How do I get a list of all the duplicate items using pandas in python?
With Pandas version 0.17, you can set 'keep = False' in the duplicated function to get all the duplicate items.
In [1]: import pandas as pd
In [2]: df = pd.DataFrame(['a','b','c','d','a','b'])
In [3]: df
Out[3]:
0
0 a
1 b
2 c
3 d
4 a
5 b
In [4]: df[df.duplicated(keep=False)]
Out[4]:
0
0 a
1 b
4 a
5 b
Method #1: print all rows where the ID is one of the IDs in duplicated:
>>> import pandas as pd
>>> df = pd.read_csv("dup.csv")
>>> ids = df["ID"]
>>> df[ids.isin(ids[ids.duplicated()])].sort_values("ID")
ID ENROLLMENT_DATE TRAINER_MANAGING TRAINER_OPERATOR FIRST_VISIT_DATE
24 11795 27-Feb-12 0643D38-Hanover NH 0643D38-Hanover NH 19-Jun-12
6 11795 3-Jul-12 0649597-White River VT 0649597-White River VT 30-Mar-12
18 8096 19-Dec-11 0649597-White River VT 0649597-White River VT 9-Apr-12
2 8096 8-Aug-12 0643D38-Hanover NH 0643D38-Hanover NH 25-Jun-12
12 A036 30-Nov-11 063B208-Randolph VT 063B208-Randolph VT NaN
3 A036 1-Apr-12 06CB8CF-Hanover NH 06CB8CF-Hanover NH 9-Aug-12
26 A036 11-Aug-12 06D3206-Hanover NH NaN 19-Jun-12
but I couldn't think of a nice way to prevent repeating ids
so many times. I prefer method #2: groupby
on the ID.
>>> pd.concat(g for _, g in df.groupby("ID") if len(g) > 1)
ID ENROLLMENT_DATE TRAINER_MANAGING TRAINER_OPERATOR FIRST_VISIT_DATE
6 11795 3-Jul-12 0649597-White River VT 0649597-White River VT 30-Mar-12
24 11795 27-Feb-12 0643D38-Hanover NH 0643D38-Hanover NH 19-Jun-12
2 8096 8-Aug-12 0643D38-Hanover NH 0643D38-Hanover NH 25-Jun-12
18 8096 19-Dec-11 0649597-White River VT 0649597-White River VT 9-Apr-12
3 A036 1-Apr-12 06CB8CF-Hanover NH 06CB8CF-Hanover NH 9-Aug-12
12 A036 30-Nov-11 063B208-Randolph VT 063B208-Randolph VT NaN
26 A036 11-Aug-12 06D3206-Hanover NH NaN 19-Jun-12