How to add an empty column to a dataframe

Question

What s the easiest way to add an empty column to a pandas DataFrame object   The best I ve stumbled upon is something like  df  foo     df apply lambda        axis 1    Is there a less perverse method

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To add to DSM s answer and building on this associated question  I d split the approach into two cases    Adding a single column  Just assign empty values to the new columns  e g  df  C     np nan Adding multiple columns  I d suggest using the  reindex columns        method of pandas to add the new columns to the dataframe s column index  This also works for adding multiple new rows with  reindex rows         Note that newer versions of Pandas  v 0 20  allow you to specify an axis keyword rather than explicitly assigning to columns or rows    Here is an example adding multiple columns   mydf   mydf reindex columns   mydf columns tolist       newcol1   newcol2      or   mydf   mydf reindex mydf columns tolist       newcol1   newcol2    axis 1     version  gt  0 20 0   You can also always concatenate a new  empty  dataframe to the existing dataframe  but that doesn t feel as pythonic to me

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One can use df insert index to insert at  column header  init value  to insert new column at a specific index   cost tbl insert 1   col name          The above statement would insert an empty Column after the first column

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You can do   df  column     None  This works  This will create a new column with None type df column   None  This will work only when the column is already present in the dataframe

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if you want to add column name from a list  df pd DataFrame   a   col1   col2   col3   col4   for i in a      df i  np nan

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Starting with v0 16 0  DF assign   could be used to assign new columns  single multiple  to a DF  These columns get inserted in alphabetical order at the end of the DF   This becomes advantageous compared to simple assignment in cases wherein you want to perform a series of chained operations directly on the returned dataframe   Consider the same DF sample demonstrated by  DSM   df   pd DataFrame   A    1 2 3    B    2 3 4    df Out 18      A  B 0  1  2 1  2  3 2  3  4  df assign C    D np nan  Out 21      A  B C   D 0  1  2   NaN 1  2  3   NaN 2  3  4   NaN   Note that this returns a copy with all the previous columns along with the newly created ones  In order for the original DF to be modified accordingly  use it like   df   df assign      as it does not support inplace operation currently

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The below code address the question  How do I add n number of empty columns to my existing dataframe   In the interest of keeping solutions to similar problems in one place  I am adding it here   Approach 1  to create 64 additional columns with column names from 1-64   m   list range 1 65 1    dd pd DataFrame columns m  df join dd  replace np nan      df is the dataframe that already exists   Approach 2  to create 64 additional columns with column names from 1-64   df reindex df columns tolist     list range 1 65 1    axis 1  replace np nan

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The reason I was looking for such a solution is simply to add spaces between multiple DFs which have been joined column-wise using the pd concat function and then written to excel using xlsxwriter  df      df apply lambda        axis 1  df 2   pd concat  df df1  axis 1                  worked but only once     Note  df  amp  df1 have the same rows which is my index     df 2      df 2 apply lambda        axis 1         didn t work this time          df 4   pd concat  df 2 df 3  axis 1   I then replaced the second lambda call with df 2                                         which appears to add a blank column df 4   pd concat  df 2 df 3  axis 1   The output I tested it on was using xlsxwriter to excel  Jupyter blank columns look the same as in excel although doesnt have xlsx formatting  Not sure why the second Lambda call didnt work

User · Answer

Sorry for I did not explain my answer really well at beginning  There is another way to add an new column to an existing dataframe  1st step  make a new empty data frame  with all the columns in your data frame  plus a new or few columns you want to add  called df temp 2nd step  combine the df temp and your data frame  df temp   pd DataFrame columns  df null columns tolist       empty     df   pd concat  df temp  df    It might be the best solution  but it is another way to think about this question  the reason of I am using this method is because I am get this warning all the time    SettingWithCopyWarning   A value is trying to be set on a copy of a slice from a DataFrame  Try using  loc row indexer col indexer    value instead  See the caveats in the documentation  https   pandas pydata org pandas-docs stable user guide indexing html returning-a-view-versus-a-copy   df  quot empty1 quot    df  quot empty2 quot      np nan   quot  quot    great I found the way to disable the Warning pd options mode chained assignment   None

User · Answer

an even simpler solution is    df   df reindex columns   header list                    where  header list  is a list of the headers you want to appear   any header included in the list that is not found already in the dataframe will be added with blank cells below   so if   header list     a   b   c    d     then c and d will be added as columns with blank cells

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I like  df  new     pd Series dtype  your required dtype    If you have an empty dataframe  this solution makes sure that no new row containing only NaN is added  Specifying dtype is not strictly necessary  however newer Pandas versions produce a DeprecationWarning if not specified

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emunsing s answer is really cool for adding multiple columns  but I couldn t get it to work for me in python 2 7   Instead  I found this works   mydf   mydf reindex columns   np append  mydf columns values    newcol1   newcol2

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If I understand correctly  assignment should fill    gt  gt  gt  import numpy as np  gt  gt  gt  import pandas as pd  gt  gt  gt  df   pd DataFrame   A    1 2 3    B    2 3 4     gt  gt  gt  df    A  B 0  1  2 1  2  3 2  3  4  gt  gt  gt  df  C         gt  gt  gt  df  D     np nan  gt  gt  gt  df    A  B C   D 0  1  2   NaN 1  2  3   NaN 2  3  4   NaN

[python] How to add an empty column to a dataframe?

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