How to filter Pandas dataframe using 'in' and 'not in' like in SQL

You can use pd.Series.isin.

For "IN" use: something.isin(somewhere)

Or for "NOT IN": ~something.isin(somewhere)

As a worked example:

>>> df
  countries
0        US
1        UK
2   Germany
3     China
>>> countries
['UK', 'China']
>>> df.countries.isin(countries)
0    False
1     True
2    False
3     True
Name: countries, dtype: bool
>>> df[df.countries.isin(countries)]
  countries
1        UK
3     China
>>> df[~df.countries.isin(countries)]
  countries
0        US
2   Germany

from : https://stackoverflow.com/questions/19960077/how-to-filter-pandas-dataframe-using-in-and-not-in-like-in-sql