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| import numpy as np
| import pytest
|
| from pandas import (
| DataFrame,
| Index,
| RangeIndex,
| Series,
| )
| import pandas._testing as tm
|
|
| def gen_obj(klass, index):
| if klass is Series:
| obj = Series(np.arange(len(index)), index=index)
| else:
| obj = DataFrame(
| np.random.randn(len(index), len(index)), index=index, columns=index
| )
| return obj
|
|
| class TestFloatIndexers:
| def check(self, result, original, indexer, getitem):
| """
| comparator for results
| we need to take care if we are indexing on a
| Series or a frame
| """
| if isinstance(original, Series):
| expected = original.iloc[indexer]
| else:
| if getitem:
| expected = original.iloc[:, indexer]
| else:
| expected = original.iloc[indexer]
|
| tm.assert_almost_equal(result, expected)
|
| @pytest.mark.parametrize(
| "index_func",
| [
| tm.makeStringIndex,
| tm.makeCategoricalIndex,
| tm.makeDateIndex,
| tm.makeTimedeltaIndex,
| tm.makePeriodIndex,
| ],
| )
| def test_scalar_non_numeric(self, index_func, frame_or_series, indexer_sl):
| # GH 4892
| # float_indexers should raise exceptions
| # on appropriate Index types & accessors
|
| i = index_func(5)
| s = gen_obj(frame_or_series, i)
|
| # getting
| with pytest.raises(KeyError, match="^3.0$"):
| indexer_sl(s)[3.0]
|
| # contains
| assert 3.0 not in s
|
| s2 = s.copy()
| indexer_sl(s2)[3.0] = 10
|
| if indexer_sl is tm.setitem:
| assert 3.0 in s2.axes[-1]
| elif indexer_sl is tm.loc:
| assert 3.0 in s2.axes[0]
| else:
| assert 3.0 not in s2.axes[0]
| assert 3.0 not in s2.axes[-1]
|
| @pytest.mark.parametrize(
| "index_func",
| [
| tm.makeStringIndex,
| tm.makeCategoricalIndex,
| tm.makeDateIndex,
| tm.makeTimedeltaIndex,
| tm.makePeriodIndex,
| ],
| )
| def test_scalar_non_numeric_series_fallback(self, index_func):
| # fallsback to position selection, series only
| i = index_func(5)
| s = Series(np.arange(len(i)), index=i)
| s[3]
| with pytest.raises(KeyError, match="^3.0$"):
| s[3.0]
|
| def test_scalar_with_mixed(self, indexer_sl):
| s2 = Series([1, 2, 3], index=["a", "b", "c"])
| s3 = Series([1, 2, 3], index=["a", "b", 1.5])
|
| # lookup in a pure string index with an invalid indexer
|
| with pytest.raises(KeyError, match="^1.0$"):
| indexer_sl(s2)[1.0]
|
| with pytest.raises(KeyError, match=r"^1\.0$"):
| indexer_sl(s2)[1.0]
|
| result = indexer_sl(s2)["b"]
| expected = 2
| assert result == expected
|
| # mixed index so we have label
| # indexing
| with pytest.raises(KeyError, match="^1.0$"):
| indexer_sl(s3)[1.0]
|
| if indexer_sl is not tm.loc:
| # __getitem__ falls back to positional
| result = s3[1]
| expected = 2
| assert result == expected
|
| with pytest.raises(KeyError, match=r"^1\.0$"):
| indexer_sl(s3)[1.0]
|
| result = indexer_sl(s3)[1.5]
| expected = 3
| assert result == expected
|
| @pytest.mark.parametrize("index_func", [tm.makeIntIndex, tm.makeRangeIndex])
| def test_scalar_integer(self, index_func, frame_or_series, indexer_sl):
| getitem = indexer_sl is not tm.loc
|
| # test how scalar float indexers work on int indexes
|
| # integer index
| i = index_func(5)
| obj = gen_obj(frame_or_series, i)
|
| # coerce to equal int
|
| result = indexer_sl(obj)[3.0]
| self.check(result, obj, 3, getitem)
|
| if isinstance(obj, Series):
|
| def compare(x, y):
| assert x == y
|
| expected = 100
| else:
| compare = tm.assert_series_equal
| if getitem:
| expected = Series(100, index=range(len(obj)), name=3)
| else:
| expected = Series(100.0, index=range(len(obj)), name=3)
|
| s2 = obj.copy()
| indexer_sl(s2)[3.0] = 100
|
| result = indexer_sl(s2)[3.0]
| compare(result, expected)
|
| result = indexer_sl(s2)[3]
| compare(result, expected)
|
| @pytest.mark.parametrize("index_func", [tm.makeIntIndex, tm.makeRangeIndex])
| def test_scalar_integer_contains_float(self, index_func, frame_or_series):
| # contains
| # integer index
| index = index_func(5)
| obj = gen_obj(frame_or_series, index)
|
| # coerce to equal int
| assert 3.0 in obj
|
| def test_scalar_float(self, frame_or_series):
| # scalar float indexers work on a float index
| index = Index(np.arange(5.0))
| s = gen_obj(frame_or_series, index)
|
| # assert all operations except for iloc are ok
| indexer = index[3]
| for idxr in [tm.loc, tm.setitem]:
| getitem = idxr is not tm.loc
|
| # getting
| result = idxr(s)[indexer]
| self.check(result, s, 3, getitem)
|
| # setting
| s2 = s.copy()
|
| result = idxr(s2)[indexer]
| self.check(result, s, 3, getitem)
|
| # random float is a KeyError
| with pytest.raises(KeyError, match=r"^3\.5$"):
| idxr(s)[3.5]
|
| # contains
| assert 3.0 in s
|
| # iloc succeeds with an integer
| expected = s.iloc[3]
| s2 = s.copy()
|
| s2.iloc[3] = expected
| result = s2.iloc[3]
| self.check(result, s, 3, False)
|
| @pytest.mark.parametrize(
| "index_func",
| [
| tm.makeStringIndex,
| tm.makeDateIndex,
| tm.makeTimedeltaIndex,
| tm.makePeriodIndex,
| ],
| )
| @pytest.mark.parametrize("idx", [slice(3.0, 4), slice(3, 4.0), slice(3.0, 4.0)])
| def test_slice_non_numeric(self, index_func, idx, frame_or_series, indexer_sli):
| # GH 4892
| # float_indexers should raise exceptions
| # on appropriate Index types & accessors
|
| index = index_func(5)
| s = gen_obj(frame_or_series, index)
|
| # getitem
| if indexer_sli is tm.iloc:
| msg = (
| "cannot do positional indexing "
| rf"on {type(index).__name__} with these indexers \[(3|4)\.0\] of "
| "type float"
| )
| else:
| msg = (
| "cannot do slice indexing "
| rf"on {type(index).__name__} with these indexers "
| r"\[(3|4)(\.0)?\] "
| r"of type (float|int)"
| )
| with pytest.raises(TypeError, match=msg):
| indexer_sli(s)[idx]
|
| # setitem
| if indexer_sli is tm.iloc:
| # otherwise we keep the same message as above
| msg = "slice indices must be integers or None or have an __index__ method"
| with pytest.raises(TypeError, match=msg):
| indexer_sli(s)[idx] = 0
|
| def test_slice_integer(self):
| # same as above, but for Integer based indexes
| # these coerce to a like integer
| # oob indicates if we are out of bounds
| # of positional indexing
| for index, oob in [
| (Index(np.arange(5, dtype=np.int64)), False),
| (RangeIndex(5), False),
| (Index(np.arange(5, dtype=np.int64) + 10), True),
| ]:
| # s is an in-range index
| s = Series(range(5), index=index)
|
| # getitem
| for idx in [slice(3.0, 4), slice(3, 4.0), slice(3.0, 4.0)]:
| result = s.loc[idx]
|
| # these are all label indexing
| # except getitem which is positional
| # empty
| if oob:
| indexer = slice(0, 0)
| else:
| indexer = slice(3, 5)
| self.check(result, s, indexer, False)
|
| # getitem out-of-bounds
| for idx in [slice(-6, 6), slice(-6.0, 6.0)]:
| result = s.loc[idx]
|
| # these are all label indexing
| # except getitem which is positional
| # empty
| if oob:
| indexer = slice(0, 0)
| else:
| indexer = slice(-6, 6)
| self.check(result, s, indexer, False)
|
| # positional indexing
| msg = (
| "cannot do slice indexing "
| rf"on {type(index).__name__} with these indexers \[-6\.0\] of "
| "type float"
| )
| with pytest.raises(TypeError, match=msg):
| s[slice(-6.0, 6.0)]
|
| # getitem odd floats
| for idx, res1 in [
| (slice(2.5, 4), slice(3, 5)),
| (slice(2, 3.5), slice(2, 4)),
| (slice(2.5, 3.5), slice(3, 4)),
| ]:
| result = s.loc[idx]
| if oob:
| res = slice(0, 0)
| else:
| res = res1
|
| self.check(result, s, res, False)
|
| # positional indexing
| msg = (
| "cannot do slice indexing "
| rf"on {type(index).__name__} with these indexers \[(2|3)\.5\] of "
| "type float"
| )
| with pytest.raises(TypeError, match=msg):
| s[idx]
|
| @pytest.mark.parametrize("idx", [slice(2, 4.0), slice(2.0, 4), slice(2.0, 4.0)])
| def test_integer_positional_indexing(self, idx):
| """make sure that we are raising on positional indexing
| w.r.t. an integer index
| """
| s = Series(range(2, 6), index=range(2, 6))
|
| result = s[2:4]
| expected = s.iloc[2:4]
| tm.assert_series_equal(result, expected)
|
| klass = RangeIndex
| msg = (
| "cannot do (slice|positional) indexing "
| rf"on {klass.__name__} with these indexers \[(2|4)\.0\] of "
| "type float"
| )
| with pytest.raises(TypeError, match=msg):
| s[idx]
| with pytest.raises(TypeError, match=msg):
| s.iloc[idx]
|
| @pytest.mark.parametrize("index_func", [tm.makeIntIndex, tm.makeRangeIndex])
| def test_slice_integer_frame_getitem(self, index_func):
| # similar to above, but on the getitem dim (of a DataFrame)
| index = index_func(5)
|
| s = DataFrame(np.random.randn(5, 2), index=index)
|
| # getitem
| for idx in [slice(0.0, 1), slice(0, 1.0), slice(0.0, 1.0)]:
| result = s.loc[idx]
| indexer = slice(0, 2)
| self.check(result, s, indexer, False)
|
| # positional indexing
| msg = (
| "cannot do slice indexing "
| rf"on {type(index).__name__} with these indexers \[(0|1)\.0\] of "
| "type float"
| )
| with pytest.raises(TypeError, match=msg):
| s[idx]
|
| # getitem out-of-bounds
| for idx in [slice(-10, 10), slice(-10.0, 10.0)]:
| result = s.loc[idx]
| self.check(result, s, slice(-10, 10), True)
|
| # positional indexing
| msg = (
| "cannot do slice indexing "
| rf"on {type(index).__name__} with these indexers \[-10\.0\] of "
| "type float"
| )
| with pytest.raises(TypeError, match=msg):
| s[slice(-10.0, 10.0)]
|
| # getitem odd floats
| for idx, res in [
| (slice(0.5, 1), slice(1, 2)),
| (slice(0, 0.5), slice(0, 1)),
| (slice(0.5, 1.5), slice(1, 2)),
| ]:
| result = s.loc[idx]
| self.check(result, s, res, False)
|
| # positional indexing
| msg = (
| "cannot do slice indexing "
| rf"on {type(index).__name__} with these indexers \[0\.5\] of "
| "type float"
| )
| with pytest.raises(TypeError, match=msg):
| s[idx]
|
| @pytest.mark.parametrize("idx", [slice(3.0, 4), slice(3, 4.0), slice(3.0, 4.0)])
| @pytest.mark.parametrize("index_func", [tm.makeIntIndex, tm.makeRangeIndex])
| def test_float_slice_getitem_with_integer_index_raises(self, idx, index_func):
| # similar to above, but on the getitem dim (of a DataFrame)
| index = index_func(5)
|
| s = DataFrame(np.random.randn(5, 2), index=index)
|
| # setitem
| sc = s.copy()
| sc.loc[idx] = 0
| result = sc.loc[idx].values.ravel()
| assert (result == 0).all()
|
| # positional indexing
| msg = (
| "cannot do slice indexing "
| rf"on {type(index).__name__} with these indexers \[(3|4)\.0\] of "
| "type float"
| )
| with pytest.raises(TypeError, match=msg):
| s[idx] = 0
|
| with pytest.raises(TypeError, match=msg):
| s[idx]
|
| @pytest.mark.parametrize("idx", [slice(3.0, 4), slice(3, 4.0), slice(3.0, 4.0)])
| def test_slice_float(self, idx, frame_or_series, indexer_sl):
| # same as above, but for floats
| index = Index(np.arange(5.0)) + 0.1
| s = gen_obj(frame_or_series, index)
|
| expected = s.iloc[3:4]
|
| # getitem
| result = indexer_sl(s)[idx]
| assert isinstance(result, type(s))
| tm.assert_equal(result, expected)
|
| # setitem
| s2 = s.copy()
| indexer_sl(s2)[idx] = 0
| result = indexer_sl(s2)[idx].values.ravel()
| assert (result == 0).all()
|
| def test_floating_index_doc_example(self):
| index = Index([1.5, 2, 3, 4.5, 5])
| s = Series(range(5), index=index)
| assert s[3] == 2
| assert s.loc[3] == 2
| assert s.iloc[3] == 3
|
| def test_floating_misc(self, indexer_sl):
| # related 236
| # scalar/slicing of a float index
| s = Series(np.arange(5), index=np.arange(5) * 2.5, dtype=np.int64)
|
| # label based slicing
| result = indexer_sl(s)[1.0:3.0]
| expected = Series(1, index=[2.5])
| tm.assert_series_equal(result, expected)
|
| # exact indexing when found
|
| result = indexer_sl(s)[5.0]
| assert result == 2
|
| result = indexer_sl(s)[5]
| assert result == 2
|
| # value not found (and no fallbacking at all)
|
| # scalar integers
| with pytest.raises(KeyError, match=r"^4$"):
| indexer_sl(s)[4]
|
| # fancy floats/integers create the correct entry (as nan)
| # fancy tests
| expected = Series([2, 0], index=Index([5.0, 0.0], dtype=np.float64))
| for fancy_idx in [[5.0, 0.0], np.array([5.0, 0.0])]: # float
| tm.assert_series_equal(indexer_sl(s)[fancy_idx], expected)
|
| expected = Series([2, 0], index=Index([5, 0], dtype="float64"))
| for fancy_idx in [[5, 0], np.array([5, 0])]:
| tm.assert_series_equal(indexer_sl(s)[fancy_idx], expected)
|
| # all should return the same as we are slicing 'the same'
| result1 = indexer_sl(s)[2:5]
| result2 = indexer_sl(s)[2.0:5.0]
| result3 = indexer_sl(s)[2.0:5]
| result4 = indexer_sl(s)[2.1:5]
| tm.assert_series_equal(result1, result2)
| tm.assert_series_equal(result1, result3)
| tm.assert_series_equal(result1, result4)
|
| expected = Series([1, 2], index=[2.5, 5.0])
| result = indexer_sl(s)[2:5]
|
| tm.assert_series_equal(result, expected)
|
| # list selection
| result1 = indexer_sl(s)[[0.0, 5, 10]]
| result2 = s.iloc[[0, 2, 4]]
| tm.assert_series_equal(result1, result2)
|
| with pytest.raises(KeyError, match="not in index"):
| indexer_sl(s)[[1.6, 5, 10]]
|
| with pytest.raises(KeyError, match="not in index"):
| indexer_sl(s)[[0, 1, 2]]
|
| result = indexer_sl(s)[[2.5, 5]]
| tm.assert_series_equal(result, Series([1, 2], index=[2.5, 5.0]))
|
| result = indexer_sl(s)[[2.5]]
| tm.assert_series_equal(result, Series([1], index=[2.5]))
|
| def test_floatindex_slicing_bug(self, float_numpy_dtype):
| # GH 5557, related to slicing a float index
| dtype = float_numpy_dtype
| ser = {
| 256: 2321.0,
| 1: 78.0,
| 2: 2716.0,
| 3: 0.0,
| 4: 369.0,
| 5: 0.0,
| 6: 269.0,
| 7: 0.0,
| 8: 0.0,
| 9: 0.0,
| 10: 3536.0,
| 11: 0.0,
| 12: 24.0,
| 13: 0.0,
| 14: 931.0,
| 15: 0.0,
| 16: 101.0,
| 17: 78.0,
| 18: 9643.0,
| 19: 0.0,
| 20: 0.0,
| 21: 0.0,
| 22: 63761.0,
| 23: 0.0,
| 24: 446.0,
| 25: 0.0,
| 26: 34773.0,
| 27: 0.0,
| 28: 729.0,
| 29: 78.0,
| 30: 0.0,
| 31: 0.0,
| 32: 3374.0,
| 33: 0.0,
| 34: 1391.0,
| 35: 0.0,
| 36: 361.0,
| 37: 0.0,
| 38: 61808.0,
| 39: 0.0,
| 40: 0.0,
| 41: 0.0,
| 42: 6677.0,
| 43: 0.0,
| 44: 802.0,
| 45: 0.0,
| 46: 2691.0,
| 47: 0.0,
| 48: 3582.0,
| 49: 0.0,
| 50: 734.0,
| 51: 0.0,
| 52: 627.0,
| 53: 70.0,
| 54: 2584.0,
| 55: 0.0,
| 56: 324.0,
| 57: 0.0,
| 58: 605.0,
| 59: 0.0,
| 60: 0.0,
| 61: 0.0,
| 62: 3989.0,
| 63: 10.0,
| 64: 42.0,
| 65: 0.0,
| 66: 904.0,
| 67: 0.0,
| 68: 88.0,
| 69: 70.0,
| 70: 8172.0,
| 71: 0.0,
| 72: 0.0,
| 73: 0.0,
| 74: 64902.0,
| 75: 0.0,
| 76: 347.0,
| 77: 0.0,
| 78: 36605.0,
| 79: 0.0,
| 80: 379.0,
| 81: 70.0,
| 82: 0.0,
| 83: 0.0,
| 84: 3001.0,
| 85: 0.0,
| 86: 1630.0,
| 87: 7.0,
| 88: 364.0,
| 89: 0.0,
| 90: 67404.0,
| 91: 9.0,
| 92: 0.0,
| 93: 0.0,
| 94: 7685.0,
| 95: 0.0,
| 96: 1017.0,
| 97: 0.0,
| 98: 2831.0,
| 99: 0.0,
| 100: 2963.0,
| 101: 0.0,
| 102: 854.0,
| 103: 0.0,
| 104: 0.0,
| 105: 0.0,
| 106: 0.0,
| 107: 0.0,
| 108: 0.0,
| 109: 0.0,
| 110: 0.0,
| 111: 0.0,
| 112: 0.0,
| 113: 0.0,
| 114: 0.0,
| 115: 0.0,
| 116: 0.0,
| 117: 0.0,
| 118: 0.0,
| 119: 0.0,
| 120: 0.0,
| 121: 0.0,
| 122: 0.0,
| 123: 0.0,
| 124: 0.0,
| 125: 0.0,
| 126: 67744.0,
| 127: 22.0,
| 128: 264.0,
| 129: 0.0,
| 260: 197.0,
| 268: 0.0,
| 265: 0.0,
| 269: 0.0,
| 261: 0.0,
| 266: 1198.0,
| 267: 0.0,
| 262: 2629.0,
| 258: 775.0,
| 257: 0.0,
| 263: 0.0,
| 259: 0.0,
| 264: 163.0,
| 250: 10326.0,
| 251: 0.0,
| 252: 1228.0,
| 253: 0.0,
| 254: 2769.0,
| 255: 0.0,
| }
|
| # smoke test for the repr
| s = Series(ser, dtype=dtype)
| result = s.value_counts()
| assert result.index.dtype == dtype
| str(result)
|
|
