Pandas Python Set value of one column based on value in another column

Question

I need to set the value of one column based on the value of another in a Pandas dataframe  This is the logic   if df  c1       Value       df  c2     10 else      df  c2     df  c3     I am unable to get this to do what I want  which is to simply create a column with new values  or change the value of an existing column  either one works for me     If I try to run the code above or if I write it as a function and use the apply method  I get the following   ValueError  The truth value of a Series is ambiguous  Use a empty  a bool    a item    a any   or a all

User · Answer

You can use np where   to set values based on a specified condition    df    c1  c2  c3 0   4   2   1 1   8   7   9 2   1   5   8 3   3   3   5 4   3   6   8   Now change values  or set  in column   c2   based on your condition   df  c2     np where df c1    8  X   df c3      c1  c3  c4 0   4   1   1 1   8   9   X 2   1   8   8 3   3   5   5 4   3   8   8

User · Answer

I had a big dataset and  loc   was taking too long so I found a vectorized way to do it   Recall that you can set a column to a logical operator  so this works  file  Flag      file  Claim Amount    gt  0  This gives a Boolean  which I wanted  but you can multiply it by  say  1 to make an Integer

User · Answer

I suggest doing it in two steps     set fixed value to  c2  where the condition is met df loc df  c1       Value    c2     10    copy value from  c3  to  c2  where the condition is NOT met df loc df  c1       Value    c2     df df  c1       Value    c3

User · Answer

one way to do this would be to use indexing with  loc    Example  In the absence of an example dataframe  I ll make one up here   import numpy as np import pandas as pd  df   pd DataFrame   c1   list  abcdefg     df loc 5   c1      Value    gt  gt  gt  df       c1 0      a 1      b 2      c 3      d 4      e 5  Value 6      g   Assuming you wanted to create a new column c2  equivalent to c1 except where c1 is Value  in which case  you would like to assign it to 10   First  you could create a new column c2  and set it to equivalent as c1  using one of the following two lines  they essentially do the same thing    df   df assign c2   df  c1      OR  df  c2     df  c1     Then  find all the indices where c1 is equal to  Value  using  loc  and assign your desired value in c2 at those indices   df loc df  c1       Value    c2     10   And you end up with this    gt  gt  gt  df       c1  c2 0      a   a 1      b   b 2      c   c 3      d   d 4      e   e 5  Value  10 6      g   g   If  as you suggested in your question  you would perhaps sometimes just want to replace the values in the column you already have  rather than create a new column  then just skip the column creation  and do the following   df  c1   loc df  c1       Value     10   or  df loc df  c1       Value    c1     10   Giving you    gt  gt  gt  df       c1 0      a 1      b 2      c 3      d 4      e 5     10 6      g

User · Answer

Try out df apply   if you ve a small medium dataframe  df  c2     df apply lambda x  10 if x  c1       Value  else x  c1    axis   1   Else  follow the slicing techniques mentioned in the above comments if you ve got a big dataframe

User · Answer

Note the tilda that reverses the selection  It uses pandas methods  i e  is faster than if else   df loc  df  c1       Value     c2     10 df loc   df  c1       Value     c2     df  c3

User · Answer

try   df  c2     df  c1   apply lambda x  10 if x     Value  else x

User · Answer

You can use pandas DataFrame mask to add virtually as many conditions as you need   data     a    1 2 3 4 5    b    6 8 9 10 11    d   pd DataFrame from dict data  orient  columns   c     c1    2   Value1     c2    3   Value2     c3    5  d  b      d  new     np nan for value in c values        d  new   mask d  a      value 0   value 1   inplace True   d  new     d  new   fillna  Else   d   Output       a   b   new 0   1   6   Else 1   2   8   Value1 2   3   9   Value2 3   4   10  Else 4   5   11  11

[python] Pandas/Python: Set value of one column based on value in another column

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