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GroupBy.nth(n, dropna=None)

Take the nth row from each group if n is an int, or a subset of rows if n is a list of ints.

If dropna, will take the nth non-null row, dropna is either Truthy (if a Series) or ‘all’, ‘any’ (if a DataFrame); this is equivalent to calling dropna(how=dropna) before the groupby.


n : int or list of ints

a single nth value for the row or a list of nth values

dropna : None or str, optional

apply the specified dropna operation before counting which row is the nth row. Needs to be None, ‘any’ or ‘all’


>>> df = DataFrame([[1, np.nan], [1, 4], [5, 6]], columns=['A', 'B'])
>>> g = df.groupby('A')
>>> g.nth(0)
   A   B
0  1 NaN
2  5   6
>>> g.nth(1)
   A  B
1  1  4
>>> g.nth(-1)
   A  B
1  1  4
2  5  6
>>> g.nth(0, dropna='any')
1  4
5  6

# NaNs denote group exhausted when using dropna >>> g.nth(1, dropna=’any’)


1 NaN 5 NaN