How to replace NaN values in a dataframe column

I have a Pandas Dataframe as below:

      itm Date                  Amount 
67    420 2012-09-30 00:00:00   65211
68    421 2012-09-09 00:00:00   29424
69    421 2012-09-16 00:00:00   29877
70    421 2012-09-23 00:00:00   30990
71    421 2012-09-30 00:00:00   61303
72    485 2012-09-09 00:00:00   71781
73    485 2012-09-16 00:00:00     NaN
74    485 2012-09-23 00:00:00   11072
75    485 2012-09-30 00:00:00  113702
76    489 2012-09-09 00:00:00   64731
77    489 2012-09-16 00:00:00     NaN

When I try to apply a function to the Amount column, I get the following error:

ValueError: cannot convert float NaN to integer

I have tried applying a function using math.isnan, pandas' .replace method, .sparse data attribute from pandas 0.9, if NaN == NaN statement in a function; I have also looked at this Q/A; none of them works.

How do I do it?

← Назад к списку