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Backport PR #47393 on branch 1.4.x (CI/TST: Don't require length for construct_1d_arraylike_from_scalar cast to float64) #47460

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Merged
merged 3 commits into from
Jun 22, 2022
Merged

Backport PR #47393 on branch 1.4.x (CI/TST: Don't require length for construct_1d_arraylike_from_scalar cast to float64) #47460

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a86fc33
Backport PR #47393: CI/TST: Don't require length for construct_1d_arr…
mroeschke Jun 22, 2022
9151f60
another ignore
simonjayhawkins Jun 22, 2022
c545fd5
lint
simonjayhawkins Jun 22, 2022
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5 changes: 4 additions & 1 deletion pandas/core/construction.py
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Original file line number Diff line number Diff line change
Expand Up @@ -533,7 +533,10 @@ def sanitize_array(
if dtype is not None and is_float_dtype(data.dtype) and is_integer_dtype(dtype):
# possibility of nan -> garbage
try:
subarr = _try_cast(data, dtype, copy, True)
# GH 47391 numpy > 1.24 will raise a RuntimeError for nan -> int
# casting aligning with IntCastingNaNError below
with np.errstate(invalid="ignore"):
subarr = _try_cast(data, dtype, copy, True)
except IntCastingNaNError:
warnings.warn(
"In a future version, passing float-dtype values containing NaN "
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4 changes: 3 additions & 1 deletion pandas/core/dtypes/cast.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1914,7 +1914,9 @@ def construct_1d_arraylike_from_scalar(
value = maybe_unbox_datetimelike_tz_deprecation(value, dtype)

subarr = np.empty(length, dtype=dtype)
subarr.fill(value)
if length:
# GH 47391: numpy > 1.24 will raise filling np.nan into int dtypes
subarr.fill(value)

return subarr

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32 changes: 18 additions & 14 deletions pandas/core/reshape/merge.py
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Expand Up @@ -1201,23 +1201,27 @@ def _maybe_coerce_merge_keys(self) -> None:

# check whether ints and floats
elif is_integer_dtype(rk.dtype) and is_float_dtype(lk.dtype):
if not (lk == lk.astype(rk.dtype))[~np.isnan(lk)].all():
warnings.warn(
"You are merging on int and float "
"columns where the float values "
"are not equal to their int representation.",
UserWarning,
)
# GH 47391 numpy > 1.24 will raise a RuntimeError for nan -> int
with np.errstate(invalid="ignore"):
if not (lk == lk.astype(rk.dtype))[~np.isnan(lk)].all():
warnings.warn(
"You are merging on int and float "
"columns where the float values "
"are not equal to their int representation.",
UserWarning,
)
continue

elif is_float_dtype(rk.dtype) and is_integer_dtype(lk.dtype):
if not (rk == rk.astype(lk.dtype))[~np.isnan(rk)].all():
warnings.warn(
"You are merging on int and float "
"columns where the float values "
"are not equal to their int representation.",
UserWarning,
)
# GH 47391 numpy > 1.24 will raise a RuntimeError for nan -> int
with np.errstate(invalid="ignore"):
if not (rk == rk.astype(lk.dtype))[~np.isnan(rk)].all():
warnings.warn(
"You are merging on int and float "
"columns where the float values "
"are not equal to their int representation.",
UserWarning,
)
continue

# let's infer and see if we are ok
Expand Down