I have a dataframe df like below :

import pandas as pd

data = {'A': ['ABCD_1', 'ABCD_1', 'ABCD_1', 'ABCD_1', 'PQRS_2', 'PQRS_2', 'PQRS_2', 'PQRS_2', 'PQRS_2', 'PQRS_3', 'PQRS_4'], 'B':[2, 3, 5, 6, 7, 8, 9, 11, 13, 15, 17]}
df = pd.DataFrame(data)
df


         |     A      |    B     |
          ------------ ---------- 
         |    ABCD_1  |    2     |
         |    ABCD_1  |    3     |
         |    ABCD_1  |    5     |
         |    ABCD_1  |    6     |
         |    PQRS_2  |    7     |
         |    PQRS_2  |    8     |
         |    PQRS_2  |    9     |
         |    PQRS_2  |    11    |
         |    PQRS_2  |    13    |
         |    PQRS_3  |    15    |
         |    PQRS_4  |    17    |
          ------------ ---------- 

What I want to achieve is that I need to assign 1 to first value of every group of column A and 0 to the rest of other values. Incase, there is a single group present in Column A I just assign 1 to that group. So, my expected result should look like below.

Expected Output :

         |     A      |    B     |    P     |
          ------------ ---------- ---------- 
         |    ABCD_1  |    2     |     1    |
         |    ABCD_1  |    3     |     0    |
         |    ABCD_1  |    5     |     0    | 
         |    ABCD_1  |    6     |     0    |
         |    PQRS_2  |    7     |     1    |
         |    PQRS_2  |    8     |     0    |
         |    PQRS_2  |    9     |     0    |
         |    PQRS_2  |    11    |     0    |
         |    PQRS_2  |    13    |     0    |
         |    PQRS_3  |    15    |     1    |
         |    PQRS_4  |    17    |     1    |
          ------------ ---------- ---------- 

I tried to group them using the below code, however, I wasn't able to get expected results.

Actual Output

df['P'] = pd.factorize(df['A'])   1

         |     A      |    B     |    P     |
          ------------ ---------- ---------- 
         |    ABCD_1  |    2     |     1    |
         |    ABCD_1  |    3     |     1    |
         |    ABCD_1  |    5     |     1    | 
         |    ABCD_1  |    6     |     1    |
         |    PQRS_2  |    7     |     1    |
         |    PQRS_2  |    8     |     2    |
         |    PQRS_2  |    9     |     2    |
         |    PQRS_2  |    11    |     2    |
         |    PQRS_2  |    13    |     2    |
         |    PQRS_3  |    15    |     3    |
         |    PQRS_4  |    17    |     4    |
          ------------ ---------- ---------- 

How can I assign 1 and 0 to each of the groups using Pandas ?

CodePudding user response：

You could achieve this as follows:

• Use

  be sure to answer the question. Provide details and share research!