python - Looking for a pandas function analogous to DataFrame.nafill() -

i apply function acts fillna() takes different value nan. unfortunately dataframe.replace() not work in case. here example: given dataframe:

    df = pd.dataframe([[1,2,3],[4,-1,-1],[5,6,-1]])         0    1    2     0  1  2.0  3.0     1  4 -1.0 -1.0     2  5  6.0 -1.0     3  7  8.0  nan 

i looking function output:

       0    1    2     0  1  2.0  3.0     1  4  2.0  3.0     2  5  6.0  3.0     3  7  8.0  nan 

so df.replace() to_replace=-1 , 'method='ffill' not work because requires column-independent value replace -1 entries. in example column-dependent. know can code loop looking efficient code applied large dataframe. suggestions? thank you.

you can replace value nan , call ffill:

in [3]:  df.replace(-1, np.nan).ffill() out[3]:    0  1  2 0  1  2  3 1  4  2  3 2  5  6  3 

i think you're on thinking this

edit

if have nan values create boolean mask , update elements again ffill on inverse of mask:

in [15]:     df[df == -1] = df[df != -1].ffill() df  out[15]:    0  1   2 0  1  2   3 1  4  2   3 2  5  6   3 3  7  8 nan 

another method (thanks @dsm in comments) use where same thing above:

in [17]: df.where(df != -1, df.replace(-1, np.nan).ffill())  out[17]:    0  1   2 0  1  2   3 1  4  2   3 2  5  6   3 3  7  8 nan