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| import numpy as np
| import pytest
|
| from pandas import (
| MultiIndex,
| Series,
| date_range,
| )
| import pandas._testing as tm
|
|
| def test_nlargest():
| a = Series([1, 3, 5, 7, 2, 9, 0, 4, 6, 10])
| b = Series(list("a" * 5 + "b" * 5))
| gb = a.groupby(b)
| r = gb.nlargest(3)
| e = Series(
| [7, 5, 3, 10, 9, 6],
| index=MultiIndex.from_arrays([list("aaabbb"), [3, 2, 1, 9, 5, 8]]),
| )
| tm.assert_series_equal(r, e)
|
| a = Series([1, 1, 3, 2, 0, 3, 3, 2, 1, 0])
| gb = a.groupby(b)
| e = Series(
| [3, 2, 1, 3, 3, 2],
| index=MultiIndex.from_arrays([list("aaabbb"), [2, 3, 1, 6, 5, 7]]),
| )
| tm.assert_series_equal(gb.nlargest(3, keep="last"), e)
|
|
| def test_nlargest_mi_grouper():
| # see gh-21411
| npr = np.random.default_rng(2)
|
| dts = date_range("20180101", periods=10)
| iterables = [dts, ["one", "two"]]
|
| idx = MultiIndex.from_product(iterables, names=["first", "second"])
| s = Series(npr.standard_normal(20), index=idx)
|
| result = s.groupby("first").nlargest(1)
|
| exp_idx = MultiIndex.from_tuples(
| [
| (dts[0], dts[0], "one"),
| (dts[1], dts[1], "one"),
| (dts[2], dts[2], "one"),
| (dts[3], dts[3], "two"),
| (dts[4], dts[4], "one"),
| (dts[5], dts[5], "one"),
| (dts[6], dts[6], "one"),
| (dts[7], dts[7], "one"),
| (dts[8], dts[8], "one"),
| (dts[9], dts[9], "one"),
| ],
| names=["first", "first", "second"],
| )
|
| exp_values = [
| 0.18905338179353307,
| -0.41306354339189344,
| 1.799707382720902,
| 0.7738065867276614,
| 0.28121066979764925,
| 0.9775674511260357,
| -0.3288239040579627,
| 0.45495807124085547,
| 0.5452887139646817,
| 0.12682784711186987,
| ]
|
| expected = Series(exp_values, index=exp_idx)
| tm.assert_series_equal(result, expected, check_exact=False, rtol=1e-3)
|
|
| def test_nsmallest():
| a = Series([1, 3, 5, 7, 2, 9, 0, 4, 6, 10])
| b = Series(list("a" * 5 + "b" * 5))
| gb = a.groupby(b)
| r = gb.nsmallest(3)
| e = Series(
| [1, 2, 3, 0, 4, 6],
| index=MultiIndex.from_arrays([list("aaabbb"), [0, 4, 1, 6, 7, 8]]),
| )
| tm.assert_series_equal(r, e)
|
| a = Series([1, 1, 3, 2, 0, 3, 3, 2, 1, 0])
| gb = a.groupby(b)
| e = Series(
| [0, 1, 1, 0, 1, 2],
| index=MultiIndex.from_arrays([list("aaabbb"), [4, 1, 0, 9, 8, 7]]),
| )
| tm.assert_series_equal(gb.nsmallest(3, keep="last"), e)
|
|
| @pytest.mark.parametrize(
| "data, groups",
| [([0, 1, 2, 3], [0, 0, 1, 1]), ([0], [0])],
| )
| @pytest.mark.parametrize("dtype", [None, *tm.ALL_INT_NUMPY_DTYPES])
| @pytest.mark.parametrize("method", ["nlargest", "nsmallest"])
| def test_nlargest_and_smallest_noop(data, groups, dtype, method):
| # GH 15272, GH 16345, GH 29129
| # Test nlargest/smallest when it results in a noop,
| # i.e. input is sorted and group size <= n
| if dtype is not None:
| data = np.array(data, dtype=dtype)
| if method == "nlargest":
| data = list(reversed(data))
| ser = Series(data, name="a")
| result = getattr(ser.groupby(groups), method)(n=2)
| expidx = np.array(groups, dtype=int) if isinstance(groups, list) else groups
| expected = Series(data, index=MultiIndex.from_arrays([expidx, ser.index]), name="a")
| tm.assert_series_equal(result, expected)
|
|
