title: Iterate over pandas dataframe and update values in columns for a specific condition
body: <p>I have a Pandas dataframe with <code>checkdataframe.shape (68125, 109)</code>. I want to perform a Operation in all the columns like I did it below for a single list.</p>
  <pre><code>def alter_column(column,batchSize=10):
  return_list=[]
  for idx,value in enumerate(column): 
          if (idx+1)%batchSize==1: 
              return_list.append(value)
          else:
              return_list.append(np.nan)
  return return_list
  </code></pre>
  <p>which Returns a list with values removed over certain intervals of 10 like this Output</p>
  <pre><code>['175,5200',nan,nan,nan,nan,nan,nan,nan,nan,nan,'175,5200',nan,nan,nan,nan,nan,nan,nan,nan,nan,'180,0000']
  </code></pre>
  <p>I wanted it to do it over entire dataframe . i tried df.iteritems and df.iterrows but it Shows error. Any possible solution or way to do it?</p>
  <pre><code>eg:df['column1']=[1,1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,2,2,2]
     df['column2']=[3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4]
  expected_output:
  column1=['1',nan,nan,nan,nan,nan,nan,nan,nan,nan,'2',nan,nan,nan,nan,nan,nan,nan,nan,nan] column2=['3',nan,nan,nan,nan,nan,nan,nan,nan,nan,'4',nan,nan,nan,nan,nan,nan,nan,nan,nan]   
  </code></pre>
  <p>But my real dataset has 109 columns</p>