cudf.core.groupby.DataFrameGroupBy.nth#

property DataFrameGroupBy.nth[source]#

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

Like pandas, supports both the call form gb.nth(n, dropna=...) and the index form gb.nth[n].

Parameters:

nint, slice or list of ints and slices: A single nth value for the row, a slice with non-negative step or a list of nth values and slices. Negative values count from the end of each group.
dropna{‘any’, ‘all’, None}, default None: Apply the specified dropna operation before counting which row is the nth row. Only supported in the call form and not currently implemented in cuDF (raises NotImplementedError; falls back to pandas under cudf.pandas).

Returns:

Series or DataFrame: The nth row(s) of each group, keeping the original index and row order (like a filter operation, the group keys are not added as an index level).

Examples

>>> import cudf
>>> df = cudf.DataFrame({"A": [1, 1, 2, 1, 2],
...                      "B": [None, 2, 3, 4, 5]})
>>> gb = df.groupby("A")
>>> gb.nth(0)
   A     B
0  1  <NA>
2  2     3
>>> gb.nth(-1)
   A  B
3  1  4
4  2  5
>>> gb.nth[:2]
   A     B
0  1  <NA>
1  1     2
2  2     3
4  2     5