Is There A Better Way To Find Duplicate Rows _including_ The First/last?

Consider a Pandas data frame: import pandas as pd df = pd.DataFrame({ 'a': pd.Series([1,1,1,2,3]), 'b': pd.Series(list('asdfg')) }) I want to return all of the rows with

Solution 1:

You can count occurrences of a and return values>1 for duplicated rows.

In [25]: df[(df.groupby('a').transform('count')>1).values]
Out[25]:
   a  b
0  1  a
1  1  s
2  1  d