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| import numpy as np
| import pytest
|
| import pandas as pd
| import pandas._testing as tm
|
|
| @pytest.fixture(params=[["inner"], ["inner", "outer"]])
| def frame(request):
| levels = request.param
| df = pd.DataFrame(
| {
| "outer": ["a", "a", "a", "b", "b", "b"],
| "inner": [1, 2, 3, 1, 2, 3],
| "A": np.arange(6),
| "B": ["one", "one", "two", "two", "one", "one"],
| }
| )
| if levels:
| df = df.set_index(levels)
|
| return df
|
|
| @pytest.fixture()
| def series():
| df = pd.DataFrame(
| {
| "outer": ["a", "a", "a", "b", "b", "b"],
| "inner": [1, 2, 3, 1, 2, 3],
| "A": np.arange(6),
| "B": ["one", "one", "two", "two", "one", "one"],
| }
| )
| s = df.set_index(["outer", "inner", "B"])["A"]
|
| return s
|
|
| @pytest.mark.parametrize(
| "key_strs,groupers",
| [
| ("inner", pd.Grouper(level="inner")), # Index name
| (["inner"], [pd.Grouper(level="inner")]), # List of index name
| (["B", "inner"], ["B", pd.Grouper(level="inner")]), # Column and index
| (["inner", "B"], [pd.Grouper(level="inner"), "B"]), # Index and column
| ],
| )
| def test_grouper_index_level_as_string(frame, key_strs, groupers):
| if "B" not in key_strs or "outer" in frame.columns:
| result = frame.groupby(key_strs).mean(numeric_only=True)
| expected = frame.groupby(groupers).mean(numeric_only=True)
| else:
| result = frame.groupby(key_strs).mean()
| expected = frame.groupby(groupers).mean()
| tm.assert_frame_equal(result, expected)
|
|
| @pytest.mark.parametrize(
| "levels",
| [
| "inner",
| "outer",
| "B",
| ["inner"],
| ["outer"],
| ["B"],
| ["inner", "outer"],
| ["outer", "inner"],
| ["inner", "outer", "B"],
| ["B", "outer", "inner"],
| ],
| )
| def test_grouper_index_level_as_string_series(series, levels):
| # Compute expected result
| if isinstance(levels, list):
| groupers = [pd.Grouper(level=lv) for lv in levels]
| else:
| groupers = pd.Grouper(level=levels)
|
| expected = series.groupby(groupers).mean()
|
| # Compute and check result
| result = series.groupby(levels).mean()
| tm.assert_series_equal(result, expected)
|
|
