{tags: show duplicates in a particular column but print whole line, show duplicates in a particular column but print other columns, show groups with more than 1 count, uniq on a single column but print duplicate lines
solution uses: do not display index, only read certain columns of a csv file}

Given a csv file such as

$ cat album.csv
Artist,AlbumId,TrackId
A,201,1022
A,201,3472
A,451,9866
B,390,6078
B,390,2634
C,272,3411
C,272,8673
C,698,2543
C,698,5837
D,235,9874
E,312,1089

1) show artists that have multiple albums along with their album ids. That is print

Artist,AlbumId
A,201
A,451
C,272
C,698

2) show artists that have multiple albums along with their album ids and track ids. That is print

Artist,AlbumId,TrackId
A,201,1022
A,201,3472
A,451,9866
C,272,3411
C,272,8673
C,698,2543
C,698,5837

In [6]:
import pandas as pd
coi = ['Artist', 'AlbumId']
df = pd.read_csv('album.csv', usecols=coi).drop_duplicates()
duplicates = df.groupby(['Artist']).filter(lambda grp: grp['AlbumId'].nunique() > 1).sort_values('Artist')
print(duplicates.to_csv(index=False))
Artist,AlbumId
A,201
A,451
C,272
C,698

To print other columns, change the coi (columns of interest) variable

In [7]:
import pandas as pd
coi = ['Artist', 'AlbumId', 'TrackId']
df = pd.read_csv('album.csv', usecols=coi).drop_duplicates()
duplicates = df.groupby(['Artist']).filter(lambda grp: grp['AlbumId'].nunique() > 1).sort_values('Artist')
print(duplicates.to_csv(index=False))
Artist,AlbumId,TrackId
A,201,1022
A,201,3472
A,451,9866
C,272,3411
C,272,8673
C,698,2543
C,698,5837

$ ipython
Python 3.11.8 | packaged by Anaconda, Inc. | (main, Feb 26 2024, 21:34:05) [MSC v.1916 64 bit (AMD64)]
IPython 8.20.0 -- An enhanced Interactive Python. Type '?' for help.

In [1]:
import pandas as pd
df = pd.read_csv('album.csv', usecols=['Artist', 'AlbumId']).drop_duplicates()
df
Out[1]:
   Artist  AlbumId
0       A      201
2       A      451
3       B      390
5       C      272
7       C      698
9       D      235
10      E      312

In [2]:
duplicates = df.groupby(['Artist']).filter(lambda grp: grp['AlbumId'].nunique() > 1).sort_values('Artist')
duplicates
Out[2]:
  Artist  AlbumId
0      A      201
2      A      451
5      C      272
7      C      698

In [3]:
print(duplicates.to_csv(index=False))
Artist,AlbumId
A,201
A,451
C,272
C,698

• https://stackoverflow.com/questions/70236139/pandas-groupby-select-groups-that-have-more-than-one-unique-values-in-a-column - this is where I found the sample data and the initial solution. I just modified it to fit my needs.
• https://stackoverflow.com/a/24646906 - shows how to display pandas dataframe without index
• https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html
• https://stackoverflow.com/questions/53979178/pandas-groupby-show-only-groups-with-more-than-one-unique-feature-value/ - similar question. My answer is in https://stackoverflow.com/a/78809363/6305733