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justmarkham/pandas_scoring_runs.ipynb

Created March 27, 2023 15:44
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Data School's Tuesday Tip #9
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pandas_scoring_runs.ipynb
{
"cells": [
{
"cell_type": "markdown",
"id": "4958ee13",
"metadata": {},
"source": [
"# [Tuesday Tip #9](https://tuesday.tips/): Calculate scoring runs in basketball 🏀\n",
"\n",
"Shout out to Josh Devlin's excellent blog post, [Calculating Streaks in Pandas](https://joshdevlin.com/blog/calculate-streaks-in-pandas/), for teaching me this approach!"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "dea20756",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "888b33ce",
"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>team</th>\n",
" <th>points</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>A</td>\n",
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" <td>A</td>\n",
" <td>3</td>\n",
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" <td>A</td>\n",
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" <tr>\n",
" <th>7</th>\n",
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" <td>B</td>\n",
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" <tr>\n",
" <th>9</th>\n",
" <td>A</td>\n",
" <td>3</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" team points\n",
"0 A 2\n",
"1 B 1\n",
"2 B 1\n",
"3 B 3\n",
"4 A 2\n",
"5 A 3\n",
"6 A 2\n",
"7 A 2\n",
"8 B 1\n",
"9 A 3"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df = pd.DataFrame({'team':'A B B B A A A A B A'.split(),\n",
" 'points':[2, 1, 1, 3, 2, 3, 2, 2, 1, 3]})\n",
"df"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "66ad0f45",
"metadata": {},
"outputs": [
{
"data": {
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"<div>\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>team</th>\n",
" <th>points</th>\n",
" <th>previous_team</th>\n",
" </tr>\n",
" </thead>\n",
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" <tr>\n",
" <th>0</th>\n",
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" <td>B</td>\n",
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" <tr>\n",
" <th>3</th>\n",
" <td>B</td>\n",
" <td>3</td>\n",
" <td>B</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>A</td>\n",
" <td>2</td>\n",
" <td>B</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>A</td>\n",
" <td>3</td>\n",
" <td>A</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>A</td>\n",
" <td>2</td>\n",
" <td>A</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>A</td>\n",
" <td>2</td>\n",
" <td>A</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>B</td>\n",
" <td>1</td>\n",
" <td>A</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>A</td>\n",
" <td>3</td>\n",
" <td>B</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" team points previous_team\n",
"0 A 2 None\n",
"1 B 1 A\n",
"2 B 1 B\n",
"3 B 3 B\n",
"4 A 2 B\n",
"5 A 3 A\n",
"6 A 2 A\n",
"7 A 2 A\n",
"8 B 1 A\n",
"9 A 3 B"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df['previous_team'] = df['team'].shift(1)\n",
"df"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "c7efd8b1",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: top;\n",
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" .dataframe thead th {\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>team</th>\n",
" <th>points</th>\n",
" <th>previous_team</th>\n",
" <th>start_of_run</th>\n",
" </tr>\n",
" </thead>\n",
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" <tr>\n",
" <th>0</th>\n",
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" <td>2</td>\n",
" <td>None</td>\n",
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" <tr>\n",
" <th>1</th>\n",
" <td>B</td>\n",
" <td>1</td>\n",
" <td>A</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>B</td>\n",
" <td>1</td>\n",
" <td>B</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>B</td>\n",
" <td>3</td>\n",
" <td>B</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>A</td>\n",
" <td>2</td>\n",
" <td>B</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>A</td>\n",
" <td>3</td>\n",
" <td>A</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>A</td>\n",
" <td>2</td>\n",
" <td>A</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>A</td>\n",
" <td>2</td>\n",
" <td>A</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>B</td>\n",
" <td>1</td>\n",
" <td>A</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>A</td>\n",
" <td>3</td>\n",
" <td>B</td>\n",
" <td>True</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" team points previous_team start_of_run\n",
"0 A 2 None True\n",
"1 B 1 A True\n",
"2 B 1 B False\n",
"3 B 3 B False\n",
"4 A 2 B True\n",
"5 A 3 A False\n",
"6 A 2 A False\n",
"7 A 2 A False\n",
"8 B 1 A True\n",
"9 A 3 B True"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df['start_of_run'] = df['team'] != df['previous_team']\n",
"df"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "9a8df09d",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
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" .dataframe thead th {\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>team</th>\n",
" <th>points</th>\n",
" <th>previous_team</th>\n",
" <th>start_of_run</th>\n",
" <th>run_id</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>A</td>\n",
" <td>2</td>\n",
" <td>None</td>\n",
" <td>True</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>B</td>\n",
" <td>1</td>\n",
" <td>A</td>\n",
" <td>True</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>B</td>\n",
" <td>1</td>\n",
" <td>B</td>\n",
" <td>False</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>B</td>\n",
" <td>3</td>\n",
" <td>B</td>\n",
" <td>False</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>A</td>\n",
" <td>2</td>\n",
" <td>B</td>\n",
" <td>True</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>A</td>\n",
" <td>3</td>\n",
" <td>A</td>\n",
" <td>False</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>A</td>\n",
" <td>2</td>\n",
" <td>A</td>\n",
" <td>False</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>A</td>\n",
" <td>2</td>\n",
" <td>A</td>\n",
" <td>False</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>B</td>\n",
" <td>1</td>\n",
" <td>A</td>\n",
" <td>True</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>A</td>\n",
" <td>3</td>\n",
" <td>B</td>\n",
" <td>True</td>\n",
" <td>5</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" team points previous_team start_of_run run_id\n",
"0 A 2 None True 1\n",
"1 B 1 A True 2\n",
"2 B 1 B False 2\n",
"3 B 3 B False 2\n",
"4 A 2 B True 3\n",
"5 A 3 A False 3\n",
"6 A 2 A False 3\n",
"7 A 2 A False 3\n",
"8 B 1 A True 4\n",
"9 A 3 B True 5"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df['run_id'] = df['start_of_run'].cumsum()\n",
"df"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "e125fdf4",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"run_id team\n",
"1 A 2\n",
"2 B 5\n",
"3 A 9\n",
"4 B 1\n",
"5 A 3\n",
"Name: points, dtype: int64"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.groupby(['run_id', 'team'])['points'].sum()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
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},
"file_extension": ".py",
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"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.9"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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