Update pages/Types Of Data.py

pages/Types Of Data.py

@@ -2,37 +2,37 @@ import streamlit as st
 import numpy as np 
 import pandas as pd 
 
-st.title("**TYPES OF DATA**")
-st.header("What are the different types of data?")
+st.header("**TYPES OF DATA**")
+st.subheader(":blue[**What are the different types of data?**]")
 st.image("https://www.mygreatlearning.com/blog/wp-content/uploads/2023/06/types-of-data-1024x555-1.png")
-st.subheader("The two main types of data are:")
+st.subheader(":blue[**The two main types of data are:**]")
 st.write("1.Qualitative Data")
 st.write("2.Quantitative Data")
 
-st.subheader("**Qualitative Data**")
+st.subheader(":blue[**Qualitative Data**]")
 st.write("**Qualitative Data** - These types of data are sorted by category, not by number. That’s why it is also known as Categorical Data. These data consist of audio, images, symbols, or text. The gender of a person, i.e., male, female, or others, is qualitative data.")
 st.write("**Example of Qualitative Data** : What language do you speak,Favorite holiday destination,Opinion on something (agree, disagree, or neutral),Colors ")
 
 st.header("The Qualitative data are classified into two parts :")
 
-st.subheader("**Nominal Data**")
+st.subheader(":blue[**Nominal Data**]")
 st.write("**Nominal Data** - The name “nominal” comes from the Latin name “nomen,” which means “name.” With the help of nominal data, we can’t do any numerical tasks or can’t give any order to sort the data.Nominal Data is used to label variables without any order or quantitative value. The color of hair can be considered nominal data, as one color can’t be compared with another color.")
 st.write("**Examples of Nominal Data** : Colour of hair (Blonde, red, Brown, Black, etc,Marital status (Single, Widowed, Married),Nationality (Indian, German, American),Gender (Male, Female, Others),Eye Color (Black, Brown, etc.)")
 
-st.subheader("**Ordinal Data**")
+st.subheader(":blue[**Ordinal Data**]")
 st.write("**Ordinal Data** - The ordinal data only shows the sequences and cannot use for statistical analysis. Compared to nominal data, ordinal data have some kind of order that is not present in nominal data.")
 st.write("**Examples of Ordinal Data** : When companies ask for feedback, experience, or satisfaction on a scale of 1 to 10,Letter grades in the exam (A, B, C, D, etc.),Ranking of people in a competition (First, Second, Third, etc.),Economic Status (High, Medium, and Low),Education Level (Higher, Secondary, Primary).")
 
-st.subheader("**Quanlitative Data**")
+st.subheader(":blue[**Quanlitative Data**]")
 st.write("**Quanlitatiave Data** - Quantitative data is a type of data that can be expressed in numerical values, making it countable and including statistical data analysis. These kinds of data are also known as Numerical data.It answers the questions like “how much,” “how many,” and “how often.” For example, the price of a phone, the computer’s ram, the height or weight of a person, etc.,falls under quantitative data.")
 st.write("**Examples of Quantitative Data** : Height or weight of a person or object,Room Temperature,Scores and Marks (Ex: 59, 80, 60, etc.),Time.")
 
 st.header("The Quantitative data are further classified into two parts :")
 
-st.subheader("**Discrete Data**")
+st.subheader(":blue[**Discrete Data**]")
 st.write("**Discrete data** - The discrete data are countable and have finite values; their subdivision is not possible. These data are represented mainly by a bar graph, number line, or frequency table.")
 st.write("**Examples of Discrete Data** :Total numbers of students present in a class,Cost of a cell phone,Numbers of employees in a company,The total number of players who participated in a competition,Days in a week.")
 
-st.subheader("**Continuous Data**")
+st.subheader(":blue[**Continuous Data**]")
 st.write("**Continuouse data** - Continuous data are in the form of fractional numbers. It can be the version of an android phone, the height of a person, the length of an object, etc. Continuous data represents information that can be divided into smaller levels. The continuous variable can take any value within a range.")
 st.write("**Examples of Continuous Data** : Height of a person,Speed of a vehicle,Market share price")