<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>Word</th>
      <th>Similar Words</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>inspired</td>
      <td>['compelling', 'discovery', 'inspired', 'inspi...</td>
    </tr>
    <tr>
      <th>1</th>
      <td>disapproving</td>
      <td>['disappointing', 'stupid', 'hate', 'fruitless']</td>
    </tr>
    <tr>
      <th>2</th>
      <td>confused</td>
      <td>['losing', 'confused', 'lost', 'meandering', '...</td>
    </tr>
    <tr>
      <th>3</th>
      <td>annoyed</td>
      <td>['annoying']</td>
    </tr>
    <tr>
      <th>4</th>
      <td>approving</td>
      <td>['approve', 'pleasant', 'excellent', 'cool', '...</td>
    </tr>
  </tbody>
</table>
</div>

           Word                                      Similar Words
0      inspired  ['compelling', 'discovery', 'inspired', 'inspi...
1  disapproving   ['disappointing', 'stupid', 'hate', 'fruitless']
2      confused  ['losing', 'confused', 'lost', 'meandering', '...
3       annoyed                                       ['annoying']
4     approving  ['approve', 'pleasant', 'excellent', 'cool', '...

stdout

Touched: ['affection', 'cherish', 'love', 'loving', 'touched', 'touching', 'sweet']
Approving: ['approve', 'pleasant', 'excellent', 'cool', 'good', 'perfect', 'splendid']
Captivated: ['beautiful', 'beauty', 'gorgeous', 'engaged', 'engaging', 'fascinated', 'fascinating', 'fascination', 'miraculous', 'overwhelming', 'immense', 'infinite', 'intense', 'insignificant', 'wonderful', 'unlimited']


<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>Word</th>
      <th>Similar Words</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>31</th>
      <td>ashamed</td>
      <td>['shame']</td>
    </tr>
    <tr>
      <th>32</th>
      <td>disgusted</td>
      <td>['filthy', 'creepy']</td>
    </tr>
    <tr>
      <th>33</th>
      <td>convivial</td>
      <td>['friendly', 'friendship']</td>
    </tr>
    <tr>
      <th>34</th>
      <td>beautystruck</td>
      <td>['beauty', 'beautiful']</td>
    </tr>
    <tr>
      <th>35</th>
      <td>passionate</td>
      <td>['passionate', 'passion']</td>
    </tr>
  </tbody>
</table>
</div>

            Word               Similar Words
31       ashamed                   ['shame']
32     disgusted        ['filthy', 'creepy']
33     convivial  ['friendly', 'friendship']
34  beautystruck     ['beauty', 'beautiful']
35    passionate   ['passionate', 'passion']

18. Iterating on the list of emotion words after manual review of 10% of the stood_out responses for all matches

Load this file

export an updated csv file called emotion_words_6.csv

add a new row in the CSV file with the word "passionate" with similar words listed as "passionate" and "passion." remove "passionate" and "passion" from the list of similar words to "captivated"

yes