title: Addition of days to all the date columns in pandas using for loop
body: <p>I have a <code>dataframe</code> of date strings which is a <code>subset</code> of big <code>data frame</code>.The first 5 <code>rows</code> of this <code>dataframe</code> are</p>
  <pre><code>dates_df = pd.DataFrame(
      {'date1':['2020-06-16','2020-06-16','2020-06-17','2020-06-21','2020-06-11'],
       'date2':['2020-06-10','2020-06-10','2020-06-10','2020-06-10','2020-06-10'],
       'date3':['2018-12-20','2018-12-19','2019-09-20','2019-05-08','2020-06-13'],
       'date4':['2020-07-07','2020-06-30','2020-07-01','2020-07-03','2020-07-24']})
  </code></pre>
  <p>I have <code>declared</code> a <code>variable</code> called <code>new_date='2020-06-29'</code></p>
  <p><code>Define a variable</code> called <code>diff_date</code> such that <code>diff_date=new_date-dates_df['date2']</code>
  Then this <code>diff_date</code> should be added to all the <code>date values</code> in each <code>date column</code>which should be my <code>final_df</code>.
  The steps I have taken so far are converting these values to <code>pd.to_datetime()</code> and got the difference also. Got final df with the given answer given.
  ############################
  Modified the above data frame a bit and wrote a function like this.</p>
  <pre><code>dates_df=pd.DataFrame(
   {'date1':['2020-06-16','2020-06-16','2020-06-17','2020-06-21','2020-06-    
   11'],'date2':['2020-06-10','2020-08-10','2020-06-10','2020-09-13','2020-06- 
   10'],'date3':['2018-12-20','2018-12-19','2019-09-20','2019-05-08','2020-06- 
   13'],'date4':['2020-07-07','2020-06-30','2020-07-01','2020-07-03','2020-07- 
   24']}) 
  
  def datechange_func(dataset,variablelist,new_run_date,temp_run_date=None):
     dataset[variablelist]=dataset[variablelist].apply(pd.to_datetime)
     li= list(dataset['date2'].unique())
     if dataset.loc[dataset['date2'].any().isin(li)]:
         dataset['date2'] = max(li)
     else:
         dataset['date2'] = temp_run_date
  
     diff = new_run_date - dataset['date2']
  
     dataset[variablelist]=dataset[variablelist].add(diff,axis=0)
  
     return dataset
  </code></pre>
  <p><code>variablelist1=['date1', 'date2', 'date3', 'date4']</code>
  <code>final_df=datechange_func(dates_df,variablelist1,new_run_date,temp_run_date=None)</code></p>
  <p>It should <code>update dates_df['date2']</code> to get the <code>maximum unique value</code> in all the rows of <code>date2 column</code>
  But I get this error
  <code>TypeError: invalid_op() got an unexpected keyword argument 'skipna'</code>
  How to rectify this?</p>