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[lab-sql-9]Pedro #27

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7a94f93
[lab-sql-9]Pedro
pedro-gui-afonso Dec 2, 2023
cf091be
[lab-sql-9]Pedro
pedro-gui-afonso Dec 2, 2023
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388 changes: 388 additions & 0 deletions lab-sql-9.ipynb
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Original file line number Diff line number Diff line change
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "de221430",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'\\n!pip install mysql.connector\\n!pip install mysql.connector.python\\n!pip install sqlalchemy\\n!pip install pymysql\\n\\n'"
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"'''\n",
"!pip install mysql.connector\n",
"!pip install mysql.connector.python\n",
"!pip install sqlalchemy\n",
"!pip install pymysql\n",
"\n",
"'''"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "37d20b1b",
"metadata": {},
"outputs": [],
"source": [
"import pymysql\n",
"from sqlalchemy import create_engine\n",
"import pandas as pd\n",
"import numpy as np"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "b4268fa3",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"········\n"
]
}
],
"source": [
"import getpass\n",
"password = getpass.getpass()"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "1639585c",
"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>customer_name</th>\n",
" <th>nr_rentals_may</th>\n",
" <th>nr_rentals_june</th>\n",
" </tr>\n",
" <tr>\n",
" <th>customer_id</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>197</th>\n",
" <td>SUE PETERS</td>\n",
" <td>8</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>176</th>\n",
" <td>JUNE CARROLL</td>\n",
" <td>5</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>371</th>\n",
" <td>BILLY POULIN</td>\n",
" <td>6</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>109</th>\n",
" <td>EDNA WEST</td>\n",
" <td>7</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>196</th>\n",
" <td>ALMA AUSTIN</td>\n",
" <td>4</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>440</th>\n",
" <td>BERNARD COLBY</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>487</th>\n",
" <td>HECTOR POINDEXTER</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>555</th>\n",
" <td>DWIGHT LOMBARDI</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>598</th>\n",
" <td>WADE DELVALLE</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>195</th>\n",
" <td>VANESSA SIMS</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>599 rows × 3 columns</p>\n",
"</div>"
],
"text/plain": [
" customer_name nr_rentals_may nr_rentals_june\n",
"customer_id \n",
"197 SUE PETERS 8 8\n",
"176 JUNE CARROLL 5 8\n",
"371 BILLY POULIN 6 7\n",
"109 EDNA WEST 7 5\n",
"196 ALMA AUSTIN 4 8\n",
"... ... ... ...\n",
"440 BERNARD COLBY 1 0\n",
"487 HECTOR POINDEXTER 0 1\n",
"555 DWIGHT LOMBARDI 0 1\n",
"598 WADE DELVALLE 0 1\n",
"195 VANESSA SIMS 0 0\n",
"\n",
"[599 rows x 3 columns]"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"connection_string = 'mysql+pymysql://root:' + password + '@localhost/bank'\n",
"engine = create_engine(connection_string)\n",
"data = pd.read_sql_query('select * from sakila.rentals_may_june', engine)\n",
"data = data.set_index('customer_id')\n",
"data"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "6eae4c81",
"metadata": {},
"outputs": [],
"source": [
"def compare_rentals_may_june(df):\n",
" df['most_rentals'] = np.where(df['nr_rentals_may'] > df['nr_rentals_june'], 'may',\n",
" np.where(df['nr_rentals_may'] < df['nr_rentals_june'], 'june', 'equal'))\n",
" return df"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "0e35377b",
"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>customer_name</th>\n",
" <th>nr_rentals_may</th>\n",
" <th>nr_rentals_june</th>\n",
" <th>most_rentals</th>\n",
" </tr>\n",
" <tr>\n",
" <th>customer_id</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>197</th>\n",
" <td>SUE PETERS</td>\n",
" <td>8</td>\n",
" <td>8</td>\n",
" <td>equal</td>\n",
" </tr>\n",
" <tr>\n",
" <th>176</th>\n",
" <td>JUNE CARROLL</td>\n",
" <td>5</td>\n",
" <td>8</td>\n",
" <td>june</td>\n",
" </tr>\n",
" <tr>\n",
" <th>371</th>\n",
" <td>BILLY POULIN</td>\n",
" <td>6</td>\n",
" <td>7</td>\n",
" <td>june</td>\n",
" </tr>\n",
" <tr>\n",
" <th>109</th>\n",
" <td>EDNA WEST</td>\n",
" <td>7</td>\n",
" <td>5</td>\n",
" <td>may</td>\n",
" </tr>\n",
" <tr>\n",
" <th>196</th>\n",
" <td>ALMA AUSTIN</td>\n",
" <td>4</td>\n",
" <td>8</td>\n",
" <td>june</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>440</th>\n",
" <td>BERNARD COLBY</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>may</td>\n",
" </tr>\n",
" <tr>\n",
" <th>487</th>\n",
" <td>HECTOR POINDEXTER</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>june</td>\n",
" </tr>\n",
" <tr>\n",
" <th>555</th>\n",
" <td>DWIGHT LOMBARDI</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>june</td>\n",
" </tr>\n",
" <tr>\n",
" <th>598</th>\n",
" <td>WADE DELVALLE</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>june</td>\n",
" </tr>\n",
" <tr>\n",
" <th>195</th>\n",
" <td>VANESSA SIMS</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>equal</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>599 rows × 4 columns</p>\n",
"</div>"
],
"text/plain": [
" customer_name nr_rentals_may nr_rentals_june most_rentals\n",
"customer_id \n",
"197 SUE PETERS 8 8 equal\n",
"176 JUNE CARROLL 5 8 june\n",
"371 BILLY POULIN 6 7 june\n",
"109 EDNA WEST 7 5 may\n",
"196 ALMA AUSTIN 4 8 june\n",
"... ... ... ... ...\n",
"440 BERNARD COLBY 1 0 may\n",
"487 HECTOR POINDEXTER 0 1 june\n",
"555 DWIGHT LOMBARDI 0 1 june\n",
"598 WADE DELVALLE 0 1 june\n",
"195 VANESSA SIMS 0 0 equal\n",
"\n",
"[599 rows x 4 columns]"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"compare_rentals_may_june(data)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"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": "3.11.5"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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