title: How to deal with "divide by zero" with pandas dataframes when manipulating columns?
body: <p>I'm working with hundreds of pandas dataframes. A typical dataframe is as follows:</p>
  
  <pre><code>import pandas as pd
  import numpy as np
  data = 'filename.csv'
  df = pd.DataFrame(data)
  df 
  
          one       two     three  four   five
  a  0.469112 -0.282863 -1.509059  bar   True
  b  0.932424  1.224234  7.823421  bar  False
  c -1.135632  1.212112 -0.173215  bar  False
  d  0.232424  2.342112  0.982342  unbar True
  e  0.119209 -1.044236 -0.861849  bar   True
  f -2.104569 -0.494929  1.071804  bar  False
  ....
  </code></pre>
  
  <p>There are certain operations whereby I'm dividing between columns values, e.g. </p>
  
  <pre><code>df['one']/df['two'] 
  </code></pre>
  
  <p>However, there are times where I am dividing by zero, or perhaps both    </p>
  
  <pre><code>df['one'] = 0
  df['two'] = 0
  </code></pre>
  
  <p>Naturally, this outputs the error: </p>
  
  <pre><code>ZeroDivisionError: division by zero
  </code></pre>
  
  <p>I would prefer for 0/0 to actually mean "there's nothing here", as this is often what such a zero means in a dataframe.</p>
  
  <p>(a) How would I code this to mean "divide by zero" is 0 ?</p>
  
  <p>(b) How would I code this to "pass" if divide by zero is encountered? </p>