pandas.core.groupby.DataFrameGroupBy.nth — pandas 3.0.0.dev0+2095.g2e141aaf99 documentation (original) (raw)

property DataFrameGroupBy.nth[source]#

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

Can be either a call or an index. dropna is not available with index notation. Index notation accepts a comma separated list of integers and slices.

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

Returns:

Series or DataFrame

N-th value within each group.

See also

Series.groupby

Apply a function groupby to a Series.

DataFrame.groupby

Apply a function groupby to each row or column of a DataFrame.

Examples

df = pd.DataFrame( ... {"A": [1, 1, 2, 1, 2], "B": [np.nan, 2, 3, 4, 5]}, columns=["A", "B"] ... ) g = df.groupby("A") g.nth(0) A B 0 1 NaN 2 2 3.0 g.nth(1) A B 1 1 2.0 4 2 5.0 g.nth(-1) A B 3 1 4.0 4 2 5.0 g.nth([0, 1]) A B 0 1 NaN 1 1 2.0 2 2 3.0 4 2 5.0 g.nth(slice(None, -1)) A B 0 1 NaN 1 1 2.0 2 2 3.0

Index notation may also be used

g.nth[0, 1] A B 0 1 NaN 1 1 2.0 2 2 3.0 4 2 5.0 g.nth[:-1] A B 0 1 NaN 1 1 2.0 2 2 3.0

Specifying dropna allows ignoring NaN values

g.nth(0, dropna="any") A B 1 1 2.0 2 2 3.0

When the specified n is larger than any of the groups, an empty DataFrame is returned

g.nth(3, dropna="any") Empty DataFrame Columns: [A, B] Index: []