103 lines
2.6 KiB
Python
103 lines
2.6 KiB
Python
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import numpy as np
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import pandas as pd
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import pandas._testing as tm
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def test_data_frame_value_counts_unsorted():
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df = pd.DataFrame(
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{"num_legs": [2, 4, 4, 6], "num_wings": [2, 0, 0, 0]},
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index=["falcon", "dog", "cat", "ant"],
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)
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result = df.value_counts(sort=False)
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expected = pd.Series(
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data=[1, 2, 1],
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index=pd.MultiIndex.from_arrays(
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[(2, 4, 6), (2, 0, 0)], names=["num_legs", "num_wings"]
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),
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)
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tm.assert_series_equal(result, expected)
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def test_data_frame_value_counts_ascending():
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df = pd.DataFrame(
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{"num_legs": [2, 4, 4, 6], "num_wings": [2, 0, 0, 0]},
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index=["falcon", "dog", "cat", "ant"],
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)
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result = df.value_counts(ascending=True)
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expected = pd.Series(
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data=[1, 1, 2],
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index=pd.MultiIndex.from_arrays(
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[(2, 6, 4), (2, 0, 0)], names=["num_legs", "num_wings"]
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),
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)
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tm.assert_series_equal(result, expected)
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def test_data_frame_value_counts_default():
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df = pd.DataFrame(
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{"num_legs": [2, 4, 4, 6], "num_wings": [2, 0, 0, 0]},
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index=["falcon", "dog", "cat", "ant"],
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)
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result = df.value_counts()
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expected = pd.Series(
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data=[2, 1, 1],
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index=pd.MultiIndex.from_arrays(
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[(4, 2, 6), (0, 2, 0)], names=["num_legs", "num_wings"]
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),
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)
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tm.assert_series_equal(result, expected)
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def test_data_frame_value_counts_normalize():
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df = pd.DataFrame(
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{"num_legs": [2, 4, 4, 6], "num_wings": [2, 0, 0, 0]},
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index=["falcon", "dog", "cat", "ant"],
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)
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result = df.value_counts(normalize=True)
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expected = pd.Series(
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data=[0.5, 0.25, 0.25],
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index=pd.MultiIndex.from_arrays(
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[(4, 2, 6), (0, 2, 0)], names=["num_legs", "num_wings"]
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),
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)
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tm.assert_series_equal(result, expected)
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def test_data_frame_value_counts_single_col_default():
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df = pd.DataFrame({"num_legs": [2, 4, 4, 6]})
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result = df.value_counts()
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expected = pd.Series(
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data=[2, 1, 1],
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index=pd.MultiIndex.from_arrays([[4, 2, 6]], names=["num_legs"]),
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)
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tm.assert_series_equal(result, expected)
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def test_data_frame_value_counts_empty():
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df_no_cols = pd.DataFrame()
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result = df_no_cols.value_counts()
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expected = pd.Series([], dtype=np.int64)
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tm.assert_series_equal(result, expected)
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def test_data_frame_value_counts_empty_normalize():
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df_no_cols = pd.DataFrame()
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result = df_no_cols.value_counts(normalize=True)
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expected = pd.Series([], dtype=np.float64)
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tm.assert_series_equal(result, expected)
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