<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>Start Date</th>
      <th>End Date</th>
      <th>Response Type</th>
      <th>Progress</th>
      <th>Duration (in seconds)</th>
      <th>Finished</th>
      <th>Recorded Date</th>
      <th>Response ID</th>
      <th>consent</th>
      <th>stood_out</th>
      <th>...</th>
      <th>interest_full_film</th>
      <th>geographic_place</th>
      <th>self_geographic_place</th>
      <th>self_geographic_place_other</th>
      <th>science_proximity</th>
      <th>ses_class</th>
      <th>self_working_class</th>
      <th>RESPONDENT_ID</th>
      <th>chapter</th>
      <th>FL_11 - Block Randomizer - Display Order</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>2025-03-22 09:37:16</td>
      <td>2025-03-22 09:37:43</td>
      <td>0</td>
      <td>35</td>
      <td>27</td>
      <td>0</td>
      <td>2025-03-29 09:37:45.788</td>
      <td>R_5MPRgeKOX7YSfD5</td>
      <td>1</td>
      <td>-88</td>
      <td>...</td>
      <td>-88</td>
      <td>-88</td>
      <td>-88</td>
      <td>NaN</td>
      <td>-88</td>
      <td>-88</td>
      <td>-88</td>
      <td>iP9bb9caec528a7f87</td>
      <td>southwest</td>
      <td>NaN</td>
    </tr>
    <tr>
      <th>1</th>
      <td>2025-03-22 09:37:27</td>
      <td>2025-03-22 12:34:25</td>
      <td>0</td>
      <td>35</td>
      <td>10617</td>
      <td>0</td>
      <td>2025-03-29 12:34:26.518</td>
      <td>R_3qZQwmRV9rQ3PNe</td>
      <td>1</td>
      <td>-88</td>
      <td>...</td>
      <td>-88</td>
      <td>-88</td>
      <td>-88</td>
      <td>NaN</td>
      <td>-88</td>
      <td>-88</td>
      <td>-88</td>
      <td>iP519bf2076970153c</td>
      <td>senegal</td>
      <td>NaN</td>
    </tr>
    <tr>
      <th>2</th>
      <td>2025-03-22 09:40:16</td>
      <td>2025-03-22 09:40:30</td>
      <td>0</td>
      <td>35</td>
      <td>14</td>
      <td>0</td>
      <td>2025-03-29 09:40:32.854</td>
      <td>R_1uk981hYcUYvsOZ</td>
      <td>1</td>
      <td>-88</td>
      <td>...</td>
      <td>-88</td>
      <td>-88</td>
      <td>-88</td>
      <td>NaN</td>
      <td>-88</td>
      <td>-88</td>
      <td>-88</td>
      <td>iPd32414ae54921bd6</td>
      <td>greenland</td>
      <td>NaN</td>
    </tr>
    <tr>
      <th>3</th>
      <td>2025-03-22 10:14:47</td>
      <td>2025-03-22 10:15:07</td>
      <td>0</td>
      <td>35</td>
      <td>19</td>
      <td>0</td>
      <td>2025-03-29 10:15:10.464</td>
      <td>R_3X6T6c1uWWD1Ixr</td>
      <td>1</td>
      <td>-88</td>
      <td>...</td>
      <td>-88</td>
      <td>-88</td>
      <td>-88</td>
      <td>NaN</td>
      <td>-88</td>
      <td>-88</td>
      <td>-88</td>
      <td>iPbd9c5ea457f90210</td>
      <td>southwest</td>
      <td>NaN</td>
    </tr>
    <tr>
      <th>4</th>
      <td>2025-03-22 10:27:38</td>
      <td>2025-03-22 10:29:44</td>
      <td>0</td>
      <td>35</td>
      <td>125</td>
      <td>0</td>
      <td>2025-03-29 10:29:48.538</td>
      <td>R_32rR7ccQDo6sgRX</td>
      <td>1</td>
      <td>-88</td>
      <td>...</td>
      <td>-88</td>
      <td>-88</td>
      <td>-88</td>
      <td>NaN</td>
      <td>-88</td>
      <td>-88</td>
      <td>-88</td>
      <td>iP9d2079fcef0219e8</td>
      <td>pantalica</td>
      <td>NaN</td>
    </tr>
  </tbody>
</table>
<p>5 rows × 51 columns</p>
</div>

           Start Date            End Date  Response Type  Progress  \
0 2025-03-22 09:37:16 2025-03-22 09:37:43              0        35   
1 2025-03-22 09:37:27 2025-03-22 12:34:25              0        35   
2 2025-03-22 09:40:16 2025-03-22 09:40:30              0        35   
3 2025-03-22 10:14:47 2025-03-22 10:15:07              0        35   
4 2025-03-22 10:27:38 2025-03-22 10:29:44              0        35   

   Duration (in seconds)  Finished           Recorded Date        Response ID  \
0                     27         0 2025-03-29 09:37:45.788  R_5MPRgeKOX7YSfD5   
1                  10617         0 2025-03-29 12:34:26.518  R_3qZQwmRV9rQ3PNe   
2                     14         0 2025-03-29 09:40:32.854  R_1uk981hYcUYvsOZ   
3                     19         0 2025-03-29 10:15:10.464  R_3X6T6c1uWWD1Ixr   
4                    125         0 2025-03-29 10:29:48.538  R_32rR7ccQDo6sgRX   

   consent stood_out  ... interest_full_film  geographic_place  \
0        1       -88  ...                -88               -88   
1        1       -88  ...                -88               -88   
2        1       -88  ...                -88               -88   
3        1       -88  ...                -88               -88   
4        1       -88  ...                -88               -88   

  self_geographic_place self_geographic_place_other  science_proximity  \
0                   -88                         NaN                -88   
1                   -88                         NaN                -88   
2                   -88                         NaN                -88   
3                   -88                         NaN                -88   
4                   -88                         NaN                -88   

   ses_class  self_working_class       RESPONDENT_ID    chapter  \
0        -88                 -88  iP9bb9caec528a7f87  southwest   
1        -88                 -88  iP519bf2076970153c    senegal   
2        -88                 -88  iPd32414ae54921bd6  greenland   
3        -88                 -88  iPbd9c5ea457f90210  southwest   
4        -88                 -88  iP9d2079fcef0219e8  pantalica   

   FL_11 - Block Randomizer - Display Order  
0                                       NaN  
1                                       NaN  
2                                       NaN  
3                                       NaN  
4                                       NaN  

[5 rows x 51 columns]

Loading and Exploring the Qualtrics Dataset

Load the dataset

Identify and subset the rows in which the values of `stood_out` and `character_impressions` are both -88.

how many rows are in df_subset

how many rows are not in df_subset

Create and save a new dataset that excludes all the rows in df_subset.

Load the dataset

Identify and subset the rows in which the values of stood_out and character_impressions are both -88.

how many rows are in df_subset

how many rows are not in df_subset

Create and save a new dataset that excludes all the rows in df_subset.

Identify and subset the rows in which the values of `stood_out` and `character_impressions` are both -88.