python - Apply a function to a specific row using the index value -

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i have following table:

import pandas pd import numpy np  #dataframe random numbers , a,b,c,d,e index df = pd.dataframe(np.random.randn(5,5), index = ['a','b','c','d','e'])  #now name columns same df.columns = ['a','b','c','d','e']  #resulting dataframe:                 b         c         d         e  2.214229  1.621352  0.083113  0.818191 -0.900224 b -0.612560 -0.028039 -0.392266  0.439679  1.596251 c  1.378928 -0.309353 -0.651817  1.499517  0.515772 d -0.061682  1.141558 -0.811471  0.242874  0.345159 e -0.714760 -0.172082  0.205638  0.220528  1.182013

how can apply function dataframes index? want round numbers every column index "c". 

#numbers round 2 decimals:                 b         c         d         e c  1.378928 -0.309353 -0.651817  1.499517  0.515772

what best way this?

for label based indexing use loc:

in [22]:  df = pd.dataframe(np.random.randn(5,5), index = ['a','b','c','d','e'])  #now name columns same df.columns = ['a','b','c','d','e'] df out[22]:                   b         c         d         e -0.051366  1.856373 -0.224172 -0.005668  0.986908 b -1.121298 -1.018863  2.328420 -0.117501 -0.231463 c  2.241418 -0.838571 -0.551222  0.662890 -1.234716 d  0.275063  0.295788  0.689171  0.227742  0.091928 e  0.269730  0.326156  0.210443 -0.494634 -0.489698 in [23]:  df.loc['c'] = np.round(df.loc['c'],decimals=2) df out[23]:                   b         c         d         e -0.051366  1.856373 -0.224172 -0.005668  0.986908 b -1.121298 -1.018863  2.328420 -0.117501 -0.231463 c  2.240000 -0.840000 -0.550000  0.660000 -1.230000 d  0.275063  0.295788  0.689171  0.227742  0.091928 e  0.269730  0.326156  0.210443 -0.494634 -0.489698

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