<div>
<style scoped>
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        vertical-align: middle;
    }

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        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 09:37:15</td>
      <td>2025-03-22 10:06:03</td>
      <td>0</td>
      <td>100</td>
      <td>1727</td>
      <td>1</td>
      <td>2025-03-22 10:06:03.466</td>
      <td>R_59vk9us5U8IP3gf</td>
      <td>1</td>
      <td>What stood out to me the most about the clip w...</td>
      <td>...</td>
      <td>4</td>
      <td>2</td>
      <td>2</td>
      <td>-99</td>
      <td>5</td>
      <td>3</td>
      <td>3</td>
      <td>iPa8503af03bb284a8</td>
      <td>atacama</td>
      <td>Trust|Valuealignment</td>
    </tr>
    <tr>
      <th>1</th>
      <td>2025-03-22 09:37:17</td>
      <td>2025-03-22 09:58:44</td>
      <td>0</td>
      <td>100</td>
      <td>1286</td>
      <td>1</td>
      <td>2025-03-22 09:58:44.783</td>
      <td>R_6JggRfb6ow9nZfc</td>
      <td>1</td>
      <td>I was more interested in the Inuet culture and...</td>
      <td>...</td>
      <td>3</td>
      <td>2</td>
      <td>1</td>
      <td>-99</td>
      <td>6</td>
      <td>3</td>
      <td>1</td>
      <td>iPb4802d8779fc7ac9</td>
      <td>greenland</td>
      <td>Trust|Valuealignment</td>
    </tr>
    <tr>
      <th>2</th>
      <td>2025-03-22 09:37:37</td>
      <td>2025-03-22 09:57:50</td>
      <td>0</td>
      <td>100</td>
      <td>1213</td>
      <td>1</td>
      <td>2025-03-22 09:57:55.730</td>
      <td>R_5tMxxNsXZ6QDuLj</td>
      <td>1</td>
      <td>-99</td>
      <td>...</td>
      <td>5</td>
      <td>2</td>
      <td>2</td>
      <td>-99</td>
      <td>10</td>
      <td>3</td>
      <td>1</td>
      <td>iPe86aa9eb73b9c47b</td>
      <td>seoul</td>
      <td>Valuealignment|Trust</td>
    </tr>
    <tr>
      <th>3</th>
      <td>2025-03-22 09:37:47</td>
      <td>2025-03-22 10:01:50</td>
      <td>0</td>
      <td>100</td>
      <td>1443</td>
      <td>1</td>
      <td>2025-03-22 10:01:50.785</td>
      <td>R_5lKeFwUGE7lDwGh</td>
      <td>1</td>
      <td>The red frame that was used to isolate differe...</td>
      <td>...</td>
      <td>2</td>
      <td>1</td>
      <td>4</td>
      <td>-99</td>
      <td>10</td>
      <td>2</td>
      <td>1</td>
      <td>iP303583bbd989478e</td>
      <td>greenland</td>
      <td>Valuealignment|Trust</td>
    </tr>
    <tr>
      <th>4</th>
      <td>2025-03-22 09:37:48</td>
      <td>2025-03-22 09:53:02</td>
      <td>0</td>
      <td>100</td>
      <td>914</td>
      <td>1</td>
      <td>2025-03-22 09:53:03.277</td>
      <td>R_6uPZbRrXC8qBe2Z</td>
      <td>1</td>
      <td>What stood out to me the most is that we are n...</td>
      <td>...</td>
      <td>5</td>
      <td>4</td>
      <td>1</td>
      <td>-99</td>
      <td>9</td>
      <td>2</td>
      <td>2</td>
      <td>iP2a6138fe72ec5982</td>
      <td>maine</td>
      <td>Trust|Valuealignment</td>
    </tr>
  </tbody>
</table>
<p>5 rows × 51 columns</p>
</div>

           Start Date            End Date  Response Type  Progress  \
0 2025-03-22 09:37:15 2025-03-22 10:06:03              0       100   
1 2025-03-22 09:37:17 2025-03-22 09:58:44              0       100   
2 2025-03-22 09:37:37 2025-03-22 09:57:50              0       100   
3 2025-03-22 09:37:47 2025-03-22 10:01:50              0       100   
4 2025-03-22 09:37:48 2025-03-22 09:53:02              0       100   

   Duration (in seconds)  Finished           Recorded Date        Response ID  \
0                   1727         1 2025-03-22 10:06:03.466  R_59vk9us5U8IP3gf   
1                   1286         1 2025-03-22 09:58:44.783  R_6JggRfb6ow9nZfc   
2                   1213         1 2025-03-22 09:57:55.730  R_5tMxxNsXZ6QDuLj   
3                   1443         1 2025-03-22 10:01:50.785  R_5lKeFwUGE7lDwGh   
4                    914         1 2025-03-22 09:53:03.277  R_6uPZbRrXC8qBe2Z   

   consent                                          stood_out  ...  \
0        1  What stood out to me the most about the clip w...  ...   
1        1  I was more interested in the Inuet culture and...  ...   
2        1                                                -99  ...   
3        1  The red frame that was used to isolate differe...  ...   
4        1  What stood out to me the most is that we are n...  ...   

  interest_full_film  geographic_place self_geographic_place  \
0                  4                 2                     2   
1                  3                 2                     1   
2                  5                 2                     2   
3                  2                 1                     4   
4                  5                 4                     1   

  self_geographic_place_other  science_proximity  ses_class  \
0                         -99                  5          3   
1                         -99                  6          3   
2                         -99                 10          3   
3                         -99                 10          2   
4                         -99                  9          2   

   self_working_class       RESPONDENT_ID    chapter  \
0                   3  iPa8503af03bb284a8    atacama   
1                   1  iPb4802d8779fc7ac9  greenland   
2                   1  iPe86aa9eb73b9c47b      seoul   
3                   1  iP303583bbd989478e  greenland   
4                   2  iP2a6138fe72ec5982      maine   

   FL_11 - Block Randomizer - Display Order  
0                      Trust|Valuealignment  
1                      Trust|Valuealignment  
2                      Valuealignment|Trust  
3                      Valuealignment|Trust  
4                      Trust|Valuealignment  

[5 rows x 51 columns]

<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>id</th>
      <th>age</th>
      <th>born_usa</th>
      <th>car_ownership</th>
      <th>children</th>
      <th>country</th>
      <th>division</th>
      <th>economic_political_ideology</th>
      <th>education</th>
      <th>employment</th>
      <th>...</th>
      <th>sexual_orientation</th>
      <th>social_media_accounts</th>
      <th>social_media_used</th>
      <th>social_political_ideology</th>
      <th>state</th>
      <th>vehicle_types</th>
      <th>voter_registration_usa</th>
      <th>yob</th>
      <th>yob_and_gender_of_children</th>
      <th>zip</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>iPa45d79f9c87e178d</td>
      <td>20</td>
      <td>1.0</td>
      <td>1.0</td>
      <td>2.0</td>
      <td>NaN</td>
      <td>2.0</td>
      <td>5.0</td>
      <td>3.0</td>
      <td>5.0</td>
      <td>...</td>
      <td>1.0</td>
      <td>NaN</td>
      <td>11;4;5</td>
      <td>3.0</td>
      <td>NY</td>
      <td>1</td>
      <td>1.0</td>
      <td>2005</td>
      <td>99</td>
      <td>13027.0</td>
    </tr>
    <tr>
      <th>1</th>
      <td>iPce757c0b555226fe</td>
      <td>25</td>
      <td>1.0</td>
      <td>99.0</td>
      <td>1.0</td>
      <td>NaN</td>
      <td>8.0</td>
      <td>7.0</td>
      <td>1.0</td>
      <td>5.0</td>
      <td>...</td>
      <td>6.0</td>
      <td>NaN</td>
      <td>16;14;11;19;15;3;2;5;13;1;4;10;17;9;12</td>
      <td>7.0</td>
      <td>NM</td>
      <td>1</td>
      <td>1.0</td>
      <td>2000</td>
      <td>12021</td>
      <td>87401.0</td>
    </tr>
    <tr>
      <th>2</th>
      <td>iP6de79d6fcf6b13da</td>
      <td>69</td>
      <td>1.0</td>
      <td>1.0</td>
      <td>2.0</td>
      <td>NaN</td>
      <td>9.0</td>
      <td>4.0</td>
      <td>3.0</td>
      <td>2.0</td>
      <td>...</td>
      <td>1.0</td>
      <td>NaN</td>
      <td>2;19;9;3;18;13;8;10;5;16</td>
      <td>6.0</td>
      <td>OR</td>
      <td>1;3</td>
      <td>1.0</td>
      <td>1956</td>
      <td>99</td>
      <td>97063.0</td>
    </tr>
    <tr>
      <th>3</th>
      <td>iPadc006bad3ec1177</td>
      <td>60</td>
      <td>1.0</td>
      <td>99.0</td>
      <td>1.0</td>
      <td>NaN</td>
      <td>2.0</td>
      <td>6.0</td>
      <td>2.0</td>
      <td>1.0</td>
      <td>...</td>
      <td>1.0</td>
      <td>NaN</td>
      <td>19;2;13;4</td>
      <td>5.0</td>
      <td>NY</td>
      <td>1</td>
      <td>1.0</td>
      <td>1965</td>
      <td>99</td>
      <td>13350.0</td>
    </tr>
    <tr>
      <th>4</th>
      <td>iP63c1310b0ad9e925</td>
      <td>34</td>
      <td>2.0</td>
      <td>99.0</td>
      <td>2.0</td>
      <td>NaN</td>
      <td>5.0</td>
      <td>4.0</td>
      <td>7.0</td>
      <td>5.0</td>
      <td>...</td>
      <td>1.0</td>
      <td>NaN</td>
      <td>1;2;10;11;13;4;9;3;5;19;12</td>
      <td>4.0</td>
      <td>MD</td>
      <td>99</td>
      <td>1.0</td>
      <td>1991</td>
      <td>99</td>
      <td>20707.0</td>
    </tr>
  </tbody>
</table>
<p>5 rows × 41 columns</p>
</div>

                   id  age  born_usa  car_ownership  children  country  \
0  iPa45d79f9c87e178d   20       1.0            1.0       2.0      NaN   
1  iPce757c0b555226fe   25       1.0           99.0       1.0      NaN   
2  iP6de79d6fcf6b13da   69       1.0            1.0       2.0      NaN   
3  iPadc006bad3ec1177   60       1.0           99.0       1.0      NaN   
4  iP63c1310b0ad9e925   34       2.0           99.0       2.0      NaN   

   division  economic_political_ideology  education  employment  ...  \
0       2.0                          5.0        3.0         5.0  ...   
1       8.0                          7.0        1.0         5.0  ...   
2       9.0                          4.0        3.0         2.0  ...   
3       2.0                          6.0        2.0         1.0  ...   
4       5.0                          4.0        7.0         5.0  ...   

  sexual_orientation social_media_accounts  \
0                1.0                   NaN   
1                6.0                   NaN   
2                1.0                   NaN   
3                1.0                   NaN   
4                1.0                   NaN   

                        social_media_used  social_political_ideology  state  \
0                                  11;4;5                        3.0     NY   
1  16;14;11;19;15;3;2;5;13;1;4;10;17;9;12                        7.0     NM   
2                2;19;9;3;18;13;8;10;5;16                        6.0     OR   
3                               19;2;13;4                        5.0     NY   
4              1;2;10;11;13;4;9;3;5;19;12                        4.0     MD   

   vehicle_types  voter_registration_usa   yob  yob_and_gender_of_children  \
0              1                     1.0  2005                          99   
1              1                     1.0  2000                       12021   
2            1;3                     1.0  1956                          99   
3              1                     1.0  1965                          99   
4             99                     1.0  1991                          99   

       zip  
0  13027.0  
1  87401.0  
2  97063.0  
3  13350.0  
4  20707.0  

[5 rows x 41 columns]

<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>sexual_orientation</th>
      <th>social_media_accounts</th>
      <th>social_media_used</th>
      <th>social_political_ideology</th>
      <th>state</th>
      <th>vehicle_types</th>
      <th>voter_registration_usa</th>
      <th>yob</th>
      <th>yob_and_gender_of_children</th>
      <th>zip</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>2025-03-22 09:37:15</td>
      <td>2025-03-22 10:06:03</td>
      <td>0</td>
      <td>100</td>
      <td>1727</td>
      <td>1</td>
      <td>2025-03-22 10:06:03.466</td>
      <td>R_59vk9us5U8IP3gf</td>
      <td>1</td>
      <td>What stood out to me the most about the clip w...</td>
      <td>...</td>
      <td>1.0</td>
      <td>NaN</td>
      <td>13;18;3;10;5;4;9;2;8;11;1;19</td>
      <td>2.0</td>
      <td>NJ</td>
      <td>1</td>
      <td>1.0</td>
      <td>1993</td>
      <td>99</td>
      <td>8093.0</td>
    </tr>
    <tr>
      <th>1</th>
      <td>2025-03-22 09:37:17</td>
      <td>2025-03-22 09:58:44</td>
      <td>0</td>
      <td>100</td>
      <td>1286</td>
      <td>1</td>
      <td>2025-03-22 09:58:44.783</td>
      <td>R_6JggRfb6ow9nZfc</td>
      <td>1</td>
      <td>I was more interested in the Inuet culture and...</td>
      <td>...</td>
      <td>1.0</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>5.0</td>
      <td>NJ</td>
      <td>NaN</td>
      <td>1.0</td>
      <td>1986</td>
      <td>99</td>
      <td>7035.0</td>
    </tr>
    <tr>
      <th>2</th>
      <td>2025-03-22 09:37:37</td>
      <td>2025-03-22 09:57:50</td>
      <td>0</td>
      <td>100</td>
      <td>1213</td>
      <td>1</td>
      <td>2025-03-22 09:57:55.730</td>
      <td>R_5tMxxNsXZ6QDuLj</td>
      <td>1</td>
      <td>-99</td>
      <td>...</td>
      <td>1.0</td>
      <td>NaN</td>
      <td>4;10;19;11</td>
      <td>4.0</td>
      <td>IL</td>
      <td>1</td>
      <td>1.0</td>
      <td>1996</td>
      <td>22019;22018</td>
      <td>62203.0</td>
    </tr>
    <tr>
      <th>3</th>
      <td>2025-03-22 09:37:47</td>
      <td>2025-03-22 10:01:50</td>
      <td>0</td>
      <td>100</td>
      <td>1443</td>
      <td>1</td>
      <td>2025-03-22 10:01:50.785</td>
      <td>R_5lKeFwUGE7lDwGh</td>
      <td>1</td>
      <td>The red frame that was used to isolate differe...</td>
      <td>...</td>
      <td>1.0</td>
      <td>NaN</td>
      <td>10;13;16;3;18;2;9;8;4;11;19</td>
      <td>3.0</td>
      <td>TX</td>
      <td>1</td>
      <td>1.0</td>
      <td>1998</td>
      <td>12021</td>
      <td>76031.0</td>
    </tr>
    <tr>
      <th>4</th>
      <td>2025-03-22 09:37:48</td>
      <td>2025-03-22 09:53:02</td>
      <td>0</td>
      <td>100</td>
      <td>914</td>
      <td>1</td>
      <td>2025-03-22 09:53:03.277</td>
      <td>R_6uPZbRrXC8qBe2Z</td>
      <td>1</td>
      <td>What stood out to me the most is that we are n...</td>
      <td>...</td>
      <td>1.0</td>
      <td>11;2;3;4;13;19;9;10</td>
      <td>4;19;18;5;2;12;3;9;13;11;10</td>
      <td>4.0</td>
      <td>WI</td>
      <td>1</td>
      <td>1.0</td>
      <td>1974</td>
      <td>99</td>
      <td>53206.0</td>
    </tr>
  </tbody>
</table>
<p>5 rows × 92 columns</p>
</div>

           Start Date            End Date  Response Type  Progress  \
0 2025-03-22 09:37:15 2025-03-22 10:06:03              0       100   
1 2025-03-22 09:37:17 2025-03-22 09:58:44              0       100   
2 2025-03-22 09:37:37 2025-03-22 09:57:50              0       100   
3 2025-03-22 09:37:47 2025-03-22 10:01:50              0       100   
4 2025-03-22 09:37:48 2025-03-22 09:53:02              0       100   

   Duration (in seconds)  Finished           Recorded Date        Response ID  \
0                   1727         1 2025-03-22 10:06:03.466  R_59vk9us5U8IP3gf   
1                   1286         1 2025-03-22 09:58:44.783  R_6JggRfb6ow9nZfc   
2                   1213         1 2025-03-22 09:57:55.730  R_5tMxxNsXZ6QDuLj   
3                   1443         1 2025-03-22 10:01:50.785  R_5lKeFwUGE7lDwGh   
4                    914         1 2025-03-22 09:53:03.277  R_6uPZbRrXC8qBe2Z   

   consent                                          stood_out  ...  \
0        1  What stood out to me the most about the clip w...  ...   
1        1  I was more interested in the Inuet culture and...  ...   
2        1                                                -99  ...   
3        1  The red frame that was used to isolate differe...  ...   
4        1  What stood out to me the most is that we are n...  ...   

  sexual_orientation  social_media_accounts             social_media_used  \
0                1.0                    NaN  13;18;3;10;5;4;9;2;8;11;1;19   
1                1.0                    NaN                           NaN   
2                1.0                    NaN                    4;10;19;11   
3                1.0                    NaN   10;13;16;3;18;2;9;8;4;11;19   
4                1.0    11;2;3;4;13;19;9;10   4;19;18;5;2;12;3;9;13;11;10   

  social_political_ideology  state  vehicle_types  voter_registration_usa  \
0                       2.0     NJ              1                     1.0   
1                       5.0     NJ            NaN                     1.0   
2                       4.0     IL              1                     1.0   
3                       3.0     TX              1                     1.0   
4                       4.0     WI              1                     1.0   

    yob  yob_and_gender_of_children      zip  
0  1993                          99   8093.0  
1  1986                          99   7035.0  
2  1996                 22019;22018  62203.0  
3  1998                       12021  76031.0  
4  1974                          99  53206.0  

[5 rows x 92 columns]

7. Merge in the demographics data.

Load the dataset

Row many rows are there in `RESPONDENT_ID`

Load this excel file into a new dataframe called demographics.

Merge the variables from the demographics dataframe into the df dataframe by doing a 1:1 match on the `RESPONDENT_ID` column in df and the `id` column in demographics.

show head of df

save the df_merged dataframe as a new excel file called chapter_study_finished_cleaned_merged