title: Computationally efficient date addition (Python)
body: <p>I have a pandas dataframe with ~42,000,000 rows and 6 columns. The index column is a timestamp, and there exists a date column of type datetime64 ("<code>data['settle']</code>"). I'm trying to run the following code to add a business day to the date if the 'holiday' column returns "1". </p>
  
  <pre><code>for i in range(len(data['settle'])-1):
      if data['holiday'].iloc[i] == 1:
          data['settle'].iloc[i] = data['settle'].iloc[i] + pd.tseries.offsets.BDay(1)
      else:
          pass
  </code></pre>
  
  <p>The only issue is that this takes a very long time to return anything (over 30 minutes!) and I'm running it on decent hardware. I can't split this to more hardware via spark or similar solution as this is an enterprise environment. How might I make this code run more quickly?</p>