replace all floats in df with corresponding index name

Question

I want to replace all values in my df that are float (excluding nans), with the name of the index of the corresponding row.

I have this:

index1                10.0                          190.6   
index2                17.9                          NaN   
index3                NaN                           8.0
index4                9.0                           70.0

I want to have this:

index1                index1                        index1                
index2                index2                        NaN   
index3                NaN                           index3                
index4                index4                        index4

Any ideas?

Asked By: Shuman_tov

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Source

Answer 1

Technically, np.nan is also float. If you want to replace non-null values with the index values, you can use df.where:

output = df.where(df.isna(), df.index.tolist())

Output:

           1     2
0       
index1  index1  index1
index2  index2  NaN
index3  NaN index3
index4  index4  index4

Answered By: Nuri Taş

Answer 2

if you want to do it for all columns of your df:

for column in df.columns:

    df[column] = [e for e in df.index if df[column].notna]

If you want to do it for some columns, replace df.columns for a list with the columns you want to handle

Regards,

Answered By: Gabino Antuña Ortiz

replace all floats in df with corresponding index name

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