Filter dataframe for value that exists in all dates

Say I have a dataframe like this:

df = pd.DataFrame({
    'PortDt': ['2022-01-31', '2022-02-28', '2022-02-28', '2022-03-31', '2022-03-31'],
    'loannum': ['111', '111', '222', '111', '333']
})

I want to filter the dataset so that I am left with only records who appear in every distinct value for PortDt.

For this example, the result would be:

PortDt     |   loannum
-----------+-------------
2022-01-31 |  111
2022-02-28 |  111
2022-03-31 |  111

>Solution :

Using groupby.transform with ‘nunique’ and comparing to the overall number of unique values:

out = df[df.groupby('loannum')['PortDt']
           .transform('nunique').eq(df['PortDt'].nunique())]

Or same logic with better efficiency:

s = df.groupby('loannum')['PortDt'].nunique().eq(df['PortDt'].nunique())

df[df['loannum'].isin(s[s].index)]

Or with crosstab+all instead of groupby:

s = pd.crosstab(df['PortDt'], df['loannum']).all()
out = df[df['loannum'].isin(s[s].index)]

Output:

       PortDt loannum
0  2022-01-31     111
1  2022-02-28     111
3  2022-03-31     111