440 lines
13 KiB
Python
440 lines
13 KiB
Python
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""" test get/set & misc """
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from datetime import timedelta
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import re
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import numpy as np
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import pytest
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from pandas.errors import IndexingError
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from pandas import (
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NA,
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DataFrame,
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Index,
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IndexSlice,
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MultiIndex,
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Series,
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Timedelta,
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Timestamp,
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concat,
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date_range,
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period_range,
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timedelta_range,
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)
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import pandas._testing as tm
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def test_basic_indexing():
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s = Series(np.random.randn(5), index=["a", "b", "a", "a", "b"])
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msg = "index 5 is out of bounds for axis 0 with size 5"
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with pytest.raises(IndexError, match=msg):
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s[5]
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with pytest.raises(IndexError, match=msg):
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s[5] = 0
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with pytest.raises(KeyError, match=r"^'c'$"):
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s["c"]
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s = s.sort_index()
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with pytest.raises(IndexError, match=msg):
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s[5]
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msg = r"index 5 is out of bounds for axis (0|1) with size 5|^5$"
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with pytest.raises(IndexError, match=msg):
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s[5] = 0
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def test_getitem_numeric_should_not_fallback_to_positional(any_numeric_dtype):
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# GH51053
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dtype = any_numeric_dtype
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idx = Index([1, 0, 1], dtype=dtype)
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ser = Series(range(3), index=idx)
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result = ser[1]
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expected = Series([0, 2], index=Index([1, 1], dtype=dtype))
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tm.assert_series_equal(result, expected, check_exact=True)
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def test_setitem_numeric_should_not_fallback_to_positional(any_numeric_dtype):
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# GH51053
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dtype = any_numeric_dtype
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idx = Index([1, 0, 1], dtype=dtype)
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ser = Series(range(3), index=idx)
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ser[1] = 10
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expected = Series([10, 1, 10], index=idx)
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tm.assert_series_equal(ser, expected, check_exact=True)
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def test_basic_getitem_with_labels(datetime_series):
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indices = datetime_series.index[[5, 10, 15]]
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result = datetime_series[indices]
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expected = datetime_series.reindex(indices)
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tm.assert_series_equal(result, expected)
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result = datetime_series[indices[0] : indices[2]]
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expected = datetime_series.loc[indices[0] : indices[2]]
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tm.assert_series_equal(result, expected)
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def test_basic_getitem_dt64tz_values():
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# GH12089
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# with tz for values
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ser = Series(
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date_range("2011-01-01", periods=3, tz="US/Eastern"), index=["a", "b", "c"]
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)
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expected = Timestamp("2011-01-01", tz="US/Eastern")
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result = ser.loc["a"]
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assert result == expected
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result = ser.iloc[0]
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assert result == expected
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result = ser["a"]
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assert result == expected
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def test_getitem_setitem_ellipsis():
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s = Series(np.random.randn(10))
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result = s[...]
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tm.assert_series_equal(result, s)
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s[...] = 5
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assert (result == 5).all()
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@pytest.mark.parametrize(
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"result_1, duplicate_item, expected_1",
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[
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[
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Series({1: 12, 2: [1, 2, 2, 3]}),
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Series({1: 313}),
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Series({1: 12}, dtype=object),
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],
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[
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Series({1: [1, 2, 3], 2: [1, 2, 2, 3]}),
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Series({1: [1, 2, 3]}),
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Series({1: [1, 2, 3]}),
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],
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],
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)
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def test_getitem_with_duplicates_indices(result_1, duplicate_item, expected_1):
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# GH 17610
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result = result_1._append(duplicate_item)
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expected = expected_1._append(duplicate_item)
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tm.assert_series_equal(result[1], expected)
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assert result[2] == result_1[2]
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def test_getitem_setitem_integers():
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# caused bug without test
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s = Series([1, 2, 3], ["a", "b", "c"])
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assert s.iloc[0] == s["a"]
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s.iloc[0] = 5
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tm.assert_almost_equal(s["a"], 5)
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def test_series_box_timestamp():
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rng = date_range("20090415", "20090519", freq="B")
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ser = Series(rng)
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assert isinstance(ser[0], Timestamp)
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assert isinstance(ser.at[1], Timestamp)
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assert isinstance(ser.iat[2], Timestamp)
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assert isinstance(ser.loc[3], Timestamp)
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assert isinstance(ser.iloc[4], Timestamp)
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ser = Series(rng, index=rng)
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assert isinstance(ser[0], Timestamp)
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assert isinstance(ser.at[rng[1]], Timestamp)
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assert isinstance(ser.iat[2], Timestamp)
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assert isinstance(ser.loc[rng[3]], Timestamp)
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assert isinstance(ser.iloc[4], Timestamp)
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def test_series_box_timedelta():
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rng = timedelta_range("1 day 1 s", periods=5, freq="h")
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ser = Series(rng)
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assert isinstance(ser[0], Timedelta)
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assert isinstance(ser.at[1], Timedelta)
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assert isinstance(ser.iat[2], Timedelta)
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assert isinstance(ser.loc[3], Timedelta)
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assert isinstance(ser.iloc[4], Timedelta)
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def test_getitem_ambiguous_keyerror(indexer_sl):
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ser = Series(range(10), index=list(range(0, 20, 2)))
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with pytest.raises(KeyError, match=r"^1$"):
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indexer_sl(ser)[1]
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def test_getitem_dups_with_missing(indexer_sl):
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# breaks reindex, so need to use .loc internally
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# GH 4246
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ser = Series([1, 2, 3, 4], ["foo", "bar", "foo", "bah"])
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with pytest.raises(KeyError, match=re.escape("['bam'] not in index")):
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indexer_sl(ser)[["foo", "bar", "bah", "bam"]]
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def test_setitem_ambiguous_keyerror(indexer_sl):
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s = Series(range(10), index=list(range(0, 20, 2)))
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# equivalent of an append
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s2 = s.copy()
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indexer_sl(s2)[1] = 5
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expected = concat([s, Series([5], index=[1])])
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tm.assert_series_equal(s2, expected)
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def test_setitem(datetime_series):
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datetime_series[datetime_series.index[5]] = np.NaN
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datetime_series[[1, 2, 17]] = np.NaN
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datetime_series[6] = np.NaN
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assert np.isnan(datetime_series[6])
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assert np.isnan(datetime_series[2])
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datetime_series[np.isnan(datetime_series)] = 5
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assert not np.isnan(datetime_series[2])
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def test_setslice(datetime_series):
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sl = datetime_series[5:20]
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assert len(sl) == len(sl.index)
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assert sl.index.is_unique is True
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def test_basic_getitem_setitem_corner(datetime_series):
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# invalid tuples, e.g. td.ts[:, None] vs. td.ts[:, 2]
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msg = "key of type tuple not found and not a MultiIndex"
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with pytest.raises(KeyError, match=msg):
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datetime_series[:, 2]
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with pytest.raises(KeyError, match=msg):
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datetime_series[:, 2] = 2
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# weird lists. [slice(0, 5)] raises but not two slices
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msg = "Indexing with a single-item list"
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with pytest.raises(ValueError, match=msg):
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# GH#31299
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datetime_series[[slice(None, 5)]]
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# but we're OK with a single-element tuple
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result = datetime_series[(slice(None, 5),)]
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expected = datetime_series[:5]
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tm.assert_series_equal(result, expected)
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# OK
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msg = r"unhashable type(: 'slice')?"
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with pytest.raises(TypeError, match=msg):
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datetime_series[[5, slice(None, None)]]
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with pytest.raises(TypeError, match=msg):
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datetime_series[[5, slice(None, None)]] = 2
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def test_slice(string_series, object_series, using_copy_on_write):
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original = string_series.copy()
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numSlice = string_series[10:20]
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numSliceEnd = string_series[-10:]
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objSlice = object_series[10:20]
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assert string_series.index[9] not in numSlice.index
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assert object_series.index[9] not in objSlice.index
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assert len(numSlice) == len(numSlice.index)
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assert string_series[numSlice.index[0]] == numSlice[numSlice.index[0]]
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assert numSlice.index[1] == string_series.index[11]
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assert tm.equalContents(numSliceEnd, np.array(string_series)[-10:])
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# Test return view.
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sl = string_series[10:20]
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sl[:] = 0
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if using_copy_on_write:
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# Doesn't modify parent (CoW)
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tm.assert_series_equal(string_series, original)
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else:
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assert (string_series[10:20] == 0).all()
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def test_timedelta_assignment():
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# GH 8209
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s = Series([], dtype=object)
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s.loc["B"] = timedelta(1)
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tm.assert_series_equal(s, Series(Timedelta("1 days"), index=["B"]))
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s = s.reindex(s.index.insert(0, "A"))
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tm.assert_series_equal(s, Series([np.nan, Timedelta("1 days")], index=["A", "B"]))
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s.loc["A"] = timedelta(1)
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expected = Series(Timedelta("1 days"), index=["A", "B"])
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tm.assert_series_equal(s, expected)
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def test_underlying_data_conversion(using_copy_on_write):
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# GH 4080
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df = DataFrame({c: [1, 2, 3] for c in ["a", "b", "c"]})
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return_value = df.set_index(["a", "b", "c"], inplace=True)
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assert return_value is None
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s = Series([1], index=[(2, 2, 2)])
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df["val"] = 0
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df_original = df.copy()
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df
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df["val"].update(s)
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if using_copy_on_write:
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expected = df_original
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else:
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expected = DataFrame(
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{"a": [1, 2, 3], "b": [1, 2, 3], "c": [1, 2, 3], "val": [0, 1, 0]}
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)
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return_value = expected.set_index(["a", "b", "c"], inplace=True)
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assert return_value is None
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tm.assert_frame_equal(df, expected)
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def test_preserve_refs(datetime_series):
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seq = datetime_series[[5, 10, 15]]
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seq[1] = np.NaN
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assert not np.isnan(datetime_series[10])
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def test_multilevel_preserve_name(lexsorted_two_level_string_multiindex, indexer_sl):
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index = lexsorted_two_level_string_multiindex
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ser = Series(np.random.randn(len(index)), index=index, name="sth")
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result = indexer_sl(ser)["foo"]
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assert result.name == ser.name
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# miscellaneous methods
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@pytest.mark.parametrize(
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"index",
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[
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date_range("2014-01-01", periods=20, freq="MS"),
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period_range("2014-01", periods=20, freq="M"),
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timedelta_range("0", periods=20, freq="H"),
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],
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)
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def test_slice_with_negative_step(index):
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keystr1 = str(index[9])
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keystr2 = str(index[13])
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ser = Series(np.arange(20), index)
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SLC = IndexSlice
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for key in [keystr1, index[9]]:
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tm.assert_indexing_slices_equivalent(ser, SLC[key::-1], SLC[9::-1])
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tm.assert_indexing_slices_equivalent(ser, SLC[:key:-1], SLC[:8:-1])
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for key2 in [keystr2, index[13]]:
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tm.assert_indexing_slices_equivalent(ser, SLC[key2:key:-1], SLC[13:8:-1])
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tm.assert_indexing_slices_equivalent(ser, SLC[key:key2:-1], SLC[0:0:-1])
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def test_tuple_index():
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# GH 35534 - Selecting values when a Series has an Index of tuples
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s = Series([1, 2], index=[("a",), ("b",)])
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assert s[("a",)] == 1
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assert s[("b",)] == 2
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s[("b",)] = 3
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assert s[("b",)] == 3
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def test_frozenset_index():
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# GH35747 - Selecting values when a Series has an Index of frozenset
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idx0, idx1 = frozenset("a"), frozenset("b")
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s = Series([1, 2], index=[idx0, idx1])
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assert s[idx0] == 1
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assert s[idx1] == 2
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s[idx1] = 3
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assert s[idx1] == 3
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def test_loc_setitem_all_false_indexer():
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# GH#45778
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ser = Series([1, 2], index=["a", "b"])
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expected = ser.copy()
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rhs = Series([6, 7], index=["a", "b"])
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ser.loc[ser > 100] = rhs
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tm.assert_series_equal(ser, expected)
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def test_loc_boolean_indexer_non_matching_index():
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# GH#46551
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ser = Series([1])
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result = ser.loc[Series([NA, False], dtype="boolean")]
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expected = Series([], dtype="int64")
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tm.assert_series_equal(result, expected)
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def test_loc_boolean_indexer_miss_matching_index():
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# GH#46551
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ser = Series([1])
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indexer = Series([NA, False], dtype="boolean", index=[1, 2])
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with pytest.raises(IndexingError, match="Unalignable"):
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ser.loc[indexer]
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def test_loc_setitem_nested_data_enlargement():
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# GH#48614
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df = DataFrame({"a": [1]})
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ser = Series({"label": df})
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ser.loc["new_label"] = df
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expected = Series({"label": df, "new_label": df})
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tm.assert_series_equal(ser, expected)
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def test_loc_ea_numeric_index_oob_slice_end():
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# GH#50161
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ser = Series(1, index=Index([0, 1, 2], dtype="Int64"))
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result = ser.loc[2:3]
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expected = Series(1, index=Index([2], dtype="Int64"))
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tm.assert_series_equal(result, expected)
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def test_getitem_bool_int_key():
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# GH#48653
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ser = Series({True: 1, False: 0})
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with pytest.raises(KeyError, match="0"):
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ser.loc[0]
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@pytest.mark.parametrize("val", [{}, {"b": "x"}])
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@pytest.mark.parametrize("indexer", [[], [False, False], slice(0, -1), np.array([])])
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def test_setitem_empty_indexer(indexer, val):
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|
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# GH#45981
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df = DataFrame({"a": [1, 2], **val})
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expected = df.copy()
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|
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df.loc[indexer] = 1.5
|
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|
|
tm.assert_frame_equal(df, expected)
|
||
|
|
|
||
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|
|
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|
|
class TestDeprecatedIndexers:
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@pytest.mark.parametrize("key", [{1}, {1: 1}])
|
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|
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def test_getitem_dict_and_set_deprecated(self, key):
|
||
|
|
# GH#42825 enforced in 2.0
|
||
|
|
ser = Series([1, 2])
|
||
|
|
with pytest.raises(TypeError, match="as an indexer is not supported"):
|
||
|
|
ser.loc[key]
|
||
|
|
|
||
|
|
@pytest.mark.parametrize("key", [{1}, {1: 1}, ({1}, 2), ({1: 1}, 2)])
|
||
|
|
def test_getitem_dict_and_set_deprecated_multiindex(self, key):
|
||
|
|
# GH#42825 enforced in 2.0
|
||
|
|
ser = Series([1, 2], index=MultiIndex.from_tuples([(1, 2), (3, 4)]))
|
||
|
|
with pytest.raises(TypeError, match="as an indexer is not supported"):
|
||
|
|
ser.loc[key]
|
||
|
|
|
||
|
|
@pytest.mark.parametrize("key", [{1}, {1: 1}])
|
||
|
|
def test_setitem_dict_and_set_disallowed(self, key):
|
||
|
|
# GH#42825 enforced in 2.0
|
||
|
|
ser = Series([1, 2])
|
||
|
|
with pytest.raises(TypeError, match="as an indexer is not supported"):
|
||
|
|
ser.loc[key] = 1
|
||
|
|
|
||
|
|
@pytest.mark.parametrize("key", [{1}, {1: 1}, ({1}, 2), ({1: 1}, 2)])
|
||
|
|
def test_setitem_dict_and_set_disallowed_multiindex(self, key):
|
||
|
|
# GH#42825 enforced in 2.0
|
||
|
|
ser = Series([1, 2], index=MultiIndex.from_tuples([(1, 2), (3, 4)]))
|
||
|
|
with pytest.raises(TypeError, match="as an indexer is not supported"):
|
||
|
|
ser.loc[key] = 1
|