Hi Samo,
Thanks a lot. It works at a row level and I can append it a row level to
the main dataframe to do further analysis.
Regards,
Sanant
On Wed, Oct 5, 2016 at 5:05 PM, Samo Turk wrote:
> Something like this might work:
>
> def non_zero(row, columns):
> return list(columns[~(row == 0)]
Hi Sanant and Samo,
Even easier and faster solution:
> df.columns[(df.values != 0).any(axis=0)]
Or if some reason != 0 does not work for you:
> df.columns[(~(df.values == 0)).any(axis=0)]
Pozdrawiam, | Best regards,
Maciek Wójcikowski
[email protected]
2016-10-05 13:35 GMT+02:00 Sa
Something like this might work:
def non_zero(row, columns):
return list(columns[~(row == 0)])
df.apply(lambda x: non_zero(x, df.columns), axis=1)
Cheers,
Samo
On Wed, Oct 5, 2016 at 11:58 AM, Startup Hire
wrote:
> Hi Pypers,
>
> Hope you are doing well.
>
> I am working on a project to fi
Hi Pypers,
Hope you are doing well.
I am working on a project to find out the column names of non-zero values
at a row level.
How can this effectively done in python pandas/dataframe?
For example,
*Column1* *Column *2 *Column *3 Column 4 Column 5 Column 6 *Column 7* New
column t
