title: How to bin nan values using pd.cut
body: <p>I am trying to write a code that creates bins from a dataframe(account_raw) that contains blank values. My problem is that python bins blank values with my first bin label: 0 - 25k. What I want ot do is to create a separate bin for blank values.Any ideas how to fix this?Thanks</p>
  
  <pre><code>Bucket = [0, 25000, 50000, 100000, 200000, 300000, 999999999999]
  Label = ['0k to 25k', '25k - 50k', '50k - 100k', '100k - 200k', '200k - 300k', 'More than 300k']
     account_raw['LoanGBVBuckets'] = pd.cut(account_raw['IfrsBalanceEUR'],bins=ls_LoanGBVBucket,                                        labels=ls_LoanGBVBucketLabel, include_lowest= True).astype(str)
  </code></pre>