title: Calculate distribution of negative values per numerical column in df
body: <p>What is a quick way to compute the % of negative values in a dataframe for each numerical column that has at least one negative value?</p>
  <p>Currently I am able to calcuate it for each numerical value.</p>
  <pre><code>for i in range(1,len(df.columns)):
    if df.dtypes[df.columns[i]] in ['float64','int64','float32','int32']:
      negatives = np.sum(np.array(df.iloc[:,[i]] &lt; 0))
      negativesP= &quot;{:.2%}&quot;.format(negatives/len(df))
      print(df.columns[i], &quot;: \n&quot;, negatives, &quot;\t&quot;, negativesP)
  </code></pre>