python - Divide all rows in a pandas dataframe by a specific row -


i have pandas dataframe below:

   sample_name  c14-cer_mean  c16-cer_mean  c18-cer_mean  c18:1-cer_mean  0          1 1      0.124749      0.285659     35.302029        8.173144    1         1 10      0.332976      0.656197     39.220933        6.446620    2         1 13      0.227423      0.272440     26.866943        5.763723    3         1 14      0.128359      0.604903     29.848169        6.801633    4          1 5      0.204000      0.242652     21.354158        4.637632    5          1 6      0.122697      0.412868     25.168258        5.866785    6          1 9      0.161679      0.569781     28.707720        6.525267    7        blank      0.408713      0.526573      0.531430        0.111025   

i want dataframe values in rows have been divided values in row sample_name "blank" (normalizing sample "blank"). how can achieve in pandas?

you can select rows , slice df using loc , call div , pass last row using iloc[-1]:

in [58]: df.loc[:,'c14-cer_mean':] = df.loc[:,'c14-cer_mean':].div(df.iloc[-1]['c14-cer_mean':]) df  out[58]:       sample_name c14-cer_mean c16-cer_mean c18-cer_mean c18:1-cer_mean index                                                                   0             1 1     0.305224     0.542487      66.4284        73.6153 1            1 10     0.814694      1.24617      73.8026        58.0646 2            1 13     0.556437     0.517383      50.5559        51.9137 3            1 14     0.314057      1.14875      56.1658        61.2622 4             1 5     0.499128     0.460814      40.1824        41.7711 5             1 6     0.300203     0.784066      47.3595         52.842 6             1 9     0.395581      1.08206      54.0198         58.773 7           blank            1            1            1              1 

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