To filter Python Pandas dataframe using ‘in’ and ‘not in’ like in SQL, we call the isin method.
For instance, we write
df[df.country.isin(countries_to_keep)]
to call df.country.isin to get the rows that has the country column set to the values in the countries_to_keep list.
We can negate isin with ~, so we can write
df[~df.country.isin(countries_to_keep)]
to call df.country.isin to get the rows that has the country column that aren’t set to the values in the countries_to_keep list.
