Changing Pandas column value if multiple conditions are met

I am trying to check a pandas row to see if two conditions are met, if these conditions are met I am changing on of the values of the dataframe.

import pandas as pd

d = {"age": [10, 20, 40, 20, 30, 20], "job": ["teacher", "teacher", "chef", "teacher", "doctor", "lifeguard"]}

df = pd.DataFrame(data=d)
print(df.head())
print("-"*20)

#mask = df[df["age"] == 20 and df["job"] == "teacher"]
df.loc[df["age"] == 20 and df["job"] == "teacher"] = "REPLACED!"
print(df.head())

I thought I would be able to make a boolean mask with the commented out section, but was unable to do so.

>Solution :

This is a common error. You’re doing two things wrong:

1. With pandas masks, you use & instead of and, and | instead of or
2. & and | have a higher precedence than ==, so you need to wrap the x == y expression in parentheses:

df.loc[(df["age"] == 20) & (df["job"] == "teacher")] = "REPLACED!"

Output:

>>> df
         age        job
0         10    teacher
1  REPLACED!  REPLACED!
2         40       chef
3  REPLACED!  REPLACED!
4         30     doctor
5         20  lifeguard

Note that if you dislike wrapping the x == y expressions in parentheses, you can use x.eq(y) (which is pandas-specific):

df.loc[df["age"].eq(20) & df["job"].eq("teacher")] = "REPLACED!"