Filter Dataframe by Column Frequency with value counts

Sometimes, I need to filter a dataset based on the specific frequency threshold from one column. For example, how many users visited a website more than 5 times a day?

import pandas as pd

# reading sample dataframe
df = pd.DataFrame( {'letters': ['E', 'E', 'B', 'C', 'B', 'D', 'E', 'B', 'E', 'A', 'E', 'B', 'C',
                                'D', 'E', 'E', 'A', 'E', 'B', 'E', 'B']} )

df.value_counts()

letters E 9 B 6 A 2 C 2 D 2 dtype: int64

Filtering for letters with more than 5 appearances. It works by retrieving the index from the series object returned by value_counts().

df[ df.letters.isin( df.letters.value_counts()[df.letters.value_counts() > 5 ].index )]