Add column in dataframe from list

Question

I have a dataframe with some columns like this   A   B   C   0    4 5 6 7 7 6 5   The possible range of values in A are only from 0 to 7    Also  I have a list of 8 elements like this   List  2 5 6 8 12 16 26 32     There are only 8 elements in this list   If the element in column A is n  I need to insert the n th element from the List in a new column  say  D    How can I do this in one go without looping over the whole dataframe    The resulting dataframe would look like this   A   B   C   D 0           2 4           12 5           16 6           26 7           32 7           32 6           26 5           16   Note  The dataframe is huge and iteration is the last option option  But I can also arrange the elements in  List  in any other data structure like dict if necessary

User · Answer

Just assign the list directly   df  new col     mylist     Alternative Convert the list to a series or array and then assign   se   pd Series mylist  df  new col     se values   or  df  new col     np array mylist

User · Answer

IIUC  if you make your  unfortunately named  List into an ndarray  you can simply index into it naturally    gt  gt  gt  import numpy as np  gt  gt  gt  m   np arange 16  10  gt  gt  gt  m df A  array    0   40   50   60  150  150  140  130    gt  gt  gt  df  D     m df A   gt  gt  gt  df     A   B   C    D 0   0 NaN NaN    0 1   4 NaN NaN   40 2   5 NaN NaN   50 3   6 NaN NaN   60 4  15 NaN NaN  150 5  15 NaN NaN  150 6  14 NaN NaN  140 7  13 NaN NaN  130   Here I built a new m  but if you use m   np asarray List   the same thing should work  the values in df A will pick out the appropriate elements of m     Note that if you re using an old version of numpy  you might have to use m df A values  instead-- in the past  numpy didn t play well with others  and some refactoring in pandas caused some headaches   Things have improved now

User · Answer

You can also use df assign  In  1559   df Out 1559       A   B   C 0  0 NaN NaN 1  4 NaN NaN 2  5 NaN NaN 3  6 NaN NaN 4  7 NaN NaN 5  7 NaN NaN 6  6 NaN NaN 7  5 NaN NaN  In  1560   mylist    2 5 6 8 12 16 26 32   In  1567   df   df assign D mylist   In  1568   df Out 1568       A   B   C   D 0  0 NaN NaN   2 1  4 NaN NaN   5 2  5 NaN NaN   6 3  6 NaN NaN   8 4  7 NaN NaN  12 5  7 NaN NaN  16 6  6 NaN NaN  26 7  5 NaN NaN  32

User · Answer

First let s create the dataframe you had  I ll ignore columns B and C as they are not relevant   df   pd DataFrame   A    0  4  5  6  7  7  6 5      And the mapping that you desire   mapping   dict enumerate  2 5 6 8 12 16 26 32     df  D     df  A   map mapping    Done   print df   Output      A   D 0  0   2 1  4  12 2  5  16 3  6  26 4  7  32 5  7  32 6  6  26 7  5  16

User · Answer

Old question  but I always try to use fastest code   I had a huge list with 69 millions of uint64  np array   was fastest for me   df  hashes     hashes Time spent  17 034842014312744  df  hashes     pd Series hashes  values Time spent  17 141014337539673  df  key     np array hashes  Time spent  10 724546194076538

User · Answer

A solution improving on the great one from  sparrow   Let df  be your dataset  and mylist the list with the values you want to add to the dataframe   Let s suppose you want to call your new column simply  new column  First make the list into a Series   column values   pd Series mylist    Then use the insert function to add the column  This function has the advantage to let you choose in which position you want to place the column  In the following example we will position the new column in the first position from left  by setting loc 0   df insert loc 0  column  new column   value column values

[python] Add column in dataframe from list

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