Cleaning Netflix-style recommendation engine datasets
The usual
Use a PEP8 linter; move global code into functions; use type hints; use a __main__ guard.
Column use
basics.drop(basics.columns[[3,4,6,7]], axis=1, inplace=True)
basics.columns = ['tconst','type','title','year','genre']

really shouldn't be necessary. Use the usecols kwarg of read_table instead; the col names are a loose guess from the IMDB documentation:
basics = pd.read_table(
    'basics.tsv',
    usecols=(
        'tconst', 'titleType', 'primaryTitle', 'startYear', 'genres',
    ),
)