I have a dataframe and and a list:

import pandas as pd
df = pd.DataFrame()
df['Orig'] = ['CA', 'OH', 'WA','CA','CA','IN','FL']
df['Dest'] = ['CA', 'CA', 'OH','WA','MI','WA','MA']

lst = ['WA','CA','OH']

I would like to do the follwing…
If value for Orig and Dest is the lst, then set column Category to ‘T’, else ‘F’. How can I accomplish that? Thank you.

orig dest
0 CA CA
1 OH CA
2 WA OH
3 CA WA
4 CA MI
5 IN WA
6 FL MA

Desire output:
orig dest category
0 CA CA T
1 OH CA T
2 WA OH T
3 CA WA T
4 CA MI F
5 IN WA F
6 FL MA F

>Solution :

You can use isin and all to generate a boolean series for numpy.where:

import numpy as np
df['category'] = np.where(df.isin(lst).all(axis=1), 'T', 'F')

Or, if more columns in the input, restrict to the chosen ones by slicing:

df['category'] = np.where(df[['orig', 'dest']].isin(lst).all(axis=1), 'T', 'F')

Alternatively, you can also select with: df['orig'].isin(lst) & df['dest'].isin(lst).

Output:

  Orig Dest category
0   CA   CA        T
1   OH   CA        T
2   WA   OH        T
3   CA   WA        T
4   CA   MI        F
5   IN   WA        F
6   FL   MA        F