77 lines
2.3 KiB
Python
77 lines
2.3 KiB
Python
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"""
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these are systematically testing all of the args to value_counts
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with different size combinations. This is to ensure stability of the sorting
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and proper parameter handling
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"""
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import pytest
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from itertools import product
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import numpy as np
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from pandas.util import testing as tm
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from pandas import MultiIndex, DataFrame, Series, date_range
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# our starting frame
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def seed_df(seed_nans, n, m):
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np.random.seed(1234)
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days = date_range('2015-08-24', periods=10)
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frame = DataFrame({
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'1st': np.random.choice(
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list('abcd'), n),
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'2nd': np.random.choice(days, n),
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'3rd': np.random.randint(1, m + 1, n)
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})
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if seed_nans:
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frame.loc[1::11, '1st'] = np.nan
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frame.loc[3::17, '2nd'] = np.nan
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frame.loc[7::19, '3rd'] = np.nan
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frame.loc[8::19, '3rd'] = np.nan
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frame.loc[9::19, '3rd'] = np.nan
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return frame
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# create input df, keys, and the bins
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binned = []
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ids = []
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for seed_nans in [True, False]:
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for n, m in product((100, 1000), (5, 20)):
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df = seed_df(seed_nans, n, m)
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bins = None, np.arange(0, max(5, df['3rd'].max()) + 1, 2)
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keys = '1st', '2nd', ['1st', '2nd']
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for k, b in product(keys, bins):
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binned.append((df, k, b, n, m))
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ids.append("{}-{}-{}".format(k, n, m))
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@pytest.mark.slow
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@pytest.mark.parametrize("df, keys, bins, n, m", binned, ids=ids)
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def test_series_groupby_value_counts(df, keys, bins, n, m):
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def rebuild_index(df):
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arr = list(map(df.index.get_level_values, range(df.index.nlevels)))
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df.index = MultiIndex.from_arrays(arr, names=df.index.names)
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return df
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for isort, normalize, sort, ascending, dropna \
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in product((False, True), repeat=5):
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kwargs = dict(normalize=normalize, sort=sort,
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ascending=ascending, dropna=dropna, bins=bins)
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gr = df.groupby(keys, sort=isort)
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left = gr['3rd'].value_counts(**kwargs)
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gr = df.groupby(keys, sort=isort)
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right = gr['3rd'].apply(Series.value_counts, **kwargs)
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right.index.names = right.index.names[:-1] + ['3rd']
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# have to sort on index because of unstable sort on values
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left, right = map(rebuild_index, (left, right)) # xref GH9212
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tm.assert_series_equal(left.sort_index(), right.sort_index())
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