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272 changes: 272 additions & 0 deletions lab-connection.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": 22,
"id": "8bc9fd2c",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"import pymysql \n",
"from sqlalchemy import create_engine\n",
"import getpass # To get the password without showing the input\n",
"password = getpass.getpass()\n"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "770a7cf3",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Engine(mysql+pymysql://root:***@localhost/sakila)"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"bd = \"sakila\"\n",
"connection_string = 'mysql+pymysql://root:' + password + '@localhost/'+bd\n",
"engine = create_engine(connection_string)\n",
"engine\n"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "d5cd0500",
"metadata": {},
"outputs": [],
"source": [
"def rentals_month(engine, month, year):\n",
" query = text(\"\"\"\n",
" SELECT\n",
" rental_id,\n",
" customer_id,\n",
" rental_date\n",
" FROM rental\n",
" WHERE MONTH(rental_date) = :month\n",
" AND YEAR(rental_date) = :year\n",
" \"\"\")\n",
" \n",
" with engine.connect() as connection:\n",
" df = pd.read_sql(query, connection, params={\n",
" \"month\": month,\n",
" \"year\": year\n",
" })\n",
" \n",
" return df\n"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "a35b1de2",
"metadata": {},
"outputs": [],
"source": [
"def rental_count_month(df, month, year):\n",
" column_name = f\"alugueis_{month:02d}_{year}\"\n",
" \n",
" result = (\n",
" df.groupby(\"customer_id\")\n",
" .size()\n",
" .reset_index(name=column_name)\n",
" )\n",
" \n",
" return result\n"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "736d9b75",
"metadata": {},
"outputs": [],
"source": [
"def compare_rentals(df1, df2):\n",
" df_combined = pd.merge(\n",
" df1,\n",
" df2,\n",
" on=\"customer_id\",\n",
" how=\"inner\"\n",
" )\n",
" \n",
" col1 = df1.columns[1]\n",
" col2 = df2.columns[1]\n",
" \n",
" df_combined[\"diferenca\"] = df_combined[col2] - df_combined[col1]\n",
" \n",
" return df_combined\n"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "e5206050",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"May rentals shape: (1156, 3)\n",
" rental_id customer_id rental_date\n",
"0 1 130 2005-05-24 22:53:30\n",
"1 2 459 2005-05-24 22:54:33\n",
"2 3 408 2005-05-24 23:03:39\n",
"3 4 333 2005-05-24 23:04:41\n",
"4 5 222 2005-05-24 23:05:21\n",
" customer_id alugueis_05_2005\n",
"0 1 2\n",
"1 2 1\n",
"2 3 2\n",
"3 5 3\n",
"4 6 3\n",
"June rentals shape: (2311, 3)\n",
" rental_id customer_id rental_date\n",
"0 1158 416 2005-06-14 22:53:33\n",
"1 1159 516 2005-06-14 22:55:13\n",
"2 1160 239 2005-06-14 23:00:34\n",
"3 1161 285 2005-06-14 23:07:08\n",
"4 1162 310 2005-06-14 23:09:38\n",
" customer_id alugueis_06_2005\n",
"0 1 7\n",
"1 2 1\n",
"2 3 4\n",
"3 4 6\n",
"4 5 5\n"
]
},
{
"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_id</th>\n",
" <th>alugueis_05_2005</th>\n",
" <th>alugueis_06_2005</th>\n",
" <th>diferenca</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>7</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" <td>4</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>5</td>\n",
" <td>3</td>\n",
" <td>5</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>6</td>\n",
" <td>3</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" customer_id alugueis_05_2005 alugueis_06_2005 diferenca\n",
"0 1 2 7 5\n",
"1 2 1 1 0\n",
"2 3 2 4 2\n",
"3 5 3 5 2\n",
"4 6 3 4 1"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"may_df = rentals_month(engine, 5, 2005)\n",
"print(\"May rentals shape:\", may_df.shape)\n",
"print(may_df.head())\n",
"\n",
"may_count = rental_count_month(may_df, 5, 2005)\n",
"print(may_count.head())\n",
"\n",
"june_df = rentals_month(engine, 6, 2005)\n",
"print(\"June rentals shape:\", june_df.shape)\n",
"print(june_df.head())\n",
"\n",
"june_count = rental_count_month(june_df, 6, 2005)\n",
"print(june_count.head())\n",
"\n",
"comparison = compare_rentals(may_count, june_count)\n",
"comparison.head()\n",
"\n"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "base",
"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": "3.13.9"
}
},
"nbformat": 4,
"nbformat_minor": 5
}