mirror of
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136 lines
4.4 KiB
Python
136 lines
4.4 KiB
Python
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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from .base import BaseExtensionTests
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class BaseMissingTests(BaseExtensionTests):
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def test_isna(self, data_missing):
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expected = np.array([True, False])
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result = pd.isna(data_missing)
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tm.assert_numpy_array_equal(result, expected)
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result = pd.Series(data_missing).isna()
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expected = pd.Series(expected)
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self.assert_series_equal(result, expected)
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# GH 21189
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result = pd.Series(data_missing).drop([0, 1]).isna()
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expected = pd.Series([], dtype=bool)
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self.assert_series_equal(result, expected)
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def test_dropna_array(self, data_missing):
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result = data_missing.dropna()
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expected = data_missing[[1]]
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self.assert_extension_array_equal(result, expected)
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def test_dropna_series(self, data_missing):
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ser = pd.Series(data_missing)
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result = ser.dropna()
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expected = ser.iloc[[1]]
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self.assert_series_equal(result, expected)
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def test_dropna_frame(self, data_missing):
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df = pd.DataFrame({"A": data_missing})
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# defaults
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result = df.dropna()
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expected = df.iloc[[1]]
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self.assert_frame_equal(result, expected)
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# axis = 1
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result = df.dropna(axis="columns")
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expected = pd.DataFrame(index=[0, 1])
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self.assert_frame_equal(result, expected)
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# multiple
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df = pd.DataFrame({"A": data_missing, "B": [1, np.nan]})
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result = df.dropna()
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expected = df.iloc[:0]
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self.assert_frame_equal(result, expected)
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def test_fillna_scalar(self, data_missing):
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valid = data_missing[1]
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result = data_missing.fillna(valid)
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expected = data_missing.fillna(valid)
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self.assert_extension_array_equal(result, expected)
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def test_fillna_limit_pad(self, data_missing):
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arr = data_missing.take([1, 0, 0, 0, 1])
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result = pd.Series(arr).fillna(method="ffill", limit=2)
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expected = pd.Series(data_missing.take([1, 1, 1, 0, 1]))
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self.assert_series_equal(result, expected)
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def test_fillna_limit_backfill(self, data_missing):
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arr = data_missing.take([1, 0, 0, 0, 1])
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result = pd.Series(arr).fillna(method="backfill", limit=2)
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expected = pd.Series(data_missing.take([1, 0, 1, 1, 1]))
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self.assert_series_equal(result, expected)
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def test_fillna_series(self, data_missing):
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fill_value = data_missing[1]
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ser = pd.Series(data_missing)
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result = ser.fillna(fill_value)
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expected = pd.Series(
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data_missing._from_sequence(
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[fill_value, fill_value], dtype=data_missing.dtype
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)
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)
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self.assert_series_equal(result, expected)
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# Fill with a series
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result = ser.fillna(expected)
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self.assert_series_equal(result, expected)
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# Fill with a series not affecting the missing values
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result = ser.fillna(ser)
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self.assert_series_equal(result, ser)
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def test_fillna_series_method(self, data_missing, fillna_method):
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fill_value = data_missing[1]
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if fillna_method == "ffill":
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data_missing = data_missing[::-1]
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result = pd.Series(data_missing).fillna(method=fillna_method)
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expected = pd.Series(
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data_missing._from_sequence(
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[fill_value, fill_value], dtype=data_missing.dtype
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)
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)
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self.assert_series_equal(result, expected)
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def test_fillna_frame(self, data_missing):
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fill_value = data_missing[1]
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result = pd.DataFrame({"A": data_missing, "B": [1, 2]}).fillna(fill_value)
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expected = pd.DataFrame(
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{
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"A": data_missing._from_sequence(
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[fill_value, fill_value], dtype=data_missing.dtype
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),
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"B": [1, 2],
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}
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)
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self.assert_frame_equal(result, expected)
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def test_fillna_fill_other(self, data):
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result = pd.DataFrame({"A": data, "B": [np.nan] * len(data)}).fillna({"B": 0.0})
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expected = pd.DataFrame({"A": data, "B": [0.0] * len(result)})
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self.assert_frame_equal(result, expected)
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def test_use_inf_as_na_no_effect(self, data_missing):
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ser = pd.Series(data_missing)
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expected = ser.isna()
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with pd.option_context("mode.use_inf_as_na", True):
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result = ser.isna()
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self.assert_series_equal(result, expected)
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