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BUG/API: prohibit dtype-changing IntervalArray.__setitem__ #32782

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Merged
merged 10 commits into from
Apr 10, 2020
Merged

BUG/API: prohibit dtype-changing IntervalArray.__setitem__ #32782

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47202dd
BUG: disallow changing IntervalArray backing data
jbrockmendel Feb 27, 2020
9f21c62
Merge branch 'master' of https://github.com/pandas-dev/pandas into in…
jbrockmendel Feb 27, 2020
477c441
Merge branch 'master' of https://github.com/pandas-dev/pandas into in…
jbrockmendel Mar 3, 2020
bdaf49b
Merge branch 'master' of https://github.com/pandas-dev/pandas into in…
jbrockmendel Mar 12, 2020
8735b58
Merge branch 'master' of https://github.com/pandas-dev/pandas into in…
jbrockmendel Mar 17, 2020
755679c
Merge branch 'master' of https://github.com/pandas-dev/pandas into in…
jbrockmendel Mar 18, 2020
23b6b93
update tests
jbrockmendel Mar 18, 2020
3e5826c
Merge branch 'master' of https://github.com/pandas-dev/pandas into in…
jbrockmendel Apr 6, 2020
934dabe
whatsnew, exception message
jbrockmendel Apr 6, 2020
959f674
Merge branch 'master' of https://github.com/pandas-dev/pandas into in…
jbrockmendel Apr 6, 2020
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4 changes: 4 additions & 0 deletions pandas/core/arrays/interval.py
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Original file line number Diff line number Diff line change
Expand Up @@ -543,7 +543,11 @@ def __setitem__(self, key, value):
msg = f"'value' should be an interval type, got {type(value)} instead."
raise TypeError(msg) from err

if needs_float_conversion:
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Since we're raising here we can remove the future references that are no longer being used:

pandas/pandas/core/arrays/interval.py

Lines 554 to 555 in 23b6b93

if needs_float_conversion:
left = left.astype("float")

pandas/pandas/core/arrays/interval.py

Lines 560 to 561 in 23b6b93

if needs_float_conversion:
right = right.astype("float")

raise ValueError("Cannot set float values for integer-backed IntervalArray")
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The needs_float_conversion name might be a bit misleading here because it's not triggered when setting arbitrary float values but rather just when np.nan is included, so we're not generically disallowing setting float values. Maybe a more accurate error message would be along the lines "Cannot set float NaN to integer-backed IntervalArray".

FWIW the behavior when setting float values without np.nan included is to truncate the float and just use the integer component, which is consistent with numpy's behavior:

In [1]: import pandas as pd; import numpy as np

In [2]: ia = pd.arrays.IntervalArray.from_breaks(range(5))

In [3]: ia[0] = pd.Interval(0.9, 1.1)

In [4]: ia
Out[4]: 
<IntervalArray>
[(0, 1], (1, 2], (2, 3], (3, 4]]
Length: 4, closed: right, dtype: interval[int64]

In [5]: a = np.arange(4)

In [6]: a[0] = 0.9

In [7]: a[1] = 1.1

In [8]: a
Out[8]: array([0, 1, 2, 3])

I'm not crazy about that behavior but I'm fine with it since it's consistent with numpy.


key = check_array_indexer(self, key)

# Need to ensure that left and right are updated atomically, so we're
# forced to copy, update the copy, and swap in the new values.
left = self.left.copy(deep=True)
Expand Down
13 changes: 10 additions & 3 deletions pandas/tests/arrays/interval/test_interval.py
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Original file line number Diff line number Diff line change
Expand Up @@ -104,6 +104,13 @@ class TestSetitem:
def test_set_na(self, left_right_dtypes):
left, right = left_right_dtypes
result = IntervalArray.from_arrays(left, right)

if result.dtype.subtype.kind in ["i", "u"]:
msg = "Cannot set float values for integer-backed IntervalArray"
with pytest.raises(ValueError, match=msg):
result[0] = np.NaN
return

result[0] = np.nan

expected_left = Index([left._na_value] + list(left[1:]))
Expand Down Expand Up @@ -182,7 +189,7 @@ def test_arrow_array_missing():
import pyarrow as pa
from pandas.core.arrays._arrow_utils import ArrowIntervalType

arr = IntervalArray.from_breaks([0, 1, 2, 3])
arr = IntervalArray.from_breaks([0.0, 1.0, 2.0, 3.0])
arr[1] = None

result = pa.array(arr)
Expand All @@ -209,8 +216,8 @@ def test_arrow_array_missing():
@pyarrow_skip
@pytest.mark.parametrize(
"breaks",
[[0, 1, 2, 3], pd.date_range("2017", periods=4, freq="D")],
ids=["int", "datetime64[ns]"],
[[0.0, 1.0, 2.0, 3.0], pd.date_range("2017", periods=4, freq="D")],
ids=["float", "datetime64[ns]"],
)
def test_arrow_table_roundtrip(breaks):
import pyarrow as pa
Expand Down
9 changes: 8 additions & 1 deletion pandas/tests/series/methods/test_convert_dtypes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,8 @@
import numpy as np
import pytest

from pandas.core.dtypes.common import is_interval_dtype

import pandas as pd
import pandas._testing as tm

Expand Down Expand Up @@ -266,7 +268,12 @@ def test_convert_dtypes(self, data, maindtype, params, answerdict):

# Test that it is a copy
copy = series.copy(deep=True)
ns[ns.notna()] = np.nan
if is_interval_dtype(ns.dtype) and ns.dtype.subtype.kind in ["i", "u"]:
msg = "Cannot set float values for integer-backed IntervalArray"
with pytest.raises(ValueError, match=msg):
ns[ns.notna()] = np.nan
else:
ns[ns.notna()] = np.nan

# Make sure original not changed
tm.assert_series_equal(series, copy)
Expand Down