diff --git a/lab-dw-data-structuring-and-combining.ipynb b/lab-dw-data-structuring-and-combining.ipynb
index ec4e3f9..eb5a63e 100644
--- a/lab-dw-data-structuring-and-combining.ipynb
+++ b/lab-dw-data-structuring-and-combining.ipynb
@@ -36,14 +36,1644 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 116,
    "id": "492d06e3-92c7-4105-ac72-536db98d3244",
    "metadata": {
     "id": "492d06e3-92c7-4105-ac72-536db98d3244"
    },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\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",
+       "    </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",
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+       "      <th>4</th>\n",
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+       "      <td>Washington</td>\n",
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+       "      <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",
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+       "    <tr>\n",
+       "      <th>4004</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
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+       "      <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",
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+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
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+       "      <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",
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+       "      <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]"
+      ]
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+     "metadata": {},
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+       "  <tbody>\n",
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+       "      <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",
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+       "      <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",
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+       "      <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]"
+      ]
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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>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",
+       "    <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>7065</th>\n",
+       "      <td>LA72316</td>\n",
+       "      <td>California</td>\n",
+       "      <td>23405.987980</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>M</td>\n",
+       "      <td>71941</td>\n",
+       "      <td>73</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>198.234764</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7066</th>\n",
+       "      <td>PK87824</td>\n",
+       "      <td>California</td>\n",
+       "      <td>3096.511217</td>\n",
+       "      <td>College</td>\n",
+       "      <td>F</td>\n",
+       "      <td>21604</td>\n",
+       "      <td>79</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>379.200000</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7067</th>\n",
+       "      <td>TD14365</td>\n",
+       "      <td>California</td>\n",
+       "      <td>8163.890428</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>M</td>\n",
+       "      <td>0</td>\n",
+       "      <td>85</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>790.784983</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7068</th>\n",
+       "      <td>UP19263</td>\n",
+       "      <td>California</td>\n",
+       "      <td>7524.442436</td>\n",
+       "      <td>College</td>\n",
+       "      <td>M</td>\n",
+       "      <td>21941</td>\n",
+       "      <td>96</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>691.200000</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7069</th>\n",
+       "      <td>Y167826</td>\n",
+       "      <td>California</td>\n",
+       "      <td>2611.836866</td>\n",
+       "      <td>College</td>\n",
+       "      <td>M</td>\n",
+       "      <td>0</td>\n",
+       "      <td>77</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>369.600000</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>7070 rows × 11 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     Customer       State  Customer Lifetime Value             Education  \\\n",
+       "0     SA25987  Washington              3479.137523  High School or Below   \n",
+       "1     TB86706     Arizona              2502.637401                Master   \n",
+       "2     ZL73902      Nevada              3265.156348              Bachelor   \n",
+       "3     KX23516  California              4455.843406  High School or Below   \n",
+       "4     FN77294  California              7704.958480  High School or Below   \n",
+       "...       ...         ...                      ...                   ...   \n",
+       "7065  LA72316  California             23405.987980              Bachelor   \n",
+       "7066  PK87824  California              3096.511217               College   \n",
+       "7067  TD14365  California              8163.890428              Bachelor   \n",
+       "7068  UP19263  California              7524.442436               College   \n",
+       "7069  Y167826  California              2611.836866               College   \n",
+       "\n",
+       "     Gender  Income  Monthly Premium Auto  Number of Open Complaints  \\\n",
+       "0         M       0                   104                          0   \n",
+       "1         M       0                    66                          0   \n",
+       "2         F   25820                    82                          0   \n",
+       "3         F       0                   121                          0   \n",
+       "4         M   30366                   101                          2   \n",
+       "...     ...     ...                   ...                        ...   \n",
+       "7065      M   71941                    73                          0   \n",
+       "7066      F   21604                    79                          0   \n",
+       "7067      M       0                    85                          3   \n",
+       "7068      M   21941                    96                          0   \n",
+       "7069      M       0                    77                          0   \n",
+       "\n",
+       "         Policy Type  Total Claim Amount  Vehicle Class  \n",
+       "0      Personal Auto          499.200000   Two-Door Car  \n",
+       "1      Personal Auto            3.468912   Two-Door Car  \n",
+       "2      Personal Auto          393.600000  Four-Door Car  \n",
+       "3      Personal Auto          699.615192            SUV  \n",
+       "4      Personal Auto          484.800000            SUV  \n",
+       "...              ...                 ...            ...  \n",
+       "7065   Personal Auto          198.234764  Four-Door Car  \n",
+       "7066  Corporate Auto          379.200000  Four-Door Car  \n",
+       "7067  Corporate Auto          790.784983  Four-Door Car  \n",
+       "7068   Personal Auto          691.200000  Four-Door Car  \n",
+       "7069  Corporate Auto          369.600000   Two-Door Car  \n",
+       "\n",
+       "[7070 rows x 11 columns]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "url1 = 'https://raw.githubusercontent.com/data-bootcamp-v4/data/main/file1.csv'\n",
+    "insurance1_df = pd.read_csv(url1)\n",
+    "display(insurance1_df)\n",
+    "\n",
+    "url2 = 'https://raw.githubusercontent.com/data-bootcamp-v4/data/main/file2.csv'\n",
+    "insurance2_df = pd.read_csv(url2)\n",
+    "display(insurance2_df)\n",
+    "\n",
+    "url3 = 'https://raw.githubusercontent.com/data-bootcamp-v4/data/main/file3.csv'\n",
+    "insurance3_df = pd.read_csv(url3)\n",
+    "display(insurance3_df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 117,
+   "id": "7c352e1c-6f6e-41c6-a65a-0322d575ac03",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 4008 entries, 0 to 4007\n",
+      "Data columns (total 11 columns):\n",
+      " #   Column                     Non-Null Count  Dtype  \n",
+      "---  ------                     --------------  -----  \n",
+      " 0   Customer                   1071 non-null   object \n",
+      " 1   ST                         1071 non-null   object \n",
+      " 2   GENDER                     954 non-null    object \n",
+      " 3   Education                  1071 non-null   object \n",
+      " 4   Customer Lifetime Value    1068 non-null   object \n",
+      " 5   Income                     1071 non-null   float64\n",
+      " 6   Monthly Premium Auto       1071 non-null   float64\n",
+      " 7   Number of Open Complaints  1071 non-null   object \n",
+      " 8   Policy Type                1071 non-null   object \n",
+      " 9   Vehicle Class              1071 non-null   object \n",
+      " 10  Total Claim Amount         1071 non-null   float64\n",
+      "dtypes: float64(3), object(8)\n",
+      "memory usage: 344.6+ KB\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "None"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 996 entries, 0 to 995\n",
+      "Data columns (total 11 columns):\n",
+      " #   Column                     Non-Null Count  Dtype  \n",
+      "---  ------                     --------------  -----  \n",
+      " 0   Customer                   996 non-null    object \n",
+      " 1   ST                         996 non-null    object \n",
+      " 2   GENDER                     991 non-null    object \n",
+      " 3   Education                  996 non-null    object \n",
+      " 4   Customer Lifetime Value    992 non-null    object \n",
+      " 5   Income                     996 non-null    int64  \n",
+      " 6   Monthly Premium Auto       996 non-null    int64  \n",
+      " 7   Number of Open Complaints  996 non-null    object \n",
+      " 8   Total Claim Amount         996 non-null    float64\n",
+      " 9   Policy Type                996 non-null    object \n",
+      " 10  Vehicle Class              996 non-null    object \n",
+      "dtypes: float64(1), int64(2), object(8)\n",
+      "memory usage: 85.7+ KB\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "None"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 7070 entries, 0 to 7069\n",
+      "Data columns (total 11 columns):\n",
+      " #   Column                     Non-Null Count  Dtype  \n",
+      "---  ------                     --------------  -----  \n",
+      " 0   Customer                   7070 non-null   object \n",
+      " 1   State                      7070 non-null   object \n",
+      " 2   Customer Lifetime Value    7070 non-null   float64\n",
+      " 3   Education                  7070 non-null   object \n",
+      " 4   Gender                     7070 non-null   object \n",
+      " 5   Income                     7070 non-null   int64  \n",
+      " 6   Monthly Premium Auto       7070 non-null   int64  \n",
+      " 7   Number of Open Complaints  7070 non-null   int64  \n",
+      " 8   Policy Type                7070 non-null   object \n",
+      " 9   Total Claim Amount         7070 non-null   float64\n",
+      " 10  Vehicle Class              7070 non-null   object \n",
+      "dtypes: float64(2), int64(3), object(6)\n",
+      "memory usage: 607.7+ KB\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "None"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "display(insurance1_df.info())\n",
+    "display(insurance2_df.info())\n",
+    "display(insurance3_df.info())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 118,
+   "id": "29abc4d6-bc97-4557-8275-0e5a4bf416ed",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def clean_data_insurance(df):\n",
+    "    new_columns=[\"state\" if column == \"ST\" else column.replace(\" \",\"_\").lower() for column in df.columns] \n",
+    "    df.columns = new_columns\n",
+    "    df[\"gender\"] = df[\"gender\"].replace({\"Femal\":\"F\",'female':\"F\",'Male':\"M\"})\n",
+    "    df[\"state\"] = df[\"state\"].replace({'Cali':\"California\",'AZ':\"Arizona\", 'WA':\"Washington\"})\n",
+    "    df[\"education\"] = df[\"education\"].replace(\"Bachelors\",\"Bachelor\")\n",
+    "    df[\"vehicle_class\"] = df[\"vehicle_class\"].replace({'Luxury SUV':\"Luxury\", 'Sports Car':\"Luxury\",'Luxury Car':\"Luxury\"})\n",
+    "    if df[\"customer_lifetime_value\"].dtype == \"object\":\n",
+    "        df[\"customer_lifetime_value\"] = df[\"customer_lifetime_value\"].str.replace(\"%\",\"\").astype(float)\n",
+    "    return df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 119,
+   "id": "d21e71a0-4c8a-4ed2-b727-06f7f5925b94",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 4008 entries, 0 to 4007\n",
+      "Data columns (total 11 columns):\n",
+      " #   Column                     Non-Null Count  Dtype  \n",
+      "---  ------                     --------------  -----  \n",
+      " 0   customer                   1071 non-null   object \n",
+      " 1   state                      1071 non-null   object \n",
+      " 2   gender                     954 non-null    object \n",
+      " 3   education                  1071 non-null   object \n",
+      " 4   customer_lifetime_value    1068 non-null   float64\n",
+      " 5   income                     1071 non-null   float64\n",
+      " 6   monthly_premium_auto       1071 non-null   float64\n",
+      " 7   number_of_open_complaints  1071 non-null   object \n",
+      " 8   policy_type                1071 non-null   object \n",
+      " 9   vehicle_class              1071 non-null   object \n",
+      " 10  total_claim_amount         1071 non-null   float64\n",
+      "dtypes: float64(4), object(7)\n",
+      "memory usage: 344.6+ KB\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "None"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 996 entries, 0 to 995\n",
+      "Data columns (total 11 columns):\n",
+      " #   Column                     Non-Null Count  Dtype  \n",
+      "---  ------                     --------------  -----  \n",
+      " 0   customer                   996 non-null    object \n",
+      " 1   state                      996 non-null    object \n",
+      " 2   gender                     991 non-null    object \n",
+      " 3   education                  996 non-null    object \n",
+      " 4   customer_lifetime_value    992 non-null    float64\n",
+      " 5   income                     996 non-null    int64  \n",
+      " 6   monthly_premium_auto       996 non-null    int64  \n",
+      " 7   number_of_open_complaints  996 non-null    object \n",
+      " 8   total_claim_amount         996 non-null    float64\n",
+      " 9   policy_type                996 non-null    object \n",
+      " 10  vehicle_class              996 non-null    object \n",
+      "dtypes: float64(2), int64(2), object(7)\n",
+      "memory usage: 85.7+ KB\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "None"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 7070 entries, 0 to 7069\n",
+      "Data columns (total 11 columns):\n",
+      " #   Column                     Non-Null Count  Dtype  \n",
+      "---  ------                     --------------  -----  \n",
+      " 0   customer                   7070 non-null   object \n",
+      " 1   state                      7070 non-null   object \n",
+      " 2   customer_lifetime_value    7070 non-null   float64\n",
+      " 3   education                  7070 non-null   object \n",
+      " 4   gender                     7070 non-null   object \n",
+      " 5   income                     7070 non-null   int64  \n",
+      " 6   monthly_premium_auto       7070 non-null   int64  \n",
+      " 7   number_of_open_complaints  7070 non-null   int64  \n",
+      " 8   policy_type                7070 non-null   object \n",
+      " 9   total_claim_amount         7070 non-null   float64\n",
+      " 10  vehicle_class              7070 non-null   object \n",
+      "dtypes: float64(2), int64(3), object(6)\n",
+      "memory usage: 607.7+ KB\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "None"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "insurance1_df = clean_data_insurance(insurance1_df)\n",
+    "insurance2_df = clean_data_insurance(insurance2_df)\n",
+    "insurance3_df =clean_data_insurance(insurance3_df)\n",
+    "display(insurance1_df.info())\n",
+    "display(insurance2_df.info())\n",
+    "display(insurance3_df.info())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 120,
+   "id": "2f9d1552-a7ce-4740-8ac0-16b65a0a8214",
+   "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code goes here"
+    "column_order = ['customer', 'state', 'gender', 'education', 'customer_lifetime_value',\n",
+    "       'income', 'monthly_premium_auto', 'number_of_open_complaints',\n",
+    "       'policy_type', 'vehicle_class', 'total_claim_amount']\n",
+    "insurance1_df = insurance1_df[column_order]\n",
+    "insurance2_df = insurance2_df[column_order]\n",
+    "insurance3_df = insurance3_df[column_order]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 121,
+   "id": "602495f0-0e3e-444a-b83b-d38131ed1525",
+   "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>1000.0</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>6.979536e+05</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>1.288743e+06</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>7.645862e+05</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>5.363077e+05</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>12069</th>\n",
+       "      <td>LA72316</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>2.340599e+04</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12070</th>\n",
+       "      <td>PK87824</td>\n",
+       "      <td>California</td>\n",
+       "      <td>F</td>\n",
+       "      <td>College</td>\n",
+       "      <td>3.096511e+03</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12071</th>\n",
+       "      <td>TD14365</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>8.163890e+03</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12072</th>\n",
+       "      <td>UP19263</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>College</td>\n",
+       "      <td>7.524442e+03</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12073</th>\n",
+       "      <td>Y167826</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>College</td>\n",
+       "      <td>2.611837e+03</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",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>12074 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",
+       "12069  LA72316  California      M              Bachelor   \n",
+       "12070  PK87824  California      F               College   \n",
+       "12071  TD14365  California      M              Bachelor   \n",
+       "12072  UP19263  California      M               College   \n",
+       "12073  Y167826  California      M               College   \n",
+       "\n",
+       "       customer_lifetime_value   income  monthly_premium_auto  \\\n",
+       "0                          NaN      0.0                1000.0   \n",
+       "1                 6.979536e+05      0.0                  94.0   \n",
+       "2                 1.288743e+06  48767.0                 108.0   \n",
+       "3                 7.645862e+05      0.0                 106.0   \n",
+       "4                 5.363077e+05  36357.0                  68.0   \n",
+       "...                        ...      ...                   ...   \n",
+       "12069             2.340599e+04  71941.0                  73.0   \n",
+       "12070             3.096511e+03  21604.0                  79.0   \n",
+       "12071             8.163890e+03      0.0                  85.0   \n",
+       "12072             7.524442e+03  21941.0                  96.0   \n",
+       "12073             2.611837e+03      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",
+       "12069                         0   Personal Auto  Four-Door Car   \n",
+       "12070                         0  Corporate Auto  Four-Door Car   \n",
+       "12071                         3  Corporate Auto  Four-Door Car   \n",
+       "12072                         0   Personal Auto  Four-Door Car   \n",
+       "12073                         0  Corporate Auto   Two-Door Car   \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",
+       "12069          198.234764  \n",
+       "12070          379.200000  \n",
+       "12071          790.784983  \n",
+       "12072          691.200000  \n",
+       "12073          369.600000  \n",
+       "\n",
+       "[12074 rows x 11 columns]"
+      ]
+     },
+     "execution_count": 121,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "insurance_df = pd.concat([insurance1_df, insurance2_df, insurance3_df]).reset_index(drop=True)\n",
+    "insurance_df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 122,
+   "id": "f7489fff-aa4e-4e25-8489-1a72e32f77dc",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[nan 'F' 'M']\n",
+      "['Washington' 'Arizona' 'Nevada' 'California' 'Oregon' nan]\n",
+      "['Master' 'Bachelor' 'High School or Below' 'College' 'Doctor' nan]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# To chek everything worked\n",
+    "print(insurance_df[\"gender\"].unique())\n",
+    "print(insurance_df[\"state\"].unique())\n",
+    "print(insurance_df[\"education\"].unique())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 123,
+   "id": "cad6a50c-7cc2-414e-b113-900e9c53ca56",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 12074 entries, 0 to 12073\n",
+      "Data columns (total 11 columns):\n",
+      " #   Column                     Non-Null Count  Dtype  \n",
+      "---  ------                     --------------  -----  \n",
+      " 0   customer                   9137 non-null   object \n",
+      " 1   state                      9137 non-null   object \n",
+      " 2   gender                     9015 non-null   object \n",
+      " 3   education                  9137 non-null   object \n",
+      " 4   customer_lifetime_value    9130 non-null   float64\n",
+      " 5   income                     9137 non-null   float64\n",
+      " 6   monthly_premium_auto       9137 non-null   float64\n",
+      " 7   number_of_open_complaints  9137 non-null   object \n",
+      " 8   policy_type                9137 non-null   object \n",
+      " 9   vehicle_class              9137 non-null   object \n",
+      " 10  total_claim_amount         9137 non-null   float64\n",
+      "dtypes: float64(4), object(7)\n",
+      "memory usage: 1.0+ MB\n"
+     ]
+    }
+   ],
+   "source": [
+    "insurance_df.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 124,
+   "id": "3b45cba3-c011-4776-bd82-93c59d029bcc",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "customer                     2937\n",
+       "state                        2937\n",
+       "gender                       3059\n",
+       "education                    2937\n",
+       "customer_lifetime_value      2944\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": 124,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "insurance_df.isna().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 125,
+   "id": "a19f410a-fc77-41e9-a679-dcaa716e9e1d",
+   "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>1000.0</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>6.979536e+05</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>1.288743e+06</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>7.645862e+05</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>5.363077e+05</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>9129</th>\n",
+       "      <td>LA72316</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>2.340599e+04</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9130</th>\n",
+       "      <td>PK87824</td>\n",
+       "      <td>California</td>\n",
+       "      <td>F</td>\n",
+       "      <td>College</td>\n",
+       "      <td>3.096511e+03</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9131</th>\n",
+       "      <td>TD14365</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>8.163890e+03</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9132</th>\n",
+       "      <td>UP19263</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>College</td>\n",
+       "      <td>7.524442e+03</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9133</th>\n",
+       "      <td>Y167826</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>College</td>\n",
+       "      <td>2.611837e+03</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",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>9134 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",
+       "9129  LA72316  California      M              Bachelor   \n",
+       "9130  PK87824  California      F               College   \n",
+       "9131  TD14365  California      M              Bachelor   \n",
+       "9132  UP19263  California      M               College   \n",
+       "9133  Y167826  California      M               College   \n",
+       "\n",
+       "      customer_lifetime_value   income  monthly_premium_auto  \\\n",
+       "0                         NaN      0.0                1000.0   \n",
+       "1                6.979536e+05      0.0                  94.0   \n",
+       "2                1.288743e+06  48767.0                 108.0   \n",
+       "3                7.645862e+05      0.0                 106.0   \n",
+       "4                5.363077e+05  36357.0                  68.0   \n",
+       "...                       ...      ...                   ...   \n",
+       "9129             2.340599e+04  71941.0                  73.0   \n",
+       "9130             3.096511e+03  21604.0                  79.0   \n",
+       "9131             8.163890e+03      0.0                  85.0   \n",
+       "9132             7.524442e+03  21941.0                  96.0   \n",
+       "9133             2.611837e+03      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",
+       "9129                         0   Personal Auto  Four-Door Car   \n",
+       "9130                         0  Corporate Auto  Four-Door Car   \n",
+       "9131                         3  Corporate Auto  Four-Door Car   \n",
+       "9132                         0   Personal Auto  Four-Door Car   \n",
+       "9133                         0  Corporate Auto   Two-Door Car   \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",
+       "9129          198.234764  \n",
+       "9130          379.200000  \n",
+       "9131          790.784983  \n",
+       "9132          691.200000  \n",
+       "9133          369.600000  \n",
+       "\n",
+       "[9134 rows x 11 columns]"
+      ]
+     },
+     "execution_count": 125,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "insurance_df.dropna(subset=[\"customer\"], inplace = True)\n",
+    "insurance_df.drop_duplicates(inplace = True)\n",
+    "insurance_df = insurance_df.reset_index(drop = True)\n",
+    "insurance_df"
    ]
   },
   {
@@ -72,14 +1702,454 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 127,
    "id": "aa10d9b0-1c27-4d3f-a8e4-db6ab73bfd26",
    "metadata": {
     "id": "aa10d9b0-1c27-4d3f-a8e4-db6ab73bfd26"
    },
-   "outputs": [],
+   "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",
+       "    <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",
+       "      <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>10905</th>\n",
+       "      <td>10905</td>\n",
+       "      <td>FE99816</td>\n",
+       "      <td>Nevada</td>\n",
+       "      <td>15563.369440</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Premium</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>2011-01-19</td>\n",
+       "      <td>Unemployed</td>\n",
+       "      <td>F</td>\n",
+       "      <td>...</td>\n",
+       "      <td>7</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Personal L1</td>\n",
+       "      <td>Offer3</td>\n",
+       "      <td>Web</td>\n",
+       "      <td>1214.400000</td>\n",
+       "      <td>Luxury Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "      <td>A</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10906</th>\n",
+       "      <td>10906</td>\n",
+       "      <td>KX53892</td>\n",
+       "      <td>Oregon</td>\n",
+       "      <td>5259.444853</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Basic</td>\n",
+       "      <td>College</td>\n",
+       "      <td>2011-01-06</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>F</td>\n",
+       "      <td>...</td>\n",
+       "      <td>6</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Personal L3</td>\n",
+       "      <td>Offer2</td>\n",
+       "      <td>Branch</td>\n",
+       "      <td>273.018929</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>10907</th>\n",
+       "      <td>10907</td>\n",
+       "      <td>TL39050</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>23893.304100</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Extended</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>2011-02-06</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>F</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Corporate L3</td>\n",
+       "      <td>Offer1</td>\n",
+       "      <td>Web</td>\n",
+       "      <td>381.306996</td>\n",
+       "      <td>Luxury SUV</td>\n",
+       "      <td>Medsize</td>\n",
+       "      <td>A</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10908</th>\n",
+       "      <td>10908</td>\n",
+       "      <td>WA60547</td>\n",
+       "      <td>California</td>\n",
+       "      <td>11971.977650</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Premium</td>\n",
+       "      <td>College</td>\n",
+       "      <td>2011-02-13</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>F</td>\n",
+       "      <td>...</td>\n",
+       "      <td>6</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Personal L1</td>\n",
+       "      <td>Offer1</td>\n",
+       "      <td>Branch</td>\n",
+       "      <td>618.288849</td>\n",
+       "      <td>SUV</td>\n",
+       "      <td>Medsize</td>\n",
+       "      <td>A</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10909</th>\n",
+       "      <td>10909</td>\n",
+       "      <td>IV32877</td>\n",
+       "      <td>California</td>\n",
+       "      <td>6857.519928</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Basic</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>2011-01-08</td>\n",
+       "      <td>Unemployed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>...</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Personal L1</td>\n",
+       "      <td>Offer4</td>\n",
+       "      <td>Web</td>\n",
+       "      <td>1021.719397</td>\n",
+       "      <td>SUV</td>\n",
+       "      <td>Medsize</td>\n",
+       "      <td>A</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>10910 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",
+       "10905       10905  FE99816      Nevada             15563.369440       No   \n",
+       "10906       10906  KX53892      Oregon              5259.444853       No   \n",
+       "10907       10907  TL39050     Arizona             23893.304100       No   \n",
+       "10908       10908  WA60547  California             11971.977650       No   \n",
+       "10909       10909  IV32877  California              6857.519928       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",
+       "10905   Premium  Bachelor        2011-01-19       Unemployed      F  ...   \n",
+       "10906     Basic   College        2011-01-06         Employed      F  ...   \n",
+       "10907  Extended  Bachelor        2011-02-06         Employed      F  ...   \n",
+       "10908   Premium   College        2011-02-13         Employed      F  ...   \n",
+       "10909     Basic  Bachelor        2011-01-08       Unemployed      M  ...   \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",
+       "10905                   7   Personal Auto   Personal L1            Offer3   \n",
+       "10906                   6   Personal Auto   Personal L3            Offer2   \n",
+       "10907                   2  Corporate Auto  Corporate L3            Offer1   \n",
+       "10908                   6   Personal Auto   Personal L1            Offer1   \n",
+       "10909                   3   Personal Auto   Personal L1            Offer4   \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",
+       "10905            Web         1214.400000     Luxury Car       Medsize   \n",
+       "10906         Branch          273.018929  Four-Door Car       Medsize   \n",
+       "10907            Web          381.306996     Luxury SUV       Medsize   \n",
+       "10908         Branch          618.288849            SUV       Medsize   \n",
+       "10909            Web         1021.719397            SUV       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",
+       "10905            A     1  \n",
+       "10906            A     1  \n",
+       "10907            A     2  \n",
+       "10908            A     2  \n",
+       "10909            A     1  \n",
+       "\n",
+       "[10910 rows x 27 columns]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# Your code goes here"
+    "url = 'https://raw.githubusercontent.com/data-bootcamp-v4/data/main/marketing_customer_analysis_clean.csv'\n",
+    "marketing_df = pd.read_csv(url)\n",
+    "display(marketing_df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 131,
+   "id": "8917da4f-050b-4d73-9e48-ee3c1341b896",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "np.int64(0)"
+      ]
+     },
+     "execution_count": 131,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "marketing_df.isna().sum()\n",
+    "marketing_df.duplicated().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 132,
+   "id": "9940cf60-88b9-4899-b9e4-c79b888479a1",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['unnamed:_0', 'customer', 'state', 'customer_lifetime_value',\n",
+       "       'response', 'coverage', 'education', 'effective_to_date',\n",
+       "       'employmentstatus', 'gender', 'income', 'location_code',\n",
+       "       'marital_status', 'monthly_premium_auto', 'months_since_last_claim',\n",
+       "       'months_since_policy_inception', 'number_of_open_complaints',\n",
+       "       'number_of_policies', 'policy_type', 'policy', 'renew_offer_type',\n",
+       "       'sales_channel', 'total_claim_amount', 'vehicle_class', 'vehicle_size',\n",
+       "       'vehicle_type', 'month'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 132,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "marketing_df.columns"
    ]
   },
   {
@@ -93,6 +2163,91 @@
     "Round the total revenue to 2 decimal points.  Analyze the resulting table to draw insights."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 136,
+   "id": "36356682-c4c8-4abe-85f3-c0c7c8b208b7",
+   "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": 136,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "marketing_df.pivot_table(index='sales_channel', values=['total_claim_amount'], aggfunc='sum').round(2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "71ce1a89-2fb7-4fde-b175-12889b052042",
+   "metadata": {},
+   "source": [
+    "Agent has the highest total claim amount, indicating that this sales channel generaates the largest volume of business.\n",
+    "\n",
+    "Branch is the second most important channel.\n",
+    "\n",
+    "Call Center and Web have lower total claim amounts, with Web being the channel with the lowest total."
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "640993b2-a291-436c-a34d-a551144f8196",
@@ -103,6 +2258,125 @@
     "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": 140,
+   "id": "1e7891f8-2227-4070-8f16-3ce5818d927b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th>customer_lifetime_value</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>gender</th>\n",
+       "      <th>education</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"5\" valign=\"top\">F</th>\n",
+       "      <th>Bachelor</th>\n",
+       "      <td>7874.27</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>College</th>\n",
+       "      <td>7748.82</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Doctor</th>\n",
+       "      <td>7328.51</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>High School or Below</th>\n",
+       "      <td>8675.22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Master</th>\n",
+       "      <td>8157.05</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"5\" valign=\"top\">M</th>\n",
+       "      <th>Bachelor</th>\n",
+       "      <td>7703.60</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>College</th>\n",
+       "      <td>8052.46</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Doctor</th>\n",
+       "      <td>7415.33</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>High School or Below</th>\n",
+       "      <td>8149.69</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Master</th>\n",
+       "      <td>8168.83</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                             customer_lifetime_value\n",
+       "gender education                                    \n",
+       "F      Bachelor                              7874.27\n",
+       "       College                               7748.82\n",
+       "       Doctor                                7328.51\n",
+       "       High School or Below                  8675.22\n",
+       "       Master                                8157.05\n",
+       "M      Bachelor                              7703.60\n",
+       "       College                               8052.46\n",
+       "       Doctor                                7415.33\n",
+       "       High School or Below                  8149.69\n",
+       "       Master                                8168.83"
+      ]
+     },
+     "execution_count": 140,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "marketing_df.pivot_table(index=['gender','education'], values=['customer_lifetime_value'], aggfunc='mean').round(2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4c942a8b-96da-4d65-8818-b3b6349a0c6b",
+   "metadata": {},
+   "source": [
+    "Customers with High School or Below have the highest average customer lifetime value among female customers.\n",
+    "\n",
+    "The average customer lifetime value is generally similar between males and females across most education levels.\n",
+    "\n",
+    "Customers with a Doctor degree have the lowest average customer lifetime value for both genders."
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "32c7f2e5-3d90-43e5-be33-9781b6069198",
@@ -130,14 +2404,92 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 153,
    "id": "3a069e0b-b400-470e-904d-d17582191be4",
    "metadata": {
     "id": "3a069e0b-b400-470e-904d-d17582191be4"
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th>number_of_open_complaints</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>policy_type</th>\n",
+       "      <th>month</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"2\" valign=\"top\">Corporate Auto</th>\n",
+       "      <th>1</th>\n",
+       "      <td>0.354181</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0.353726</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"2\" valign=\"top\">Personal Auto</th>\n",
+       "      <th>1</th>\n",
+       "      <td>0.399077</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0.382649</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"2\" valign=\"top\">Special Auto</th>\n",
+       "      <th>1</th>\n",
+       "      <td>0.367401</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0.466798</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                      number_of_open_complaints\n",
+       "policy_type    month                           \n",
+       "Corporate Auto 1                       0.354181\n",
+       "               2                       0.353726\n",
+       "Personal Auto  1                       0.399077\n",
+       "               2                       0.382649\n",
+       "Special Auto   1                       0.367401\n",
+       "               2                       0.466798"
+      ]
+     },
+     "execution_count": 153,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code goes here"
+    "marketing_df.pivot_table(index=['policy_type','month'], values='number_of_open_complaints')"
    ]
   }
  ],
@@ -146,9 +2498,9 @@
    "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 +2512,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.13.9"
   }
  },
  "nbformat": 4,