diff --git a/lab-dw-data-structuring-and-combining.ipynb b/lab-dw-data-structuring-and-combining.ipynb
index ec4e3f9..097bbb2 100644
--- a/lab-dw-data-structuring-and-combining.ipynb
+++ b/lab-dw-data-structuring-and-combining.ipynb
@@ -36,14 +36,2322 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
+   "id": "fa2260cc-b023-47c2-9d1d-869c038dbba8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
    "id": "492d06e3-92c7-4105-ac72-536db98d3244",
    "metadata": {
     "id": "492d06e3-92c7-4105-ac72-536db98d3244"
    },
+   "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</th>\n",
+       "      <th>ST</th>\n",
+       "      <th>GENDER</th>\n",
+       "      <th>Education</th>\n",
+       "      <th>Customer Lifetime Value</th>\n",
+       "      <th>Income</th>\n",
+       "      <th>Monthly Premium Auto</th>\n",
+       "      <th>Number of Open Complaints</th>\n",
+       "      <th>Policy Type</th>\n",
+       "      <th>Vehicle Class</th>\n",
+       "      <th>Total Claim Amount</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>RB50392</td>\n",
+       "      <td>Washington</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Master</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1000.0</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>2.704934</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>QZ44356</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>F</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>697953.59%</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>94.0</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>1131.464935</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>AI49188</td>\n",
+       "      <td>Nevada</td>\n",
+       "      <td>F</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>1288743.17%</td>\n",
+       "      <td>48767.0</td>\n",
+       "      <td>108.0</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>566.472247</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>WW63253</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>764586.18%</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>106.0</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>SUV</td>\n",
+       "      <td>529.881344</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>GA49547</td>\n",
+       "      <td>Washington</td>\n",
+       "      <td>M</td>\n",
+       "      <td>High School or Below</td>\n",
+       "      <td>536307.65%</td>\n",
+       "      <td>36357.0</td>\n",
+       "      <td>68.0</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>17.269323</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4003</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4004</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4005</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4006</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4007</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>4008 rows × 11 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     Customer          ST GENDER             Education  \\\n",
+       "0     RB50392  Washington    NaN                Master   \n",
+       "1     QZ44356     Arizona      F              Bachelor   \n",
+       "2     AI49188      Nevada      F              Bachelor   \n",
+       "3     WW63253  California      M              Bachelor   \n",
+       "4     GA49547  Washington      M  High School or Below   \n",
+       "...       ...         ...    ...                   ...   \n",
+       "4003      NaN         NaN    NaN                   NaN   \n",
+       "4004      NaN         NaN    NaN                   NaN   \n",
+       "4005      NaN         NaN    NaN                   NaN   \n",
+       "4006      NaN         NaN    NaN                   NaN   \n",
+       "4007      NaN         NaN    NaN                   NaN   \n",
+       "\n",
+       "     Customer Lifetime Value   Income  Monthly Premium Auto  \\\n",
+       "0                        NaN      0.0                1000.0   \n",
+       "1                 697953.59%      0.0                  94.0   \n",
+       "2                1288743.17%  48767.0                 108.0   \n",
+       "3                 764586.18%      0.0                 106.0   \n",
+       "4                 536307.65%  36357.0                  68.0   \n",
+       "...                      ...      ...                   ...   \n",
+       "4003                     NaN      NaN                   NaN   \n",
+       "4004                     NaN      NaN                   NaN   \n",
+       "4005                     NaN      NaN                   NaN   \n",
+       "4006                     NaN      NaN                   NaN   \n",
+       "4007                     NaN      NaN                   NaN   \n",
+       "\n",
+       "     Number of Open Complaints     Policy Type  Vehicle Class  \\\n",
+       "0                       1/0/00   Personal Auto  Four-Door Car   \n",
+       "1                       1/0/00   Personal Auto  Four-Door Car   \n",
+       "2                       1/0/00   Personal Auto   Two-Door Car   \n",
+       "3                       1/0/00  Corporate Auto            SUV   \n",
+       "4                       1/0/00   Personal Auto  Four-Door Car   \n",
+       "...                        ...             ...            ...   \n",
+       "4003                       NaN             NaN            NaN   \n",
+       "4004                       NaN             NaN            NaN   \n",
+       "4005                       NaN             NaN            NaN   \n",
+       "4006                       NaN             NaN            NaN   \n",
+       "4007                       NaN             NaN            NaN   \n",
+       "\n",
+       "      Total Claim Amount  \n",
+       "0               2.704934  \n",
+       "1            1131.464935  \n",
+       "2             566.472247  \n",
+       "3             529.881344  \n",
+       "4              17.269323  \n",
+       "...                  ...  \n",
+       "4003                 NaN  \n",
+       "4004                 NaN  \n",
+       "4005                 NaN  \n",
+       "4006                 NaN  \n",
+       "4007                 NaN  \n",
+       "\n",
+       "[4008 rows x 11 columns]"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df1 = pd.read_csvdf = pd.read_csv (\"https://raw.githubusercontent.com/data-bootcamp-v4/data/main/file1.csv\")\n",
+    "df1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "73e4dbf2-e2f6-48a5-9547-91866405aa32",
+   "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</th>\n",
+       "      <th>ST</th>\n",
+       "      <th>GENDER</th>\n",
+       "      <th>Education</th>\n",
+       "      <th>Customer Lifetime Value</th>\n",
+       "      <th>Income</th>\n",
+       "      <th>Monthly Premium Auto</th>\n",
+       "      <th>Number of Open Complaints</th>\n",
+       "      <th>Total Claim Amount</th>\n",
+       "      <th>Policy Type</th>\n",
+       "      <th>Vehicle Class</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>GS98873</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>F</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>323912.47%</td>\n",
+       "      <td>16061</td>\n",
+       "      <td>88</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>633.600000</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>CW49887</td>\n",
+       "      <td>California</td>\n",
+       "      <td>F</td>\n",
+       "      <td>Master</td>\n",
+       "      <td>462680.11%</td>\n",
+       "      <td>79487</td>\n",
+       "      <td>114</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>547.200000</td>\n",
+       "      <td>Special Auto</td>\n",
+       "      <td>SUV</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>MY31220</td>\n",
+       "      <td>California</td>\n",
+       "      <td>F</td>\n",
+       "      <td>College</td>\n",
+       "      <td>899704.02%</td>\n",
+       "      <td>54230</td>\n",
+       "      <td>112</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>537.600000</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>UH35128</td>\n",
+       "      <td>Oregon</td>\n",
+       "      <td>F</td>\n",
+       "      <td>College</td>\n",
+       "      <td>2580706.30%</td>\n",
+       "      <td>71210</td>\n",
+       "      <td>214</td>\n",
+       "      <td>1/1/00</td>\n",
+       "      <td>1027.200000</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Luxury Car</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>WH52799</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>F</td>\n",
+       "      <td>College</td>\n",
+       "      <td>380812.21%</td>\n",
+       "      <td>94903</td>\n",
+       "      <td>94</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>451.200000</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>991</th>\n",
+       "      <td>HV85198</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>M</td>\n",
+       "      <td>Master</td>\n",
+       "      <td>847141.75%</td>\n",
+       "      <td>63513</td>\n",
+       "      <td>70</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>185.667213</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>992</th>\n",
+       "      <td>BS91566</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>F</td>\n",
+       "      <td>College</td>\n",
+       "      <td>543121.91%</td>\n",
+       "      <td>58161</td>\n",
+       "      <td>68</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>140.747286</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>993</th>\n",
+       "      <td>IL40123</td>\n",
+       "      <td>Nevada</td>\n",
+       "      <td>F</td>\n",
+       "      <td>College</td>\n",
+       "      <td>568964.41%</td>\n",
+       "      <td>83640</td>\n",
+       "      <td>70</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>471.050488</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>994</th>\n",
+       "      <td>MY32149</td>\n",
+       "      <td>California</td>\n",
+       "      <td>F</td>\n",
+       "      <td>Master</td>\n",
+       "      <td>368672.38%</td>\n",
+       "      <td>0</td>\n",
+       "      <td>96</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>28.460568</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>995</th>\n",
+       "      <td>SA91515</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>399258.39%</td>\n",
+       "      <td>0</td>\n",
+       "      <td>111</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>700.349052</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>SUV</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>996 rows × 11 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    Customer          ST GENDER Education Customer Lifetime Value  Income  \\\n",
+       "0    GS98873     Arizona      F  Bachelor              323912.47%   16061   \n",
+       "1    CW49887  California      F    Master              462680.11%   79487   \n",
+       "2    MY31220  California      F   College              899704.02%   54230   \n",
+       "3    UH35128      Oregon      F   College             2580706.30%   71210   \n",
+       "4    WH52799     Arizona      F   College              380812.21%   94903   \n",
+       "..       ...         ...    ...       ...                     ...     ...   \n",
+       "991  HV85198     Arizona      M    Master              847141.75%   63513   \n",
+       "992  BS91566     Arizona      F   College              543121.91%   58161   \n",
+       "993  IL40123      Nevada      F   College              568964.41%   83640   \n",
+       "994  MY32149  California      F    Master              368672.38%       0   \n",
+       "995  SA91515  California      M  Bachelor              399258.39%       0   \n",
+       "\n",
+       "     Monthly Premium Auto Number of Open Complaints  Total Claim Amount  \\\n",
+       "0                      88                    1/0/00          633.600000   \n",
+       "1                     114                    1/0/00          547.200000   \n",
+       "2                     112                    1/0/00          537.600000   \n",
+       "3                     214                    1/1/00         1027.200000   \n",
+       "4                      94                    1/0/00          451.200000   \n",
+       "..                    ...                       ...                 ...   \n",
+       "991                    70                    1/0/00          185.667213   \n",
+       "992                    68                    1/0/00          140.747286   \n",
+       "993                    70                    1/0/00          471.050488   \n",
+       "994                    96                    1/0/00           28.460568   \n",
+       "995                   111                    1/0/00          700.349052   \n",
+       "\n",
+       "        Policy Type  Vehicle Class  \n",
+       "0     Personal Auto  Four-Door Car  \n",
+       "1      Special Auto            SUV  \n",
+       "2     Personal Auto   Two-Door Car  \n",
+       "3     Personal Auto     Luxury Car  \n",
+       "4    Corporate Auto   Two-Door Car  \n",
+       "..              ...            ...  \n",
+       "991   Personal Auto  Four-Door Car  \n",
+       "992  Corporate Auto  Four-Door Car  \n",
+       "993  Corporate Auto   Two-Door Car  \n",
+       "994   Personal Auto   Two-Door Car  \n",
+       "995   Personal Auto            SUV  \n",
+       "\n",
+       "[996 rows x 11 columns]"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df2 = pd.read_csvdf = pd.read_csv (\"https://raw.githubusercontent.com/data-bootcamp-v4/data/main/file2.csv\")\n",
+    "df2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "f228e79e-03b1-4992-8a88-4c84ca653af1",
+   "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",
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+       "\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</th>\n",
+       "      <th>State</th>\n",
+       "      <th>Customer Lifetime Value</th>\n",
+       "      <th>Education</th>\n",
+       "      <th>Gender</th>\n",
+       "      <th>Income</th>\n",
+       "      <th>Monthly Premium Auto</th>\n",
+       "      <th>Number of Open Complaints</th>\n",
+       "      <th>Policy Type</th>\n",
+       "      <th>Total Claim Amount</th>\n",
+       "      <th>Vehicle Class</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>SA25987</td>\n",
+       "      <td>Washington</td>\n",
+       "      <td>3479.137523</td>\n",
+       "      <td>High School or Below</td>\n",
+       "      <td>M</td>\n",
+       "      <td>0</td>\n",
+       "      <td>104</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>499.200000</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>TB86706</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>2502.637401</td>\n",
+       "      <td>Master</td>\n",
+       "      <td>M</td>\n",
+       "      <td>0</td>\n",
+       "      <td>66</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>3.468912</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>ZL73902</td>\n",
+       "      <td>Nevada</td>\n",
+       "      <td>3265.156348</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>F</td>\n",
+       "      <td>25820</td>\n",
+       "      <td>82</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>393.600000</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>KX23516</td>\n",
+       "      <td>California</td>\n",
+       "      <td>4455.843406</td>\n",
+       "      <td>High School or Below</td>\n",
+       "      <td>F</td>\n",
+       "      <td>0</td>\n",
+       "      <td>121</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>699.615192</td>\n",
+       "      <td>SUV</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>FN77294</td>\n",
+       "      <td>California</td>\n",
+       "      <td>7704.958480</td>\n",
+       "      <td>High School or Below</td>\n",
+       "      <td>M</td>\n",
+       "      <td>30366</td>\n",
+       "      <td>101</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>484.800000</td>\n",
+       "      <td>SUV</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  Customer       State  Customer Lifetime Value             Education Gender  \\\n",
+       "0  SA25987  Washington              3479.137523  High School or Below      M   \n",
+       "1  TB86706     Arizona              2502.637401                Master      M   \n",
+       "2  ZL73902      Nevada              3265.156348              Bachelor      F   \n",
+       "3  KX23516  California              4455.843406  High School or Below      F   \n",
+       "4  FN77294  California              7704.958480  High School or Below      M   \n",
+       "\n",
+       "   Income  Monthly Premium Auto  Number of Open Complaints    Policy Type  \\\n",
+       "0       0                   104                          0  Personal Auto   \n",
+       "1       0                    66                          0  Personal Auto   \n",
+       "2   25820                    82                          0  Personal Auto   \n",
+       "3       0                   121                          0  Personal Auto   \n",
+       "4   30366                   101                          2  Personal Auto   \n",
+       "\n",
+       "   Total Claim Amount  Vehicle Class  \n",
+       "0          499.200000   Two-Door Car  \n",
+       "1            3.468912   Two-Door Car  \n",
+       "2          393.600000  Four-Door Car  \n",
+       "3          699.615192            SUV  \n",
+       "4          484.800000            SUV  "
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df3 = pd.read_csvdf = pd.read_csv (\"https://raw.githubusercontent.com/data-bootcamp-v4/data/main/file3.csv\")\n",
+    "df3.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "6a21ea05-7b32-48c5-9b7a-668eb0bf358e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "\n",
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+       "\n",
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Customer</th>\n",
+       "      <th>ST</th>\n",
+       "      <th>GENDER</th>\n",
+       "      <th>Education</th>\n",
+       "      <th>Customer Lifetime Value</th>\n",
+       "      <th>Income</th>\n",
+       "      <th>Monthly Premium Auto</th>\n",
+       "      <th>Number of Open Complaints</th>\n",
+       "      <th>Policy Type</th>\n",
+       "      <th>Vehicle Class</th>\n",
+       "      <th>Total Claim Amount</th>\n",
+       "      <th>State</th>\n",
+       "      <th>Gender</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>RB50392</td>\n",
+       "      <td>Washington</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Master</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1000.0</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
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+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>QZ44356</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>F</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>697953.59%</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>94.0</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>1131.464935</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>AI49188</td>\n",
+       "      <td>Nevada</td>\n",
+       "      <td>F</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>1288743.17%</td>\n",
+       "      <td>48767.0</td>\n",
+       "      <td>108.0</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>566.472247</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>WW63253</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>764586.18%</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>106.0</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>SUV</td>\n",
+       "      <td>529.881344</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>GA49547</td>\n",
+       "      <td>Washington</td>\n",
+       "      <td>M</td>\n",
+       "      <td>High School or Below</td>\n",
+       "      <td>536307.65%</td>\n",
+       "      <td>36357.0</td>\n",
+       "      <td>68.0</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>17.269323</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
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+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7065</th>\n",
+       "      <td>LA72316</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>23405.98798</td>\n",
+       "      <td>71941.0</td>\n",
+       "      <td>73.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>198.234764</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7066</th>\n",
+       "      <td>PK87824</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>College</td>\n",
+       "      <td>3096.511217</td>\n",
+       "      <td>21604.0</td>\n",
+       "      <td>79.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>379.200000</td>\n",
+       "      <td>California</td>\n",
+       "      <td>F</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7067</th>\n",
+       "      <td>TD14365</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>8163.890428</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>85.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>790.784983</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7068</th>\n",
+       "      <td>UP19263</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>College</td>\n",
+       "      <td>7524.442436</td>\n",
+       "      <td>21941.0</td>\n",
+       "      <td>96.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>691.200000</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7069</th>\n",
+       "      <td>Y167826</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>College</td>\n",
+       "      <td>2611.836866</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>77.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>369.600000</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>12074 rows × 13 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     Customer          ST GENDER             Education  \\\n",
+       "0     RB50392  Washington    NaN                Master   \n",
+       "1     QZ44356     Arizona      F              Bachelor   \n",
+       "2     AI49188      Nevada      F              Bachelor   \n",
+       "3     WW63253  California      M              Bachelor   \n",
+       "4     GA49547  Washington      M  High School or Below   \n",
+       "...       ...         ...    ...                   ...   \n",
+       "7065  LA72316         NaN    NaN              Bachelor   \n",
+       "7066  PK87824         NaN    NaN               College   \n",
+       "7067  TD14365         NaN    NaN              Bachelor   \n",
+       "7068  UP19263         NaN    NaN               College   \n",
+       "7069  Y167826         NaN    NaN               College   \n",
+       "\n",
+       "     Customer Lifetime Value   Income  Monthly Premium Auto  \\\n",
+       "0                        NaN      0.0                1000.0   \n",
+       "1                 697953.59%      0.0                  94.0   \n",
+       "2                1288743.17%  48767.0                 108.0   \n",
+       "3                 764586.18%      0.0                 106.0   \n",
+       "4                 536307.65%  36357.0                  68.0   \n",
+       "...                      ...      ...                   ...   \n",
+       "7065             23405.98798  71941.0                  73.0   \n",
+       "7066             3096.511217  21604.0                  79.0   \n",
+       "7067             8163.890428      0.0                  85.0   \n",
+       "7068             7524.442436  21941.0                  96.0   \n",
+       "7069             2611.836866      0.0                  77.0   \n",
+       "\n",
+       "     Number of Open Complaints     Policy Type  Vehicle Class  \\\n",
+       "0                       1/0/00   Personal Auto  Four-Door Car   \n",
+       "1                       1/0/00   Personal Auto  Four-Door Car   \n",
+       "2                       1/0/00   Personal Auto   Two-Door Car   \n",
+       "3                       1/0/00  Corporate Auto            SUV   \n",
+       "4                       1/0/00   Personal Auto  Four-Door Car   \n",
+       "...                        ...             ...            ...   \n",
+       "7065                         0   Personal Auto  Four-Door Car   \n",
+       "7066                         0  Corporate Auto  Four-Door Car   \n",
+       "7067                         3  Corporate Auto  Four-Door Car   \n",
+       "7068                         0   Personal Auto  Four-Door Car   \n",
+       "7069                         0  Corporate Auto   Two-Door Car   \n",
+       "\n",
+       "      Total Claim Amount       State Gender  \n",
+       "0               2.704934         NaN    NaN  \n",
+       "1            1131.464935         NaN    NaN  \n",
+       "2             566.472247         NaN    NaN  \n",
+       "3             529.881344         NaN    NaN  \n",
+       "4              17.269323         NaN    NaN  \n",
+       "...                  ...         ...    ...  \n",
+       "7065          198.234764  California      M  \n",
+       "7066          379.200000  California      F  \n",
+       "7067          790.784983  California      M  \n",
+       "7068          691.200000  California      M  \n",
+       "7069          369.600000  California      M  \n",
+       "\n",
+       "[12074 rows x 13 columns]"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pd.concat([df1, df2, df3], axis=0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "b3d034c6-25b9-4d57-9c11-273e4c4d2200",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "      <th>0</th>\n",
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+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4003</th>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4004</th>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4005</th>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4006</th>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4007</th>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>4008 rows × 11 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      Customer     ST  GENDER  Education  Customer Lifetime Value  Income  \\\n",
+       "0        False  False    True      False                     True   False   \n",
+       "1        False  False   False      False                    False   False   \n",
+       "2        False  False   False      False                    False   False   \n",
+       "3        False  False   False      False                    False   False   \n",
+       "4        False  False   False      False                    False   False   \n",
+       "...        ...    ...     ...        ...                      ...     ...   \n",
+       "4003      True   True    True       True                     True    True   \n",
+       "4004      True   True    True       True                     True    True   \n",
+       "4005      True   True    True       True                     True    True   \n",
+       "4006      True   True    True       True                     True    True   \n",
+       "4007      True   True    True       True                     True    True   \n",
+       "\n",
+       "      Monthly Premium Auto  Number of Open Complaints  Policy Type  \\\n",
+       "0                    False                      False        False   \n",
+       "1                    False                      False        False   \n",
+       "2                    False                      False        False   \n",
+       "3                    False                      False        False   \n",
+       "4                    False                      False        False   \n",
+       "...                    ...                        ...          ...   \n",
+       "4003                  True                       True         True   \n",
+       "4004                  True                       True         True   \n",
+       "4005                  True                       True         True   \n",
+       "4006                  True                       True         True   \n",
+       "4007                  True                       True         True   \n",
+       "\n",
+       "      Vehicle Class  Total Claim Amount  \n",
+       "0             False               False  \n",
+       "1             False               False  \n",
+       "2             False               False  \n",
+       "3             False               False  \n",
+       "4             False               False  \n",
+       "...             ...                 ...  \n",
+       "4003           True                True  \n",
+       "4004           True                True  \n",
+       "4005           True                True  \n",
+       "4006           True                True  \n",
+       "4007           True                True  \n",
+       "\n",
+       "[4008 rows x 11 columns]"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    " df.isnull()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "3dcbea52-68d6-424e-a482-0b71f1b2f6bb",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Customer                     True\n",
+       "ST                           True\n",
+       "GENDER                       True\n",
+       "Education                    True\n",
+       "Customer Lifetime Value      True\n",
+       "Income                       True\n",
+       "Monthly Premium Auto         True\n",
+       "Number of Open Complaints    True\n",
+       "Policy Type                  True\n",
+       "Vehicle Class                True\n",
+       "Total Claim Amount           True\n",
+       "dtype: bool"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.isna().any()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "5fb9208d-6e20-4206-9129-0e8c087cd44e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Customer                     2937\n",
+       "ST                           2937\n",
+       "GENDER                       3054\n",
+       "Education                    2937\n",
+       "Customer Lifetime Value      2940\n",
+       "Income                       2937\n",
+       "Monthly Premium Auto         2937\n",
+       "Number of Open Complaints    2937\n",
+       "Policy Type                  2937\n",
+       "Vehicle Class                2937\n",
+       "Total Claim Amount           2937\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.isna().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "a378d21d-5ef8-49d7-aa73-3658f763369b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0        2\n",
+       "1        0\n",
+       "2        0\n",
+       "3        0\n",
+       "4        0\n",
+       "        ..\n",
+       "4003    11\n",
+       "4004    11\n",
+       "4005    11\n",
+       "4006    11\n",
+       "4007    11\n",
+       "Length: 4008, dtype: int64"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.isna().sum(axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "4ed75f4a-37dd-483f-a89b-7fdd18de6342",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(4008, 11)"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "33836ac6-d833-406d-84ac-f2a3f635e0e1",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Customer                      object\n",
+       "ST                            object\n",
+       "GENDER                        object\n",
+       "Education                     object\n",
+       "Customer Lifetime Value       object\n",
+       "Income                       float64\n",
+       "Monthly Premium Auto         float64\n",
+       "Number of Open Complaints     object\n",
+       "Policy Type                   object\n",
+       "Vehicle Class                 object\n",
+       "Total Claim Amount           float64\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.dtypes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "d0862e10-6069-42a5-acf4-cabe309b1dba",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<bound method NDFrame.head of 0           0.000000\n",
+       "1           0.000000\n",
+       "2       48767.000000\n",
+       "3           0.000000\n",
+       "4       36357.000000\n",
+       "            ...     \n",
+       "4003    39295.701214\n",
+       "4004    39295.701214\n",
+       "4005    39295.701214\n",
+       "4006    39295.701214\n",
+       "4007    39295.701214\n",
+       "Name: Income, Length: 4008, dtype: float64>"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.Income.fillna(df.Income.mean()).head"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "id": "7ce0bba0-98f4-49ec-9fc0-f05fb819e0e9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0       1000.00000\n",
+       "1         94.00000\n",
+       "2        108.00000\n",
+       "3        106.00000\n",
+       "4         68.00000\n",
+       "           ...    \n",
+       "4003     193.23436\n",
+       "4004     193.23436\n",
+       "4005     193.23436\n",
+       "4006     193.23436\n",
+       "4007     193.23436\n",
+       "Name: Monthly Premium Auto, Length: 4008, dtype: float64"
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df[\"Monthly Premium Auto\"].fillna(df[\"Monthly Premium Auto\"].mean())\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "id": "784117be-a0f0-47d1-855e-5b3d9d77ad8c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0          2.704934\n",
+       "1       1131.464935\n",
+       "2        566.472247\n",
+       "3        529.881344\n",
+       "4         17.269323\n",
+       "           ...     \n",
+       "4003     404.986909\n",
+       "4004     404.986909\n",
+       "4005     404.986909\n",
+       "4006     404.986909\n",
+       "4007     404.986909\n",
+       "Name: Total Claim Amount, Length: 4008, dtype: float64"
+      ]
+     },
+     "execution_count": 45,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df[\"Total Claim Amount\"].fillna(df[\"Total Claim Amount\"].mean())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "id": "64dd0640-9a2a-4624-8d29-e36c7bca28a4",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The history saving thread hit an unexpected error (OperationalError('attempt to write a readonly database')).History will not be written to the database.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "np.int64(2936)"
+      ]
+     },
+     "execution_count": 46,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.duplicated().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "id": "a25c5d24-6015-4446-b1fe-a8f9d5b7703f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "np.True_"
+      ]
+     },
+     "execution_count": 47,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.duplicated().any()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "id": "1643bf84-1976-4340-a611-83681a7be8c5",
+   "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code goes here"
+    "df.drop_duplicates(inplace=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "id": "c0ba21f0-8d25-4798-92b5-de620aa4129a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<bound method NDFrame.head of      Customer          ST GENDER             Education  \\\n",
+       "0     RB50392  Washington    NaN                Master   \n",
+       "1     QZ44356     Arizona      F              Bachelor   \n",
+       "2     AI49188      Nevada      F              Bachelor   \n",
+       "3     WW63253  California      M              Bachelor   \n",
+       "4     GA49547  Washington      M  High School or Below   \n",
+       "...       ...         ...    ...                   ...   \n",
+       "1067  VJ51327        Cali      F  High School or Below   \n",
+       "1068  GS98873     Arizona      F              Bachelor   \n",
+       "1069  CW49887  California      F                Master   \n",
+       "1070  MY31220  California      F               College   \n",
+       "1071      NaN         NaN    NaN                   NaN   \n",
+       "\n",
+       "     Customer Lifetime Value   Income  Monthly Premium Auto  \\\n",
+       "0                        NaN      0.0            1000.00000   \n",
+       "1                 697953.59%      0.0              94.00000   \n",
+       "2                1288743.17%  48767.0             108.00000   \n",
+       "3                 764586.18%      0.0             106.00000   \n",
+       "4                 536307.65%  36357.0              68.00000   \n",
+       "...                      ...      ...                   ...   \n",
+       "1067             2031499.76%  63209.0             102.00000   \n",
+       "1068              323912.47%  16061.0              88.00000   \n",
+       "1069              462680.11%  79487.0             114.00000   \n",
+       "1070              899704.02%  54230.0             112.00000   \n",
+       "1071                     NaN      NaN             193.23436   \n",
+       "\n",
+       "     Number of Open Complaints     Policy Type  Vehicle Class  \\\n",
+       "0                       1/0/00   Personal Auto  Four-Door Car   \n",
+       "1                       1/0/00   Personal Auto  Four-Door Car   \n",
+       "2                       1/0/00   Personal Auto   Two-Door Car   \n",
+       "3                       1/0/00  Corporate Auto            SUV   \n",
+       "4                       1/0/00   Personal Auto  Four-Door Car   \n",
+       "...                        ...             ...            ...   \n",
+       "1067                    1/2/00   Personal Auto            SUV   \n",
+       "1068                    1/0/00   Personal Auto  Four-Door Car   \n",
+       "1069                    1/0/00    Special Auto            SUV   \n",
+       "1070                    1/0/00   Personal Auto   Two-Door Car   \n",
+       "1071                       NaN             NaN            NaN   \n",
+       "\n",
+       "      Total Claim Amount  \n",
+       "0               2.704934  \n",
+       "1            1131.464935  \n",
+       "2             566.472247  \n",
+       "3             529.881344  \n",
+       "4              17.269323  \n",
+       "...                  ...  \n",
+       "1067          207.320041  \n",
+       "1068          633.600000  \n",
+       "1069          547.200000  \n",
+       "1070          537.600000  \n",
+       "1071                 NaN  \n",
+       "\n",
+       "[1072 rows x 11 columns]>"
+      ]
+     },
+     "execution_count": 49,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.head"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "id": "6f935055-dc6e-423e-98cb-4a4111324f54",
+   "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</th>\n",
+       "      <th>ST</th>\n",
+       "      <th>GENDER</th>\n",
+       "      <th>Education</th>\n",
+       "      <th>Customer Lifetime Value</th>\n",
+       "      <th>Income</th>\n",
+       "      <th>Monthly Premium Auto</th>\n",
+       "      <th>Number of Open Complaints</th>\n",
+       "      <th>Policy Type</th>\n",
+       "      <th>Vehicle Class</th>\n",
+       "      <th>Total Claim Amount</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1067</th>\n",
+       "      <td>VJ51327</td>\n",
+       "      <td>Cali</td>\n",
+       "      <td>F</td>\n",
+       "      <td>High School or Below</td>\n",
+       "      <td>2031499.76%</td>\n",
+       "      <td>63209.0</td>\n",
+       "      <td>102.00000</td>\n",
+       "      <td>1/2/00</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>SUV</td>\n",
+       "      <td>207.320041</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1068</th>\n",
+       "      <td>GS98873</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>F</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>323912.47%</td>\n",
+       "      <td>16061.0</td>\n",
+       "      <td>88.00000</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>633.600000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1069</th>\n",
+       "      <td>CW49887</td>\n",
+       "      <td>California</td>\n",
+       "      <td>F</td>\n",
+       "      <td>Master</td>\n",
+       "      <td>462680.11%</td>\n",
+       "      <td>79487.0</td>\n",
+       "      <td>114.00000</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>Special Auto</td>\n",
+       "      <td>SUV</td>\n",
+       "      <td>547.200000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1070</th>\n",
+       "      <td>MY31220</td>\n",
+       "      <td>California</td>\n",
+       "      <td>F</td>\n",
+       "      <td>College</td>\n",
+       "      <td>899704.02%</td>\n",
+       "      <td>54230.0</td>\n",
+       "      <td>112.00000</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>537.600000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1071</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>193.23436</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     Customer          ST GENDER             Education  \\\n",
+       "1067  VJ51327        Cali      F  High School or Below   \n",
+       "1068  GS98873     Arizona      F              Bachelor   \n",
+       "1069  CW49887  California      F                Master   \n",
+       "1070  MY31220  California      F               College   \n",
+       "1071      NaN         NaN    NaN                   NaN   \n",
+       "\n",
+       "     Customer Lifetime Value   Income  Monthly Premium Auto  \\\n",
+       "1067             2031499.76%  63209.0             102.00000   \n",
+       "1068              323912.47%  16061.0              88.00000   \n",
+       "1069              462680.11%  79487.0             114.00000   \n",
+       "1070              899704.02%  54230.0             112.00000   \n",
+       "1071                     NaN      NaN             193.23436   \n",
+       "\n",
+       "     Number of Open Complaints    Policy Type  Vehicle Class  \\\n",
+       "1067                    1/2/00  Personal Auto            SUV   \n",
+       "1068                    1/0/00  Personal Auto  Four-Door Car   \n",
+       "1069                    1/0/00   Special Auto            SUV   \n",
+       "1070                    1/0/00  Personal Auto   Two-Door Car   \n",
+       "1071                       NaN            NaN            NaN   \n",
+       "\n",
+       "      Total Claim Amount  \n",
+       "1067          207.320041  \n",
+       "1068          633.600000  \n",
+       "1069          547.200000  \n",
+       "1070          537.600000  \n",
+       "1071                 NaN  "
+      ]
+     },
+     "execution_count": 55,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_without_duplicates = df.copy()\n",
+    "df_without_duplicates = df.drop_duplicates()\n",
+    "df_without_duplicates.tail()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "id": "6faf81e9-0413-4910-8f61-6f122ca78880",
+   "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>index</th>\n",
+       "      <th>Customer</th>\n",
+       "      <th>ST</th>\n",
+       "      <th>GENDER</th>\n",
+       "      <th>Education</th>\n",
+       "      <th>Customer Lifetime Value</th>\n",
+       "      <th>Income</th>\n",
+       "      <th>Monthly Premium Auto</th>\n",
+       "      <th>Number of Open Complaints</th>\n",
+       "      <th>Policy Type</th>\n",
+       "      <th>Vehicle Class</th>\n",
+       "      <th>Total Claim Amount</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>RB50392</td>\n",
+       "      <td>Washington</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Master</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1000.00000</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>2.704934</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>QZ44356</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>F</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>697953.59%</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>94.00000</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>1131.464935</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2</td>\n",
+       "      <td>AI49188</td>\n",
+       "      <td>Nevada</td>\n",
+       "      <td>F</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>1288743.17%</td>\n",
+       "      <td>48767.0</td>\n",
+       "      <td>108.00000</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>566.472247</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>3</td>\n",
+       "      <td>WW63253</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>764586.18%</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>106.00000</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>SUV</td>\n",
+       "      <td>529.881344</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4</td>\n",
+       "      <td>GA49547</td>\n",
+       "      <td>Washington</td>\n",
+       "      <td>M</td>\n",
+       "      <td>High School or Below</td>\n",
+       "      <td>536307.65%</td>\n",
+       "      <td>36357.0</td>\n",
+       "      <td>68.00000</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>17.269323</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1067</th>\n",
+       "      <td>1067</td>\n",
+       "      <td>VJ51327</td>\n",
+       "      <td>Cali</td>\n",
+       "      <td>F</td>\n",
+       "      <td>High School or Below</td>\n",
+       "      <td>2031499.76%</td>\n",
+       "      <td>63209.0</td>\n",
+       "      <td>102.00000</td>\n",
+       "      <td>1/2/00</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>SUV</td>\n",
+       "      <td>207.320041</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1068</th>\n",
+       "      <td>1068</td>\n",
+       "      <td>GS98873</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>F</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>323912.47%</td>\n",
+       "      <td>16061.0</td>\n",
+       "      <td>88.00000</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>633.600000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1069</th>\n",
+       "      <td>1069</td>\n",
+       "      <td>CW49887</td>\n",
+       "      <td>California</td>\n",
+       "      <td>F</td>\n",
+       "      <td>Master</td>\n",
+       "      <td>462680.11%</td>\n",
+       "      <td>79487.0</td>\n",
+       "      <td>114.00000</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>Special Auto</td>\n",
+       "      <td>SUV</td>\n",
+       "      <td>547.200000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1070</th>\n",
+       "      <td>1070</td>\n",
+       "      <td>MY31220</td>\n",
+       "      <td>California</td>\n",
+       "      <td>F</td>\n",
+       "      <td>College</td>\n",
+       "      <td>899704.02%</td>\n",
+       "      <td>54230.0</td>\n",
+       "      <td>112.00000</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>537.600000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1071</th>\n",
+       "      <td>1071</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>193.23436</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1072 rows × 12 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      index Customer          ST GENDER             Education  \\\n",
+       "0         0  RB50392  Washington    NaN                Master   \n",
+       "1         1  QZ44356     Arizona      F              Bachelor   \n",
+       "2         2  AI49188      Nevada      F              Bachelor   \n",
+       "3         3  WW63253  California      M              Bachelor   \n",
+       "4         4  GA49547  Washington      M  High School or Below   \n",
+       "...     ...      ...         ...    ...                   ...   \n",
+       "1067   1067  VJ51327        Cali      F  High School or Below   \n",
+       "1068   1068  GS98873     Arizona      F              Bachelor   \n",
+       "1069   1069  CW49887  California      F                Master   \n",
+       "1070   1070  MY31220  California      F               College   \n",
+       "1071   1071      NaN         NaN    NaN                   NaN   \n",
+       "\n",
+       "     Customer Lifetime Value   Income  Monthly Premium Auto  \\\n",
+       "0                        NaN      0.0            1000.00000   \n",
+       "1                 697953.59%      0.0              94.00000   \n",
+       "2                1288743.17%  48767.0             108.00000   \n",
+       "3                 764586.18%      0.0             106.00000   \n",
+       "4                 536307.65%  36357.0              68.00000   \n",
+       "...                      ...      ...                   ...   \n",
+       "1067             2031499.76%  63209.0             102.00000   \n",
+       "1068              323912.47%  16061.0              88.00000   \n",
+       "1069              462680.11%  79487.0             114.00000   \n",
+       "1070              899704.02%  54230.0             112.00000   \n",
+       "1071                     NaN      NaN             193.23436   \n",
+       "\n",
+       "     Number of Open Complaints     Policy Type  Vehicle Class  \\\n",
+       "0                       1/0/00   Personal Auto  Four-Door Car   \n",
+       "1                       1/0/00   Personal Auto  Four-Door Car   \n",
+       "2                       1/0/00   Personal Auto   Two-Door Car   \n",
+       "3                       1/0/00  Corporate Auto            SUV   \n",
+       "4                       1/0/00   Personal Auto  Four-Door Car   \n",
+       "...                        ...             ...            ...   \n",
+       "1067                    1/2/00   Personal Auto            SUV   \n",
+       "1068                    1/0/00   Personal Auto  Four-Door Car   \n",
+       "1069                    1/0/00    Special Auto            SUV   \n",
+       "1070                    1/0/00   Personal Auto   Two-Door Car   \n",
+       "1071                       NaN             NaN            NaN   \n",
+       "\n",
+       "      Total Claim Amount  \n",
+       "0               2.704934  \n",
+       "1            1131.464935  \n",
+       "2             566.472247  \n",
+       "3             529.881344  \n",
+       "4              17.269323  \n",
+       "...                  ...  \n",
+       "1067          207.320041  \n",
+       "1068          633.600000  \n",
+       "1069          547.200000  \n",
+       "1070          537.600000  \n",
+       "1071                 NaN  \n",
+       "\n",
+       "[1072 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 57,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_without_duplicates.reset_index()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "id": "ca275cff-9981-4a7c-85da-d611cf1fdaf0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['Customer', 'ST', 'GENDER', 'Education', 'Customer Lifetime Value',\n",
+       "       'Income', 'Monthly Premium Auto', 'Number of Open Complaints',\n",
+       "       'Policy Type', 'Vehicle Class', 'Total Claim Amount'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 58,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "id": "28a9788a-f36f-4da4-9820-280031242b05",
+   "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</th>\n",
+       "      <th>State</th>\n",
+       "      <th>GENDER</th>\n",
+       "      <th>Education</th>\n",
+       "      <th>Customer Lifetime Value</th>\n",
+       "      <th>Income</th>\n",
+       "      <th>Monthly Premium Auto</th>\n",
+       "      <th>Number of Open Complaints</th>\n",
+       "      <th>Policy Type</th>\n",
+       "      <th>Vehicle Class</th>\n",
+       "      <th>Total Claim Amount</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>RB50392</td>\n",
+       "      <td>Washington</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Master</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1000.00000</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>2.704934</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>QZ44356</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>F</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>697953.59%</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>94.00000</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>1131.464935</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>AI49188</td>\n",
+       "      <td>Nevada</td>\n",
+       "      <td>F</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>1288743.17%</td>\n",
+       "      <td>48767.0</td>\n",
+       "      <td>108.00000</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>566.472247</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>WW63253</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>764586.18%</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>106.00000</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>SUV</td>\n",
+       "      <td>529.881344</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>GA49547</td>\n",
+       "      <td>Washington</td>\n",
+       "      <td>M</td>\n",
+       "      <td>High School or Below</td>\n",
+       "      <td>536307.65%</td>\n",
+       "      <td>36357.0</td>\n",
+       "      <td>68.00000</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>17.269323</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1067</th>\n",
+       "      <td>VJ51327</td>\n",
+       "      <td>Cali</td>\n",
+       "      <td>F</td>\n",
+       "      <td>High School or Below</td>\n",
+       "      <td>2031499.76%</td>\n",
+       "      <td>63209.0</td>\n",
+       "      <td>102.00000</td>\n",
+       "      <td>1/2/00</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>SUV</td>\n",
+       "      <td>207.320041</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1068</th>\n",
+       "      <td>GS98873</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>F</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>323912.47%</td>\n",
+       "      <td>16061.0</td>\n",
+       "      <td>88.00000</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>633.600000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1069</th>\n",
+       "      <td>CW49887</td>\n",
+       "      <td>California</td>\n",
+       "      <td>F</td>\n",
+       "      <td>Master</td>\n",
+       "      <td>462680.11%</td>\n",
+       "      <td>79487.0</td>\n",
+       "      <td>114.00000</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>Special Auto</td>\n",
+       "      <td>SUV</td>\n",
+       "      <td>547.200000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1070</th>\n",
+       "      <td>MY31220</td>\n",
+       "      <td>California</td>\n",
+       "      <td>F</td>\n",
+       "      <td>College</td>\n",
+       "      <td>899704.02%</td>\n",
+       "      <td>54230.0</td>\n",
+       "      <td>112.00000</td>\n",
+       "      <td>1/0/00</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>537.600000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1071</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>193.23436</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1072 rows × 11 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     Customer       State GENDER             Education  \\\n",
+       "0     RB50392  Washington    NaN                Master   \n",
+       "1     QZ44356     Arizona      F              Bachelor   \n",
+       "2     AI49188      Nevada      F              Bachelor   \n",
+       "3     WW63253  California      M              Bachelor   \n",
+       "4     GA49547  Washington      M  High School or Below   \n",
+       "...       ...         ...    ...                   ...   \n",
+       "1067  VJ51327        Cali      F  High School or Below   \n",
+       "1068  GS98873     Arizona      F              Bachelor   \n",
+       "1069  CW49887  California      F                Master   \n",
+       "1070  MY31220  California      F               College   \n",
+       "1071      NaN         NaN    NaN                   NaN   \n",
+       "\n",
+       "     Customer Lifetime Value   Income  Monthly Premium Auto  \\\n",
+       "0                        NaN      0.0            1000.00000   \n",
+       "1                 697953.59%      0.0              94.00000   \n",
+       "2                1288743.17%  48767.0             108.00000   \n",
+       "3                 764586.18%      0.0             106.00000   \n",
+       "4                 536307.65%  36357.0              68.00000   \n",
+       "...                      ...      ...                   ...   \n",
+       "1067             2031499.76%  63209.0             102.00000   \n",
+       "1068              323912.47%  16061.0              88.00000   \n",
+       "1069              462680.11%  79487.0             114.00000   \n",
+       "1070              899704.02%  54230.0             112.00000   \n",
+       "1071                     NaN      NaN             193.23436   \n",
+       "\n",
+       "     Number of Open Complaints     Policy Type  Vehicle Class  \\\n",
+       "0                       1/0/00   Personal Auto  Four-Door Car   \n",
+       "1                       1/0/00   Personal Auto  Four-Door Car   \n",
+       "2                       1/0/00   Personal Auto   Two-Door Car   \n",
+       "3                       1/0/00  Corporate Auto            SUV   \n",
+       "4                       1/0/00   Personal Auto  Four-Door Car   \n",
+       "...                        ...             ...            ...   \n",
+       "1067                    1/2/00   Personal Auto            SUV   \n",
+       "1068                    1/0/00   Personal Auto  Four-Door Car   \n",
+       "1069                    1/0/00    Special Auto            SUV   \n",
+       "1070                    1/0/00   Personal Auto   Two-Door Car   \n",
+       "1071                       NaN             NaN            NaN   \n",
+       "\n",
+       "      Total Claim Amount  \n",
+       "0               2.704934  \n",
+       "1            1131.464935  \n",
+       "2             566.472247  \n",
+       "3             529.881344  \n",
+       "4              17.269323  \n",
+       "...                  ...  \n",
+       "1067          207.320041  \n",
+       "1068          633.600000  \n",
+       "1069          547.200000  \n",
+       "1070          537.600000  \n",
+       "1071                 NaN  \n",
+       "\n",
+       "[1072 rows x 11 columns]"
+      ]
+     },
+     "execution_count": 61,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.rename(columns={'ST': 'State'}, inplace=True)\n",
+    "df"
    ]
   },
   {
@@ -72,14 +2380,309 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 78,
    "id": "aa10d9b0-1c27-4d3f-a8e4-db6ab73bfd26",
    "metadata": {
     "id": "aa10d9b0-1c27-4d3f-a8e4-db6ab73bfd26"
    },
    "outputs": [],
    "source": [
-    "# Your code goes here"
+    "import pandas as pd\n",
+    "\n",
+    "df = pd.read_csv(\"https://raw.githubusercontent.com/data-bootcamp-v4/data/main/marketing_customer_analysis_clean.csv\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "id": "0bca1aba-6e82-4b83-950c-fd7e1c0b809b",
+   "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>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_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",
+       "      <th>month</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>2011-02-18</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>...</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>A</td>\n",
+       "      <td>2</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>2011-01-18</td>\n",
+       "      <td>Unemployed</td>\n",
+       "      <td>F</td>\n",
+       "      <td>...</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>A</td>\n",
+       "      <td>1</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>2011-02-10</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>...</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",
+       "      <td>2</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>2011-01-11</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>...</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",
+       "      <td>1</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>2011-01-17</td>\n",
+       "      <td>Medical Leave</td>\n",
+       "      <td>F</td>\n",
+       "      <td>...</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>A</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 27 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        2011-02-18         Employed      M  ...   \n",
+       "1     Basic   College        2011-01-18       Unemployed      F  ...   \n",
+       "2     Basic  Bachelor        2011-02-10         Employed      M  ...   \n",
+       "3  Extended   College        2011-01-11         Employed      M  ...   \n",
+       "4   Premium  Bachelor        2011-01-17    Medical Leave      F  ...   \n",
+       "\n",
+       "   number_of_policies     policy_type        policy  renew_offer_type  \\\n",
+       "0                   9  Corporate Auto  Corporate L3            Offer3   \n",
+       "1                   1   Personal Auto   Personal L3            Offer4   \n",
+       "2                   2   Personal Auto   Personal L3            Offer3   \n",
+       "3                   2  Corporate Auto  Corporate L3            Offer2   \n",
+       "4                   7   Personal Auto   Personal L2            Offer1   \n",
+       "\n",
+       "   sales_channel  total_claim_amount  vehicle_class  vehicle_size  \\\n",
+       "0          Agent          292.800000  Four-Door Car       Medsize   \n",
+       "1    Call Center          744.924331  Four-Door Car       Medsize   \n",
+       "2    Call Center          480.000000            SUV       Medsize   \n",
+       "3         Branch          484.013411  Four-Door Car       Medsize   \n",
+       "4         Branch          707.925645  Four-Door Car       Medsize   \n",
+       "\n",
+       "  vehicle_type month  \n",
+       "0            A     2  \n",
+       "1            A     1  \n",
+       "2            A     2  \n",
+       "3            A     1  \n",
+       "4            A     1  \n",
+       "\n",
+       "[5 rows x 27 columns]"
+      ]
+     },
+     "execution_count": 79,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "id": "49ba083a-9d4f-4025-aae0-d3493c5a09c6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "unnamed:_0                       False\n",
+       "customer                         False\n",
+       "state                            False\n",
+       "customer_lifetime_value          False\n",
+       "response                         False\n",
+       "coverage                         False\n",
+       "education                        False\n",
+       "effective_to_date                False\n",
+       "employmentstatus                 False\n",
+       "gender                           False\n",
+       "income                           False\n",
+       "location_code                    False\n",
+       "marital_status                   False\n",
+       "monthly_premium_auto             False\n",
+       "months_since_last_claim          False\n",
+       "months_since_policy_inception    False\n",
+       "number_of_open_complaints        False\n",
+       "number_of_policies               False\n",
+       "policy_type                      False\n",
+       "policy                           False\n",
+       "renew_offer_type                 False\n",
+       "sales_channel                    False\n",
+       "total_claim_amount               False\n",
+       "vehicle_class                    False\n",
+       "vehicle_size                     False\n",
+       "vehicle_type                     False\n",
+       "month                            False\n",
+       "dtype: bool"
+      ]
+     },
+     "execution_count": 80,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.isna().any()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "id": "42b0bcfc-497c-45d6-aca1-29b062e6e81c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "np.int64(0)"
+      ]
+     },
+     "execution_count": 81,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.duplicated().sum()"
    ]
   },
   {
@@ -93,6 +2696,116 @@
     "Round the total revenue to 2 decimal points.  Analyze the resulting table to draw insights."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 90,
+   "id": "baeaf18a-7a90-4a19-b178-2356071397e7",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "               total_claim_amount\n",
+      "sales_channel                    \n",
+      "Agent                1.810227e+06\n",
+      "Branch               1.301204e+06\n",
+      "Call Center          9.266008e+05\n",
+      "Web                  7.066000e+05\n"
+     ]
+    }
+   ],
+   "source": [
+    "summary = df.pivot_table(index=\"sales_channel\",values=\"total_claim_amount\",aggfunc=\"sum\")\n",
+    "print(summary)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 95,
+   "id": "517e43fb-79e1-434f-8595-399527737827",
+   "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>total_claim_amount</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>sales_channel</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Agent</th>\n",
+       "      <td>1810226.82</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Branch</th>\n",
+       "      <td>1301204.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Call Center</th>\n",
+       "      <td>926600.82</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Web</th>\n",
+       "      <td>706600.04</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "               total_claim_amount\n",
+       "sales_channel                    \n",
+       "Agent                  1810226.82\n",
+       "Branch                 1301204.00\n",
+       "Call Center             926600.82\n",
+       "Web                     706600.04"
+      ]
+     },
+     "execution_count": 95,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "summary = summary.round(2)\n",
+    "summary"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 96,
+   "id": "1735e50d-a4ae-4254-b7d3-891efee90957",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# The Agent channel generated the highest revenue (1.81M), almost 40% more than Branch.\n",
+    "#Web brought the lowest total revenue, only 706K, less than half of Agent.\n",
+    "#Strongest channels are Agent and Branch."
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "640993b2-a291-436c-a34d-a551144f8196",
@@ -103,6 +2816,49 @@
     "2. Create a pivot table that shows the average customer lifetime value per gender and education level. Analyze the resulting table to draw insights."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 111,
+   "id": "a9a2eb9a-7cbf-46fc-a364-655d6c65e416",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "gender                      F        M\n",
+      "education                             \n",
+      "Bachelor              7874.27  7703.60\n",
+      "College               7748.82  8052.46\n",
+      "Doctor                7328.51  7415.33\n",
+      "High School or Below  8675.22  8149.69\n",
+      "Master                8157.05  8168.83\n"
+     ]
+    }
+   ],
+   "source": [
+    "summary = df.pivot_table(\n",
+    "    index=\"education\",\n",
+    "    columns=\"gender\",\n",
+    "    values=\"customer_lifetime_value\",\n",
+    "    aggfunc=\"mean\"\n",
+    ").round(2)\n",
+    "\n",
+    "print(summary)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 104,
+   "id": "c2e404cb-aeeb-491f-888c-98b19d09d32b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Customers with Doctorate and Master’s degrees show the highest lifetime values, suggesting that higher education correlates with higher long-term revenue potential.\n",
+    "#Across all education levels, the gap between Female and Male customers is small.\n",
+    "#This means education level matters more than gender when predicting customer value."
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "32c7f2e5-3d90-43e5-be33-9781b6069198",
@@ -130,15 +2886,105 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "3a069e0b-b400-470e-904d-d17582191be4",
-   "metadata": {
-    "id": "3a069e0b-b400-470e-904d-d17582191be4"
-   },
-   "outputs": [],
+   "execution_count": 113,
+   "id": "be4a576f-e317-4c16-ba0c-0f4ff5132677",
+   "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>month</th>\n",
+       "      <th>policy_type</th>\n",
+       "      <th>number_of_complaints</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>443.434952</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>1727.605722</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1</td>\n",
+       "      <td>Special Auto</td>\n",
+       "      <td>87.074049</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>385.208135</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>1453.684441</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2</td>\n",
+       "      <td>Special Auto</td>\n",
+       "      <td>95.226817</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   month     policy_type  number_of_complaints\n",
+       "0      1  Corporate Auto            443.434952\n",
+       "1      1   Personal Auto           1727.605722\n",
+       "2      1    Special Auto             87.074049\n",
+       "3      2  Corporate Auto            385.208135\n",
+       "4      2   Personal Auto           1453.684441\n",
+       "5      2    Special Auto             95.226817"
+      ]
+     },
+     "execution_count": 113,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code goes here"
+    "long_table = summary3.stack().reset_index()\n",
+    "long_table.columns = [\"month\", \"policy_type\", \"number_of_complaints\"]\n",
+    "long_table"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f42d06af-1a7d-4ba2-9f92-faf12d5218dc",
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -146,9 +2992,9 @@
    "provenance": []
   },
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Python [conda env:base] *",
    "language": "python",
-   "name": "python3"
+   "name": "conda-base-py"
   },
   "language_info": {
    "codemirror_mode": {
@@ -160,7 +3006,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.13.5"
   }
  },
  "nbformat": 4,