243 lines
7.7 KiB
Python
243 lines
7.7 KiB
Python
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import pytest
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import numpy as np
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import pandas as pd
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import pandas.util.testing as tm
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from .base import BaseExtensionTests
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class BaseGetitemTests(BaseExtensionTests):
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"""Tests for ExtensionArray.__getitem__."""
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def test_iloc_series(self, data):
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ser = pd.Series(data)
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result = ser.iloc[:4]
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expected = pd.Series(data[:4])
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self.assert_series_equal(result, expected)
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result = ser.iloc[[0, 1, 2, 3]]
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self.assert_series_equal(result, expected)
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def test_iloc_frame(self, data):
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df = pd.DataFrame({"A": data, 'B':
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np.arange(len(data), dtype='int64')})
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expected = pd.DataFrame({"A": data[:4]})
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# slice -> frame
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result = df.iloc[:4, [0]]
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self.assert_frame_equal(result, expected)
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# sequence -> frame
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result = df.iloc[[0, 1, 2, 3], [0]]
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self.assert_frame_equal(result, expected)
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expected = pd.Series(data[:4], name='A')
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# slice -> series
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result = df.iloc[:4, 0]
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self.assert_series_equal(result, expected)
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# sequence -> series
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result = df.iloc[:4, 0]
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self.assert_series_equal(result, expected)
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def test_loc_series(self, data):
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ser = pd.Series(data)
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result = ser.loc[:3]
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expected = pd.Series(data[:4])
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self.assert_series_equal(result, expected)
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result = ser.loc[[0, 1, 2, 3]]
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self.assert_series_equal(result, expected)
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def test_loc_frame(self, data):
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df = pd.DataFrame({"A": data,
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'B': np.arange(len(data), dtype='int64')})
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expected = pd.DataFrame({"A": data[:4]})
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# slice -> frame
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result = df.loc[:3, ['A']]
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self.assert_frame_equal(result, expected)
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# sequence -> frame
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result = df.loc[[0, 1, 2, 3], ['A']]
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self.assert_frame_equal(result, expected)
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expected = pd.Series(data[:4], name='A')
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# slice -> series
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result = df.loc[:3, 'A']
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self.assert_series_equal(result, expected)
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# sequence -> series
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result = df.loc[:3, 'A']
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self.assert_series_equal(result, expected)
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def test_getitem_scalar(self, data):
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result = data[0]
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assert isinstance(result, data.dtype.type)
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result = pd.Series(data)[0]
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assert isinstance(result, data.dtype.type)
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def test_getitem_scalar_na(self, data_missing, na_cmp, na_value):
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result = data_missing[0]
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assert na_cmp(result, na_value)
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def test_getitem_mask(self, data):
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# Empty mask, raw array
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mask = np.zeros(len(data), dtype=bool)
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result = data[mask]
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assert len(result) == 0
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assert isinstance(result, type(data))
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# Empty mask, in series
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mask = np.zeros(len(data), dtype=bool)
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result = pd.Series(data)[mask]
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assert len(result) == 0
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assert result.dtype == data.dtype
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# non-empty mask, raw array
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mask[0] = True
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result = data[mask]
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assert len(result) == 1
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assert isinstance(result, type(data))
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# non-empty mask, in series
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result = pd.Series(data)[mask]
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assert len(result) == 1
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assert result.dtype == data.dtype
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def test_getitem_slice(self, data):
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# getitem[slice] should return an array
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result = data[slice(0)] # empty
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assert isinstance(result, type(data))
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result = data[slice(1)] # scalar
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assert isinstance(result, type(data))
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def test_get(self, data):
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# GH 20882
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s = pd.Series(data, index=[2 * i for i in range(len(data))])
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assert s.get(4) == s.iloc[2]
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result = s.get([4, 6])
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expected = s.iloc[[2, 3]]
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self.assert_series_equal(result, expected)
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result = s.get(slice(2))
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expected = s.iloc[[0, 1]]
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self.assert_series_equal(result, expected)
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assert s.get(-1) == s.iloc[-1]
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assert s.get(s.index.max() + 1) is None
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s = pd.Series(data[:6], index=list('abcdef'))
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assert s.get('c') == s.iloc[2]
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result = s.get(slice('b', 'd'))
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expected = s.iloc[[1, 2, 3]]
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self.assert_series_equal(result, expected)
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result = s.get('Z')
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assert result is None
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assert s.get(4) == s.iloc[4]
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assert s.get(-1) == s.iloc[-1]
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assert s.get(len(s)) is None
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def test_take_sequence(self, data):
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result = pd.Series(data)[[0, 1, 3]]
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assert result.iloc[0] == data[0]
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assert result.iloc[1] == data[1]
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assert result.iloc[2] == data[3]
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def test_take(self, data, na_value, na_cmp):
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result = data.take([0, -1])
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assert result.dtype == data.dtype
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assert result[0] == data[0]
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assert result[1] == data[-1]
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result = data.take([0, -1], allow_fill=True, fill_value=na_value)
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assert result[0] == data[0]
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assert na_cmp(result[1], na_value)
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with tm.assert_raises_regex(IndexError, "out of bounds"):
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data.take([len(data) + 1])
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def test_take_empty(self, data, na_value, na_cmp):
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empty = data[:0]
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result = empty.take([-1], allow_fill=True)
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assert na_cmp(result[0], na_value)
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with pytest.raises(IndexError):
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empty.take([-1])
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with tm.assert_raises_regex(IndexError, "cannot do a non-empty take"):
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empty.take([0, 1])
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def test_take_negative(self, data):
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# https://github.com/pandas-dev/pandas/issues/20640
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n = len(data)
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result = data.take([0, -n, n - 1, -1])
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expected = data.take([0, 0, n - 1, n - 1])
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self.assert_extension_array_equal(result, expected)
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def test_take_non_na_fill_value(self, data_missing):
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fill_value = data_missing[1] # valid
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na = data_missing[0]
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array = data_missing._from_sequence([na, fill_value, na])
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result = array.take([-1, 1], fill_value=fill_value, allow_fill=True)
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expected = array.take([1, 1])
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self.assert_extension_array_equal(result, expected)
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def test_take_pandas_style_negative_raises(self, data, na_value):
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with pytest.raises(ValueError):
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data.take([0, -2], fill_value=na_value, allow_fill=True)
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@pytest.mark.parametrize('allow_fill', [True, False])
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def test_take_out_of_bounds_raises(self, data, allow_fill):
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arr = data[:3]
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with pytest.raises(IndexError):
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arr.take(np.asarray([0, 3]), allow_fill=allow_fill)
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def test_take_series(self, data):
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s = pd.Series(data)
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result = s.take([0, -1])
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expected = pd.Series(
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data._from_sequence([data[0], data[len(data) - 1]]),
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index=[0, len(data) - 1])
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self.assert_series_equal(result, expected)
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def test_reindex(self, data, na_value):
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s = pd.Series(data)
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result = s.reindex([0, 1, 3])
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expected = pd.Series(data.take([0, 1, 3]), index=[0, 1, 3])
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self.assert_series_equal(result, expected)
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n = len(data)
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result = s.reindex([-1, 0, n])
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expected = pd.Series(
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data._from_sequence([na_value, data[0], na_value]),
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index=[-1, 0, n])
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self.assert_series_equal(result, expected)
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result = s.reindex([n, n + 1])
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expected = pd.Series(data._from_sequence([na_value, na_value]),
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index=[n, n + 1])
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self.assert_series_equal(result, expected)
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def test_reindex_non_na_fill_value(self, data_missing):
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valid = data_missing[1]
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na = data_missing[0]
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array = data_missing._from_sequence([na, valid])
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ser = pd.Series(array)
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result = ser.reindex([0, 1, 2], fill_value=valid)
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expected = pd.Series(data_missing._from_sequence([na, valid, valid]))
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self.assert_series_equal(result, expected)
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