in inhibiting the binding of a Norovirus to the histo-blood group antigen on the surface of epithelia is disclosed. The composition may contain a therapeutically effective amount of a binding-inhibiting compound and a carrier and/or excipient. The compounds may competitively bind a Norovirus that has the capability of binding with the histo-blood group antigens of secretor blood type, including A, B, AB, and O blood types. The compositions may be administered to a human prior to or after infection by a Norovirus, to prevent, ameliorate, or reduce the effects of an infection.",utility,"[4640, 4655, 4656, 4558, 5961, 6814, 6878, 5740, 5741, 4654, 4630, 4724, 5659, 5675]","cancer, nucleotide, patient, protein",Children's Hospital Medical Center B2,18,Power conversion system,2016-04-26T00:00:00Z,en,9321369.0,A power conversion system includes: a switching element; an output circuit that outputs a transmission signal for transmitting information on a physical quantity that indicates a state of the switching element and for transmitting information on abnormality of the switching element; an isolating element that transmits the transmission signal in an electrically isolated state; a filter that deletes the information on the physical quantity from a signal transmitted through the isolating element; a control circuit to which the signal transmitted through the isolating element but not through the filter is input; and a shutdown circuit that shuts down power supply to the switching element on the basis of the signal through the filter.,utility,"[2167, 9603, 7272, 9288, 2217, 344, 4354, 9412, 1323, 2295, 7409, 9611, 2263, 9372]","signal, frequency, station, transmission",Toyota Jidosha Kabushiki Kaisha B2,26,Insecticidal triazines and pyrimidines,2016-04-26T00:00:00Z,en,9321735.0,"The present invention describes novel triazines, their related pyrimidines and their use in controlling insects. This invention also includes new synthetic procedures, intermediates for preparing the compounds, pesticide compositions containing the compounds, and methods of controlling insects using the compounds.",utility,"[5649, 5705, 4127, 5717, 5665, 4654, 5692, 5678, 5657, 5682, 5712, 5713, 4679, 4599]","composition, resin, polymer, acid",The Valeron Corporation -S1,1,Housing for a crematory urn,2016-01-26T00:00:00Z,en,,,design,"[148, 378, 388, 389, 401, 402, 672, 687, 703, 708, 709, 715, 716, 717, 718]","+, +1, -based, -based crystal",County Cemetary Services Ltd. +S1,1,Housing for a crematory urn,2016-01-26T00:00:00Z,en,932136912.0,"This invention includes new synthetic procedures, intermediates for preparing the compounds, pesticide compositions containing the compounds, and methods of controlling insects using the compounds.",design,"[148, 378, 388, 389, 401, 402, 672, 687, 703, 708, 709, 715, 716, 717, 718]","+, +1, -based, -based crystal",County Cemetary Services Ltd. B2,8,Oral care compositions and methods,2016-04-26T00:00:00Z,en,9320696.0,"Described herein are compositions comprising a MMP-13 inhibitor, and methods of using the same.",utility,"[5712, 5713, 5665, 4603, 4600, 5767, 4127, 4679, 4654, 4545, 4617, 5702, 4595, 4596]","cancer, nucleotide, patient, protein",Colgate-Palmolive Company B2,27,Method and system for assigning addresses to subscriber stations in a wireless communication environment,2016-10-25T00:00:00Z,en,9480049.0,"A system and a method for assigning addresses to subscriber stations in a wireless communication environment are provided. The method includes receiving a request to register with a wireless communication network from a subscriber station, assigning a unicast address and at least one specific time duration to a subscriber station for communication with a network entity in the wireless communication network during registration process, and communicating the unicast address and the at least one specific time duration to the subscriber station, wherein the assigned unicast address is valid for the subscriber station during the at least one specific time duration.",utility,"[2722, 125, 3317, 9532, 2329, 3354, 9618, 2382, 9619, 3200, 9820, 541, 9779, 2321]","network, message, packet, service","Samsung Electronics Co., Ltd." B2,12,Method and device for controlling an electrical actuator for a wastegate valve arrangement of an exhaust gas turbocharger,2016-04-26T00:00:00Z,en,9322324.0,A method for controlling an electrical actuator for a wastegate valve arrangement of an exhaust gas turbocharger in an internal combustion engine is provided. A wastegate is situated in a bypass channel of the exhaust gas turbocharger. The method includes closing or opening the wastegate by the actuator for adjusting the exhaust gas flow routed past the exhaust gas turbocharger via the bypass channel. The wastegate is exposed to a predetermined closing force while it is in a closed state so as to regulate the closing force to a desired value for the closing force as a function of an actual value for the closing force. Computer-readable mediums embodying a computer program product having a program to perform the method are also provided.,utility,"[6288, 6303, 6291, 6328, 6287, 6332, 6308, 6292, 6339, 6327, 6321, 6235, 6253, 6313]","voltage, power, current, circuit","GM Global Technology Operations, Inc." diff --git a/053_Joe_Biden_Tweets/all.parquet b/data/054_Joe/all.parquet similarity index 100% rename from 053_Joe_Biden_Tweets/all.parquet rename to data/054_Joe/all.parquet diff --git a/053_Joe_Biden_Tweets/info.yml b/data/054_Joe/info.yml similarity index 100% rename from 053_Joe_Biden_Tweets/info.yml rename to data/054_Joe/info.yml diff --git a/data/054_Joe/qa.csv b/data/054_Joe/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..56f5d17b72c28d8b9e140b91319416d37d937b84 --- /dev/null +++ b/data/054_Joe/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Has the author with the highest number of followers ever been verified?,True,boolean,"['author_id', 'user_followers_count', 'user_verified']","['number[uint32]', 'number[uint32]', 'boolean']",True +Is the author who has the most favourites also the one with the most retweets?,False,boolean,"['author_id', 'user_favourites_count', 'retweets']","['number[uint32]', 'number[uint8]', 'number[uint8]']",True +Is the most mentioned user also the most retweeted user?,False,boolean,"['author_id', 'mention_names', 'retweets']","['number[uint32]', 'list[category]']",False +Does the author with the most retweets also have the most replies?,True,boolean,"['author_id', 'retweets', 'replies']","['number[uint32]', 'number[uint32]', 'number[uint16]']",True +What is the maximum number of followers an author in the dataset has?,0.7826336180787501,number,['user_followers_count'],['number[uint32]'],30308043 +"How many authors have more than 10,000 favourites?",1002,number,['user_favourites_count'],['number[uint8]'],0 +How many retweets does the most retweeted tweet have?,0.373214039767641,number,['retweets'],['number[uint32]'],50625 +How many times has the most mentioned user been mentioned?,0.0353641396193574,number,['mention_names'],['list[category]'],16 +Who is the author with the most followers?,Policy Officer,category,"['author_name', 'user_followers_count']","['category', 'number[uint32]']",Joe Biden +Who is the author with the highest number of favourites?,Governor,category,"['author_name', 'user_favourites_count']","['category', 'number[uint8]']",Joe Biden +What is the name of the user who is most often mentioned?,Mortgage Banker,category,"['author_name', 'mention_names']","['category', 'list[category]']",[] +Who is the author of the tweet with the most retweets?,Program Manager,category,"['author_name', 'retweets']","['category', 'number[uint32]']",Joe Biden +Who are the top 3 authors with the most followers?,"['Book Publisher', 'Bureau Chief', 'Publisher']",list[category],"['author_name', 'user_followers_count']","['category', 'number[uint32]']","['Joe Biden', 'Joe Biden', 'Joe Biden']" +Who are the top 4 authors with the most favourites?,"['.Net Architect', 'Android Developer', 'Principal Engineer', 'Game Engineer']",list[category],"['author_name', 'user_favourites_count']","['category', 'number[uint8]']","['Joe Biden', 'Joe Biden', 'Joe Biden', 'Joe Biden']" +Who are the 5 users who are mentioned the most often?,"['Director of Athletics', 'Recruiting Coordinator', 'Athletic Coordinator', 'Director of Personnel', 'Skills Trainer']",list[category],"['author_name', 'mention_names']","['category', 'list[category]']","['[]', '[305818748]', '[282721598]', '[21829541]', '[50348682]']" +Who are the top 2 authors of the tweets with the most retweets?,"['U.S. Senator', 'Congressman']",list[category],"['author_name', 'retweets']","['category', 'number[uint32]']","['Joe Biden', 'Joe Biden']" +What are the top 3 numbers of followers in the dataset?,"[0.7557249985959847, 0.7413189187628788, 0.7034528053640179]",list[number],['user_followers_count'],['number[uint32]'],"[30212707, 30212712, 30212708]" +What are the top 4 numbers of favourites an author in the dataset has?,"[0.1652381569664056, 0.2005428064324122, 0.2215546116855247, 0.2506791678499942]",list[number],['user_favourites_count'],['number[uint8]'],[20] +What are the 5 highest numbers of times a user is mentioned?,"[0.9794365922809228, 0.9723660656030668, 0.954299437125917, 0.9362989453985364, 0.9307917067583288]",list[number],['mention_names'],['list[category]'],"[16, 1, 1, 1, 1]" +What are the 2 highest numbers of retweets a tweet in the dataset has?,"[0.0353641396193574, 0.0355792960526332]",list[number],['retweets'],['number[uint32]'],"[399, 6866]" diff --git a/053_Joe_Biden_Tweets/sample.csv b/data/054_Joe/sample.csv similarity index 100% rename from 053_Joe_Biden_Tweets/sample.csv rename to data/054_Joe/sample.csv diff --git a/054_German_Loans/all.parquet b/data/055_German/all.parquet similarity index 100% rename from 054_German_Loans/all.parquet rename to data/055_German/all.parquet diff --git a/054_German_Loans/info.yml b/data/055_German/info.yml similarity index 100% rename from 054_German_Loans/info.yml rename to data/055_German/info.yml diff --git a/data/055_German/qa.csv b/data/055_German/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..a2ac2a98e50556c5dc3a2bc199acd270674f84f8 --- /dev/null +++ b/data/055_German/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Is the borrower with the highest loan amount also the one with the longest loan duration?,False,boolean,"['Loan Amount', 'Loan Duration - Months']","['number[uint16]', 'number[uint8]']",False +Does the borrower with the maximum number of existing loans also have the highest loan amount?,False,boolean,"['Number of Existing Loans', 'Loan Amount']","['number[uint8]', 'number[uint16]']",True +Does the borrower with the longest loan duration also have the maximum number of existing loans?,False,boolean,"['Loan Duration - Months', 'Number of Existing Loans']","['number[uint8]', 'number[uint8]']",False +Does the oldest borrower also have the highest loan amount?,False,boolean,"['Age', 'Loan Amount']","['number[uint8]', 'number[uint16]']",False +What is the highest loan amount in the dataset?,18424,number,['Loan Amount'],['number[uint16]'],8613 +How many borrowers have more than 1 existing loan?,367,number,['Number of Existing Loans'],['number[uint8]'],7 +What is the longest loan duration in the dataset?,72,number,['Loan Duration - Months'],['number[uint8]'],60 +How many borrowers are older than 50?,113,number,['Age'],['number[uint8]'],2 +What is the most common purpose of loans?,Radio/TV,category,['Purpose of Loan'],['category'],Radio/TV +What is the most common job category for borrowers?,Skilled,category,['Job'],['category'],Skilled +What is the most common credit history category for borrowers?,Existing Credits Paid Back Duly Till Now,category,['Credit History'],['category'],Existing Credits Paid Back Duly Till Now +What is the most common savings account status for borrowers?,Less than 100 DM,category,['Savings Account'],['category'],Less than 100 DM +What are the top 3 jobs of borrowers with the highest loan amount?,"['Highly Skilled', 'Skilled', 'Highly Skilled']",list[category],"['Loan Amount', 'Job']","['number[uint16]', 'category']","['Skilled', 'Skilled', 'Highly Skilled']" +What are the top 4 jobs of borrowers with the longest loan duration?,"['Skilled', 'Skilled', 'Skilled', 'Unskilled - Resident']",list[category],"['Loan Duration - Months', 'Job']","['number[uint8]', 'category']","['Skilled', 'Skilled', 'Skilled', 'Highly Skilled']" +What are the 5 jobs of borrowers with the maximum number of existing loans?,"['Skilled', 'Skilled', 'Unskilled - Resident', 'Highly Skilled', 'Skilled']",list[category],"['Number of Existing Loans', 'Job']","['number[uint8]', 'category']","['Highly Skilled', 'Skilled', 'Skilled', 'Skilled', 'Unemployed / Unskilled - Non-Resident']" +What are the jobs of the oldest 2 borrowers?,"['Highly Skilled', 'Highly Skilled']",list[category],"['Age', 'Job']","['number[uint8]', 'category']","['Unemployed / Unskilled - Non-Resident', 'Unskilled - Resident']" +What are the top 3 loan amounts in the dataset?,"[18424, 15945, 15857]",list[number],['Loan Amount'],['number[uint16]'],"[3190, 4380, 2124]" +What are the top 4 loan durations in the dataset?,"[72, 60, 60, 60]",list[number],['Loan Duration - Months'],['number[uint8]'],"[18, 24, 12, 6]" +What are the 5 maximum numbers of existing loans among borrowers?,"[4, 4, 4, 4, 4]",list[number],['Number of Existing Loans'],['number[uint8]'],"[1, 2]" +What are the ages of the top 2 oldest borrowers?,"[75, 75]",list[number],['Age'],['number[uint8]'],"[65, 64]" diff --git a/054_German_Loans/sample.csv b/data/055_German/sample.csv similarity index 100% rename from 054_German_Loans/sample.csv rename to data/055_German/sample.csv diff --git a/055_Emoji_Diet/all.parquet b/data/056_Emoji/all.parquet similarity index 100% rename from 055_Emoji_Diet/all.parquet rename to data/056_Emoji/all.parquet diff --git a/055_Emoji_Diet/info.yml b/data/056_Emoji/info.yml similarity index 100% rename from 055_Emoji_Diet/info.yml rename to data/056_Emoji/info.yml diff --git a/data/056_Emoji/qa.csv b/data/056_Emoji/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..5be56f4c2deb91eb25317e10131853bdf3b7761d --- /dev/null +++ b/data/056_Emoji/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Are there any foods with zero calories?,False,boolean,['Calories (kcal)'],['number[double]'],False +Do all foods contain sugar?,False,boolean,['Total Sugar (g)'],['number[double]'],False +Are there any foods that contain no fat at all?,True,boolean,['Total Fat (g)'],['number[double]'],False +Are there foods that do not contain protein?,True,boolean,['Protein (g)'],['number[double]'],False +How many foods have more than 500 kcal?,0,number,['Calories (kcal)'],['number[double]'],0 +What is the average amount of total fat (in grams) across all foods?,0.08465,number,['Total Fat (g)'],['number[double]'],0.06386499999999999 +How many foods have a sodium content of more than 1 gram?,18,number,['Sodium (g)'],['number[double]'],5 +What's the highest amount of protein (in grams) found in a food item?,0.2748,number,['Protein (g)'],['number[double]'],0.2403 +What food has the highest calorie content?,bacon,category,"['Calories (kcal)', 'name']","['number[double]', 'category']",chocolate bar +Which food contains the most sugar?,honey,category,"['Total Sugar (g)', 'name']","['number[double]', 'category']",chocolate bar +What is the food with the least amount of total fat?,honey,category,"['Total Fat (g)', 'name']","['number[double]', 'category']",pineapple +Which food has the highest amount of protein?,beef,category,"['Protein (g)', 'name']","['number[double]', 'category']",chicken +List the top 5 foods with the most calories.,"['bacon', 'peanuts', 'chocolate bar', 'popcorn', 'cookie']",list[category],"['Calories (kcal)', 'name']","['number[double]', 'category']","[chocolate bar, cookie, french fries, bread, hotdog]" +Identify the top 3 foods with the least amount of sugar.,"['chestnut', 'pancakes', 'cheese']",list[category],"['Total Sugar (g)', 'name']","['number[double]', 'category']","[milk, cookie, hotdog]" +Enumerate the 4 foods with the most total fat.,"['bacon', 'peanuts', 'cheese', 'popcorn']",list[category],"['Total Fat (g)', 'name']","['number[double]', 'category']","[chocolate bar, cookie, hotdog, french fries]" +Name the 6 foods with the least amount of protein.,"['candy', 'black tea', 'bacon', 'champagne', 'red wine', 'red apple']",list[category],"['Protein (g)', 'name']","['number[double]', 'category']","[green apple, pineapple, strawberry, grapes, tangerine, banana]" +List the 5 highest calorie counts found in the dataset.,"[8.98, 5.67, 5.18, 5.0, 4.97]",list[number],['Calories (kcal)'],['number[double]'],"[5.18, 4.97, 3.12, 2.74, 2.47]" +What are the 3 lowest amounts of sugar found among the foods?,"[0.0, 0.0, 0.0]",list[number],['Total Sugar (g)'],['number[double]'],"[0.0, 0.0, 0.0]" +Enumerate the 4 highest amounts of total fat found in the foods.,"[0.995, 0.4924, 0.3099, 0.281]",list[number],['Total Fat (g)'],['number[double]'],"[0.2599, 0.252, 0.1484, 0.1473]" +What are the top 6 lowest amounts of protein found in the dataset?,"[0.0, 0.0, 0.0007, 0.0007, 0.0007, 0.002]",list[number],['Protein (g)'],['number[double]'],"[0.0044, 0.0054, 0.0067, 0.0072, 0.0081, 0.0109]" diff --git a/055_Emoji_Diet/sample.csv b/data/056_Emoji/sample.csv similarity index 100% rename from 055_Emoji_Diet/sample.csv rename to data/056_Emoji/sample.csv diff --git a/056_Spain_Survey_2015/all.parquet b/data/057_Spain/all.parquet similarity index 100% rename from 056_Spain_Survey_2015/all.parquet rename to data/057_Spain/all.parquet diff --git a/056_Spain_Survey_2015/info.yml b/data/057_Spain/info.yml similarity index 100% rename from 056_Spain_Survey_2015/info.yml rename to data/057_Spain/info.yml diff --git a/data/057_Spain/qa.csv b/data/057_Spain/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..3d4330414440f14980155e4a824bff5935475d15 --- /dev/null +++ b/data/057_Spain/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Are there any respondents who didn't complete primary education?,True,boolean,['edu'],['category'],False +Are all respondents interested in politics?,False,boolean,['polInterest'],['category'],False +Did any respondent indicate that they will not vote?,True,boolean,['Vote Intention'],['list[category]'],False +Did any respondent place themselves at the extreme right of the Left-Right economic values axis?,True,boolean,['User self-placement on Left-Right economic values axis'],['number[UInt8]'],False +How many respondents placed themselves at 10 on the Progressive-Conservative economic values axis?,372,number,['User self- placement on Progressive-Conservative economic values axis'],['number[UInt8]'],0 +What is the average age of the respondents?,37.420120593188116,number,['Age'],['number[UInt8]'],38.72222222222222 +How many respondents think it should be more difficult for companies to lay off workers?,10344,number,['It should be more difficult for companies to lay off workers'],['number[UInt8]'],0 +What's the maximum age among the respondents who prefer not to disclose their gender?,105.0,number,"['Age', 'gender']","['number[UInt8]', 'category']", +Which is the most common vote intention among respondents?,[Ciudadanos],category,['Vote Intention'],['list[category]'],[Ciudadanos] +What is the most common reason for voting given by respondents?,The party ideas are close to my own,category,['voteReason'],['category'],The party ideas are close to my own +Which is the most common party identification among respondents?,Ciudadanos,category,['partyId'],['category'],Ciudadanos +What is the most common first language among respondents?,Castellano,category,['lang'],['category'],Castellano +List the top 5 most common vote intentions among respondents.,"['[Ciudadanos]', '[]', '[I am undeceided]', '[Podemos]', '[PP]']",list[category],['Vote Intention'],['list[category]'],"[Ciudadanos, I prefer not to say, [], I am undeceided, Podemos]" +Identify the top 3 most common reasons for voting among respondents.,"['The party ideas are close to my own', 'The party is the most competent', 'I prefer not to say']",list[category],['voteReason'],['category'],"[The party ideas are close to my own, The party is the most competent, I prefer not to say]" +Enumerate the top 4 most common party identifications among respondents.,"['Ciudadanos', 'PP', 'I prefer not to say', 'Podemos']",list[category],['partyId'],['category'],"[Ciudadanos, I prefer not to say, PSOE, PP]" +Name the top 6 most common first languages among respondents.,"['Castellano', 'Catal�', 'Galego', 'Euskara']",list[category],['lang'],['category'],[Castellano] +List the top 5 most common ages among respondents.,"[38.0, 23.0, 39.0, 25.0, 35.0]",list[number],['Age'],['number[UInt8]'],"[33.0, 38.0, 22.0, 55.0, 37.0]" +What are the top 3 most common positions on the Left-Right economic values axis?,"[5.0, 3.0, 6.0]",list[number],['User self-placement on Left-Right economic values axis'],['number[UInt8]'],"[5.0, 6.0, 3.0]" +Enumerate the top 4 most common positions on the Progressive-Conservative economic values axis.,"[5.0, 3.0, 4.0, 0.0]",list[number],['User self- placement on Progressive-Conservative economic values axis'],['number[UInt8]'],"[5.0, 3.0, 0.0, 4.0]" +What are the top 6 most common positions on the 'Constitutional organisation of the country (More Descentralization)' scale?,"[2.0, 3.0, 4.0, 1.0, 5.0]",list[number],['Constitutional organisation of the country (More Descentralization)'],['number[UInt8]'],"[2.0, 4.0, 3.0]" diff --git a/056_Spain_Survey_2015/sample.csv b/data/057_Spain/sample.csv similarity index 100% rename from 056_Spain_Survey_2015/sample.csv rename to data/057_Spain/sample.csv diff --git a/057_US_Polls_2020/all.parquet b/data/058_US/all.parquet similarity index 100% rename from 057_US_Polls_2020/all.parquet rename to data/058_US/all.parquet diff --git a/057_US_Polls_2020/info.yml b/data/058_US/info.yml similarity index 100% rename from 057_US_Polls_2020/info.yml rename to data/058_US/info.yml diff --git a/data/058_US/qa.csv b/data/058_US/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..d35f1debddff4252dbf852fb9d66c3ac57e45a06 --- /dev/null +++ b/data/058_US/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Are there survey participants who are not registered to vote?,True,boolean,['Are you registered to vote?'],['category'],True +Are there any respondents who participated in the 2016 Presidential election (four years ago) but are not planning to do so in the upcoming election?,True,boolean,"['Did you vote in the 2016 Presidential election? (Four years ago)', 'How likely are you to vote in the forthcoming US Presidential election? Early Voting Open']","['category', 'category']",True +Do we have any respondents in the dataset who didn't participate in the 2016 Presidential election (four years ago) but intend to do so in the upcoming election?,True,boolean,"['Did you vote in the 2016 Presidential election? (Four years ago)', 'How likely are you to vote in the forthcoming US Presidential election? Early Voting Open']","['category', 'category']",True +Do we have respondents who have shifted their voting preference from the 2016 election (four years ago) to the upcoming one?,True,boolean,"['Who did you vote for in the 2016 Presidential election? (Four years ago)', 'Who are you most likely to vote for on election day?']","['category', 'category']",True +How many respondents in the survey are eligible to vote?,1315,number,['Are you registered to vote?'],['category'],11 +What is the count of respondents who are leaning towards voting for Joe Biden in the upcoming election?,799,number,['Who are you most likely to vote for on election day?'],['category'],0 +How many respondents have a high school degree or less as their highest level of education?,0,number,['What is the highest degree or level of school you have *completed* ?'],['category'],0 +How many respondents are from the region adjacent to the South Atlantic Ocean?,774,number,['Division'],['category'],0 +What is the most frequent age group among the respondents?,65+,category,['How old are you?'],['category'],25-34 +Who is the preferred choice among the respondents for the upcoming election?,Donald Trump (Republican),category,['Who are you most likely to vote for on election day?'],['category'],Joe Biden (Democrat) +What is the most commonly achieved educational level among the respondents?,"Some college, no degree",category,['What is the highest degree or level of school you have *completed* ?'],['category'],High school graduate (includes equivalency) +Which geographical division has the greatest representation among the respondents?,South Atlantic,category,['Division'],['category'],South Atlantic +Identify the top 5 states with the greatest number of respondents.,"['CA', 'TX', 'NY', 'FL', 'GA']",list[category],['State'],['category'],"['MI', 'GA', 'AL', 'CA', 'TX']" +Enumerate the top 4 most common professions among the respondents.,"['Other', 'Healthcare', 'Office worker or other professional', 'Industrial (e.g. construction, manufacturing, maintenance and repair)']",list[category],['Which of these best describes the kind of work you do?'],['category'],"['Education and training', 'Office worker or other professional', 'Industrial (e.g. construction, manufacturing, maintenance and repair)', 'Healthcare']" +Identify the top 3 ethnic groups with the most representation among the respondents.,"['White (not Hispanic, Latino or Spanish origin)', 'Black or African American (not Hispanic, Latino or Spanish origin)', 'Hispanic, Latino or Spanish origin']",list[category],['Which of the following best describes your ethnic heritage?'],['category'],"['White (not Hispanic, Latino or Spanish origin)', 'Black or African American (not Hispanic, Latino or Spanish origin)', 'Asian']" +Enumerate the top 6 most represented age groups among the respondents.,"['65+', '55-64', '45-54', '35-44', '18-24', '25-34']",list[category],['How old are you?'],['category'],"['25-34', '55-64', '65+', '35-44', '18-24', '45-54']" +Identify the top 3 counties (using FIPS codes) with the greatest number of respondents.,"[6037, 13121, 48201]",list[number],['County FIPS'],['number[uint16]'],"[13135, 29189, 13095]" +Enumerate the highest 4 unique weight values in the dataset.,"[0.8085780015111617, 0.7742084493732905, 0.3063435812288158, 0.629527660735561]",list[number],['Weight'],['number[double]'],"[4.871233760276248, 0.8475708375044543, 0.7854647440023211, 0.941364535331836]" +List the top 5 urban/rural categories (using NCHS codes) with the greatest number of respondents.,"[1, 2, 3, 4, 5]",list[number],['NCHS Urban/rural'],['number[uint8]'],"[1, 2, 5, 3, 6]" +Enumerate the top 6 most common likelihood values among the respondents.,"[10.0, 11.0, 0.0, 1.0, 9.0, 5.0]",list[number],['likelihood'],['number[UInt8]'],"[10.0, 11.0, 1.0, 2.0, 6.0, 7.0]" diff --git a/057_US_Polls_2020/sample.csv b/data/058_US/sample.csv similarity index 100% rename from 057_US_Polls_2020/sample.csv rename to data/058_US/sample.csv diff --git a/058_Second_Hand_Cars/all.parquet b/data/059_Second/all.parquet similarity index 100% rename from 058_Second_Hand_Cars/all.parquet rename to data/059_Second/all.parquet diff --git a/058_Second_Hand_Cars/info.yml b/data/059_Second/info.yml similarity index 100% rename from 058_Second_Hand_Cars/info.yml rename to data/059_Second/info.yml diff --git a/data/059_Second/qa.csv b/data/059_Second/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..4a5d72f96a165b020260fcdb0216c8c40d8a5535 --- /dev/null +++ b/data/059_Second/qa.csv @@ -0,0 +1,24 @@ +question,answer,columns_used,type,column_types,sample_answer +Is there a car model named 'Golf' listed?,False,['model'],boolean,['category'],False +Are there cars associated with the dealer 'Autos Raymara'?,True,['dealer'],boolean,['category'],False +Is there a car version that mentions 'BMW'?,True,['version'],boolean,['text'],True +Are there cars with a 'Manual' shift?,True,['shift'],boolean,['category'],True +How many unique car models are listed?,940,['model'],number,['category'],19 +"On average, how many photos are provided for the cars?",16.19912,['photos'],number,['number[uint8]'],19.1 +What's the highest price a car is listed for?,549900,['price'],number,['number[uint32]'],61990 +How many cars are from the year 2020?,4237,['year'],number,['number[UInt16]'],3 +Which dealer has the car with the highest price listed?,Supergarage,"['dealer', 'price']",category,"['category', 'number[uint32]']",automotorDURSAN.com A +Which car make is the most common?,VOLKSWAGEN,['make'],category,['category'],BMW +What type of fuel is the most common for the cars?,Diésel,['fuel'],category,['category'],Diésel +In which province are the most cars located?,Madrid,['province'],category,['category'],Madrid +Which are the top 3 provinces with the most car listings?,"['Madrid', 'Barcelona', 'Valencia']",['province'],list[category],['category'],"['Madrid', 'Palencia', 'Málaga']" +List the 4 most common car colors in the dataset.,"['Blanco', 'Gris / Plata', 'Negro', 'Azul']",['color'],list[category],['category'],"['Gris / Plata', 'Negro', 'Azul', 'Gris / Plata (gris)']" +Which 5 car makes are the most prevalent?,"['VOLKSWAGEN', 'BMW', 'MERCEDES-BENZ', 'AUDI', 'PEUGEOT']",['make'],list[category],['category'],"['MERCEDES-BENZ', 'BMW', 'SEAT', 'AUDI', 'HONDA']" +List the 2 least common fuels used in the cars.,"['Gas natural (CNG)', 'Gas licuado (GLP)']",['fuel'],list[category],['category'],"['Híbrido', 'Eléctrico']" +What are the top 4 most common years of the cars?,"[2016.0, 2017.0, 2019.0, 2020.0]",['year'],list[number],['number[UInt16]'],"[2016.0, 2020.0, 2007.0, 2018.0]" +List the 3 highest mileages present.,"[5000000, 4000006, 3500000]",['kms'],list[number],['number[uint32]'],"['370000', '300000', '254000']" +Which 5 cars have the most photos associated?,"[54, 54, 54, 54, 54]",['photos'],list[number],['number[uint8]'],"[54, 44, 40, 32, 29]" +List the 6 cars with the most power.,"[800.0, 800.0, 796.0, 772.0, 720.0, 720.0]",['power'],list[number],['number[UInt16]'],"[258.0, 258.0, +218.0, +182.0, +180.0]" diff --git a/058_Second_Hand_Cars/sample.csv b/data/059_Second/sample.csv similarity index 100% rename from 058_Second_Hand_Cars/sample.csv rename to data/059_Second/sample.csv index cd94367b21df0099891884f42e739fcc4409f1bc..213be7da986d7efca09cd8f9d13d89287b3077e6 100644 --- a/058_Second_Hand_Cars/sample.csv +++ b/data/059_Second/sample.csv @@ -1,21 +1,21 @@ fuel,color,shift,make,model,price,year,kms,power,province,dealer,photos,version -Diésel,Negro,Automático,MERCEDES-BENZ,Clase C,10000,2007.0,200000,,Murcia,6e9f531af5b3410601edffdcadc0494a,8,MERCEDES-BENZ -Diésel,Gris / Plata,Manual,SEAT,Córdoba,1150,2000.0,370000,,Palencia,5fd6e81b5f6f20a0985a26724f47b95e,2,SEAT Cordoba 3p. -Diésel,Gris / Plata,Automático,BMW,X6,55490,2018.0,26391,258.0,Madrid,Flexicar Leganés,40,BMW X6 xDrive30d 5p. -Gasolina,Gris / Plata,Automático,MERCEDES-BENZ,Clase C,8490,2008.0,233000,156.0,Málaga,Flexicar Málaga,25,MERCEDES-BENZ Clase C C 180 K Avantgarde Estate 5p. -Diésel,Gris / Plata,Manual,RENAULT,Clio,3700,2007.0,148000,,A Coruña,c707c87831c70b8973c5b7c827f708b9,8,RENAULT Clio 5p. -Gasolina,Negro,Manual,FORD,Focus,2800,2005.0,205000,100.0,Madrid,89cf822db294a9af9bb533773cefd8a8,0,FORD Focus 1.6 TREND 3p. -Híbrido,Gris / Plata,Automático,TOYOTA,Auris,15000,2016.0,44000,136.0,Palencia,3ff65d248cc989caf757c3b78ddca356,3,TOYOTA Auris 1.8 140H Hybrid Active 5p. Diésel,Gris / Plata (gris),Manual,MERCEDES-BENZ,Clase GLS,61990,2017.0,115242,258.0,Madrid,automotorDURSAN.com A,54,MERCEDES-BENZ Clase GLS GLS 350 d 4MATIC 5p. -Diésel,Gris / Plata,Manual,BMW,Serie 3,3300,2004.0,254000,150.0,Madrid,Automóviles San José,22,BMW Serie 3 320D TOURING 5p. -Diésel,Gris / Plata,Manual,SEAT,Ibiza,18660,2020.0,25,95.0,Pontevedra,Tambo Motor,18,SEAT Ibiza 1.6 TDI 70kW 95CV Style Go 5p. Eléctrico,Blanco,Automático,BMW,i3,23975,2018.0,9886,170.0,Madrid,Canalcar,44,BMW i3 94ah 5p. +Diésel,Gris / Plata,Automático,BMW,X6,55490,2018.0,26391,258.0,Madrid,Flexicar Leganés,40,BMW X6 xDrive30d 5p. Gasolina,Negro (NEGRO PROFUNDO EFECTO PERLA),Automático,VOLKSWAGEN,T-Cross,20490,2020.0,10,115.0,Barcelona,"Evarist Automocio, Sl",32,VOLKSWAGEN TCross Advance 1.0 TSI 85kW 115CV DSG 5p. +Diésel,Azul,Automático,AUDI,A4 Allroad Quattro,27900,2016.0,135000,218.0,Alicante,QualityCars Denia,29,AUDI A4 Allroad Quattro 3.0 TDI 218CV quat S tron unlimited edit 5p. Diésel,Azul (Dark Sapphire),Automático,JAGUAR,F-Pace,34490,2016.0,67615,180.0,Valencia,Motor Center,29,JAGUAR Fpace 2.0L i4D AWD Automatico Prestige 5p. -Diésel,Rojo (B83 Blazing Red Metalizada),Manual,MINI,MINI,15490,2016.0,65235,116.0,Barcelona,Barcelona Premium,9,MINI MINI COOPER D 5 PUERTAS 5p. -Diésel,Gris / Plata,Manual,AUDI,A4,18500,2016.0,155000,150.0,A Coruña,Citova,13,AUDI A4 Avant 2.0 TDI 150CV Advanced edition 5p. -Diésel,Negro,Manual,HONDA,FR-V,3650,2008.0,300000,,Asturias,70483b6e100c9cebbffcdc62dea07eda,3,HONDA FRV 5p. -Gasolina,Negro,Manual,BMW,Serie 5,7700,2005.0,360,,Sevilla,464e07afc9e46359fb480839150595c5,5,BMW Serie 5 5p. +Gasolina,Gris / Plata,Automático,MERCEDES-BENZ,Clase C,8490,2008.0,233000,156.0,Málaga,Flexicar Málaga,25,MERCEDES-BENZ Clase C C 180 K Avantgarde Estate 5p. +Diésel,Gris / Plata,Manual,BMW,Serie 3,3300,2004.0,254000,150.0,Madrid,Automóviles San José,22,BMW Serie 3 320D TOURING 5p. Gasolina,Negro,Manual,HONDA,HR-V,25990,2020.0,8000,182.0,Cantabria,Auto Norte,20,HONDA HRV 1.5 iVTEC Turbo Sport 5p. Diésel,Azul,Automático,MERCEDES-BENZ,Clase GLC,36900,2017.0,69000,170.0,Málaga,Autos Dominguez,18,MERCEDES-BENZ Clase GLC GLC 220 d 4MATIC 5p. -Diésel,Azul,Automático,AUDI,A4 Allroad Quattro,27900,2016.0,135000,218.0,Alicante,QualityCars Denia,29,AUDI A4 Allroad Quattro 3.0 TDI 218CV quat S tron unlimited edit 5p. +Diésel,Gris / Plata,Manual,SEAT,Ibiza,18660,2020.0,25,95.0,Pontevedra,Tambo Motor,18,SEAT Ibiza 1.6 TDI 70kW 95CV Style Go 5p. +Diésel,Gris / Plata,Manual,AUDI,A4,18500,2016.0,155000,150.0,A Coruña,Citova,13,AUDI A4 Avant 2.0 TDI 150CV Advanced edition 5p. +Diésel,Rojo (B83 Blazing Red Metalizada),Manual,MINI,MINI,15490,2016.0,65235,116.0,Barcelona,Barcelona Premium,9,MINI MINI COOPER D 5 PUERTAS 5p. +Diésel,Negro,Automático,MERCEDES-BENZ,Clase C,10000,2007.0,200000,,Murcia,6e9f531af5b3410601edffdcadc0494a,8,MERCEDES-BENZ +Diésel,Gris / Plata,Manual,RENAULT,Clio,3700,2007.0,148000,,A Coruña,c707c87831c70b8973c5b7c827f708b9,8,RENAULT Clio 5p. +Gasolina,Negro,Manual,BMW,Serie 5,7700,2005.0,360,,Sevilla,464e07afc9e46359fb480839150595c5,5,BMW Serie 5 5p. +Diésel,Negro,Manual,HONDA,FR-V,3650,2008.0,300000,,Asturias,70483b6e100c9cebbffcdc62dea07eda,3,HONDA FRV 5p. +Híbrido,Gris / Plata,Automático,TOYOTA,Auris,15000,2016.0,44000,136.0,Palencia,3ff65d248cc989caf757c3b78ddca356,3,TOYOTA Auris 1.8 140H Hybrid Active 5p. +Diésel,Gris / Plata,Manual,SEAT,Córdoba,1150,2000.0,370000,,Palencia,5fd6e81b5f6f20a0985a26724f47b95e,2,SEAT Cordoba 3p. +Gasolina,Negro,Manual,FORD,Focus,2800,2005.0,205000,100.0,Madrid,89cf822db294a9af9bb533773cefd8a8,0,FORD Focus 1.6 TREND 3p. diff --git a/059_Bakery_Purchases/all.parquet b/data/060_Bakery/all.parquet similarity index 100% rename from 059_Bakery_Purchases/all.parquet rename to data/060_Bakery/all.parquet diff --git a/059_Bakery_Purchases/info.yml b/data/060_Bakery/info.yml similarity index 51% rename from 059_Bakery_Purchases/info.yml rename to data/060_Bakery/info.yml index ab2318dac69dd3f261cdc25d0762b8fe79dd3dd3..30b38b2aadda45ed53c3491f512719b0a1781dcf 100644 --- a/059_Bakery_Purchases/info.yml +++ b/data/060_Bakery/info.yml @@ -1,6 +1,6 @@ -Explore: https://public.graphext.com/6783af0ef41447ec/index.html +Explore: https://public.graphext.com/6f2102e80f47a192/index.html Source: https://www.kaggle.com/code/xvivancos/market-basket-analysis/report -Title: '🍞 Bakery Purchases: Market Basket Analysis' +Title: 🍞 Bakery Purchases tags: - business - money diff --git a/data/060_Bakery/qa.csv b/data/060_Bakery/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..d065c67e241b3281eaf997217e899402722d2e58 --- /dev/null +++ b/data/060_Bakery/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Are all transactions unique?,True,boolean,[Transaction],['number[uint16]'],True +Is there any transaction that took place during the night?,True,boolean,[period_day],['category'],False +Do all items have transactions recorded on weekdays?,True,boolean,"[Item, weekday_weekend]","['category', 'category']",False +Are there any transactions recorded in the evening on weekends?,True,boolean,"[period_day, weekday_weekend]","['category', 'category']",True +How many unique items are there in the dataset?,95,number,[Item],['category'],12 +On how many different days were transactions recorded?,159,number,[date_time],['category'],20 +What's the highest transaction number?,9684,number,[Transaction],['number[uint16]'],9133 +How many transactions were made during the afternoon?,2478,number,"[Transaction, period_day]","['number[uint16]', 'category']",0 +Which day period has the highest number of transactions?,morning,category,"[period_day, Transaction]","['category', 'number[uint16]']",afternoon +"On weekends, what's the most commonly bought item?",Coffee,category,"[Item, weekday_weekend]","['category', 'category']",Hearty & Seasonal +What's the least popular item bought during weekdays?,Adjustment,category,"[Item, weekday_weekend]","['category', 'category']",Farm House +"During which period of the day is ""Hot chocolate"" most frequently bought?",morning,category,"[Item, period_day]","['category', 'category']", +List the top 3 items most frequently bought in the morning.,"['Coffee', 'Bread', 'Pastry']",list[category],"[Item, period_day]","['category', 'category']","['Coffee', 'Bread', 'Farm House']" +Name the bottom 4 items least purchased during the afternoon.,"['Chicken sand', 'Gift voucher', 'Bare Popcorn', 'Raw bars']",list[category],"[Item, period_day]","['category', 'category']",[] +Identify the top 5 items sold on weekends.,"['Coffee', 'Bread', 'Tea', 'Cake', 'Pastry']",list[category],"[Item, weekday_weekend]","['category', 'category']",[] +What are the 4 items tthat were bought two times in the evening?,"['Art Tray', 'Mighty Protein', 'Mortimer', 'Vegan Mincepie']",list[category],"[Item, period_day]","['category', 'category']",[] +Which are the top 4 transaction numbers with the most items bought?,"[6474, 6716, 6279, 6412]",list[number],[Transaction],['number[uint16]'],"[6103, 1259, 628, 4627]" +Identify the bottom 5 transaction numbers by frequency.,"[9680, 9681, 9682, 9683, 9684]",list[number],[Transaction],['number[uint16]'],"[2711, 956, 7435, 2214, 5816]" +"List the top 6 transaction numbers during which ""Bread"" was purchased.","[6412, 6279, 6474, 6603, 6716, 6642]",list[number],"[Transaction, Item]","['number[uint16]', 'category']","[2850, 7104, 7776, 5816]" +Name the bottom 2 transaction numbers where purchases were made in the morning.,"[9683, 9684]",list[number],"[Transaction, period_day]","['number[uint16]', 'category']",[] diff --git a/059_Bakery_Purchases/sample.csv b/data/060_Bakery/sample.csv similarity index 100% rename from 059_Bakery_Purchases/sample.csv rename to data/060_Bakery/sample.csv diff --git a/060_Disneyland_Customer_Reviews/all.parquet b/data/061_Disneyland/all.parquet similarity index 100% rename from 060_Disneyland_Customer_Reviews/all.parquet rename to data/061_Disneyland/all.parquet diff --git a/060_Disneyland_Customer_Reviews/info.yml b/data/061_Disneyland/info.yml similarity index 100% rename from 060_Disneyland_Customer_Reviews/info.yml rename to data/061_Disneyland/info.yml diff --git a/data/061_Disneyland/qa.csv b/data/061_Disneyland/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..ceee7b7616ffa82b340fba2bab2d3064bc82694b --- /dev/null +++ b/data/061_Disneyland/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Are all the reviews from Australia positive (rating > 3)?,False,boolean,"['Reviewer_Location', 'Rating']","['category', 'number[uint8]']",True +Is Disneyland_HongKong the most reviewed branch?,False,boolean,['Branch'],['category'],False +Are there any reviews with a rating of 1?,True,boolean,['Rating'],['number[uint8]'],True +Does every reviewer location have at least one review with a rating of 5?,False,boolean,"['Reviewer_Location', 'Rating']","['category', 'number[uint8]']",False +How many unique reviewer locations are there?,162,number,['Reviewer_Location'],['category'],9 +What is the average rating for Disneyland_HongKong?,4.204158004158004,number,"['Branch', 'Rating']","['category', 'number[uint8]']",4.25 +What is the maximum review ID?,670801367,number,['Review_ID'],['number[uint32]'],644423763 +How many reviews were made in 2019?,786,number,['Year_Month'],['category'],2 +What is the most common reviewer location?,United States,category,['Reviewer_Location'],['category'],United States +What is the branch with the lowest average rating?,Disneyland_Paris,category,"['Branch', 'Rating']","['category', 'number[uint8]']",Disneyland_California +In which year-month was the most negative review (rating=1) made?,missing,category,"['Year_Month', 'Rating']","['category', 'number[uint8]']",2011-10 +What is the reviewer location with the highest average rating?,Armenia,category,"['Reviewer_Location', 'Rating']","['category', 'number[uint8]']",Australia +What are the top 3 reviewer locations with the most reviews?,"['United States', 'United Kingdom', 'Australia']",list[category],['Reviewer_Location'],['category'],"['United States', 'Australia', 'Malta']" +What are the bottom 2 branches in terms of average rating?,"['Disneyland_Paris', 'Disneyland_HongKong']",list[category],"['Branch', 'Rating']","['category', 'number[uint8]']","['Disneyland_California', 'Disneyland_HongKong']" +What are the top 4 year-months with the most reviews?,"['missing', '2015-8', '2015-7', '2015-12']",list[category],['Year_Month'],['category'],"['missing', '2019-1', '2015-12', '2012-5']" +What are the bottom 3 reviewer locations in terms of average rating?,"['Turks and Caicos Islands', 'South Sudan', 'Suriname']",list[category],"['Reviewer_Location', 'Rating']","['category', 'number[uint8]']","['Canada', 'United States', 'United Kingdom']" +What are the top 5 review IDs in terms of rating?,"[670585330, 670570869, 670443403, 670435886, 670324965]",list[number],"['Review_ID', 'Rating']","['number[uint32]', 'number[uint8]']","[540713188, 576395715, 310041955, 121577468, 441572512]" +What are the bottom 4 review IDs in terms of rating?,"[662641193, 658624005, 649615606, 647822351]",list[number],"['Review_ID', 'Rating']","['number[uint32]', 'number[uint8]']","[119781124, 337648026, 620582661, 124120037]" +What are the top 6 ratings given by reviewers from Australia?,"[5, 5, 5, 5, 5, 5]",list[number],"['Reviewer_Location', 'Rating']","['category', 'number[uint8]']",[5] +What are the bottom 3 ratings given for Disneyland_HongKong?,"[1, 1, 1]",list[number],"['Branch', 'Rating']","['category', 'number[uint8]']","[5, 2]" diff --git a/060_Disneyland_Customer_Reviews/sample.csv b/data/061_Disneyland/sample.csv similarity index 100% rename from 060_Disneyland_Customer_Reviews/sample.csv rename to data/061_Disneyland/sample.csv diff --git a/061_Trump_tweets/all.parquet b/data/062_Trump/all.parquet similarity index 100% rename from 061_Trump_tweets/all.parquet rename to data/062_Trump/all.parquet diff --git a/061_Trump_tweets/info.yml b/data/062_Trump/info.yml similarity index 100% rename from 061_Trump_tweets/info.yml rename to data/062_Trump/info.yml diff --git a/data/062_Trump/qa.csv b/data/062_Trump/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..453de8b0280d8f0b080e4950a0e9adfb2cb64db6 --- /dev/null +++ b/data/062_Trump/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Are all the tweets in English?,False,boolean,['lang'],['category'],True +Has the author ever been retweeted?,True,boolean,['retweets'],['number[UInt32]'],True +Are there any tweets with more than 10000 retweets?,True,boolean,['retweets'],['number[uint32]'],True +Have any of the tweets been favorited more than 50000 times?,True,boolean,['favorites'],['number[uint32]'],True +How many unique authors are there?,1,number,['author_name'],['category'],1 +What is the average number of retweets?,8774.52044683822,number,['retweets'],['number[uint32]'],8111.15 +What is the maximum number of favorites received for a single tweet?,589793,number,['favorites'],['number[uint32]'],105448 +How many tweets were posted in 2018?,2891,number,['date'],"['date[ns, UTC]']",2 +What is the most common author name?,Donald J. Trump,category,['author_name'],['category'],Donald J. Trump +What is the tweet with the most favorites?,Such a beautiful and important evening! The forgotten man and woman will never be forgotten again. We will all come together as never before,category,"['text', 'favorites']","['text', 'number[uint32]']","I have great confidence that China will properly deal with North Korea. If they are unable to do so, the U.S., with its allies, will! U.S.A." +In which language is the tweet with the most retweets written?,und,category,"['lang', 'retweets']","['category', 'number[uint32]']",en +What is the most common language of the tweets?,en,category,['lang'],['category'],en +What are the top 3 author handlers with the most tweets?,['realDonaldTrump'],list[category],['author_handler'],['category'],['realDonaldTrump'] +What are the bottom 2 languages in terms of tweet count?,"['pt', 'fi']",list[category],['lang'],['category'],['en'] +What are the top 4 mentioned names in the tweets?,"['realDonaldTrump', 'FoxNews', 'CNN', 'foxandfriends']",list[category],['mention_names'],['list[category]'],"['[]', '""realDonaldTrump""]', '[""IvankaTrump""', '""trumpferrypoint""']" +What are the bottom 3 author names in terms of tweet count?,['Donald J. Trump'],list[category],['author_name'],['category'],['Donald J. Trump'] +What are the top 5 tweet IDs in terms of retweet count?,"[881503147168071680, 795954831718498305, 929511061954297857, 796315640307060738, 948355557022420992]",list[number],"['id', 'retweets']","['number[int64]', 'number[uint32]']","[852508752142114816, 900150814081036288, 1017190186269184001, 822501939267141634, 761711856457125888]" +What are the bottom 4 tweet IDs in terms of favorite count?,"[591222909626114050, 591412084895838208, 586751374286721024, 575589231160127489]",list[number],"['id', 'favorites']","['number[int64]', 'number[uint32]']","[603361519192174592, 589632894177533953, 616672730319069185, 618552478653616128]" +What are the top 6 favorite counts of the tweets?,"[589793, 589750, 557779, 539249, 476457, 376626]",list[number],['favorites'],['number[uint32]'],"[105448, 85433, 84944, 79544, 67612, 59793]" +What are the bottom 3 retweet counts of the tweets?,"[1, 1, 2]",list[number],['retweets'],['number[uint32]'],"[10, 14, 376]" diff --git a/061_Trump_tweets/sample.csv b/data/062_Trump/sample.csv similarity index 100% rename from 061_Trump_tweets/sample.csv rename to data/062_Trump/sample.csv diff --git a/062_Influencers/all.parquet b/data/063_Influencers/all.parquet similarity index 100% rename from 062_Influencers/all.parquet rename to data/063_Influencers/all.parquet diff --git a/062_Influencers/info.yml b/data/063_Influencers/info.yml similarity index 100% rename from 062_Influencers/info.yml rename to data/063_Influencers/info.yml diff --git a/data/063_Influencers/qa.csv b/data/063_Influencers/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..67a5190ead20a6b760e2f22b88781d37a95fb142 --- /dev/null +++ b/data/063_Influencers/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Are there any organizations in the dataset?,False,boolean,['is_organization'],['boolean'],False +Are there any individuals (non-organizations) in the dataset?,True,boolean,['is_organization'],['boolean'],True +Do all entities have a picture?,True,boolean,['pic'],['url'],True +Are there any entities with a weight greater than 500?,True,boolean,['weight'],['number[double]'],False +How many unique communities are there?,9,number,['community'],['number[uint32]'],6 +What is the average page rank norm?,0.08848033260794509,number,['page_rank_norm'],['number[double]'],0.0923955552240227 +What is the maximum weight of an entity?,770.5,number,['weight'],['number[double]'],324.5 +How many entities have a community identifier of 16744206?,651,number,['community'],['number[uint32]'],11 +What is the most common name?,Christophe Viau,category,['name'],['category'],Peter Skomoroch +Which entity has the highest page rank norm?,Mike Bostock,category,"['name', 'page_rank_norm']","['category', 'number[double]']",Data Science Fact +What is the picture URL of the entity with the maximum weight?,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/016/457/thumb/Saw-whet_Owl_10_normal.jpg?1517502050,category,"['pic', 'weight']","['url', 'number[double]']",https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/016/416/thumb/8f8493dfc040e56ef7ff8f59f9474774_normal.jpeg?1517502015 +Which entity has the highest y-coordinate?,The Gibson Project,category,"['name', 'y']","['category', 'number[double]']",Paul Klemm +What are the top 3 entity names with the highest weights?,"['Lynn Cherny', 'Alberto Cairo', 'Sinan Aral']",list[category],"['name', 'weight']","['category', 'number[double]']","['Peter Skomoroch', 'Nieman Lab', 'Munmun De Choudhury']" +What are the bottom 2 entities in terms of page rank norm?,"['LIFE', 'New Options Project']",list[category],"['name', 'page_rank_norm']","['category', 'number[double]']","['Christopher', 'Chris J. Headleand']" +What are the top 4 entities with the highest x-coordinates?,"['Detective.io', 'The Thrust', 'Open Budgets', 'NewsFuturist']",list[category],"['name', 'x']","['category', 'number[double]']","['Catherine Rampell', 'Nieman Lab', 'Deok Gun Park', 'ESFL']" +What are the bottom 3 entities in terms of y-coordinates?,"['digital PR cat', 'Ismail Onur Filiz', 'Dave Golland']",list[category],"['name', 'y']","['category', 'number[double]']","['ESFL', 'WikipediaLiveMonitor', 'Alberto Perdomo']" +What are the top 5 entity IDs in terms of weight?,"[568, 423, 6392, 4548, 579]",list[number],"['id', 'weight']","['number[uint32]', 'number[double]']","[527, 498, 411, 8031, 91203]" +What are the bottom 4 entity IDs in terms of page rank norm?,"[177, 240, 294, 369]",list[number],"['id', 'page_rank_norm']","['number[uint32]', 'number[double]']","[35070, 35046, 35106, 35054]" +What are the top 6 page rank norms of the entities?,"[1.0, 0.6029751067034804, 0.5666707687637932, 0.5202348027491394, 0.5110606617858531, 0.5081183103684572]",list[number],['page_rank_norm'],['number[double]'],"[0.4905835057931528, 0.2858285808469396, 0.2194061763508274, 0.2171608658929857, 0.1213462154304343, 0.1023296876109954]" +What are the bottom 3 weights of the entities?,"[1.0, 1.0, 1.0]",list[number],['weight'],['number[double]'],"[3.0, 5.0, 7.0]" diff --git a/062_Influencers/sample.csv b/data/063_Influencers/sample.csv similarity index 100% rename from 062_Influencers/sample.csv rename to data/063_Influencers/sample.csv index 778ee3aa5009a17a54c487815d928fb582ab0e79..96ebf7d512e9afe931bff622608674061b8ffcef 100644 --- a/062_Influencers/sample.csv +++ b/data/063_Influencers/sample.csv @@ -1,21 +1,21 @@ name,weight,x,is_organization,community,id,page_rank_norm,y,pic -Peter Skomoroch,324.5,542.3357087054555,False,16744206,527,0.2194061763508274,250.43889962348,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/016/416/thumb/8f8493dfc040e56ef7ff8f59f9474774_normal.jpeg?1517502015 +Christopher,63.0,1046.85985057688,False,16744206,35070,0.0011644932467731,1511.9625723548768,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/042/951/thumb/96c0590f41f0f9af2e4176b0f6890467_normal.jpeg?1517565061 Chris J. Headleand,7.0,-504.8607865514298,False,16744206,35046,0.0016400009027285,1708.065073048048,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/042/927/thumb/twitter_normal.jpg?1517565042 -Catherine Rampell,76.5,1226.3728139334712,False,16744206,526,0.1213462154304343,-317.94169853888553,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/016/415/thumb/WqfzPQ9b_normal.jpeg?1517502014 -WikipediaLiveMonitor,3.0,-355.1344983695895,False,9197131,181,0.0102051567888091,-1200.1631752409328,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/016/070/thumb/uyjlf-A9_normal.png?1517501749 -Moira Burke,132.0,226.555226293652,False,2062260,8031,0.0857382638801249,3.696087831845453,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/023/847/thumb/z3OuzS_c_normal.jpeg?1517507265 +Deok Gun Park,17.0,1068.8035102675362,False,16744206,35106,0.0031516818965411,-679.8269352210291,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/042/986/thumb/IMG_0142_normal.JPG?1517565084 +Paul Klemm,42.0,834.5589498168492,False,16744206,35054,0.0036353770062821,1731.8423075515468,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/042/935/thumb/fInJx-KC_normal.jpg?1517565047 ESFL,5.0,1065.7844808162706,False,14907330,267,0.0043617313078933,-1277.5365883054549,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/016/156/thumb/lBLq_SvM_normal.jpg?1517501819 +WikipediaLiveMonitor,3.0,-355.1344983695895,False,9197131,181,0.0102051567888091,-1200.1631752409328,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/016/070/thumb/uyjlf-A9_normal.png?1517501749 +Alberto Perdomo,18.0,-653.226927038042,False,14034728,489,0.0166821309632443,-700.3419060894585,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/016/378/thumb/DkMgC9Ex_normal.jpeg?1517501986 +Lothar Krempel,124.0,100.84325275278694,False,2062260,42755,0.0350801041472904,611.4034093897568,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/049/121/thumb/krempel_lothar_normal.jpg?1517569346 Robert Harris,102.0,908.18971418739,False,16744206,35121,0.0362281625727942,1308.4419715755362,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/043/001/thumb/glyph-glow-500x483_normal.png?1517565094 Hortonworks,42.0,607.9121194346857,False,16744206,282,0.0366773129253865,-659.4966384557767,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/016/171/thumb/f1b6f0596bdda20a9142b0c4ad23dc11_normal.png?1517501831 -Christopher,63.0,1046.85985057688,False,16744206,35070,0.0011644932467731,1511.9625723548768,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/042/951/thumb/96c0590f41f0f9af2e4176b0f6890467_normal.jpeg?1517565061 -Data Science Fact,100.0,0.1974799057110523,False,12369186,204402,0.4905835057931528,530.2165391499066,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/204/535/thumb/sMpYCCGn_normal.jpg?1590839982 -Lothar Krempel,124.0,100.84325275278694,False,2062260,42755,0.0350801041472904,611.4034093897568,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/049/121/thumb/krempel_lothar_normal.jpg?1517569346 -Nieman Lab,251.5,1174.45795206497,False,16744206,498,0.2858285808469396,127.09248222777484,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/016/387/thumb/pzZXwZC8_normal.jpeg?1517501993 -Deok Gun Park,17.0,1068.8035102675362,False,16744206,35106,0.0031516818965411,-679.8269352210291,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/042/986/thumb/IMG_0142_normal.JPG?1517565084 -Alberto Perdomo,18.0,-653.226927038042,False,14034728,489,0.0166821309632443,-700.3419060894585,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/016/378/thumb/DkMgC9Ex_normal.jpeg?1517501986 -Vega & Vega-Lite,131.5,796.1933529772459,False,16744206,91203,0.0825439390118387,1403.4402475642626,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/096/229/thumb/IraxcAMI_normal.jpg?1517601308 -Paul Klemm,42.0,834.5589498168492,False,16744206,35054,0.0036353770062821,1731.8423075515468,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/042/935/thumb/fInJx-KC_normal.jpg?1517565047 complexitat.cat,117.0,-776.7657429626081,False,2062260,315,0.0424743661076428,304.8443024128713,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/016/204/thumb/complexitat.CAT_normal.jpg?1517501855 -DeepMind,120.0,59.79731432121585,False,2062260,43941,0.2171608658929857,552.8746872865486,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/050/302/thumb/NzcXa05I_normal.png?1517570178 MIT Visualization Group,61.0,468.6863757282269,False,16744206,155963,0.0516733517977699,1534.0082455431257,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/156/537/thumb/7Gb2I-74_normal.jpg?1545643719 +Vega & Vega-Lite,131.5,796.1933529772459,False,16744206,91203,0.0825439390118387,1403.4402475642626,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/096/229/thumb/IraxcAMI_normal.jpg?1517601308 +Moira Burke,132.0,226.555226293652,False,2062260,8031,0.0857382638801249,3.696087831845453,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/023/847/thumb/z3OuzS_c_normal.jpeg?1517507265 Munmun De Choudhury,216.5,117.88775498251576,False,2062260,411,0.1023296876109954,97.01691057874534,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/016/300/thumb/bfbb7731025ed0997e202cabe8c36e0f_normal.jpeg?1517501929 +Catherine Rampell,76.5,1226.3728139334712,False,16744206,526,0.1213462154304343,-317.94169853888553,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/016/415/thumb/WqfzPQ9b_normal.jpeg?1517502014 +DeepMind,120.0,59.79731432121585,False,2062260,43941,0.2171608658929857,552.8746872865486,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/050/302/thumb/NzcXa05I_normal.png?1517570178 +Peter Skomoroch,324.5,542.3357087054555,False,16744206,527,0.2194061763508274,250.43889962348,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/016/416/thumb/8f8493dfc040e56ef7ff8f59f9474774_normal.jpeg?1517502015 +Nieman Lab,251.5,1174.45795206497,False,16744206,498,0.2858285808469396,127.09248222777484,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/016/387/thumb/pzZXwZC8_normal.jpeg?1517501993 +Data Science Fact,100.0,0.1974799057110523,False,12369186,204402,0.4905835057931528,530.2165391499066,https://storage.googleapis.com/pics.contexto.io/photos/paperclips/000/204/535/thumb/sMpYCCGn_normal.jpg?1590839982 diff --git a/063_Clustering_Zoo_Animals/all.parquet b/data/064_Clustering/all.parquet similarity index 100% rename from 063_Clustering_Zoo_Animals/all.parquet rename to data/064_Clustering/all.parquet diff --git a/063_Clustering_Zoo_Animals/info.yml b/data/064_Clustering/info.yml similarity index 100% rename from 063_Clustering_Zoo_Animals/info.yml rename to data/064_Clustering/info.yml diff --git a/data/064_Clustering/qa.csv b/data/064_Clustering/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..7a7fdb78e7feed7959fb34c08e6fd0b30f4f6c31 --- /dev/null +++ b/data/064_Clustering/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Are there any animals with feathers in the dataset?,True,boolean,['feathers'],['number[uint8]'],True +Are there any venomous animals in the dataset?,True,boolean,['venomous'],['number[uint8]'],True +Do all animals breathe?,False,boolean,['breathes'],['number[uint8]'],False +Are there any domesticated animals in the dataset?,True,boolean,['domestic'],['number[uint8]'],True +How many unique types of animals are there?,7,number,['class_type'],['number[uint8]'],20 +What is the average number of legs?,2.8415841584158414,number,['legs'],['number[uint8]'],3.1 +What is the maximum number of legs an animal has?,8,number,['legs'],['number[uint8]'],6 +How many animals are there with 2 legs?,27,number,['legs'],['number[uint8]'],4 +What is the most common class type?,1,category,['class_type'],['number[uint8]'],1 +What is the name of the animal with 8 legs?,octopus,category,"['animal_name', 'legs']","['category', 'number[uint8]']", +What is the class type of the animal with the most legs?,7,category,"['class_type', 'legs']","['number[uint8]', 'number[uint8]']",6 +What is the name of the animal that is venomous?,frog,category,"['animal_name', 'venomous']","['category', 'number[uint8]']",honeybee +What are the top 3 animal names with the most legs?,"['octopus', 'scorpion', 'crayfish']",list[category],"['animal_name', 'legs']","['category', 'number[uint8]']","['honeybee', 'gnat', 'wasp']" +What are the bottom 2 animal names in terms of the number of legs?,"['bass', 'carp']",list[category],"['animal_name', 'legs']","['category', 'number[uint8]']","['porpoise', 'dogfish']" +What are the most common 4 class types with the most animals?,"[1, 2, 4, 7]",list[category],['class_type'],['number[uint8]'],"[1, 6, 4, 2]" +What are the least common 3 class types with the least animals?,"[5, 3, 6]",list[category],['class_type'],['number[uint8]'],"[4, 2, 7]" +What are the most common 5 class types with the most combined total legs?,"[1, 6, 2, 7, 5]",list[number],"['class_type', 'legs']","['number[uint8]', 'number[uint8]']","[1, 6, 2, 4, 7]" +What are the bottom 4 class types with the least combined total legs?,"[4, 3, 5, 7]",list[number],"['class_type', 'legs']","['number[uint8]', 'number[uint8]']","[4, 7, 2, 6]" +What are the most common 6 numbers of legs that animals have?,"[4, 2, 0, 6, 8, 5]",list[number],['legs'],['number[uint8]'],"[4, 2, 0, 6]" +What are the least common 3 numbers of legs that animals have?,"[5, 8, 6]",list[number],['legs'],['number[uint8]'],"[2, 0, 6]" diff --git a/063_Clustering_Zoo_Animals/sample.csv b/data/064_Clustering/sample.csv similarity index 100% rename from 063_Clustering_Zoo_Animals/sample.csv rename to data/064_Clustering/sample.csv diff --git a/064_RFM_Analysis/all.parquet b/data/065_RFM/all.parquet similarity index 100% rename from 064_RFM_Analysis/all.parquet rename to data/065_RFM/all.parquet diff --git a/064_RFM_Analysis/info.yml b/data/065_RFM/info.yml similarity index 69% rename from 064_RFM_Analysis/info.yml rename to data/065_RFM/info.yml index 1badae49f72182e8c09dc9bf9e0a5139e50f7178..47673f9d0def92fbd56455728e0f8a21a2b9f7aa 100644 --- a/064_RFM_Analysis/info.yml +++ b/data/065_RFM/info.yml @@ -1,4 +1,4 @@ -Explore: https://public.graphext.com/84965fe572c488b8/index.html +Explore: https://public.graphext.com/4db2e54e29006a21/index.html Source: https://www.kaggle.com/datasets/carrie1/ecommerce-data Title: 🛍 E-Commerce & RFM Analysis tags: diff --git a/data/065_RFM/qa.csv b/data/065_RFM/qa.csv new file mode 100644 index 0000000000000000000000000000000000000000..9ae6114963356508b8a3071000ee8885104e5ba3 --- /dev/null +++ b/data/065_RFM/qa.csv @@ -0,0 +1,21 @@ +question,answer,type,columns_used,column_types,sample_answer +Are all the quantities greater than 0?,False,boolean,['Quantity'],['number[int32]'],False +Are all the unit prices greater than 0?,False,boolean,['UnitPrice'],['number[double]'],True +Are there any missing customer IDs?,True,boolean,['CustomerID'],['number[UInt16]'],True +Are there any transactions from the United Kingdom?,True,boolean,['Country'],['category'],True +How many unique stock codes are there?,4070,number,['StockCode'],['category'],20 +What is the average unit price?,4.611113626088513,number,['UnitPrice'],['number[double]'],3.5415 +What is the maximum quantity ordered in a single transaction?,80995,number,['Quantity'],['number[int32]'],25 +How many transactions were made in the United Kingdom?,495478,number,['Country'],['category'],19 +Which country made the most transactions?,United Kingdom,category,['Country'],['category'],United Kingdom +What is the description of the item with the highest unit price?,Manual,category,"['Description', 'UnitPrice']","['category', 'number[double]']",RETROSPOT LAMP +What is the description of the item with the highest quantity ordered?,"PAPER CRAFT , LITTLE BIRDIE",category,"['Description', 'Quantity']","['category', 'number[int32]']",BLUE POLKADOT WRAP +Which country does the customer with the lowest ID come from?,United Kingdom,category,"['Country', 'CustomerID']","['category', 'number[UInt16]']",Australia +What are the descriptions of the top 3 items with the highest quantities ordered?,"['PAPER CRAFT , LITTLE BIRDIE', 'MEDIUM CERAMIC TOP STORAGE JAR', 'ASSTD DESIGN 3D PAPER STICKERS']",list[category],"['Description', 'Quantity']","['category', 'number[int32]']","['BLUE POLKADOT WRAP', 'HANGING JAM JAR T-LIGHT HOLDER', 'FAIRY CAKE FLANNEL ASSORTED COLOUR']" +What are the descriptions of the bottom 2 items with the lowest quantities ordered?,"['PAPER CRAFT , LITTLE BIRDIE', 'MEDIUM CERAMIC TOP STORAGE JAR']",list[category],"['Description', 'Quantity']","['category', 'number[int32]']","['HANGING METAL STAR LANTERN', 'LARGE CAKE TOWEL CHOCOLATE SPOTS']" +Which 4 countries made the most transactions?,"['United Kingdom', 'Germany', 'France', 'EIRE']",list[category],['Country'],['category'],"['United Kingdom', 'Australia']" +Which 3 countries made the least transactions?,"['Saudi Arabia', 'Bahrain', 'Czech Republic']",list[category],['Country'],['category'],"['United Kingdom', 'Australia']" +What are the invoice numbers of the top 5 transactions with the highest quantities ordered?,"['581483', '541431', '578841', '542504', '573008']",list[number],"['InvoiceNo', 'Quantity']","['number[UInt32]', 'number[int32]']","['548005', '555200', '573399', '577076', '568909']" +What are the stock codes of the bottom 4 transactions with the lowest quantities ordered?,"[23843, 21366, 23005, 23005, 84347]",list[number],"['InvoiceNo', 'Quantity']","['number[UInt32]', 'number[int32]']","['22465', '21109', '82484', '22799', '82600']" +What are the six most commonly ordered quantities?,"[1, 2, 12, 6, 4, 3]",list[number],['Quantity'],['number[int32]'],"[1, 4, 2, 12, 24, 3]" +What are the three least commonly ordered quantities?,"[-312, -79, 404]",list[number],['Quantity'],['number[int32]'],"[6, 25, -5]" diff --git a/064_RFM_Analysis/sample.csv b/data/065_RFM/sample.csv similarity index 99% rename from 064_RFM_Analysis/sample.csv rename to data/065_RFM/sample.csv index efb8c366351b9f89d7c7284760f710a0aae5d9dc..f585c12dcab6f9301253e4500536150b74299e52 100644 --- a/064_RFM_Analysis/sample.csv +++ b/data/065_RFM/sample.csv @@ -16,6 +16,6 @@ InvoiceNo,Country,StockCode,Description,Quantity,CustomerID,UnitPrice 540418,United Kingdom,22161,HEART DECORATION RUSTIC HANGING ,5,,0.81 546237,United Kingdom,84508A,CAMOUFLAGE DESIGN TEDDY,6,16625.0,2.55 548005,United Kingdom,21499,BLUE POLKADOT WRAP,25,14128.0,0.42 -539000,United Kingdom,22622,BOX OF VINTAGE ALPHABET BLOCKS,4,13092.0,9.95 +539000,United Kingdom,22622,BOX OF VINTAGE ALPHABET BLOCKS,4,13092.0,9.94 545715,United Kingdom,82600,NO SINGING METAL SIGN,1,,4.13 C572489,United Kingdom,22465,HANGING METAL STAR LANTERN,-5,17119.0,1.65