Fillna is not working in pandas DataFrame-CodePudding

I have a DataFrame where some columns have NaNs values, but when I try to replace it by zero values with fillna(), It doesn't work.

print(df_sample[["Cantidad_GofrePack_lag8_rol7_med", 'Cantidad_AdultoGeneral_lag8_rol7_med']].head(5))

   Cantidad_GofrePack_lag8_rol7_med  Cantidad_AdultoGeneral_lag8_rol7_med
0                               NaN                                   NaN
1                               NaN                                   NaN
2                               NaN                                   NaN
3                               NaN                                   NaN

others_cols_with_missing = ["Cantidad_GofrePack_lag8_rol7_med", 'Cantidad_AdultoGeneral_lag8_rol7_med', (...others columns more)]
df_sample[others_cols_with_missing].fillna(value=0.0, inplace = True)
print(df_sample[["Cantidad_GofrePack_lag8_rol7_med", 'Cantidad_AdultoGeneral_lag8_rol7_med']].head(5))

   Cantidad_GofrePack_lag8_rol7_med  Cantidad_AdultoGeneral_lag8_rol7_med
0                               NaN                                   NaN
1                               NaN                                   NaN
2                               NaN                                   NaN
3                               NaN                                   NaN

I'm not getting any change, why?

CodePudding user response：

It looks like inplace=True cannot be used for only a part of the DataFrame, like on the example, where only a few columns are gived to the fillna(), because it creates a copy but only of this part, not for the whole DataFrame, where the NaN remain.

It works properly in this way:

df_sample[others_cols_with_missing] = df_sample[others_cols_with_missing].fillna(value=0, inplace = False, axis=1)

and now, here it is:

   Cantidad_GofrePack_lag8_rol7_med  Cantidad_AdultoGeneral_lag8_rol7_med
0                               0.0                                   0.0
1                               0.0                                   0.0
2                               0.0                                   0.0
3                               0.0                                   0.0

CodePudding user response：

inplace fillna with multiple columns does not work for some reasons https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy

you can do without inplace like this

dframe[['A', 'B']] = dframe[['A', 'B']].fillna(0.0)

or you can fillna all columns

dframe = dframe.fillna(0.0)