Pandas: return rows that have two matching columns commonality

I am trying to write a commonality script which will return rows in a pandas dataframe that have two matching columns, and also will sum up the number of rows with matches into a new column

OPERATION and MACHINE are the columns to match

Input:

BATCH	OPERATION	MACHINE	DATE
1A	4000	Printer1	01-Jan-22
1A	2000	Fax1	02-Jan-22
1B	4000	Printer2	03-Jan-22
1B	2000	Phone1	04-Jan-22
1C	2000	Phone2	05-Jan-22
1A	2000	Phone2	06-Jan-22

Output: just the last two rows in this example with OPERATION =2000 and MACHINE = Phone2

BATCH	OPERATION	MACHINE	DATE	MATCHES
1C	2000	Phone2	05-Jan-22	2
1A	2000	Phone2	06-Jan-22	2

I have tried several merge and duplicated df commands but can’t get it work.

Answer

df[df.groupby(['OPERATION', 'MACHINE'])['BATCH'].transform('count') > 1].assign(MATCHES = df.groupby(['OPERATION', 'MACHINE'])['BATCH'].transform('count'))

  BATCH  OPERATION MACHINE       DATE  MATCHES
4    1C       2000  Phone2  05-Jan-22        2
5    1A       2000  Phone2  06-Jan-22        2

OR

df['MATCHES'] = df.groupby(['OPERATION', 'MACHINE'])['BATCH'].transform('count')
df[df['MATCHES']>1]

Note: one may be faster than other depending on the source dataframe