How to lowercase a pandas dataframe string column if it has missing values

Question

The following code does not work    import pandas as pd import numpy as np df pd DataFrame   ONE   Two   np nan  columns   x     xLower   df  x   map lambda x  x lower      How should I tweak it to get xLower     one   two  np nan    Efficiency is important since the real data frame is huge

User · Answer

copy your Dataframe column and simply apply  df data  x   newdf df str lower

User · Answer

you can try this one also   df  df applymap lambda s s lower   if type s     str else s

User · Answer

A possible solution   import pandas as pd import numpy as np  df pd DataFrame   ONE   Two   np nan  columns   x     xLower   df  x   map lambda x  x if type x   str else x lower    print  xLower    And a result   0    one 1    two 2    NaN Name  x  dtype  object   Not sure about the efficiency though

User · Answer

Use apply function   Xlower   df  x   apply lambda x  x upper    head 10

User · Answer

use pandas vectorized string methods  as in the documentation      these methods exclude missing NA values automatically    str lower   is the very first example there    gt  gt  gt  df  x   str lower   0    one 1    two 2    NaN Name  x  dtype  object

User · Answer

May be using List comprehension   import pandas as pd import numpy as np df pd DataFrame   ONE   Two   np nan  columns   Name     df  Name      str i  lower   for i in df  Name      print df

User · Answer

Another possible solution  in case the column has not only strings but numbers too  is to use astype str  str lower   or to string na rep     because otherwise  given that a number is not a string  when lowered it will return NaN  therefore   import pandas as pd import numpy as np df pd DataFrame   ONE   Two   np nan 2  columns   x     xSecureLower   df  x   to string na rep     lower   xLower   df  x   str lower     then we have    gt  gt  gt  xSecureLower 0    one 1    two 2    3      2 Name  x  dtype  object   and not   gt  gt  gt  xLower 0    one 1    two 2    NaN 3    NaN Name  x  dtype  object     edit   if you don t want to lose the NaNs  then using map will be better   from  wojciech-walczak  and  cs95 comment  it will look something like this  xSecureLower   df  x   map lambda x  x lower   if isinstance x str  else x

User · Answer

Apply lambda function  df  original category     df  original category   apply lambda x x lower

User · Answer

Pandas    0 25  Remove Case Distinctions with str casefold  Starting from v0 25  I recommend using the  vectorized  string method str casefold if you re dealing with unicode data  it works regardless of string or unicodes    s   pd Series   lower    CAPITALS   np nan   SwApCaSe    s str casefold    0       lower 1    capitals 2         NaN 3    swapcase dtype  object   Also see related GitHub issue GH25405    casefold lends itself to more aggressive case-folding comparison  It also handles NaNs gracefully  just as str lower does    But why is this better   The difference is seen with unicodes  Taking the example in the python str casefold docs       Casefolding is similar to lowercasing but more aggressive because it   is intended to remove all case distinctions in a string  For example    the German lowercase letter      is equivalent to  ss   Since it is   already lowercase  lower   would do nothing to       casefold     converts it to  ss     Compare the output of lower for   s   pd Series   der Flu      s str lower    0    der flu   dtype  object   Versus casefold   s str casefold    0    der fluss dtype  object   Also see Python  lower   vs  casefold   in string matching and converting to lowercase

[python] How to lowercase a pandas dataframe string column if it has missing values?

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