title: Administer randomly nan values in dataframe
body: <p>Update :
  I woud like randomly administrer NaN values ​​into my dataset for each column taking into account the null values ​​already in my starting data.</p>
  
  <p>At the begening i have to calculate for each columns the NaN values rate contained in my data :</p>
  
  <pre><code>{'A': 0.1, 'B': 0.0, 'C': 0.47, 'D': 0.0, 'E': 0.41, 'F': 0.0}
  </code></pre>
  
  <p>Now i woud like to introduce randomly NaN values ​​by column to up :</p>
  
  <p>'nan_percent':</p>
  
  <pre><code>{'A': 0.15, 'B': 0.0, 'C': 0.9, 'D': 0.5, 'E': 0.41, 'F': 0.2}
  </code></pre>
  
  <p>Why I do that ? Is to have data that is more looks like the reality of my studie problem.</p>
  
  <p>An i try this code :</p>
  
  <pre><code>df = df.mask(np.random.choice([True, False], size=df.shape, p= nan_percent))
  </code></pre>
  
  <p>I have an error :</p>
  
  <pre><code>TypeError: float() argument must be a string or a number, not 'dict'
  </code></pre>
  
  <p>How to administer to each column the right percentage of nan values dandomly via the dict "nan_percent" ?</p>