Add column with constant value to pandas dataframe

Question

Given a DataFrame   np random seed 0  df   pd DataFrame np random randn 3  3   columns list  ABC    index  1  2  3   df            A         B         C 1  1 764052  0 400157  0 978738 2  2 240893  1 867558 -0 977278 3  0 950088 -0 151357 -0 103219   What is the simplest way to add a new column containing a constant value eg 0             A         B         C  new 1  1 764052  0 400157  0 978738    0 2  2 240893  1 867558 -0 977278    0 3  0 950088 -0 151357 -0 103219    0     This is my solution  but I don t know why this puts NaN into  new  column   df  new     pd Series  0 for x in range len df index                A         B         C  new 1  1 764052  0 400157  0 978738  0 0 2  2 240893  1 867558 -0 977278  0 0 3  0 950088 -0 151357 -0 103219  NaN

User · Answer

Here is another one liner using lambdas  create column with constant value   10     df  newCol     df apply lambda x  10  axis 1    before  df     A           B           C 1   1 764052    0 400157    0 978738 2   2 240893    1 867558    -0 977278 3   0 950088    -0 151357   -0 103219   after  df         A           B           C           newCol     1   1 764052    0 400157    0 978738    10     2   2 240893    1 867558    -0 977278   10     3   0 950088    -0 151357   -0 103219   10

User · Answer

With modern pandas you can just do  df  new     0

User · Answer

Super simple in-place assignment  df  new     0  For in-place modification  perform direct assignment  This assignment is broadcasted by pandas for each row   df   pd DataFrame  x   index range 4   columns list  ABC    df     A  B  C 0  x  x  x 1  x  x  x 2  x  x  x 3  x  x  x     df  new      y    Same as    df loc     new      y  df     A  B  C new 0  x  x  x   y 1  x  x  x   y 2  x  x  x   y 3  x  x  x   y   Note for object columns  If you want to add an column of empty lists  here is my advice    Consider not doing this  object columns are bad news in terms of performance  Rethink how your data is structured   Consider storing your data in a sparse data structure  More information  sparse data structures If you must store a column of lists  ensure not to copy the same reference multiple times      Wrong df  new            len df    Right df  new         for   in range len df         Generating a copy  df assign new 0   If you need a copy instead  use DataFrame assign   df assign new  y       A  B  C new 0  x  x  x   y 1  x  x  x   y 2  x  x  x   y 3  x  x  x   y   And  if you need to assign multiple such columns with the same value  this is as simple as   c     new1    new2        df assign   dict fromkeys c   y        A  B  C new1 new2 0  x  x  x    y    y 1  x  x  x    y    y 2  x  x  x    y    y 3  x  x  x    y    y   Multiple column assignment  Finally  if you need to assign multiple columns with different values  you can use assign with a dictionary   c     new1    w    new2    y    new3    z   df assign   c      A  B  C new1 new2 new3 0  x  x  x    w    y    z 1  x  x  x    w    y    z 2  x  x  x    w    y    z 3  x  x  x    w    y    z

User · Answer

The reason this puts NaN into a column is because df index and the Index of your right-hand-side object are different   zach shows the proper way to assign a new column of zeros  In general  pandas tries to do as much alignment of indices as possible  One downside is that when indices are not aligned you get NaN wherever they aren t aligned  Play around with the reindex and align methods to gain some intuition for alignment works with objects that have partially  totally  and not-aligned-all aligned indices  For example here s how DataFrame align   works with partially aligned indices   In  7   from pandas import DataFrame  In  8   from numpy random import randint  In  9   df   DataFrame   a   randint 3  size 10     In  10    In  10   df Out 10      a 0  0 1  2 2  0 3  1 4  0 5  0 6  0 7  0 8  0 9  0  In  11   s   df a  5   In  12   dfa  sa   df align s  axis 0   In  13   dfa Out 13      a 0  0 1  2 2  0 3  1 4  0 5  0 6  0 7  0 8  0 9  0  In  14   sa Out 14   0     0 1     2 2     0 3     1 4     0 5   NaN 6   NaN 7   NaN 8   NaN 9   NaN Name  a  dtype  float64

[python] Add column with constant value to pandas dataframe

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