99 lines
3.2 KiB
Python
99 lines
3.2 KiB
Python
import numpy as np
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import pytest
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import pandas as pd
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from pandas import (
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Categorical,
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MultiIndex,
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Series,
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)
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import pandas._testing as tm
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class TestSeriesCount:
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def test_count_level_series(self):
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index = MultiIndex(
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levels=[["foo", "bar", "baz"], ["one", "two", "three", "four"]],
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codes=[[0, 0, 0, 2, 2], [2, 0, 1, 1, 2]],
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)
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ser = Series(np.random.randn(len(index)), index=index)
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with tm.assert_produces_warning(FutureWarning):
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result = ser.count(level=0)
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expected = ser.groupby(level=0).count()
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tm.assert_series_equal(
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result.astype("f8"), expected.reindex(result.index).fillna(0)
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)
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with tm.assert_produces_warning(FutureWarning):
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result = ser.count(level=1)
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expected = ser.groupby(level=1).count()
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tm.assert_series_equal(
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result.astype("f8"), expected.reindex(result.index).fillna(0)
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)
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def test_count_multiindex(self, series_with_multilevel_index):
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ser = series_with_multilevel_index
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series = ser.copy()
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series.index.names = ["a", "b"]
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with tm.assert_produces_warning(FutureWarning):
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result = series.count(level="b")
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with tm.assert_produces_warning(FutureWarning):
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expect = ser.count(level=1).rename_axis("b")
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tm.assert_series_equal(result, expect)
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with tm.assert_produces_warning(FutureWarning):
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result = series.count(level="a")
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with tm.assert_produces_warning(FutureWarning):
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expect = ser.count(level=0).rename_axis("a")
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tm.assert_series_equal(result, expect)
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msg = "Level x not found"
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with pytest.raises(KeyError, match=msg):
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with tm.assert_produces_warning(FutureWarning):
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series.count("x")
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def test_count_level_without_multiindex(self):
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ser = Series(range(3))
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msg = "Series.count level is only valid with a MultiIndex"
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with pytest.raises(ValueError, match=msg):
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with tm.assert_produces_warning(FutureWarning):
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ser.count(level=1)
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def test_count(self, datetime_series):
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assert datetime_series.count() == len(datetime_series)
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datetime_series[::2] = np.NaN
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assert datetime_series.count() == np.isfinite(datetime_series).sum()
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mi = MultiIndex.from_arrays([list("aabbcc"), [1, 2, 2, np.nan, 1, 2]])
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ts = Series(np.arange(len(mi)), index=mi)
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with tm.assert_produces_warning(FutureWarning):
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left = ts.count(level=1)
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right = Series([2, 3, 1], index=[1, 2, np.nan])
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tm.assert_series_equal(left, right)
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ts.iloc[[0, 3, 5]] = np.nan
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with tm.assert_produces_warning(FutureWarning):
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tm.assert_series_equal(ts.count(level=1), right - 1)
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# GH#29478
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with pd.option_context("use_inf_as_na", True):
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assert Series([pd.Timestamp("1990/1/1")]).count() == 1
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def test_count_categorical(self):
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ser = Series(
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Categorical(
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[np.nan, 1, 2, np.nan], categories=[5, 4, 3, 2, 1], ordered=True
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)
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)
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result = ser.count()
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assert result == 2
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