How to properly apply a lambda function into a pandas data frame column

Question

I have a pandas data frame  sample  with one of the columns called PR to which am applying a lambda function as follows   sample  PR     sample  PR   apply lambda x  NaN if x  lt  90    I then get the following syntax error message   sample  PR     sample  PR   apply lambda x  NaN if x  lt  90                                                             SyntaxError  invalid syntax   What am I doing wrong

User · Answer

You need to add else in your lambda function  Because you are telling what to do in case your condition here x  lt  90  is met  but you are not telling what to do in case the condition is not met   sample  PR     sample  PR   apply lambda x   NaN  if x  lt  90 else x

User · Answer

You need mask   sample  PR     sample  PR   mask sample  PR    lt  90  np nan    Another solution with loc and boolean indexing   sample loc sample  PR    lt  90   PR     np nan   Sample   import pandas as pd import numpy as np  sample   pd DataFrame   PR   10 100 40     print  sample      PR 0   10 1  100 2   40  sample  PR     sample  PR   mask sample  PR    lt  90  np nan  print  sample        PR 0    NaN 1  100 0 2    NaN     sample loc sample  PR    lt  90   PR     np nan print  sample        PR 0    NaN 1  100 0 2    NaN   EDIT   Solution with apply   sample  PR     sample  PR   apply lambda x  np nan if x  lt  90 else x    Timings len df  300k   sample   pd concat  sample  100000  reset index drop True   In  853    timeit sample  PR   apply lambda x  np nan if x  lt  90 else x  10 loops  best of 3  102 ms per loop  In  854    timeit sample  PR   mask sample  PR    lt  90  np nan  The slowest run took 4 28 times longer than the fastest  This could mean that an intermediate result is being cached  100 loops  best of 3  3 71 ms per loop

[pandas] How to properly apply a lambda function into a pandas data frame column

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