diff --git a/lab-dw-aggregating.ipynb b/lab-dw-aggregating.ipynb
index fadd718..afe3670 100644
--- a/lab-dw-aggregating.ipynb
+++ b/lab-dw-aggregating.ipynb
@@ -127,14 +127,702 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 18,
       "id": "449513f4-0459-46a0-a18d-9398d974c9ad",
       "metadata": {
         "id": "449513f4-0459-46a0-a18d-9398d974c9ad"
       },
+      "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>unnamed:_0</th>\n",
+              "      <th>customer</th>\n",
+              "      <th>state</th>\n",
+              "      <th>customer_lifetime_value</th>\n",
+              "      <th>response</th>\n",
+              "      <th>coverage</th>\n",
+              "      <th>education</th>\n",
+              "      <th>effective_to_date</th>\n",
+              "      <th>employmentstatus</th>\n",
+              "      <th>gender</th>\n",
+              "      <th>...</th>\n",
+              "      <th>number_of_open_complaints</th>\n",
+              "      <th>number_of_policies</th>\n",
+              "      <th>policy_type</th>\n",
+              "      <th>policy</th>\n",
+              "      <th>renew_offer_type</th>\n",
+              "      <th>sales_channel</th>\n",
+              "      <th>total_claim_amount</th>\n",
+              "      <th>vehicle_class</th>\n",
+              "      <th>vehicle_size</th>\n",
+              "      <th>vehicle_type</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>0</td>\n",
+              "      <td>DK49336</td>\n",
+              "      <td>Arizona</td>\n",
+              "      <td>4809.216960</td>\n",
+              "      <td>No</td>\n",
+              "      <td>Basic</td>\n",
+              "      <td>College</td>\n",
+              "      <td>2/18/11</td>\n",
+              "      <td>Employed</td>\n",
+              "      <td>M</td>\n",
+              "      <td>...</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>9</td>\n",
+              "      <td>Corporate Auto</td>\n",
+              "      <td>Corporate L3</td>\n",
+              "      <td>Offer3</td>\n",
+              "      <td>Agent</td>\n",
+              "      <td>292.800000</td>\n",
+              "      <td>Four-Door Car</td>\n",
+              "      <td>Medsize</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>1</td>\n",
+              "      <td>KX64629</td>\n",
+              "      <td>California</td>\n",
+              "      <td>2228.525238</td>\n",
+              "      <td>No</td>\n",
+              "      <td>Basic</td>\n",
+              "      <td>College</td>\n",
+              "      <td>1/18/11</td>\n",
+              "      <td>Unemployed</td>\n",
+              "      <td>F</td>\n",
+              "      <td>...</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Personal Auto</td>\n",
+              "      <td>Personal L3</td>\n",
+              "      <td>Offer4</td>\n",
+              "      <td>Call Center</td>\n",
+              "      <td>744.924331</td>\n",
+              "      <td>Four-Door Car</td>\n",
+              "      <td>Medsize</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>2</td>\n",
+              "      <td>LZ68649</td>\n",
+              "      <td>Washington</td>\n",
+              "      <td>14947.917300</td>\n",
+              "      <td>No</td>\n",
+              "      <td>Basic</td>\n",
+              "      <td>Bachelor</td>\n",
+              "      <td>2/10/11</td>\n",
+              "      <td>Employed</td>\n",
+              "      <td>M</td>\n",
+              "      <td>...</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>2</td>\n",
+              "      <td>Personal Auto</td>\n",
+              "      <td>Personal L3</td>\n",
+              "      <td>Offer3</td>\n",
+              "      <td>Call Center</td>\n",
+              "      <td>480.000000</td>\n",
+              "      <td>SUV</td>\n",
+              "      <td>Medsize</td>\n",
+              "      <td>A</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>3</td>\n",
+              "      <td>XL78013</td>\n",
+              "      <td>Oregon</td>\n",
+              "      <td>22332.439460</td>\n",
+              "      <td>Yes</td>\n",
+              "      <td>Extended</td>\n",
+              "      <td>College</td>\n",
+              "      <td>1/11/11</td>\n",
+              "      <td>Employed</td>\n",
+              "      <td>M</td>\n",
+              "      <td>...</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>2</td>\n",
+              "      <td>Corporate Auto</td>\n",
+              "      <td>Corporate L3</td>\n",
+              "      <td>Offer2</td>\n",
+              "      <td>Branch</td>\n",
+              "      <td>484.013411</td>\n",
+              "      <td>Four-Door Car</td>\n",
+              "      <td>Medsize</td>\n",
+              "      <td>A</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>4</td>\n",
+              "      <td>QA50777</td>\n",
+              "      <td>Oregon</td>\n",
+              "      <td>9025.067525</td>\n",
+              "      <td>No</td>\n",
+              "      <td>Premium</td>\n",
+              "      <td>Bachelor</td>\n",
+              "      <td>1/17/11</td>\n",
+              "      <td>Medical Leave</td>\n",
+              "      <td>F</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>7</td>\n",
+              "      <td>Personal Auto</td>\n",
+              "      <td>Personal L2</td>\n",
+              "      <td>Offer1</td>\n",
+              "      <td>Branch</td>\n",
+              "      <td>707.925645</td>\n",
+              "      <td>Four-Door Car</td>\n",
+              "      <td>Medsize</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>5 rows × 26 columns</p>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "   unnamed:_0 customer       state  customer_lifetime_value response  \\\n",
+              "0           0  DK49336     Arizona              4809.216960       No   \n",
+              "1           1  KX64629  California              2228.525238       No   \n",
+              "2           2  LZ68649  Washington             14947.917300       No   \n",
+              "3           3  XL78013      Oregon             22332.439460      Yes   \n",
+              "4           4  QA50777      Oregon              9025.067525       No   \n",
+              "\n",
+              "   coverage education effective_to_date employmentstatus gender  ...  \\\n",
+              "0     Basic   College           2/18/11         Employed      M  ...   \n",
+              "1     Basic   College           1/18/11       Unemployed      F  ...   \n",
+              "2     Basic  Bachelor           2/10/11         Employed      M  ...   \n",
+              "3  Extended   College           1/11/11         Employed      M  ...   \n",
+              "4   Premium  Bachelor           1/17/11    Medical Leave      F  ...   \n",
+              "\n",
+              "   number_of_open_complaints number_of_policies     policy_type        policy  \\\n",
+              "0                        0.0                  9  Corporate Auto  Corporate L3   \n",
+              "1                        0.0                  1   Personal Auto   Personal L3   \n",
+              "2                        0.0                  2   Personal Auto   Personal L3   \n",
+              "3                        0.0                  2  Corporate Auto  Corporate L3   \n",
+              "4                        NaN                  7   Personal Auto   Personal L2   \n",
+              "\n",
+              "   renew_offer_type  sales_channel  total_claim_amount  vehicle_class  \\\n",
+              "0            Offer3          Agent          292.800000  Four-Door Car   \n",
+              "1            Offer4    Call Center          744.924331  Four-Door Car   \n",
+              "2            Offer3    Call Center          480.000000            SUV   \n",
+              "3            Offer2         Branch          484.013411  Four-Door Car   \n",
+              "4            Offer1         Branch          707.925645  Four-Door Car   \n",
+              "\n",
+              "  vehicle_size vehicle_type  \n",
+              "0      Medsize          NaN  \n",
+              "1      Medsize          NaN  \n",
+              "2      Medsize            A  \n",
+              "3      Medsize            A  \n",
+              "4      Medsize          NaN  \n",
+              "\n",
+              "[5 rows x 26 columns]"
+            ]
+          },
+          "execution_count": 18,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "import pandas as pd\n",
+        "import numpy as np\n",
+        "\n",
+        "url = \"https://raw.githubusercontent.com/data-bootcamp-v4/data/main/marketing_customer_analysis.csv\"\n",
+        "df = pd.read_csv(url)\n",
+        "\n",
+        "df.columns = df.columns.str.strip().str.lower().str.replace(' ', '_')\n",
+        "df.head()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "9c832fd6",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "new_df = df[(df['total_claim_amount'] < 1000) & (df['response'] == 'Yes')]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 30,
+      "id": "1368a438",
+      "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></th>\n",
+              "      <th></th>\n",
+              "      <th>customer_lifetime_value</th>\n",
+              "      <th>total_claim_amount</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>response</th>\n",
+              "      <th>gender</th>\n",
+              "      <th>policy_type</th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th rowspan=\"6\" valign=\"top\">No</th>\n",
+              "      <th rowspan=\"3\" valign=\"top\">F</th>\n",
+              "      <th>Corporate Auto</th>\n",
+              "      <td>8025.383273</td>\n",
+              "      <td>388.104574</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Personal Auto</th>\n",
+              "      <td>8074.641406</td>\n",
+              "      <td>407.499560</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Special Auto</th>\n",
+              "      <td>8442.125882</td>\n",
+              "      <td>458.313057</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th rowspan=\"3\" valign=\"top\">M</th>\n",
+              "      <th>Corporate Auto</th>\n",
+              "      <td>7696.807337</td>\n",
+              "      <td>472.461272</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Personal Auto</th>\n",
+              "      <td>8065.774774</td>\n",
+              "      <td>462.554331</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Special Auto</th>\n",
+              "      <td>9151.145060</td>\n",
+              "      <td>425.032393</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th rowspan=\"6\" valign=\"top\">Yes</th>\n",
+              "      <th rowspan=\"3\" valign=\"top\">F</th>\n",
+              "      <th>Corporate Auto</th>\n",
+              "      <td>7712.628736</td>\n",
+              "      <td>433.738499</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Personal Auto</th>\n",
+              "      <td>8339.791842</td>\n",
+              "      <td>452.965929</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Special Auto</th>\n",
+              "      <td>7691.584111</td>\n",
+              "      <td>453.280164</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th rowspan=\"3\" valign=\"top\">M</th>\n",
+              "      <th>Corporate Auto</th>\n",
+              "      <td>7944.465414</td>\n",
+              "      <td>408.582459</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Personal Auto</th>\n",
+              "      <td>7448.383281</td>\n",
+              "      <td>457.010178</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Special Auto</th>\n",
+              "      <td>8247.088702</td>\n",
+              "      <td>429.527942</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "                                customer_lifetime_value  total_claim_amount\n",
+              "response gender policy_type                                                \n",
+              "No       F      Corporate Auto              8025.383273          388.104574\n",
+              "                Personal Auto               8074.641406          407.499560\n",
+              "                Special Auto                8442.125882          458.313057\n",
+              "         M      Corporate Auto              7696.807337          472.461272\n",
+              "                Personal Auto               8065.774774          462.554331\n",
+              "                Special Auto                9151.145060          425.032393\n",
+              "Yes      F      Corporate Auto              7712.628736          433.738499\n",
+              "                Personal Auto               8339.791842          452.965929\n",
+              "                Special Auto                7691.584111          453.280164\n",
+              "         M      Corporate Auto              7944.465414          408.582459\n",
+              "                Personal Auto               7448.383281          457.010178\n",
+              "                Special Auto                8247.088702          429.527942"
+            ]
+          },
+          "execution_count": 30,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "df.groupby(['response', 'gender', 'policy_type']).agg({'customer_lifetime_value': 'mean', 'total_claim_amount': 'mean'})\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "e3ac688e",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# When it comes to customers with a 'Corporate Auto' policy or 'Special Auto' policy, it seems that males are the most profitable,\n",
+        "# but this changes when we look at 'Personal Auto', with women being the most profitable in that category."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "1980792a",
+      "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>state</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>state</th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>Arizona</th>\n",
+              "      <td>1937</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>California</th>\n",
+              "      <td>3552</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Nevada</th>\n",
+              "      <td>993</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Oregon</th>\n",
+              "      <td>2909</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Washington</th>\n",
+              "      <td>888</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "            state\n",
+              "state            \n",
+              "Arizona      1937\n",
+              "California   3552\n",
+              "Nevada        993\n",
+              "Oregon       2909\n",
+              "Washington    888"
+            ]
+          },
+          "execution_count": 32,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "df.groupby('state').agg({'state': 'count'}) #all states have more than 500 customers"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 34,
+      "id": "0c12319c",
+      "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 tr th {\n",
+              "        text-align: left;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead tr:last-of-type th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th colspan=\"3\" halign=\"left\">customer_lifetime_value</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th>mean</th>\n",
+              "      <th>max</th>\n",
+              "      <th>min</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>gender</th>\n",
+              "      <th>education</th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th rowspan=\"5\" valign=\"top\">F</th>\n",
+              "      <th>Bachelor</th>\n",
+              "      <td>7874.269478</td>\n",
+              "      <td>73225.95652</td>\n",
+              "      <td>1904.000852</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>College</th>\n",
+              "      <td>7748.823325</td>\n",
+              "      <td>61850.18803</td>\n",
+              "      <td>1898.683686</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Doctor</th>\n",
+              "      <td>7328.508916</td>\n",
+              "      <td>44856.11397</td>\n",
+              "      <td>2395.570000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>High School or Below</th>\n",
+              "      <td>8675.220201</td>\n",
+              "      <td>55277.44589</td>\n",
+              "      <td>2144.921535</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Master</th>\n",
+              "      <td>8157.053154</td>\n",
+              "      <td>51016.06704</td>\n",
+              "      <td>2417.777032</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th rowspan=\"5\" valign=\"top\">M</th>\n",
+              "      <th>Bachelor</th>\n",
+              "      <td>7703.601675</td>\n",
+              "      <td>67907.27050</td>\n",
+              "      <td>1898.007675</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>College</th>\n",
+              "      <td>8052.459288</td>\n",
+              "      <td>61134.68307</td>\n",
+              "      <td>1918.119700</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Doctor</th>\n",
+              "      <td>7415.333638</td>\n",
+              "      <td>32677.34284</td>\n",
+              "      <td>2267.604038</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>High School or Below</th>\n",
+              "      <td>8149.687783</td>\n",
+              "      <td>83325.38119</td>\n",
+              "      <td>1940.981221</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Master</th>\n",
+              "      <td>8168.832659</td>\n",
+              "      <td>50568.25912</td>\n",
+              "      <td>2272.307310</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "                            customer_lifetime_value                          \n",
+              "                                               mean          max          min\n",
+              "gender education                                                             \n",
+              "F      Bachelor                         7874.269478  73225.95652  1904.000852\n",
+              "       College                          7748.823325  61850.18803  1898.683686\n",
+              "       Doctor                           7328.508916  44856.11397  2395.570000\n",
+              "       High School or Below             8675.220201  55277.44589  2144.921535\n",
+              "       Master                           8157.053154  51016.06704  2417.777032\n",
+              "M      Bachelor                         7703.601675  67907.27050  1898.007675\n",
+              "       College                          8052.459288  61134.68307  1918.119700\n",
+              "       Doctor                           7415.333638  32677.34284  2267.604038\n",
+              "       High School or Below             8149.687783  83325.38119  1940.981221\n",
+              "       Master                           8168.832659  50568.25912  2272.307310"
+            ]
+          },
+          "execution_count": 34,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "df.groupby(['gender','education']).agg({'customer_lifetime_value': ['mean', 'max', 'min']})"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "98f09f14",
+      "metadata": {},
       "outputs": [],
       "source": [
-        "# your code goes here"
+        "# You could think that customers with a Master's degree would have the highest customer lifetime value, but this is not the case,\n",
+        "# for both women and men its possible to observe that customers with only high school have an average higher or almost equal to \n",
+        "# those with a Master's degree. "
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 35,
+      "id": "512dcc65",
+      "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>effective_to_date</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>state</th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>Arizona</th>\n",
+              "      <td>1937</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>California</th>\n",
+              "      <td>3552</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Nevada</th>\n",
+              "      <td>993</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Oregon</th>\n",
+              "      <td>2909</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Washington</th>\n",
+              "      <td>888</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "            effective_to_date\n",
+              "state                        \n",
+              "Arizona                  1937\n",
+              "California               3552\n",
+              "Nevada                    993\n",
+              "Oregon                   2909\n",
+              "Washington                888"
+            ]
+          },
+          "execution_count": 35,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "df.groupby('state').agg({'effective_to_date': 'count'})"
       ]
     }
   ],
@@ -143,7 +831,7 @@
       "provenance": []
     },
     "kernelspec": {
-      "display_name": "Python 3 (ipykernel)",
+      "display_name": "base",
       "language": "python",
       "name": "python3"
     },
@@ -157,7 +845,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.9.13"
+      "version": "3.13.5"
     }
   },
   "nbformat": 4,