<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>user_id</th>
      <th>email</th>
      <th>stripe_customer_id</th>
      <th>created_at</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>0187c3e7-98a1-4aee-9793-a0fc119274b2</td>
      <td>parth45730@gmail.com</td>
      <td>cus_PHr7Q0ZGVyXbZ0</td>
      <td>2023-12-31 05:17:32.525532+00</td>
    </tr>
    <tr>
      <th>1</th>
      <td>01d21640-dd89-468f-ab35-860112ed3d2b</td>
      <td>bebobob540@gmail.com</td>
      <td>cus_PENzy5kSCQPjrb</td>
      <td>2023-12-21 22:59:23.518708+00</td>
    </tr>
    <tr>
      <th>2</th>
      <td>01d5b242-2628-44ba-afab-15d6358d23fe</td>
      <td>1911512372@student.budiluhur.ac.id</td>
      <td>cus_PAao3KjXrE8sMn</td>
      <td>2023-12-11 19:59:11.47942+00</td>
    </tr>
    <tr>
      <th>3</th>
      <td>01ecd9ad-276d-46cf-9ed9-2895d714195e</td>
      <td>muhammad.ikram.ariff@gmail.com</td>
      <td>cus_PLiIHQcUthRdVR</td>
      <td>2024-01-10 12:26:48.36858+00</td>
    </tr>
    <tr>
      <th>4</th>
      <td>034f7616-bfb5-418d-a041-6859cb69d302</td>
      <td>yapiji4040@wenkuu.com</td>
      <td>cus_PGGIpCBbUx94R8</td>
      <td>2023-12-26 23:10:40.747049+00</td>
    </tr>
  </tbody>
</table>
</div>

                                user_id                               email  \
0  0187c3e7-98a1-4aee-9793-a0fc119274b2                parth45730@gmail.com   
1  01d21640-dd89-468f-ab35-860112ed3d2b                bebobob540@gmail.com   
2  01d5b242-2628-44ba-afab-15d6358d23fe  1911512372@student.budiluhur.ac.id   
3  01ecd9ad-276d-46cf-9ed9-2895d714195e      muhammad.ikram.ariff@gmail.com   
4  034f7616-bfb5-418d-a041-6859cb69d302               yapiji4040@wenkuu.com   

   stripe_customer_id                     created_at  
0  cus_PHr7Q0ZGVyXbZ0  2023-12-31 05:17:32.525532+00  
1  cus_PENzy5kSCQPjrb  2023-12-21 22:59:23.518708+00  
2  cus_PAao3KjXrE8sMn   2023-12-11 19:59:11.47942+00  
3  cus_PLiIHQcUthRdVR   2024-01-10 12:26:48.36858+00  
4  cus_PGGIpCBbUx94R8  2023-12-26 23:10:40.747049+00  

<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>email_domain</th>
      <th>user_count</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>gmail.com</td>
      <td>267</td>
    </tr>
    <tr>
      <th>1</th>
      <td>163.com</td>
      <td>3</td>
    </tr>
    <tr>
      <th>2</th>
      <td>qq.com</td>
      <td>3</td>
    </tr>
    <tr>
      <th>3</th>
      <td>googlemail.com</td>
      <td>3</td>
    </tr>
    <tr>
      <th>4</th>
      <td>outlook.com</td>
      <td>2</td>
    </tr>
  </tbody>
</table>
</div>

     email_domain  user_count
0       gmail.com         267
1         163.com           3
2          qq.com           3
3  googlemail.com           3
4     outlook.com           2

Analyzing User Acquisition by Email Domain from CSV Data

Visualize user acquisition by email domain.