Inserting Rows for some missing columns in Pandas Dataframe

Question

My Dataframe looks like this and i have to insert a few rows

 Date     AccessType    PrePaidSubsRev
 2013-11-01  1    584190
 2013-11-01  2    0
 2013-11-02  1    800020
 2013-11-02  2    0
 2013-11-03  1    705800
 2013-11-03  2    0
 2013-11-04  1    699930
 2013-11-04  3    0
 2013-11-04  2    0
 2013-11-05  1    963270
 2013-11-05  3    0
 2013-11-05  2    0
 2013-11-06  1    874530
 2013-11-06  3    0
 2013-11-06  2    0
 2013-11-07  1    886005
 2013-11-07  2    0
 2013-11-08  1    1209300
 2013-11-08  3    0
 2013-11-08  2    0
 2013-11-09  1    762560
 2013-11-09  2    0
 2013-11-10  1    489730
 2013-11-10  2    0

For dates where the accesstype 3 is missing i have to insert rows with the same date and accesstype as 3 and PrePaidSubsRev value as 0 .

If someone has any idea please go ahead.

roman · Accepted Answer · 2013-12-04 07:51:22Z

2

>>> group = df.groupby(['Date','AccessType']).sum()
>>> temp = group.unstack()
>>> temp = temp.replace('nan',0)
>>> temp = temp1.stack()
>>> df = temp.reset_index()

This part worked for me..Thanks

edited Dec 4, 2013 at 7:51

roman

118k30 gold badges205 silver badges209 bronze badges

answered Dec 4, 2013 at 6:33

itsaruns

6692 gold badges11 silver badges16 bronze badges

Sign up to request clarification or add additional context in comments.

2 Comments

itsaruns Over a year ago

Hi i tried it out in Python 2.6.6 the replace command does not work there ,but in python 2.7 it works fine ..any help please feel free

itsaruns Over a year ago

The part temp = temp.replace('nan',0) is not working ,its not replacing nan with 0 in the groupby object and thanks for the response Roman

Collectives™ on Stack Overflow

Inserting Rows for some missing columns in Pandas Dataframe

1 Answer 1

2 Comments

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

2 Comments

Your Answer

Sign up or log in

Post as a guest

Related