data-bootcamp-v4 · camilla-scandola · Feb 1, 2026 · Feb 1, 2026
diff --git a/.DS_Store b/.DS_Store
diff --git a/.ipynb_checkpoints/sql-python-connection-checkpoint.ipynb b/.ipynb_checkpoints/sql-python-connection-checkpoint.ipynb
@@ -0,0 +1,6 @@
+{
+ "cells": [],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/sql-python-connection-lab.ipynb b/sql-python-connection-lab.ipynb
@@ -0,0 +1,200 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "c36f412d-502f-4653-a6bb-e6e164089e15",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "from sqlalchemy import create_engine, text\n",
+    "\n",
+    "# 1) Connect Python to the Sakila DB\n",
+    "\n",
+    "#engine = create_engine(\"mysql+pymysql://username:password@localhost:3306/sakila\")\n",
+    "\n",
+    "# 2) Pull raw rentals for a given month/year\n",
+    "def rentals_month(engine, month: int, year: int) -> pd.DataFrame:\n",
+    "    \"\"\"\n",
+    "    Returns rows from sakila.rental for the given month/year as a DataFrame.\n",
+    "    \"\"\"\n",
+    "    query = text(\"\"\"\n",
+    "        SELECT rental_id, rental_date, inventory_id, customer_id, staff_id, return_date\n",
+    "        FROM rental\n",
+    "        WHERE YEAR(rental_date) = :year\n",
+    "          AND MONTH(rental_date) = :month\n",
+    "        ORDER BY rental_date;\n",
+    "    \"\"\")\n",
+    "\n",
+    "    with engine.connect() as conn:\n",
+    "        df = pd.read_sql(query, conn, params={\"year\": year, \"month\": month})\n",
+    "\n",
+    "    return df\n",
+    "\n",
+    "\n",
+    "# 3) Count rentals per customer for that month/year\n",
+    "def rental_count_month(rentals_df: pd.DataFrame, month: int, year: int) -> pd.DataFrame:\n",
+    "    \"\"\"\n",
+    "    Groups rentals_df by customer_id and returns a DataFrame:\n",
+    "      customer_id | rentals_MM_YYYY\n",
+    "    \"\"\"\n",
+    "    col_name = f\"rentals_{month:02d}_{year}\"\n",
+    "    counts = (\n",
+    "        rentals_df\n",
+    "        .groupby(\"customer_id\", as_index=False)\n",
+    "        .size()\n",
+    "        .rename(columns={\"size\": col_name})\n",
+    "    )\n",
+    "    return counts\n",
+    "\n",
+    "\n",
+    "# 4) Compare two month-count DataFrames and compute difference\n",
+    "def compare_rentals(df_a: pd.DataFrame, df_b: pd.DataFrame) -> pd.DataFrame:\n",
+    "    \"\"\"\n",
+    "    where difference = (second month column) - (first month column)\n",
+    "    also filters to customers active in both months (inner join)\n",
+    "    \"\"\"\n",
+    "    # Identify the rentals columns (everything except customer_id)\n",
+    "    col_a = [c for c in df_a.columns if c != \"customer_id\"]\n",
+    "    col_b = [c for c in df_b.columns if c != \"customer_id\"]\n",
+    "    if len(col_a) != 1 or len(col_b) != 1:\n",
+    "        raise ValueError(\"Each input DataFrame must have exactly one rentals_* column plus customer_id.\")\n",
+    "\n",
+    "    col_a = col_a[0]\n",
+    "    col_b = col_b[0]\n",
+    "\n",
+    "    merged = df_a.merge(df_b, on=\"customer_id\", how=\"inner\")  # active in BOTH months\n",
+    "    merged[\"difference\"] = merged[col_b] - merged[col_a]\n",
+    "    return merged.sort_values([\"difference\", \"customer_id\"], ascending=[False, True]).reset_index(drop=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "e8ac67f2-4936-4c71-bcae-99bb59c489a5",
+   "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_id</th>\n",
+       "      <th>rentals_05_2005</th>\n",
+       "      <th>rentals_06_2005</th>\n",
+       "      <th>difference</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>454</td>\n",
+       "      <td>1</td>\n",
+       "      <td>10</td>\n",
+       "      <td>9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>213</td>\n",
+       "      <td>1</td>\n",
+       "      <td>9</td>\n",
+       "      <td>8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>295</td>\n",
+       "      <td>1</td>\n",
+       "      <td>9</td>\n",
+       "      <td>8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>457</td>\n",
+       "      <td>1</td>\n",
+       "      <td>9</td>\n",
+       "      <td>8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>27</td>\n",
+       "      <td>1</td>\n",
+       "      <td>8</td>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   customer_id  rentals_05_2005  rentals_06_2005  difference\n",
+       "0          454                1               10           9\n",
+       "1          213                1                9           8\n",
+       "2          295                1                9           8\n",
+       "3          457                1                9           8\n",
+       "4           27                1                8           7"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Example: customers active in BOTH May and June 2005, and how activity differed\n",
+    "\n",
+    "may_df  = rentals_month(engine, 5, 2005)\n",
+    "jun_df  = rentals_month(engine, 6, 2005)\n",
+    "may_ct  = rental_count_month(may_df, 5, 2005)\n",
+    "jun_ct  = rental_count_month(jun_df, 6, 2005)\n",
+    "comparison = compare_rentals(may_ct, jun_ct)\n",
+    "comparison.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6a0c519e-ef9a-4e51-9dbc-f41e425c4077",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
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+   "display_name": "Python [conda env:base] *",
+   "language": "python",
+   "name": "conda-base-py"
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+   "codemirror_mode": {
+    "name": "ipython",
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+   "file_extension": ".py",
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