I have a DF like this, it's a transposed DF (pd.transpose()) :
0 1 2
COL_5 NaN NaN NaN
COL_4 NaN NaN 4
COL_3 NaN 12 7
COL_2 15 4 11
COL_1 7 8 9
I want to replace the NaN's with the values below :
0 1 2
COL_5 15 12 4
COL_4 7 4 7
COL_3 8 11
COL_2 9
COL_1
I don't know how to do it...
CodePudding user response:
You can use:
out = (df
.apply(lambda c: pd.Series(c.dropna().to_numpy()))
.reindex(range(len(df)))
.set_axis(df.index)
)
Better alternative if you only have the NaNs at the top and no more afterwards:
out = df.apply(lambda c: c.shift(-c.isna().sum()))
output:
0 1 2
COL_5 15.0 12.0 4.0
COL_4 7.0 4.0 7.0
COL_3 NaN 8.0 11.0
COL_2 NaN NaN 9.0
COL_1 NaN NaN NaN