How to display pandas DataFrame of floats using a format string for columns

Question

I would like to display a pandas dataframe with a given format using print   and the IPython display    For example   df   pd DataFrame  123 4567  234 5678  345 6789  456 7890                     index   foo   bar   baz   quux                      columns   cost    print df           cost foo   123 4567 bar   234 5678 baz   345 6789 quux  456 7890   I would like to somehow coerce this into printing           cost foo    123 46 bar    234 57 baz    345 68 quux   456 79   without having to modify the data itself or create a copy  just change the way it is displayed   How can I do this

User · Answer

If you don t want to modify the dataframe  you could use a custom formatter for that column   import pandas as pd pd options display float format         2f   format df   pd DataFrame  123 4567  234 5678  345 6789  456 7890                     index   foo   bar   baz   quux                      columns   cost      print df to string formatters   cost        2f   format     yields          cost foo   123 46 bar   234 57 baz   345 68 quux  456 79

User · Answer

import pandas as pd pd options display float format         2f   format df   pd DataFrame  123 4567  234 5678  345 6789  456 7890                     index   foo   bar   baz   quux                      columns   cost    print df    yields          cost foo   123 46 bar   234 57 baz   345 68 quux  456 79   but this only works if you want every float to be formatted with a dollar sign   Otherwise  if you want dollar formatting for some floats only  then I think you ll have to pre-modify the dataframe  converting those floats to strings    import pandas as pd df   pd DataFrame  123 4567  234 5678  345 6789  456 7890                     index   foo   bar   baz   quux                      columns   cost    df  foo     df  cost   df  cost     df  cost   map       2f   format  print df    yields           cost       foo foo    123 46  123 4567 bar    234 57  234 5678 baz    345 68  345 6789 quux   456 79  456 7890

User · Answer

As of Pandas 0 17 there is now a styling system which essentially provides formatted views of a DataFrame using Python format strings   import pandas as pd import numpy as np  constants   pd DataFrame    pi  np pi    e  np e                       columns   name   value    C   constants style format   name                value   -- gt    15 10f   lt --    C   which displays    This is a view object  the DataFrame itself does not change formatting  but updates in the DataFrame are reflected in the view   constants name     pie   eek   C     However it appears to have some limitations    Adding new rows and or columns in-place seems to cause inconsistency in the styled view  doesn t add row column labels    constants loc 2    dict name  bogus   value 123 456  constants  comment       fee   fie   fo   constants      which looks ok but   C      Formatting works only for values  not index entries   constants   pd DataFrame    pi  np pi    e  np e                   columns   name   value    constants set index  name  inplace True  C   constants style format   name                value   -- gt    15 10f   lt --    C

User · Answer

summary        df   pd DataFrame   money    100 456  200 789    share     100 000    200 000         print df      print df to string formatters   money         2f   format        for col name in   share             df col name    df col name  map lambda p  int p replace                print df                  money    share     0  100 456  100 000     1  200 789  200 000          money    share     0  100 46  100 000     1  200 79  200 000           money   share     0  100 456  100000     1  200 789  200000

User · Answer

You can also set locale to your region and set float format to use a currency format  This will automatically set   sign for currency in USA   import locale  locale setlocale locale LC ALL   en US UTF-8    pd set option  float format   locale currency   df   pd DataFrame       123 4567  234 5678  345 6789  456 7890       index   foo    bar    baz    quux        columns   cost      print df           cost foo   123 46 bar   234 57 baz   345 68 quux  456 79

User · Answer

Similar to unutbu above  you could also use applymap as follows   import pandas as pd df   pd DataFrame  123 4567  234 5678  345 6789  456 7890                     index   foo   bar   baz   quux                      columns   cost     df   df applymap    0  2f   format

User · Answer

I like using pandas apply   with python format     import pandas as pd s   pd Series  1 357  1 489  2 333333    make float   lambda x        2f   format x  s apply make float    Also  it can be easily used with multiple columns     df   pd concat  s  s   2   axis 1   make floats   lambda row        2f        3f   format row 0   row 1   df apply make floats  axis 1

User · Answer

If you do not want to change the display format permanently  and perhaps apply a new format later on  I personally favour the use of a resource manager  the with statement in Python   In your case you could do something like this  with pd option context  display float format       0 2f   format      print df   If you happen to need a different format further down in your code  you can change it by varying just the format in the snippet above

[python] How to display pandas DataFrame of floats using a format string for columns?

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