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{
"cells": [
{
"cell_type": "code",
"execution_count": 47,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"import numpy as np\n",
"sns.set_style(\"darkgrid\")"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {},
"outputs": [],
"source": [
"error_by_markets = pd.read_parquet('../data/error_by_markets.parquet')"
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Index(['tool', 'request_month_year_week', 'market_creator', '0', '1',\n",
" 'error_perc', 'total_requests'],\n",
" dtype='object')"
]
},
"execution_count": 49,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"error_by_markets.columns"
]
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>tool</th>\n",
" <th>request_month_year_week</th>\n",
" <th>market_creator</th>\n",
" <th>0</th>\n",
" <th>1</th>\n",
" <th>error_perc</th>\n",
" <th>total_requests</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>355</th>\n",
" <td>superforcaster</td>\n",
" <td>Dec-22</td>\n",
" <td>all</td>\n",
" <td>1087.0</td>\n",
" <td>61.0</td>\n",
" <td>5.313589</td>\n",
" <td>1148.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>356</th>\n",
" <td>superforcaster</td>\n",
" <td>Dec-22</td>\n",
" <td>pearl</td>\n",
" <td>75.0</td>\n",
" <td>10.0</td>\n",
" <td>11.764706</td>\n",
" <td>85.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>357</th>\n",
" <td>superforcaster</td>\n",
" <td>Dec-29</td>\n",
" <td>quickstart</td>\n",
" <td>678.0</td>\n",
" <td>59.0</td>\n",
" <td>8.005427</td>\n",
" <td>737.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>358</th>\n",
" <td>superforcaster</td>\n",
" <td>Dec-29</td>\n",
" <td>all</td>\n",
" <td>705.0</td>\n",
" <td>60.0</td>\n",
" <td>7.843137</td>\n",
" <td>765.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>359</th>\n",
" <td>superforcaster</td>\n",
" <td>Dec-29</td>\n",
" <td>pearl</td>\n",
" <td>27.0</td>\n",
" <td>1.0</td>\n",
" <td>3.571429</td>\n",
" <td>28.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" tool request_month_year_week market_creator 0 1 \\\n",
"355 superforcaster Dec-22 all 1087.0 61.0 \n",
"356 superforcaster Dec-22 pearl 75.0 10.0 \n",
"357 superforcaster Dec-29 quickstart 678.0 59.0 \n",
"358 superforcaster Dec-29 all 705.0 60.0 \n",
"359 superforcaster Dec-29 pearl 27.0 1.0 \n",
"\n",
" error_perc total_requests \n",
"355 5.313589 1148.0 \n",
"356 11.764706 85.0 \n",
"357 8.005427 737.0 \n",
"358 7.843137 765.0 \n",
"359 3.571429 28.0 "
]
},
"execution_count": 51,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"error_by_markets.tail()"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {},
"outputs": [],
"source": [
"error_total = (\n",
" error_by_markets.groupby([\"request_month_year_week\", \"market_creator\"], sort=False)\n",
" .agg({\"total_requests\": \"sum\", '1': \"sum\", '0': \"sum\"})\n",
" .reset_index()\n",
")\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [],
"source": [
"new_tools = pd.read_parquet('../data/new_tools.parquet')\n"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"155789"
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(new_tools)"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Index(['request_id', 'request_block', 'request_time', 'tx_hash',\n",
" 'prompt_request', 'tool', 'nonce', 'trader_address', 'deliver_block',\n",
" 'error', 'error_message', 'prompt_response', 'mech_address', 'p_yes',\n",
" 'p_no', 'confidence', 'info_utility', 'vote', 'win_probability',\n",
" 'market_creator'],\n",
" dtype='object')"
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"new_tools.columns"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 155789 entries, 0 to 155788\n",
"Data columns (total 20 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 request_id 155789 non-null object \n",
" 1 request_block 155789 non-null object \n",
" 2 request_time 155789 non-null datetime64[ns, UTC]\n",
" 3 tx_hash 155789 non-null object \n",
" 4 prompt_request 155789 non-null object \n",
" 5 tool 155789 non-null object \n",
" 6 nonce 155789 non-null object \n",
" 7 trader_address 155789 non-null object \n",
" 8 deliver_block 155789 non-null object \n",
" 9 error 155789 non-null int64 \n",
" 10 error_message 61690 non-null object \n",
" 11 prompt_response 131002 non-null object \n",
" 12 mech_address 131002 non-null object \n",
" 13 p_yes 94099 non-null float64 \n",
" 14 p_no 94099 non-null float64 \n",
" 15 confidence 94099 non-null float64 \n",
" 16 info_utility 94099 non-null float64 \n",
" 17 vote 66870 non-null object \n",
" 18 win_probability 94099 non-null float64 \n",
" 19 market_creator 155789 non-null object \n",
"dtypes: datetime64[ns, UTC](1), float64(5), int64(1), object(13)\n",
"memory usage: 23.8+ MB\n"
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"request_time 2024-12-23 12:37:05+00:00\n",
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"metadata": {},
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"data": {
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"metadata": {},
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{
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"source": [
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" <td>0x8dd0f0f64e575a356545d9ed096122a1887e64bf</td>\n",
" <td>36701099</td>\n",
" <td>0</td>\n",
" <td>None</td>\n",
" <td>\\nYou are an advanced AI system which has been...</td>\n",
" <td>...</td>\n",
" <td>0.4</td>\n",
" <td>No</td>\n",
" <td>0.7</td>\n",
" <td>quickstart</td>\n",
" <td>Will any new human rights organizations public...</td>\n",
" <td>Yes</td>\n",
" <td>2024-10-26 12:40:25+00:00</td>\n",
" <td>2024-10</td>\n",
" <td>2024-10-21/2024-10-27</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 24 columns</p>\n",
"</div>"
],
"text/plain": [
" request_id request_block \\\n",
"0 1065794400559258224527965821794720648636282516... 36701352 \n",
"1 9015207976398091689774872599965107755141252481... 36749933 \n",
"2 8204183583678326945661870665906374091080896102... 36756777 \n",
"3 1225398943131371197254748096595691861478679945... 36749393 \n",
"4 7954746357421406217625419969909404056225427053... 36701081 \n",
"\n",
" prompt_request \\\n",
"0 Please take over the role of a Data Scientist ... \n",
"1 Please take over the role of a Data Scientist ... \n",
"2 Please take over the role of a Data Scientist ... \n",
"3 Please take over the role of a Data Scientist ... \n",
"4 Please take over the role of a Data Scientist ... \n",
"\n",
" tool nonce \\\n",
"0 claude-prediction-offline fd5cfa7f-fb38-435b-b571-69f253397a69 \n",
"1 claude-prediction-offline a61c894b-fa0d-40d9-ab02-e512ef9dd7e6 \n",
"2 claude-prediction-offline e64fa0a7-a98b-4c95-ac1a-755d212a5b78 \n",
"3 claude-prediction-offline f84d34ae-3dd0-4d0c-a4d3-d8f28d25677c \n",
"4 superforcaster 1b609b7e-e0d2-4bb8-ad6b-7d0e6e6610b5 \n",
"\n",
" trader_address deliver_block error \\\n",
"0 0x42cc3f5a30420e8964be3c18d0e560b10e8957fa 36701366 0 \n",
"1 0xc84d1f9fc28ce5628f69cc138ba3092a036b8f69 36749986 0 \n",
"2 0x992448484862672eb95ca1c877cc43f935c389ce 36756791 0 \n",
"3 0x3de0f1a8d9c227af2e324dd92905bbf8bb852ff8 36749408 0 \n",
"4 0x8dd0f0f64e575a356545d9ed096122a1887e64bf 36701099 0 \n",
"\n",
" error_message prompt_response ... \\\n",
"0 None \\nYou are an LLM inside a multi-agent system t... ... \n",
"1 None \\nYou are an LLM inside a multi-agent system t... ... \n",
"2 None \\nYou are an LLM inside a multi-agent system t... ... \n",
"3 None \\nYou are an LLM inside a multi-agent system t... ... \n",
"4 None \\nYou are an advanced AI system which has been... ... \n",
"\n",
" info_utility vote win_probability market_creator \\\n",
"0 0.2 No 0.7 quickstart \n",
"1 0.2 No 0.9 quickstart \n",
"2 0.2 No 0.7 quickstart \n",
"3 0.1 None 0.5 quickstart \n",
"4 0.4 No 0.7 quickstart \n",
"\n",
" title currentAnswer \\\n",
"0 Will the Caspian Sea countries announce a join... No \n",
"1 Will Iran launch another ballistic missile att... Yes \n",
"2 Will the United Nations Security Council hold ... Yes \n",
"3 Will the Bank of Japan issue a public statemen... Yes \n",
"4 Will any new human rights organizations public... Yes \n",
"\n",
" request_time request_month_year request_month_year_week tx_hash \n",
"0 2024-10-26 13:03:55+00:00 2024-10 2024-10-21/2024-10-27 NaN \n",
"1 2024-10-29 10:50:55+00:00 2024-10 2024-10-28/2024-11-03 NaN \n",
"2 2024-10-29 20:41:55+00:00 2024-10 2024-10-28/2024-11-03 NaN \n",
"3 2024-10-29 10:02:45+00:00 2024-10 2024-10-28/2024-11-03 NaN \n",
"4 2024-10-26 12:40:25+00:00 2024-10 2024-10-21/2024-10-27 NaN \n",
"\n",
"[5 rows x 24 columns]"
]
},
"execution_count": 39,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"merge_df.head()"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [],
"source": [
"merge_df.drop(columns=\"tx_hash\", inplace=True)"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [],
"source": [
"merge_df.to_parquet(\"../tmp/tools.parquet\", index=False)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"tool\n",
"claude-prediction-offline 110152\n",
"claude-prediction-online 46686\n",
"prediction-offline-sme 43917\n",
"prediction-request-reasoning 41645\n",
"prediction-request-rag-claude 25431\n",
"prediction-offline 6215\n",
"prediction-online 2289\n",
"prediction-online-sme 2203\n",
"prediction-request-rag 2172\n",
"prediction-request-reasoning-claude 2025\n",
"prediction-url-cot-claude 1992\n",
"superforcaster 1080\n",
"stabilityai-stable-diffusion-v1-6 119\n",
"stabilityai-stable-diffusion-xl-1024-v1-0 116\n",
"Name: count, dtype: int64"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tools.tool.value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"tools_superforcaster = tools.loc[tools[\"tool\"]==\"superforcaster\"]"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"Index: 1080 entries, 25 to 285910\n",
"Data columns (total 23 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 request_id 1080 non-null object \n",
" 1 request_block 1080 non-null object \n",
" 2 prompt_request 1080 non-null object \n",
" 3 tool 1080 non-null object \n",
" 4 nonce 1080 non-null object \n",
" 5 trader_address 1080 non-null object \n",
" 6 deliver_block 1080 non-null object \n",
" 7 error 1080 non-null int64 \n",
" 8 error_message 0 non-null object \n",
" 9 prompt_response 1080 non-null object \n",
" 10 mech_address 1080 non-null object \n",
" 11 p_yes 1080 non-null float64\n",
" 12 p_no 1080 non-null float64\n",
" 13 confidence 1080 non-null float64\n",
" 14 info_utility 1080 non-null float64\n",
" 15 vote 1068 non-null object \n",
" 16 win_probability 1080 non-null float64\n",
" 17 market_creator 1080 non-null object \n",
" 18 title 1080 non-null object \n",
" 19 currentAnswer 763 non-null object \n",
" 20 request_time 1080 non-null object \n",
" 21 request_month_year 1080 non-null object \n",
" 22 request_month_year_week 1080 non-null object \n",
"dtypes: float64(5), int64(1), object(17)\n",
"memory usage: 202.5+ KB\n"
]
}
],
"source": [
"tools_superforcaster.info()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"219"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(list(tools_superforcaster.trader_address.unique()))"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
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" <th></th>\n",
" <th>request_id</th>\n",
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" <tr>\n",
" <th>25</th>\n",
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" <td>0xea1f46f9ea5bb3119a94bff2e4b95aaf8a93f594</td>\n",
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" <td>0</td>\n",
" <td>None</td>\n",
" <td>\\nYou are an advanced AI system which has been...</td>\n",
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" <td>0.4</td>\n",
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" <td>quickstart</td>\n",
" <td>Will the COP29 summit in Baku result in any ne...</td>\n",
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" <td>2024-10</td>\n",
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" <td>2024-10-28/2024-11-03</td>\n",
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" request_id request_block \\\n",
"25 7954746357421406217625419969909404056225427053... 36701081 \n",
"487 3893466766708161182364759698039339419255094338... 36811522 \n",
"1200 7937905446830497137329572363351508546160463954... 36759585 \n",
"2999 7132897945614190217838117925907875446836020321... 36702802 \n",
"3104 8199746255688176940073355030356696899510084324... 36795210 \n",
"\n",
" prompt_request tool \\\n",
"25 Please take over the role of a Data Scientist ... superforcaster \n",
"487 Please take over the role of a Data Scientist ... superforcaster \n",
"1200 Please take over the role of a Data Scientist ... superforcaster \n",
"2999 Please take over the role of a Data Scientist ... superforcaster \n",
"3104 Please take over the role of a Data Scientist ... superforcaster \n",
"\n",
" nonce \\\n",
"25 1b609b7e-e0d2-4bb8-ad6b-7d0e6e6610b5 \n",
"487 80f86c11-29b7-480d-a73d-a1cc2738c911 \n",
"1200 544f9e46-1293-4d61-abcf-15eae6406281 \n",
"2999 a8e456c8-b87a-41fd-ba17-a69d9b2dc195 \n",
"3104 c4163205-eef9-43b5-8e3f-b879f1e69d7b \n",
"\n",
" trader_address deliver_block error \\\n",
"25 0x8dd0f0f64e575a356545d9ed096122a1887e64bf 36701099 0 \n",
"487 0x6f2f057275f7072203b70aa4212d7d2448a2b16f 36811532 0 \n",
"1200 0xea1f46f9ea5bb3119a94bff2e4b95aaf8a93f594 36759592 0 \n",
"2999 0xacb24b20805c6e475d2c17edb2a997c1ba47de79 36702815 0 \n",
"3104 0xb2912a22ee91272861931b693c434d420610abfe 36795222 0 \n",
"\n",
" error_message prompt_response ... \\\n",
"25 None \\nYou are an advanced AI system which has been... ... \n",
"487 None \\nYou are an advanced AI system which has been... ... \n",
"1200 None \\nYou are an advanced AI system which has been... ... \n",
"2999 None \\nYou are an advanced AI system which has been... ... \n",
"3104 None \\nYou are an advanced AI system which has been... ... \n",
"\n",
" confidence info_utility vote win_probability market_creator \\\n",
"25 0.6 0.4 No 0.70 quickstart \n",
"487 0.8 0.3 No 0.99 quickstart \n",
"1200 0.6 0.4 No 0.70 quickstart \n",
"2999 0.6 0.4 No 0.70 quickstart \n",
"3104 0.6 0.4 No 0.70 quickstart \n",
"\n",
" title currentAnswer \\\n",
"25 Will any new human rights organizations public... Yes \n",
"487 Will any official statement from Russia confir... Yes \n",
"1200 Will the COP29 summit in Baku result in any ne... Yes \n",
"2999 Will any of the Caspian Sea countries publicly... No \n",
"3104 Will the Brazilian government announce a forma... None \n",
"\n",
" request_time request_month_year request_month_year_week \n",
"25 2024-10-26 12:40:25 2024-10 2024-10-21/2024-10-27 \n",
"487 2024-11-02 03:18:25 2024-11 2024-10-28/2024-11-03 \n",
"1200 2024-10-30 00:44:50 2024-10 2024-10-28/2024-11-03 \n",
"2999 2024-10-26 15:09:35 2024-10 2024-10-21/2024-10-27 \n",
"3104 2024-11-01 03:54:10 2024-11 2024-10-28/2024-11-03 \n",
"\n",
"[5 rows x 23 columns]"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
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]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"market_creator\n",
"quickstart 944\n",
"pearl 136\n",
"Name: count, dtype: int64"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
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]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='vote', ylabel='currentAnswer'>"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.histplot(tools_superforcaster, x=\"vote\", y=\"currentAnswer\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='currentAnswer', ylabel='vote'>"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.heatmap(pd.crosstab(tools_superforcaster['vote'], tools_superforcaster['currentAnswer']), \n",
" annot=True, \n",
" fmt='d', \n",
" cmap='YlOrRd')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"error\n",
"0 1080\n",
"Name: count, dtype: int64"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tools_superforcaster.error.value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"tools_errors = tools.loc[tools[\"error\"]==1]"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>request_id</th>\n",
" <th>request_block</th>\n",
" <th>prompt_request</th>\n",
" <th>tool</th>\n",
" <th>nonce</th>\n",
" <th>trader_address</th>\n",
" <th>deliver_block</th>\n",
" <th>error</th>\n",
" <th>error_message</th>\n",
" <th>prompt_response</th>\n",
" <th>...</th>\n",
" <th>confidence</th>\n",
" <th>info_utility</th>\n",
" <th>vote</th>\n",
" <th>win_probability</th>\n",
" <th>market_creator</th>\n",
" <th>title</th>\n",
" <th>currentAnswer</th>\n",
" <th>request_time</th>\n",
" <th>request_month_year</th>\n",
" <th>request_month_year_week</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>86</th>\n",
" <td>4881674922867639641311571037228957716478871650...</td>\n",
" <td>35999601</td>\n",
" <td>Please take over the role of a Data Scientist ...</td>\n",
" <td>prediction-request-reasoning</td>\n",
" <td>717e6b3a-fb8e-46b8-b08f-09b7688bd3f5</td>\n",
" <td>0x75c0366bd0cbc3db434fd117267e32f26c5ed857</td>\n",
" <td>35999619</td>\n",
" <td>1</td>\n",
" <td>Response parsing error</td>\n",
" <td></td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>None</td>\n",
" <td>NaN</td>\n",
" <td>quickstart</td>\n",
" <td>Will Jalen Ramsey remain the highest-paid corn...</td>\n",
" <td>Yes</td>\n",
" <td>2024-09-14 16:36:10</td>\n",
" <td>2024-09</td>\n",
" <td>2024-09-09/2024-09-15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>150</th>\n",
" <td>1635603471143500367687547686004256739020540606...</td>\n",
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" <td>Please take over the role of a Data Scientist ...</td>\n",
" <td>prediction-request-reasoning</td>\n",
" <td>906015ba-4b44-4f16-865b-a78ec20fbd43</td>\n",
" <td>0x9373cb196a3542afa583a91db604aee92068552a</td>\n",
" <td>36085552</td>\n",
" <td>1</td>\n",
" <td>Response parsing error</td>\n",
" <td>None</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>None</td>\n",
" <td>NaN</td>\n",
" <td>quickstart</td>\n",
" <td>Will the DNA-based storage technology develope...</td>\n",
" <td>No</td>\n",
" <td>2024-09-19 19:04:55</td>\n",
" <td>2024-09</td>\n",
" <td>2024-09-16/2024-09-22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>171</th>\n",
" <td>9605346928838243745282196096485039029835957400...</td>\n",
" <td>36153230</td>\n",
" <td>Please take over the role of a Data Scientist ...</td>\n",
" <td>prediction-request-reasoning</td>\n",
" <td>03dea35f-4e35-4d2d-9a6c-8f47e22fbeac</td>\n",
" <td>0x61766a46659b67bbda5484bba45e524ccc652ee4</td>\n",
" <td>36153243</td>\n",
" <td>1</td>\n",
" <td>Response parsing error</td>\n",
" <td></td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>None</td>\n",
" <td>NaN</td>\n",
" <td>quickstart</td>\n",
" <td>Will the DJI Air 3S drone be launched on or by...</td>\n",
" <td>No</td>\n",
" <td>2024-09-23 19:36:20</td>\n",
" <td>2024-09</td>\n",
" <td>2024-09-23/2024-09-29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>302</th>\n",
" <td>8665095948962365369308240696967816065773728349...</td>\n",
" <td>36242586</td>\n",
" <td>Please take over the role of a Data Scientist ...</td>\n",
" <td>prediction-request-reasoning</td>\n",
" <td>f359963a-595c-44e0-bd26-0e9d7fd7eb55</td>\n",
" <td>0x839eaee319420e6dc83383bbb41fce4f8b0bb9aa</td>\n",
" <td>36242602</td>\n",
" <td>1</td>\n",
" <td>Response parsing error</td>\n",
" <td></td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>None</td>\n",
" <td>NaN</td>\n",
" <td>quickstart</td>\n",
" <td>Will New York Mayor Eric Adams resign due to t...</td>\n",
" <td>No</td>\n",
" <td>2024-09-29 03:27:40</td>\n",
" <td>2024-09</td>\n",
" <td>2024-09-23/2024-09-29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>320</th>\n",
" <td>8760585200747573871316640694310284358194695510...</td>\n",
" <td>36031841</td>\n",
" <td>Please take over the role of a Data Scientist ...</td>\n",
" <td>prediction-request-reasoning</td>\n",
" <td>12bd33ad-88f6-4792-833b-b9bd22d8fe60</td>\n",
" <td>0x1d942103400c1f1657dcbffd5e08904787ea936b</td>\n",
" <td>36031861</td>\n",
" <td>1</td>\n",
" <td>Response parsing error</td>\n",
" <td></td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>None</td>\n",
" <td>NaN</td>\n",
" <td>quickstart</td>\n",
" <td>Will the Miami Dolphins win their game on 18 S...</td>\n",
" <td>No</td>\n",
" <td>2024-09-16 14:30:55</td>\n",
" <td>2024-09</td>\n",
" <td>2024-09-16/2024-09-22</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 23 columns</p>\n",
"</div>"
],
"text/plain": [
" request_id request_block \\\n",
"86 4881674922867639641311571037228957716478871650... 35999601 \n",
"150 1635603471143500367687547686004256739020540606... 36085486 \n",
"171 9605346928838243745282196096485039029835957400... 36153230 \n",
"302 8665095948962365369308240696967816065773728349... 36242586 \n",
"320 8760585200747573871316640694310284358194695510... 36031841 \n",
"\n",
" prompt_request \\\n",
"86 Please take over the role of a Data Scientist ... \n",
"150 Please take over the role of a Data Scientist ... \n",
"171 Please take over the role of a Data Scientist ... \n",
"302 Please take over the role of a Data Scientist ... \n",
"320 Please take over the role of a Data Scientist ... \n",
"\n",
" tool nonce \\\n",
"86 prediction-request-reasoning 717e6b3a-fb8e-46b8-b08f-09b7688bd3f5 \n",
"150 prediction-request-reasoning 906015ba-4b44-4f16-865b-a78ec20fbd43 \n",
"171 prediction-request-reasoning 03dea35f-4e35-4d2d-9a6c-8f47e22fbeac \n",
"302 prediction-request-reasoning f359963a-595c-44e0-bd26-0e9d7fd7eb55 \n",
"320 prediction-request-reasoning 12bd33ad-88f6-4792-833b-b9bd22d8fe60 \n",
"\n",
" trader_address deliver_block error \\\n",
"86 0x75c0366bd0cbc3db434fd117267e32f26c5ed857 35999619 1 \n",
"150 0x9373cb196a3542afa583a91db604aee92068552a 36085552 1 \n",
"171 0x61766a46659b67bbda5484bba45e524ccc652ee4 36153243 1 \n",
"302 0x839eaee319420e6dc83383bbb41fce4f8b0bb9aa 36242602 1 \n",
"320 0x1d942103400c1f1657dcbffd5e08904787ea936b 36031861 1 \n",
"\n",
" error_message prompt_response ... confidence info_utility \\\n",
"86 Response parsing error ... NaN NaN \n",
"150 Response parsing error None ... NaN NaN \n",
"171 Response parsing error ... NaN NaN \n",
"302 Response parsing error ... NaN NaN \n",
"320 Response parsing error ... NaN NaN \n",
"\n",
" vote win_probability market_creator \\\n",
"86 None NaN quickstart \n",
"150 None NaN quickstart \n",
"171 None NaN quickstart \n",
"302 None NaN quickstart \n",
"320 None NaN quickstart \n",
"\n",
" title currentAnswer \\\n",
"86 Will Jalen Ramsey remain the highest-paid corn... Yes \n",
"150 Will the DNA-based storage technology develope... No \n",
"171 Will the DJI Air 3S drone be launched on or by... No \n",
"302 Will New York Mayor Eric Adams resign due to t... No \n",
"320 Will the Miami Dolphins win their game on 18 S... No \n",
"\n",
" request_time request_month_year request_month_year_week \n",
"86 2024-09-14 16:36:10 2024-09 2024-09-09/2024-09-15 \n",
"150 2024-09-19 19:04:55 2024-09 2024-09-16/2024-09-22 \n",
"171 2024-09-23 19:36:20 2024-09 2024-09-23/2024-09-29 \n",
"302 2024-09-29 03:27:40 2024-09 2024-09-23/2024-09-29 \n",
"320 2024-09-16 14:30:55 2024-09 2024-09-16/2024-09-22 \n",
"\n",
"[5 rows x 23 columns]"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tools_errors.head()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"market_creator\n",
"quickstart 2581\n",
"pearl 291\n",
"Name: count, dtype: int64"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tools_errors.market_creator.value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"tools_errors_pearl = tools_errors.loc[tools_errors[\"market_creator\"]==\"pearl\"]"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"tool\n",
"prediction-request-reasoning 173\n",
"prediction-offline-sme 83\n",
"prediction-request-reasoning-claude 20\n",
"prediction-request-rag 7\n",
"prediction-request-rag-claude 5\n",
"prediction-online-sme 2\n",
"claude-prediction-offline 1\n",
"Name: count, dtype: int64"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tools_errors_pearl.tool.value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"tools_errors_pearl_reasoning = tools_errors_pearl.loc[tools_errors_pearl[\"tool\"]==\"prediction-request-reasoning\"]"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"error_message\n",
"Response parsing error 173\n",
"Name: count, dtype: int64"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tools_errors_pearl_reasoning.error_message.value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"request_month_year_week\n",
"2024-08-19/2024-08-25 54\n",
"2024-10-07/2024-10-13 53\n",
"2024-09-02/2024-09-08 33\n",
"2024-09-23/2024-09-29 12\n",
"2024-09-09/2024-09-15 12\n",
"2024-08-26/2024-09-01 5\n",
"2024-09-30/2024-10-06 4\n",
"Name: count, dtype: int64"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tools_errors_pearl_reasoning.request_month_year_week.value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"tools_errors_pearl_reasoning_oct = tools_errors_pearl_reasoning.loc[tools_errors_pearl_reasoning[\"request_month_year_week\"]==\"2024-10-07/2024-10-13\"]"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
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" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>request_id</th>\n",
" <th>request_block</th>\n",
" <th>prompt_request</th>\n",
" <th>tool</th>\n",
" <th>nonce</th>\n",
" <th>trader_address</th>\n",
" <th>deliver_block</th>\n",
" <th>error</th>\n",
" <th>error_message</th>\n",
" <th>prompt_response</th>\n",
" <th>...</th>\n",
" <th>confidence</th>\n",
" <th>info_utility</th>\n",
" <th>vote</th>\n",
" <th>win_probability</th>\n",
" <th>market_creator</th>\n",
" <th>title</th>\n",
" <th>currentAnswer</th>\n",
" <th>request_time</th>\n",
" <th>request_month_year</th>\n",
" <th>request_month_year_week</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1301</th>\n",
" <td>6096315197620058968806130972169678143719505006...</td>\n",
" <td>36413260</td>\n",
" <td>Please take over the role of a Data Scientist ...</td>\n",
" <td>prediction-request-reasoning</td>\n",
" <td>f2016229-4284-4178-ba31-6d3d79c08db2</td>\n",
" <td>0x04430ebfb7d088960233b7353cb4cefb528dc31e</td>\n",
" <td>36413276</td>\n",
" <td>1</td>\n",
" <td>Response parsing error</td>\n",
" <td></td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>None</td>\n",
" <td>NaN</td>\n",
" <td>pearl</td>\n",
" <td>Will Rivian produce more electric vehicles in ...</td>\n",
" <td>No</td>\n",
" <td>2024-10-09 07:16:50</td>\n",
" <td>2024-10</td>\n",
" <td>2024-10-07/2024-10-13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4446</th>\n",
" <td>5354600326067223816020518930816563773467758113...</td>\n",
" <td>36403643</td>\n",
" <td>Please take over the role of a Data Scientist ...</td>\n",
" <td>prediction-request-reasoning</td>\n",
" <td>c74f8eb6-5570-4258-b86b-6e92eca1a09b</td>\n",
" <td>0x04430ebfb7d088960233b7353cb4cefb528dc31e</td>\n",
" <td>36403657</td>\n",
" <td>1</td>\n",
" <td>Response parsing error</td>\n",
" <td></td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>None</td>\n",
" <td>NaN</td>\n",
" <td>pearl</td>\n",
" <td>Will the Dyson WashG1 wet floor cleaner reach ...</td>\n",
" <td>No</td>\n",
" <td>2024-10-08 17:32:55</td>\n",
" <td>2024-10</td>\n",
" <td>2024-10-07/2024-10-13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4482</th>\n",
" <td>6150779611250311931991788339674513841446857824...</td>\n",
" <td>36490063</td>\n",
" <td>Please take over the role of a Data Scientist ...</td>\n",
" <td>prediction-request-reasoning</td>\n",
" <td>3bb89890-6b83-4788-94f8-e7eacf6ea121</td>\n",
" <td>0x8069ea45a18910fa493a6a736438971b0e59ec9b</td>\n",
" <td>36490078</td>\n",
" <td>1</td>\n",
" <td>Response parsing error</td>\n",
" <td></td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>None</td>\n",
" <td>NaN</td>\n",
" <td>pearl</td>\n",
" <td>Will Biden speak to Netanyahu about Iran retal...</td>\n",
" <td>Yes</td>\n",
" <td>2024-10-13 20:56:30</td>\n",
" <td>2024-10</td>\n",
" <td>2024-10-07/2024-10-13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5281</th>\n",
" <td>2629357539419898379977886858224971150345341996...</td>\n",
" <td>36396729</td>\n",
" <td>Please take over the role of a Data Scientist ...</td>\n",
" <td>prediction-request-reasoning</td>\n",
" <td>858c4497-836e-43e8-b234-868d3d542f0d</td>\n",
" <td>0x04430ebfb7d088960233b7353cb4cefb528dc31e</td>\n",
" <td>36396742</td>\n",
" <td>1</td>\n",
" <td>Response parsing error</td>\n",
" <td></td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>None</td>\n",
" <td>NaN</td>\n",
" <td>pearl</td>\n",
" <td>Will the Dyson WashG1 wet floor cleaner reach ...</td>\n",
" <td>No</td>\n",
" <td>2024-10-08 07:38:25</td>\n",
" <td>2024-10</td>\n",
" <td>2024-10-07/2024-10-13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5978</th>\n",
" <td>6657538643069097666675831403759282242594505545...</td>\n",
" <td>36405500</td>\n",
" <td>Please take over the role of a Data Scientist ...</td>\n",
" <td>prediction-request-reasoning</td>\n",
" <td>cb9b0663-3eea-43ec-b791-43f3d5946f91</td>\n",
" <td>0x04430ebfb7d088960233b7353cb4cefb528dc31e</td>\n",
" <td>36405513</td>\n",
" <td>1</td>\n",
" <td>Response parsing error</td>\n",
" <td></td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>None</td>\n",
" <td>NaN</td>\n",
" <td>pearl</td>\n",
" <td>Will Rivian produce more electric vehicles in ...</td>\n",
" <td>No</td>\n",
" <td>2024-10-08 20:10:45</td>\n",
" <td>2024-10</td>\n",
" <td>2024-10-07/2024-10-13</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 23 columns</p>\n",
"</div>"
],
"text/plain": [
" request_id request_block \\\n",
"1301 6096315197620058968806130972169678143719505006... 36413260 \n",
"4446 5354600326067223816020518930816563773467758113... 36403643 \n",
"4482 6150779611250311931991788339674513841446857824... 36490063 \n",
"5281 2629357539419898379977886858224971150345341996... 36396729 \n",
"5978 6657538643069097666675831403759282242594505545... 36405500 \n",
"\n",
" prompt_request \\\n",
"1301 Please take over the role of a Data Scientist ... \n",
"4446 Please take over the role of a Data Scientist ... \n",
"4482 Please take over the role of a Data Scientist ... \n",
"5281 Please take over the role of a Data Scientist ... \n",
"5978 Please take over the role of a Data Scientist ... \n",
"\n",
" tool nonce \\\n",
"1301 prediction-request-reasoning f2016229-4284-4178-ba31-6d3d79c08db2 \n",
"4446 prediction-request-reasoning c74f8eb6-5570-4258-b86b-6e92eca1a09b \n",
"4482 prediction-request-reasoning 3bb89890-6b83-4788-94f8-e7eacf6ea121 \n",
"5281 prediction-request-reasoning 858c4497-836e-43e8-b234-868d3d542f0d \n",
"5978 prediction-request-reasoning cb9b0663-3eea-43ec-b791-43f3d5946f91 \n",
"\n",
" trader_address deliver_block error \\\n",
"1301 0x04430ebfb7d088960233b7353cb4cefb528dc31e 36413276 1 \n",
"4446 0x04430ebfb7d088960233b7353cb4cefb528dc31e 36403657 1 \n",
"4482 0x8069ea45a18910fa493a6a736438971b0e59ec9b 36490078 1 \n",
"5281 0x04430ebfb7d088960233b7353cb4cefb528dc31e 36396742 1 \n",
"5978 0x04430ebfb7d088960233b7353cb4cefb528dc31e 36405513 1 \n",
"\n",
" error_message prompt_response ... confidence info_utility \\\n",
"1301 Response parsing error ... NaN NaN \n",
"4446 Response parsing error ... NaN NaN \n",
"4482 Response parsing error ... NaN NaN \n",
"5281 Response parsing error ... NaN NaN \n",
"5978 Response parsing error ... NaN NaN \n",
"\n",
" vote win_probability market_creator \\\n",
"1301 None NaN pearl \n",
"4446 None NaN pearl \n",
"4482 None NaN pearl \n",
"5281 None NaN pearl \n",
"5978 None NaN pearl \n",
"\n",
" title currentAnswer \\\n",
"1301 Will Rivian produce more electric vehicles in ... No \n",
"4446 Will the Dyson WashG1 wet floor cleaner reach ... No \n",
"4482 Will Biden speak to Netanyahu about Iran retal... Yes \n",
"5281 Will the Dyson WashG1 wet floor cleaner reach ... No \n",
"5978 Will Rivian produce more electric vehicles in ... No \n",
"\n",
" request_time request_month_year request_month_year_week \n",
"1301 2024-10-09 07:16:50 2024-10 2024-10-07/2024-10-13 \n",
"4446 2024-10-08 17:32:55 2024-10 2024-10-07/2024-10-13 \n",
"4482 2024-10-13 20:56:30 2024-10 2024-10-07/2024-10-13 \n",
"5281 2024-10-08 07:38:25 2024-10 2024-10-07/2024-10-13 \n",
"5978 2024-10-08 20:10:45 2024-10 2024-10-07/2024-10-13 \n",
"\n",
"[5 rows x 23 columns]"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tools_errors_pearl_reasoning_oct.head()"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"title\n",
"Will Rivian produce more electric vehicles in 2024 than it did in 2023 by 11 October 2024? 27\n",
"Will the Dyson WashG1 wet floor cleaner reach a sales target of 500,000 units in the US by 10 October 2024? 25\n",
"Will Biden speak to Netanyahu about Iran retaliation on 16 October 2024? 1\n",
"Name: count, dtype: int64"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tools_errors_pearl_reasoning_oct.title.value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"title trader_address \n",
"Will Biden speak to Netanyahu about Iran retaliation on 16 October 2024? 0x8069ea45a18910fa493a6a736438971b0e59ec9b 1\n",
"Will Rivian produce more electric vehicles in 2024 than it did in 2023 by 11 October 2024? 0x032533005f65026fa7f360ff9a211bc94315325d 5\n",
" 0x04430ebfb7d088960233b7353cb4cefb528dc31e 18\n",
" 0x4b9e1890640e5f56f7fdc580347c938aaab56c25 1\n",
" 0x75c10935141d740b71e1763aa6a3139643754655 1\n",
" 0x9db7e7a0c82a229a7f3bb15046ff0c3a778b7291 1\n",
" 0xcbb7f0dc4daac0654d6f18638b4416666a01dff2 1\n",
"Will the Dyson WashG1 wet floor cleaner reach a sales target of 500,000 units in the US by 10 October 2024? 0x032533005f65026fa7f360ff9a211bc94315325d 4\n",
" 0x04430ebfb7d088960233b7353cb4cefb528dc31e 21\n",
"Name: request_id, dtype: int64"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tools_errors_pearl_reasoning_oct.groupby([\"title\",\"trader_address\"])[\"request_id\"].count()"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
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" .dataframe thead th {\n",
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" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
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" <th>tool</th>\n",
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" <th>confidence</th>\n",
" <th>info_utility</th>\n",
" <th>vote</th>\n",
" <th>win_probability</th>\n",
" <th>market_creator</th>\n",
" <th>title</th>\n",
" <th>currentAnswer</th>\n",
" <th>request_time</th>\n",
" <th>request_month_year</th>\n",
" <th>request_month_year_week</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1301</th>\n",
" <td>6096315197620058968806130972169678143719505006...</td>\n",
" <td>36413260</td>\n",
" <td>Please take over the role of a Data Scientist ...</td>\n",
" <td>prediction-request-reasoning</td>\n",
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" <td></td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>None</td>\n",
" <td>NaN</td>\n",
" <td>pearl</td>\n",
" <td>Will Rivian produce more electric vehicles in ...</td>\n",
" <td>No</td>\n",
" <td>2024-10-09 07:16:50</td>\n",
" <td>2024-10</td>\n",
" <td>2024-10-07/2024-10-13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4446</th>\n",
" <td>5354600326067223816020518930816563773467758113...</td>\n",
" <td>36403643</td>\n",
" <td>Please take over the role of a Data Scientist ...</td>\n",
" <td>prediction-request-reasoning</td>\n",
" <td>c74f8eb6-5570-4258-b86b-6e92eca1a09b</td>\n",
" <td>0x04430ebfb7d088960233b7353cb4cefb528dc31e</td>\n",
" <td>36403657</td>\n",
" <td>1</td>\n",
" <td>Response parsing error</td>\n",
" <td></td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>None</td>\n",
" <td>NaN</td>\n",
" <td>pearl</td>\n",
" <td>Will the Dyson WashG1 wet floor cleaner reach ...</td>\n",
" <td>No</td>\n",
" <td>2024-10-08 17:32:55</td>\n",
" <td>2024-10</td>\n",
" <td>2024-10-07/2024-10-13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5281</th>\n",
" <td>2629357539419898379977886858224971150345341996...</td>\n",
" <td>36396729</td>\n",
" <td>Please take over the role of a Data Scientist ...</td>\n",
" <td>prediction-request-reasoning</td>\n",
" <td>858c4497-836e-43e8-b234-868d3d542f0d</td>\n",
" <td>0x04430ebfb7d088960233b7353cb4cefb528dc31e</td>\n",
" <td>36396742</td>\n",
" <td>1</td>\n",
" <td>Response parsing error</td>\n",
" <td></td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>None</td>\n",
" <td>NaN</td>\n",
" <td>pearl</td>\n",
" <td>Will the Dyson WashG1 wet floor cleaner reach ...</td>\n",
" <td>No</td>\n",
" <td>2024-10-08 07:38:25</td>\n",
" <td>2024-10</td>\n",
" <td>2024-10-07/2024-10-13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5978</th>\n",
" <td>6657538643069097666675831403759282242594505545...</td>\n",
" <td>36405500</td>\n",
" <td>Please take over the role of a Data Scientist ...</td>\n",
" <td>prediction-request-reasoning</td>\n",
" <td>cb9b0663-3eea-43ec-b791-43f3d5946f91</td>\n",
" <td>0x04430ebfb7d088960233b7353cb4cefb528dc31e</td>\n",
" <td>36405513</td>\n",
" <td>1</td>\n",
" <td>Response parsing error</td>\n",
" <td></td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>None</td>\n",
" <td>NaN</td>\n",
" <td>pearl</td>\n",
" <td>Will Rivian produce more electric vehicles in ...</td>\n",
" <td>No</td>\n",
" <td>2024-10-08 20:10:45</td>\n",
" <td>2024-10</td>\n",
" <td>2024-10-07/2024-10-13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13521</th>\n",
" <td>5425044058976052235962273954205049658875702880...</td>\n",
" <td>36400070</td>\n",
" <td>Please take over the role of a Data Scientist ...</td>\n",
" <td>prediction-request-reasoning</td>\n",
" <td>f1d2af5e-b1ab-4818-94b7-14f8d6e8c5a1</td>\n",
" <td>0x04430ebfb7d088960233b7353cb4cefb528dc31e</td>\n",
" <td>36400080</td>\n",
" <td>1</td>\n",
" <td>Response parsing error</td>\n",
" <td></td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>None</td>\n",
" <td>NaN</td>\n",
" <td>pearl</td>\n",
" <td>Will Rivian produce more electric vehicles in ...</td>\n",
" <td>No</td>\n",
" <td>2024-10-08 12:25:15</td>\n",
" <td>2024-10</td>\n",
" <td>2024-10-07/2024-10-13</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 23 columns</p>\n",
"</div>"
],
"text/plain": [
" request_id request_block \\\n",
"1301 6096315197620058968806130972169678143719505006... 36413260 \n",
"4446 5354600326067223816020518930816563773467758113... 36403643 \n",
"5281 2629357539419898379977886858224971150345341996... 36396729 \n",
"5978 6657538643069097666675831403759282242594505545... 36405500 \n",
"13521 5425044058976052235962273954205049658875702880... 36400070 \n",
"\n",
" prompt_request \\\n",
"1301 Please take over the role of a Data Scientist ... \n",
"4446 Please take over the role of a Data Scientist ... \n",
"5281 Please take over the role of a Data Scientist ... \n",
"5978 Please take over the role of a Data Scientist ... \n",
"13521 Please take over the role of a Data Scientist ... \n",
"\n",
" tool nonce \\\n",
"1301 prediction-request-reasoning f2016229-4284-4178-ba31-6d3d79c08db2 \n",
"4446 prediction-request-reasoning c74f8eb6-5570-4258-b86b-6e92eca1a09b \n",
"5281 prediction-request-reasoning 858c4497-836e-43e8-b234-868d3d542f0d \n",
"5978 prediction-request-reasoning cb9b0663-3eea-43ec-b791-43f3d5946f91 \n",
"13521 prediction-request-reasoning f1d2af5e-b1ab-4818-94b7-14f8d6e8c5a1 \n",
"\n",
" trader_address deliver_block error \\\n",
"1301 0x04430ebfb7d088960233b7353cb4cefb528dc31e 36413276 1 \n",
"4446 0x04430ebfb7d088960233b7353cb4cefb528dc31e 36403657 1 \n",
"5281 0x04430ebfb7d088960233b7353cb4cefb528dc31e 36396742 1 \n",
"5978 0x04430ebfb7d088960233b7353cb4cefb528dc31e 36405513 1 \n",
"13521 0x04430ebfb7d088960233b7353cb4cefb528dc31e 36400080 1 \n",
"\n",
" error_message prompt_response ... confidence info_utility \\\n",
"1301 Response parsing error ... NaN NaN \n",
"4446 Response parsing error ... NaN NaN \n",
"5281 Response parsing error ... NaN NaN \n",
"5978 Response parsing error ... NaN NaN \n",
"13521 Response parsing error ... NaN NaN \n",
"\n",
" vote win_probability market_creator \\\n",
"1301 None NaN pearl \n",
"4446 None NaN pearl \n",
"5281 None NaN pearl \n",
"5978 None NaN pearl \n",
"13521 None NaN pearl \n",
"\n",
" title currentAnswer \\\n",
"1301 Will Rivian produce more electric vehicles in ... No \n",
"4446 Will the Dyson WashG1 wet floor cleaner reach ... No \n",
"5281 Will the Dyson WashG1 wet floor cleaner reach ... No \n",
"5978 Will Rivian produce more electric vehicles in ... No \n",
"13521 Will Rivian produce more electric vehicles in ... No \n",
"\n",
" request_time request_month_year request_month_year_week \n",
"1301 2024-10-09 07:16:50 2024-10 2024-10-07/2024-10-13 \n",
"4446 2024-10-08 17:32:55 2024-10 2024-10-07/2024-10-13 \n",
"5281 2024-10-08 07:38:25 2024-10 2024-10-07/2024-10-13 \n",
"5978 2024-10-08 20:10:45 2024-10 2024-10-07/2024-10-13 \n",
"13521 2024-10-08 12:25:15 2024-10 2024-10-07/2024-10-13 \n",
"\n",
"[5 rows x 23 columns]"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"target = tools_errors_pearl_reasoning_oct.loc[tools_errors_pearl_reasoning_oct[\"trader_address\"]==\"0x04430ebfb7d088960233b7353cb4cefb528dc31e\"]\n",
"target.head()"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/var/folders/gp/02mb1d514ng739czlxw1lhh00000gn/T/ipykernel_17275/2686300214.py:2: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" target['request_time'] = pd.to_datetime(target['request_time'])\n",
"/var/folders/gp/02mb1d514ng739czlxw1lhh00000gn/T/ipykernel_17275/2686300214.py:6: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" target['request_date'] = target['request_time'].dt.date\n"
]
}
],
"source": [
"# Step 1: Convert 'request_time' to datetime\n",
"target['request_time'] = pd.to_datetime(target['request_time'])\n",
"\n",
"# Step 2: Extract only the date\n",
"# Option 1: Using .dt.date (results in Python date objects)\n",
"target['request_date'] = target['request_time'].dt.date"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"request_date\n",
"2024-10-08 29\n",
"2024-10-09 10\n",
"Name: count, dtype: int64"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"target.request_date.value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"request_id 6096315197620058968806130972169678143719505006...\n",
"request_block 36413260\n",
"prompt_request Please take over the role of a Data Scientist ...\n",
"tool prediction-request-reasoning\n",
"nonce f2016229-4284-4178-ba31-6d3d79c08db2\n",
"trader_address 0x04430ebfb7d088960233b7353cb4cefb528dc31e\n",
"deliver_block 36413276\n",
"error 1\n",
"error_message Response parsing error\n",
"prompt_response \n",
"mech_address 0x5e1d1eb61e1164d5a50b28c575da73a29595dff7\n",
"p_yes NaN\n",
"p_no NaN\n",
"confidence NaN\n",
"info_utility NaN\n",
"vote None\n",
"win_probability NaN\n",
"market_creator pearl\n",
"title Will Rivian produce more electric vehicles in ...\n",
"currentAnswer No\n",
"request_time 2024-10-09 07:16:50\n",
"request_month_year 2024-10\n",
"request_month_year_week 2024-10-07/2024-10-13\n",
"request_date 2024-10-09\n",
"Name: 1301, dtype: object"
]
},
"execution_count": 42,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"target.iloc[0]"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array(['60963151976200589688061309721696781437195050065672302545071004901874091643033',\n",
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" '37702190955051676132208606978682620139157915260199519916929970381323219753604',\n",
" '39569294324786741974231872134377826545140874888007473009293927983710957931560'],\n",
" dtype=object)"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"list_ids = target.request_id.values\n",
"list_ids[:10]"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array(['90593985923458899196810962386588286156538155570078296690881210441404684587554',\n",
" '68767283695784515860585993729057039088040186058017842377406754894591756511455',\n",
" '30463708402138539553111489893542873324945145496769326313504030362000739912217',\n",
" '107009206247715009517848578229257123443621203954825272856731050187387798698104',\n",
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" '83410164700209236856544326193231329461555897050465870148582616961224625051174',\n",
" '18800709011076966851620908913623693327374337392203674994417817827748941031712',\n",
" '52968186234915567486999518373725017068484409050337977059157445056559429258274',\n",
" '25079816768578500534050631284042535400266565749897206799037169746242652065181'],\n",
" dtype=object)"
]
},
"execution_count": 43,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"list_ids[11:20]"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [
{
"data": {
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" <td>5701187523179160021887695614981479044834603062...</td>\n",
" <td>2024-10-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>151939</th>\n",
" <td>6965041493166381160828548950817860788478600202...</td>\n",
" <td>2024-10-09</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156075</th>\n",
" <td>1094553406895658377755024653190865186935248795...</td>\n",
" <td>2024-10-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>158713</th>\n",
" <td>2482181328413474980777782435770046521802662164...</td>\n",
" <td>2024-10-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>159533</th>\n",
" <td>7477199406563092998546889148948661086790369208...</td>\n",
" <td>2024-10-09</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" request_id request_date\n",
"1301 6096315197620058968806130972169678143719505006... 2024-10-09\n",
"4446 5354600326067223816020518930816563773467758113... 2024-10-08\n",
"5281 2629357539419898379977886858224971150345341996... 2024-10-08\n",
"5978 6657538643069097666675831403759282242594505545... 2024-10-08\n",
"13521 5425044058976052235962273954205049658875702880... 2024-10-08\n",
"19109 6770666406121314451083377426288764710285960616... 2024-10-09\n",
"26394 9882802537427860483726914295813636736938924269... 2024-10-09\n",
"28451 7948766573310943370126776177067177745586006884... 2024-10-08\n",
"30496 3770219095505167613220860697868262013915791526... 2024-10-08\n",
"36292 3956929432478674197423187213437782654514087488... 2024-10-08\n",
"51084 8175211455282203482379491678632547763247823116... 2024-10-08\n",
"59234 9059398592345889919681096238658828615653815557... 2024-10-09\n",
"61875 6876728369578451586058599372905703908804018605... 2024-10-09\n",
"66420 3046370840213853955311148989354287332494514549... 2024-10-08\n",
"67950 1070092062477150095178485782292571234436212039... 2024-10-08\n",
"72643 1791452603581598622819765450305918309250605837... 2024-10-08\n",
"75088 8341016470020923685654432619323132946155589705... 2024-10-08\n",
"78791 1880070901107696685162090891362369332737433739... 2024-10-08\n",
"79145 5296818623491556748699951837372501706848440905... 2024-10-08\n",
"83216 2507981676857850053405063128404253540026656574... 2024-10-08\n",
"85167 7575008210195058310304416239166201007781878905... 2024-10-08\n",
"88188 9552646687631779229885168355150323079613443891... 2024-10-08\n",
"100246 4692241561430217878941029480346287939590785051... 2024-10-09\n",
"100677 7206378347489269040486803921098426780132051076... 2024-10-08\n",
"101088 1092955896466926617598161352358541141356344922... 2024-10-08\n",
"101210 1527068083956919475597593744421530347315167151... 2024-10-08\n",
"108656 1324300681984336956521266305617936389896556358... 2024-10-09\n",
"108846 8289032326759732887661005089261149134628471095... 2024-10-08\n",
"109312 5912452484774403202939990022063726888631215178... 2024-10-08\n",
"110341 6190847215316949218633078224850239375241342048... 2024-10-08\n",
"116511 1153012652040846748107002862035076676381200652... 2024-10-08\n",
"121108 1557391800733738917341431736907154545224724694... 2024-10-08\n",
"138827 2220225315128610064534249140893399020559732644... 2024-10-09\n",
"146315 1060705375579050874189318472528055944551818109... 2024-10-08\n",
"149805 5701187523179160021887695614981479044834603062... 2024-10-08\n",
"151939 6965041493166381160828548950817860788478600202... 2024-10-09\n",
"156075 1094553406895658377755024653190865186935248795... 2024-10-08\n",
"158713 2482181328413474980777782435770046521802662164... 2024-10-08\n",
"159533 7477199406563092998546889148948661086790369208... 2024-10-09"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"target[[\"request_id\", \"request_date\"]]"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [],
"source": [
"# Step 1: Convert 'request_time' to datetime\n",
"tools['request_time'] = pd.to_datetime(tools['request_time'])\n",
"\n",
"# Step 2: Extract only the date\n",
"# Option 1: Using .dt.date (results in Python date objects)\n",
"tools['request_date'] = tools['request_time'].dt.date\n"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>request_id</th>\n",
" <th>request_date</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>6000436570989704155944120385884952057858004900...</td>\n",
" <td>2024-10-11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>1110041886165814728304049774267297117864784041...</td>\n",
" <td>2024-10-11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>1540850207513454596143653889780703543734000659...</td>\n",
" <td>2024-10-12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>32</th>\n",
" <td>7893228936705618570277338740495039782889689581...</td>\n",
" <td>2024-10-10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>33</th>\n",
" <td>7526736795473306673180277838498078624434571449...</td>\n",
" <td>2024-10-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>162083</th>\n",
" <td>8155539169659776751020900439047793303819631815...</td>\n",
" <td>2024-10-13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>162093</th>\n",
" <td>4091897651903844948533305264746058547870099773...</td>\n",
" <td>2024-10-09</td>\n",
" </tr>\n",
" <tr>\n",
" <th>162094</th>\n",
" <td>1060448907408309804546320958065157755251608511...</td>\n",
" <td>2024-10-12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>162109</th>\n",
" <td>4235777061025284573352646490318646198795416762...</td>\n",
" <td>2024-10-07</td>\n",
" </tr>\n",
" <tr>\n",
" <th>162111</th>\n",
" <td>5209142730053796928793404697801186735890129172...</td>\n",
" <td>2024-10-07</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>20516 rows × 2 columns</p>\n",
"</div>"
],
"text/plain": [
" request_id request_date\n",
"7 6000436570989704155944120385884952057858004900... 2024-10-11\n",
"11 1110041886165814728304049774267297117864784041... 2024-10-11\n",
"17 1540850207513454596143653889780703543734000659... 2024-10-12\n",
"32 7893228936705618570277338740495039782889689581... 2024-10-10\n",
"33 7526736795473306673180277838498078624434571449... 2024-10-08\n",
"... ... ...\n",
"162083 8155539169659776751020900439047793303819631815... 2024-10-13\n",
"162093 4091897651903844948533305264746058547870099773... 2024-10-09\n",
"162094 1060448907408309804546320958065157755251608511... 2024-10-12\n",
"162109 4235777061025284573352646490318646198795416762... 2024-10-07\n",
"162111 5209142730053796928793404697801186735890129172... 2024-10-07\n",
"\n",
"[20516 rows x 2 columns]"
]
},
"execution_count": 31,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tools.loc[tools[\"request_month_year_week\"]==\"2024-10-07/2024-10-13\"][[\"request_id\", \"request_date\"]]"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"request_date\n",
"2024-10-20 4616\n",
"2024-10-18 4474\n",
"2024-10-17 4180\n",
"2024-10-19 4093\n",
"2024-09-10 4018\n",
" ... \n",
"2024-09-21 1853\n",
"2024-08-29 1700\n",
"2024-09-15 1614\n",
"2024-08-22 1421\n",
"2024-10-21 742\n",
"Name: count, Length: 61, dtype: int64"
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tools.request_date.value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"object\n"
]
}
],
"source": [
"print(tools['request_date'].dtype)"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array(['75267367954733066731802778384980786244345714492617935729431679575835641281777',\n",
" '84777531641003257941101275192333838936553813208125088407536800860673481676974',\n",
" '96220126533195686874770414750092684778689303224171939903636393563147529566805',\n",
" '85111692869695695070820477101480929103128037048651644814553376046710657331686',\n",
" '70955678141080262808382265854526736034962899352147754109605797381118648546015',\n",
" '89888925059941001916258915191647589006859959225855447761356001840604632558824',\n",
" '64072963113962902370586870420814897514043034924401758496712860053069476945214',\n",
" '49558713491944943262949682898061227957325052054046197143378203615269796493658',\n",
" '111138854287366484154634943297210669395092434185286519533898615765972894294967',\n",
" '63485197917885194773892649042188753341615679859375446649536109613725800096903'],\n",
" dtype=object)"
]
},
"execution_count": 41,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tools['request_date'] = pd.to_datetime(tools['request_date'])\n",
"oct_sample = tools.loc[(tools[\"request_date\"]==\"2024-10-08\") & (tools[\"error\"]!=1)]\n",
"oct_sample.request_id.values[:10]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "hf_dashboards",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.2"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
|