Changing a specific column name in pandas DataFrame

Question

I was looking for an elegant way to change a specified column name in a DataFrame   play data      import pandas as pd d               one    1  2  3  4  5             two    9  8  7  6  5             three     a    b    c    d    e         df   pd DataFrame d    The most elegant solution I have found so far      names   df columns tolist   names names index  two       new name  df columns   names   I was hoping for a simple one-liner     this attempt failed      df columns df columns tolist   index  one       another name    Any hints gratefully received

User · Answer

Another option would be to simply copy  amp  drop the column   df   pd DataFrame d  df  new name     df  two   df   df drop  two   axis 1  df head     After that you get the result       one three   new name 0   1   a       9 1   2   b       8 2   3   c       7 3   4   d       6 4   5   e       5

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Pandas 0 21 now has an axis parameter  The rename method has gained an axis parameter to match most of the rest of the pandas API   So  in addition to this   df rename columns     two   new name      You can do   df rename   two   new name    axis 1    or  df rename   two   new name    axis  columns

User · Answer

A one liner does exist   In  27   df df rename columns     two   new name     In  28   df Out 28      one three  new name 0    1     a         9 1    2     b         8 2    3     c         7 3    4     d         6 4    5     e         5   Following is the docstring for the rename method    Definition  df rename self  index None  columns None  copy True  inplace False  Docstring  Alter index and   or columns using input function or functions  Function   dict values must be unique  1-to-1   Labels not contained in a dict   Series will be left as-is   Parameters ---------- index   dict-like or function  optional     Transformation to apply to index values columns   dict-like or function  optional     Transformation to apply to column values copy   boolean  default True     Also copy underlying data inplace   boolean  default False     Whether to return a new DataFrame  If True then value of copy is     ignored   See also -------- Series rename  Returns ------- renamed   DataFrame  new object

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x000D   x000D  size   10 df rename columns  df columns i   someList i  for i in range size    inplace   True  x000D   x000D   x000D

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If you know which column   it is  first   second   nth  then this solution posted on a similar question works regardless of whether it is named or unnamed  and in one line  https   stackoverflow com a 26336314 4355695  df rename columns    list df  1   new name    inplace True    1 is for second column  0 1 2

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For renaming the columns here is the simple one which will work for both Default 0 1 2 etc   and existing columns but not much useful for a larger data sets having many columns    For a larger data set we can slice the columns that we need and apply the below code   df columns     new name   new name1   old name

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Following short code can help   df3   df3 rename columns  c  c replace          for c in df3 columns     Remove spaces from columns

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Since inplace argument is available  you don t need to copy and assign the original data frame back to itself  but do as follows   df rename columns   two   new name    inplace True

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What about   df columns values 2     new name

User · Answer

pandas version 0 23 4  df rename index str columns   old name   new name   inplace True    For the record      omitting index str will give error replace has an unexpected argument    columns

[python] Changing a specific column name in pandas DataFrame

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