Rename specific column s in pandas

Question

I ve got a dataframe called data  How would I rename the only one column header  For example gdp to log gdp    data       y  gdp  cap 0   1    2    5 1   2    3    9 2   8    7    2 3   3    4    7 4   6    7    7 5   4    8    3 6   8    2    8 7   9    9   10 8   6    6    4 9  10   10    7

User · Answer

A much faster implementation would be to use list-comprehension if you need to rename a single column.

df.columns = ['log(gdp)' if x=='gdp' else x for x in df.columns]

If the need arises to rename multiple columns, either use conditional expressions like:

df.columns = ['log(gdp)' if x=='gdp' else 'cap_mod' if x=='cap' else x for x in df.columns]

Or, construct a mapping using a dictionary and perform the list-comprehension with it's get operation by setting default value as the old name:

col_dict = {'gdp': 'log(gdp)', 'cap': 'cap_mod'}   ## key?old name, value?new name

df.columns = [col_dict.get(x, x) for x in df.columns]

Timings:

%%timeit
df.rename(columns={'gdp':'log(gdp)'}, inplace=True)
10000 loops, best of 3: 168 µs per loop

%%timeit
df.columns = ['log(gdp)' if x=='gdp' else x for x in df.columns]
10000 loops, best of 3: 58.5 µs per loop

User · Answer

How do I rename a specific column in pandas   From v0 24   to rename one  or more  columns at a time   DataFrame rename   with axis 1 or axis  columns   the axis argument was introduced in v0 21   Index str replace   for string regex based replacement    If you need to rename ALL columns at once   DataFrame set axis   method with axis 1  Pass a list-like sequence  Options are available for in-place modification as well    rename with axis 1 df   pd DataFrame  x   columns   y    gdp    cap    index range 5   df     y gdp cap 0  x   x   x 1  x   x   x 2  x   x   x 3  x   x   x 4  x   x   x  With 0 21   you can now specify an axis parameter with rename  df rename   gdp   log gdp     axis 1    df rename   gdp   log gdp     axis  columns           y log gdp  cap 0  x        x   x 1  x        x   x 2  x        x   x 3  x        x   x 4  x        x   x   Note that rename is not in-place by default  so you will need to assign the result back   This addition has been made to improve consistency with the rest of the API  The new axis argument is analogous to the columns parameter   they do the same thing  df rename columns   gdp    log gdp         y log gdp  cap 0  x        x   x 1  x        x   x 2  x        x   x 3  x        x   x 4  x        x   x  rename also accepts a callback that is called once for each column  df rename lambda x  x 0   axis 1    df rename lambda x  x 0   axis  columns       y  g  c 0  x  x  x 1  x  x  x 2  x  x  x 3  x  x  x 4  x  x  x  For this specific scenario  you would want to use df rename lambda x   log gdp   if x     gdp  else x  axis 1    Index str replace Similar to replace method of strings in python  pandas Index and Series  object dtype only  define a   quot vectorized quot   str replace method for string and regex-based replacement  df columns   df columns str replace  gdp    log gdp    df      y log gdp  cap 0  x        x   x 1  x        x   x 2  x        x   x 3  x        x   x 4  x        x   x  The advantage of this over the other methods is that str replace supports regex  enabled by default   See the docs for more information   Passing a list to set axis with axis 1 Call set axis with a list of header s   The list must be equal in length to the columns index size  set axis mutates the original DataFrame by default  but you can specify inplace False to return a modified copy  df set axis   cap    log gdp     y    axis 1  inplace False    df set axis   cap    log gdp     y    axis  columns   inplace False     cap log gdp   y 0   x        x  x 1   x        x  x 2   x        x  x 3   x        x  x 4   x        x  x  Note  In future releases  inplace will default to True  Method Chaining Why choose set axis when we already have an efficient way of assigning columns with df columns        As shown by Ted Petrou in this answer set axis is useful when trying to chain methods  Compare   new for pandas 0 21  df some method1      some method2      set axis      some method3    Versus   old way df1   df some method1            some method2   df1 columns   columns df1 some method3    The former is more natural and free flowing syntax

User · Answer

There are at least five different ways to rename specific columns in pandas  and I have listed them below along with links to the original answers  I also timed these methods and found them to perform about the same  though YMMV depending on your data set and scenario   The test case below is to rename columns A M N Z to A2 M2 N2 Z2 in a dataframe with columns A to Z containing a million rows     Import required modules import numpy as np import pandas as pd import timeit    Create sample data df   pd DataFrame np random randint 0 9999 size  1000000  26    columns list  ABCDEFGHIJKLMNOPQRSTUVWXYZ       Standard way - https   stackoverflow com a 19758398 452587 def method 1        df renamed   df rename columns   A    A2    M    M2    N    N2    Z    Z2       Lambda function - https   stackoverflow com a 16770353 452587 def method 2        df renamed   df rename columns lambda x  x    2  if x in   A    M    N    Z   else x     Mapping function - https   stackoverflow com a 19758398 452587 def rename some x       if x   A  or x   M  or x   N  or x   Z           return x    2      return x def method 3        df renamed   df rename columns rename some     Dictionary comprehension - https   stackoverflow com a 58143182 452587 def method 4        df renamed   df rename columns  col  col    2  for col in df columns          np asarray  i for i  col in enumerate df columns  if  A  in col or  M  in col or  N  in col or  Z  in col              Dictionary comprehension - https   stackoverflow com a 38101084 452587 def method 5        df renamed   df rename columns dict zip df   A    M    N    Z       A2    M2    N2    Z2       print  Method 1    timeit timeit method 1  number 10   print  Method 2    timeit timeit method 2  number 10   print  Method 3    timeit timeit method 3  number 10   print  Method 4    timeit timeit method 4  number 10   print  Method 5    timeit timeit method 5  number 10     Output   Method 1  3 650640267 Method 2  3 163998427 Method 3  2 998530871 Method 4  2 9918436889999995 Method 5  3 2436501520000007   Use the method that is most intuitive to you and easiest for you to implement in your application

User · Answer

Use the pandas DataFrame rename funtion  Check this link for description  data rename columns     gdp    log gdp     inplace   True   If you intend to rename multiple columns then data rename columns     gdp    log gdp     cap    log cap         inplace   True

User · Answer

data rename columns   gdp   log gdp     inplace True    The rename show that it accepts a dict as a param for columns so you just pass a dict with a single entry   Also see related

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