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import numpy as np |
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import pandas as pd |
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import unittest |
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from klib.describe import _missing_vals |
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5
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6
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if __name__ == '__main__': |
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unittest.main() |
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8
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9
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data_mv = pd.DataFrame([[1, np.nan, 3, 4], |
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10
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[None, 4, 5, ], |
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['a', 'b', pd.NA, 'd'], |
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12
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[True, False, 7, pd.NaT]], |
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columns=['Col1', 'Col2', 'Col3', 'Col4']) |
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14
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15
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16
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class Test__missing_vals(unittest.TestCase): |
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def test_mv_total(self): |
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# Test total missing values |
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self.assertAlmostEqual(_missing_vals(data_mv)['mv_total'], 5) |
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def test_mv_rows(self): |
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# Test missing values for each row |
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self.assertAlmostEqual(_missing_vals(data_mv)['mv_rows'][0], 1) |
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25
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self.assertAlmostEqual(_missing_vals(data_mv)['mv_rows'][1], 2) |
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self.assertAlmostEqual(_missing_vals(data_mv)['mv_rows'][2], 1) |
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self.assertAlmostEqual(_missing_vals(data_mv)['mv_rows'][2], 1) |
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29
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def test_mv_cols(self): |
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# Test missing values for each column |
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self.assertAlmostEqual(_missing_vals(data_mv)['mv_cols'][0], 1) |
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self.assertAlmostEqual(_missing_vals(data_mv)['mv_cols'][1], 1) |
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self.assertAlmostEqual(_missing_vals(data_mv)['mv_cols'][2], 1) |
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self.assertAlmostEqual(_missing_vals(data_mv)['mv_cols'][3], 2) |
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def test_mv_rows_ratio(self): |
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# Test missing values ratio for each row |
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self.assertAlmostEqual(_missing_vals(data_mv)['mv_rows_ratio'][0], 0.25) |
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self.assertAlmostEqual(_missing_vals(data_mv)['mv_rows_ratio'][1], 0.5) |
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self.assertAlmostEqual(_missing_vals(data_mv)['mv_rows_ratio'][2], 0.25) |
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self.assertAlmostEqual(_missing_vals(data_mv)['mv_rows_ratio'][3], 0.25) |
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def test_mv_cols_ratio(self): |
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# Test missing values ratio for each row |
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self.assertAlmostEqual(_missing_vals(data_mv)['mv_cols_ratio'][0], 0.25) |
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self.assertAlmostEqual(_missing_vals(data_mv)['mv_cols_ratio'][1], 0.25) |
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self.assertAlmostEqual(_missing_vals(data_mv)['mv_cols_ratio'][2], 0.25) |
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self.assertAlmostEqual(_missing_vals(data_mv)['mv_cols_ratio'][3], 0.5) |
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49
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akanz1 /
klib
