Multiple sets of duplicate records from a pandas dataframe

Question

How to get all the existing duplicated sets of records(based on a column) from a dataframe?

I got a dataframe as follows:

flight_id | from_location  | to_location |  schedule |  
1         |   Vancouver    |   Toronto   |   3-Jan   |  
2         |   Amsterdam    |   Tokyo     |   15-Feb  |  
4         |   Fairbanks    |   Glasgow   |   12-Jan  |  
9         |   Halmstad     |   Athens    |   21-Jan  |  
3         |   Brisbane     |   Lisbon    |   4-Feb   |  
4         | Johannesburg   |   Venice    |   23-Jan  |
9         | LosAngeles     |  Perth      |   3-Mar   |

Here flight_id is the column on which I need to check duplicates. And there are 2 sets of duplicates.

Output for this specific example should look like--[(2,5),(3,6)]. List of tuples of record index values

Answer 1

Is this what you need ? duplicated+groupby

(df.loc[df['flight_id'].duplicated(keep=False)].reset_index()).groupby('flight_id')['index'].apply(tuple)
Out[510]: 
flight_id
4    (2, 5)
9    (3, 6)
Name: index, dtype: object

Adding tolist at the end

(df.loc[df['flight_id'].duplicated(keep=False)].reset_index()).groupby('flight_id')['index'].apply(tuple).tolist()
Out[511]: [(2, 5), (3, 6)]

And another solution ... for fun only

s=df['flight_id'].value_counts()
list(map(lambda x : tuple(df[df['flight_id']==x].index.tolist()), s[s.gt(1)].index))
Out[519]: [(2, 5), (3, 6)]