Creating a new column based on if-elif-else condition

Question

I have a DataFrame df       A    B a   2    2  b   3    1 c   1    3   I want to create a new column based on the following criteria   if row A    B  0  if rowA  gt  B  1  if row A  lt  B  -1   so given the above table  it should be       A    B    C a   2    2    0 b   3    1    1 c   1    3   -1    For typical if else cases I do np where df A  gt  df B  1  -1   does pandas provide a special syntax for solving my problem with one step  without the necessity of creating 3 new columns and then combining the result

User · Answer

df loc df  A      df  B     C     0 df loc df  A    gt  df  B     C     1 df loc df  A    lt  df  B     C     -1   Easy to solve using indexing  The first line of code reads like so  if column A is equal to column B then create and set column C equal to 0

User · Answer

When you have multiple if conditions  numpy select is the way to go  In  4102   import numpy as np In  4098   conditions    df A eq df B   df A gt df B   df A lt df B   In  4096   choices    0  1  -1   In  4100   df  C     np select conditions  choices   In  4101   df Out 4101       A  B  C a  2  2  0 b  3  1  1 c  1  3 -1

User · Answer

To formalize some of the approaches laid out above  Create a function that operates on the rows of your dataframe like so  def f row       if row  A      row  B            val   0     elif row  A    gt  row  B            val   1     else          val   -1     return val  Then apply it to your dataframe passing in the axis 1 option  In  1   df  C     df apply f  axis 1   In  2   df Out 2      A  B  C a  2  2  0 b  3  1  1 c  1  3 -1  Of course  this is not vectorized so performance may not be as good when scaled to a large number of records   Still  I think it is much more readable  Especially coming from a SAS background  Edit Here is the vectorized version df  C     np where      df  A      df  B    0  np where      df  A    gt   df  B    1  -1

User · Answer

For this particular relationship  you could use np sign    gt  gt  gt  df  C     np sign df A - df B   gt  gt  gt  df    A  B  C a  2  2  0 b  3  1  1 c  1  3 -1

User · Answer

Lets say above one is your original dataframe and you want to add a new column  old    If age greater than 50 then we consider as older yes otherwise False  step 1  Get the indexes of rows whose age greater than 50      row indexes df df  age   gt  50  index   step 2   Using  loc we can assign a new value to column      df loc row indexes  elderly    yes   same for age below less than 50      row indexes df df  age   lt 50  index      df row indexes  elderly    no

[python] Creating a new column based on if-elif-else condition

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