python - how do I best validate email in pandas data frame

Question

I have a data frame (df) with emails and numbers like

    email                          euro
0   firstname@firstdomain.com      150
1   secondname@seconddomain.com     50
2   thirdname@thirddomain.com      300
3   kjfslkfj                         0
4   fourthname@fourthdomain.com    200

I need to filter all rows with correct emails and euro equal to or greater than 100 and another list with correct emails and euro lower than 100. I know that I can filter by euro like this

df_gt_100 = df.euro >= 100

and

df_lt_100 = df.euro < 100

But I can't find a way to filter the email addresses. I imported the email_validate package and tried things like this

validate_email(df.email)

which gives me a TypeError: expected string or bytes-like object.

Can anyone pls give me a hint how to approach this issue. It'd be nice if I could do this all in one filter with the AND and OR operators.

Thanks in advance, Manuel

Answer 1

Use apply, chain mask by & for AND and filter by boolean indexing:

from validate_email import validate_email

df1 = df[(df['euro'] > 100) & df['email'].apply(validate_email)]
print (df1)
                         email  euro
0    firstname@firstdomain.com   150
2    thirdname@thirddomain.com   300
4  fourthname@fourthdomain.com   200

Another approach with regex and contains:

df1 = df[(df['euro'] > 100) &df['email'].str.contains(r'[^@]+@[^@]+.[^@]+')]
print (df1)
                         email  euro
0    firstname@firstdomain.com   150
2    thirdname@thirddomain.com   300
4  fourthname@fourthdomain.com   200