title: Create a Dictionary from dataframe with first column as keys and remaining as values
body: <p>I am trying to create a dictionary that has the elements of the first column of a dataframe as the keys and the remaining columns as values. My dataframe <code>test_df</code> has on its first column the names of the images and the rest contain scores for each image (see code below). The goal is to create a variable that contains a key-value pair which maps the image name (key) to the labels (values).</p>
  <pre><code>print(test_df)
  
      1.jpg   0.21337     0.83585 0.13824     0.16486
  0   101.jpg 0.087876    0.86553 0.038267    0.046497
  1   106.jpg 0.231350    0.73344 0.038267    0.164860
  2   107.jpg 0.406980    0.56384 0.862520    0.164860
  3   109.jpg 0.257200    0.25579 0.686770    0.046497
  </code></pre>
  <p>So what I want to do is something like this:</p>
  <pre><code>dict = {'1.jpg': 0.21337 0.83585 0.13824 0.16486
          '101.jpg': 0.087876 0.86553 0.038267 0.046497....
          '106.jpg':.......etc}
  </code></pre>
  <p>but the closest thing I got is</p>
  <pre><code>print(test_df.transpose().to_dict())
  
   {0: {'1.jpg': '101.jpg', '0.21337': 0.087876, '0.83585': 0.8655299999999999, '0.13824': 0.038267, '0.16486': 0.046497000000000004}, 1: {'1.jpg': '106.jpg', '0.21337': 0.23135, '0.83585': 0.73344, '0.13824': 0.038267, '0.16486': 0.16485999999999998},...
  </code></pre>
  <p>I also tried this but did not work well</p>
  <pre><code>dict = {k: v for k, v in zip(test_df.iloc[:,0], test_df.iloc[0,1:])}
  </code></pre>
  <p>I don't have a lot of experience on dictionaries so I would appreciate any help.
  Thank you in advance</p>