Ignoring NaNs with str contains

Question

I want to find rows that contain a string  like so   DF DF col str contains  foo      However  this fails because some elements are NaN      ValueError  cannot index with vector containing NA   NaN values   So I resort to the obfuscated  DF DF col notnull    DF col dropna   str contains  foo      Is there a better way

User · Answer

I m not 100  on why  actually came here to search for the answer   but this also works  and doesn t require replacing all nan values   import pandas as pd import numpy as np  df   pd DataFrame    foo1      foo2      bar     np nan    columns   a     newdf   df loc df  a   str contains  foo      True    Works with or without  loc   I have no idea why this works  as I understand it when you re indexing with brackets pandas evaluates whatever s inside the bracket as either True or False  I can t tell why making the phrase inside the brackets  extra boolean  has any effect at all

User · Answer

df df col str contains  quot foo quot   fillna False

User · Answer

In addition to the above answers  I would say for columns having no single word name  you may use -  df df  Product ID   str contains  foo      True    Hope this helps

User · Answer

There s a flag for that   In  11   df   pd DataFrame    foo1      foo2      bar     np nan    columns   a     In  12   df a str contains  foo   Out 12   0     True 1     True 2    False 3      NaN Name  a  dtype  object  In  13   df a str contains  foo   na False  Out 13   0     True 1     True 2    False 3    False Name  a  dtype  bool   See the str replace docs      na   default NaN  fill value for missing values      So you can do the following   In  21   df loc df a str contains  foo   na False   Out 21         a 0  foo1 1  foo2

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User · Answer

You can also patern    DF DF col str contains pat     foo    regex   True

[python] Ignoring NaNs with str.contains

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