How do count the number of duplicate DataFrames after using grouby in pandas?

import pandas as pd


df = pd.read_csv('chim_work.csv')

df_col = df[['ID #','Init Acct Type','Subs Acct Type','Max Days Diff']]

df_drop_null = df_col.dropna()

df_group = df_drop_null.groupby('ID #')


for i, d in df_group:
    dfn = d.drop(columns=['ID #'])
    print(i)
    print(dfn)

This code gives me my ID#s attached to 3 column DataFrames.

I want to figure out which DataFrames have duplicates, the id# of the duplicates and the count. Then create new labels for them.

So the output would be:

A
5 Duplicates
Id: 101, 102, 105, 107, 120