Resolved: fill missing value based on index

Question:

i try to percentace missing value like this
and filter like this

null_column = null[(null>= 10.0) & (null <= 40.0)].index [/code]

the output type is index
how can i using fillna to replace median in every column based on index
my code before like this

null_column = null[(null>= 10.0) & (null <= 40.0)].index data.fillna(percent_column2.median(), inplace=True) [/code]

the result always

index doesnt have median

but when i deleted index it works but the median that replaced is not median in every column. But, median that 2 values of percentage missing value not in original dataframe. How can i fill nan value based on index to replace in original data frame?

Answer:

I guess something like this:

data = pd.DataFrame([[0,1,np.nan],[np.nan,1,np.nan],[1,np.nan,2],[23,12,3],[1,3,1]])
cols = list(null[(null>=10) & (null<=40)].index) data.iloc[:, cols] = data.iloc[:, cols].fillna(data.iloc[:, cols].median(), inplace=False) [/code]

If you have better answer, please add a comment about this, thank you!