diff --git a/.ipynb_checkpoints/lab-sql-python-connection-checkpoint.ipynb b/.ipynb_checkpoints/lab-sql-python-connection-checkpoint.ipynb
new file mode 100644
index 0000000..740f448
--- /dev/null
+++ b/.ipynb_checkpoints/lab-sql-python-connection-checkpoint.ipynb
@@ -0,0 +1,295 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "53022ce9-0fe0-4039-8c67-27538ef9c821",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Requirement already satisfied: pymysql in c:\\users\\kraus\\anaconda3\\lib\\site-packages (1.2.0)\n"
+     ]
+    }
+   ],
+   "source": [
+    "!pip install pymysql"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "789390e3-97ec-431a-986d-bd7164d389a5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sqlalchemy import create_engine\n",
+    "\n",
+    "engine = create_engine('mysql+pymysql://root:Ironhacksummer2026!@localhost/sakila')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "2e114ebd-c6c7-4dd7-b597-651e12e9440f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "def rentals_month(engine, month, year):\n",
+    "    query = f\"\"\"\n",
+    "        SELECT * FROM rental\n",
+    "        WHERE MONTH(rental_date) = {month} AND YEAR(rental_date) = {year}\n",
+    "    \"\"\"\n",
+    "    df = pd.read_sql(query, engine)\n",
+    "    return df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "f0f65640-ae5c-472e-b675-6794f6858f8f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def rental_count_month(df, month, year):\n",
+    "    counts = df.groupby('customer_id').size().reset_index(name=f'rentals_{month:02d}_{year}')\n",
+    "    return counts"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "9682820f-eed2-4dc1-9280-4bb852973bd2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def compare_rentals(df1, df2):\n",
+    "    merged = pd.merge(df1, df2, on='customer_id', how='outer')\n",
+    "    merged['difference'] = merged.iloc[:, 1] - merged.iloc[:, 2]\n",
+    "    return merged"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "ee55df88-0a9b-4855-a8f9-2286e599ea23",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "may_df = rentals_month(engine, 5, 2005)\n",
+    "june_df = rentals_month(engine, 6, 2005)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "5ba6da4a-c516-469d-badb-16ffcaf2901c",
+   "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_06_2005_x</th>\n",
+       "      <th>rentals_06_2005_y</th>\n",
+       "      <th>difference</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>7</td>\n",
+       "      <td>7</td>\n",
+       "      <td>0</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>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>5</td>\n",
+       "      <td>5</td>\n",
+       "      <td>0</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>585</th>\n",
+       "      <td>595</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>586</th>\n",
+       "      <td>596</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>587</th>\n",
+       "      <td>597</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>588</th>\n",
+       "      <td>598</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>589</th>\n",
+       "      <td>599</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>590 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     customer_id  rentals_06_2005_x  rentals_06_2005_y  difference\n",
+       "0              1                  7                  7           0\n",
+       "1              2                  1                  1           0\n",
+       "2              3                  4                  4           0\n",
+       "3              4                  6                  6           0\n",
+       "4              5                  5                  5           0\n",
+       "..           ...                ...                ...         ...\n",
+       "585          595                  2                  2           0\n",
+       "586          596                  2                  2           0\n",
+       "587          597                  3                  3           0\n",
+       "588          598                  1                  1           0\n",
+       "589          599                  4                  4           0\n",
+       "\n",
+       "[590 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "may_counts = rental_count_month(june_df, 6, 2005)\n",
+    "june_counts = rental_count_month(june_df, 6, 2005)\n",
+    "\n",
+    "result = compare_rentals(may_counts, june_counts)\n",
+    "result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "17f2be36-b8a4-4e05-9135-484215470705",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "aef1fa62-fcd2-4a24-8fe3-373129346735",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f26136db-0d4e-4e32-ad42-09c25c0cec70",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d33cd019-9e3a-433f-b709-ce4dfef79310",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "60e39851-b6e3-4a07-b77a-b4931b09f22e",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python [conda env:base] *",
+   "language": "python",
+   "name": "conda-base-py"
+  },
+  "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
+}
diff --git a/lab-sql-python-connection.ipynb b/lab-sql-python-connection.ipynb
new file mode 100644
index 0000000..740f448
--- /dev/null
+++ b/lab-sql-python-connection.ipynb
@@ -0,0 +1,295 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "53022ce9-0fe0-4039-8c67-27538ef9c821",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Requirement already satisfied: pymysql in c:\\users\\kraus\\anaconda3\\lib\\site-packages (1.2.0)\n"
+     ]
+    }
+   ],
+   "source": [
+    "!pip install pymysql"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "789390e3-97ec-431a-986d-bd7164d389a5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sqlalchemy import create_engine\n",
+    "\n",
+    "engine = create_engine('mysql+pymysql://root:Ironhacksummer2026!@localhost/sakila')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "2e114ebd-c6c7-4dd7-b597-651e12e9440f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "def rentals_month(engine, month, year):\n",
+    "    query = f\"\"\"\n",
+    "        SELECT * FROM rental\n",
+    "        WHERE MONTH(rental_date) = {month} AND YEAR(rental_date) = {year}\n",
+    "    \"\"\"\n",
+    "    df = pd.read_sql(query, engine)\n",
+    "    return df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "f0f65640-ae5c-472e-b675-6794f6858f8f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def rental_count_month(df, month, year):\n",
+    "    counts = df.groupby('customer_id').size().reset_index(name=f'rentals_{month:02d}_{year}')\n",
+    "    return counts"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "9682820f-eed2-4dc1-9280-4bb852973bd2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def compare_rentals(df1, df2):\n",
+    "    merged = pd.merge(df1, df2, on='customer_id', how='outer')\n",
+    "    merged['difference'] = merged.iloc[:, 1] - merged.iloc[:, 2]\n",
+    "    return merged"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "ee55df88-0a9b-4855-a8f9-2286e599ea23",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "may_df = rentals_month(engine, 5, 2005)\n",
+    "june_df = rentals_month(engine, 6, 2005)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "5ba6da4a-c516-469d-badb-16ffcaf2901c",
+   "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_06_2005_x</th>\n",
+       "      <th>rentals_06_2005_y</th>\n",
+       "      <th>difference</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>7</td>\n",
+       "      <td>7</td>\n",
+       "      <td>0</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>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>5</td>\n",
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+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
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+       "      <th>585</th>\n",
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+       "      <td>2</td>\n",
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+       "    <tr>\n",
+       "      <th>586</th>\n",
+       "      <td>596</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>587</th>\n",
+       "      <td>597</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>588</th>\n",
+       "      <td>598</td>\n",
+       "      <td>1</td>\n",
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+       "    <tr>\n",
+       "      <th>589</th>\n",
+       "      <td>599</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>590 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     customer_id  rentals_06_2005_x  rentals_06_2005_y  difference\n",
+       "0              1                  7                  7           0\n",
+       "1              2                  1                  1           0\n",
+       "2              3                  4                  4           0\n",
+       "3              4                  6                  6           0\n",
+       "4              5                  5                  5           0\n",
+       "..           ...                ...                ...         ...\n",
+       "585          595                  2                  2           0\n",
+       "586          596                  2                  2           0\n",
+       "587          597                  3                  3           0\n",
+       "588          598                  1                  1           0\n",
+       "589          599                  4                  4           0\n",
+       "\n",
+       "[590 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "may_counts = rental_count_month(june_df, 6, 2005)\n",
+    "june_counts = rental_count_month(june_df, 6, 2005)\n",
+    "\n",
+    "result = compare_rentals(may_counts, june_counts)\n",
+    "result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "17f2be36-b8a4-4e05-9135-484215470705",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "aef1fa62-fcd2-4a24-8fe3-373129346735",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f26136db-0d4e-4e32-ad42-09c25c0cec70",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d33cd019-9e3a-433f-b709-ce4dfef79310",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "60e39851-b6e3-4a07-b77a-b4931b09f22e",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python [conda env:base] *",
+   "language": "python",
+   "name": "conda-base-py"
+  },
+  "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"
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+ },
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+ "nbformat_minor": 5
+}