Pandas Python update column with another row value

Question

I have à dataframe with millions of row. As example of my dataframe :

Col0, Col1, Col2, Col3
Val0, Val1, Nan, Nan
Val0, Nan, Val3, Nan
Val0, Nan, Nan, Val5

My desired output is :

Col0, Col1, Col2, Col3
Val0, Val1, Val3, Val5

I make an iteration request for the desired output but this take hours.

Regards

Serge de Gosson de Varennes · Accepted Answer · 2020-11-27 05:46:25Z

1

It is unclear to me what the advantage of doing this would be unless your df simply is a list in which there is no realtion between columns, but here is a solution to this:

for this df:

 Col0  Col1  Col2  Col3
0     3     5   Nan   Nan
1     3   Nan    12   Nan
2     3   Nan   Nan    17

do this

pd.concat([testcol[col].sort_values().reset_index(drop=True) for col in testcol], axis=1, ignore_index=True)

which gives

   0     1     2     3
0  3     5    12    17
1  3   Nan   Nan   Nan
2  3   Nan   Nan   Nan

answered Nov 27, 2020 at 5:46

Serge de Gosson de Varennes

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2 Comments

Jan Christoph Terasa Over a year ago

If you drop all but the first row this is the answer. Though pretty pointless using a DataFrame for that, as you rightly pointed out

Serge de Gosson de Varennes Over a year ago

Yes. I thought the nan row drop could be left to the asker as it doesn't demand any effort.

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