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Hello community,
here is the log from the commit of package python-pandas for openSUSE:Factory
checked in at 2022-01-07 12:44:42
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Comparing /work/SRC/openSUSE:Factory/python-pandas (Old)
and /work/SRC/openSUSE:Factory/.python-pandas.new.1896 (New)
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Package is "python-pandas"
Fri Jan 7 12:44:42 2022 rev:39 rq:943930 version:1.3.5
Changes:
--------
--- /work/SRC/openSUSE:Factory/python-pandas/python-pandas.changes
2021-10-25 15:17:44.869687428 +0200
+++ /work/SRC/openSUSE:Factory/.python-pandas.new.1896/python-pandas.changes
2022-01-07 12:45:13.963797606 +0100
@@ -1,0 +2,25 @@
+Tue Jan 4 21:56:55 UTC 2022 - Ben Greiner <c...@bnavigator.de>
+
+- Update to version 1.3.5
+ * Fixed regression in Series.equals() when comparing floats with
+ dtype object to None (GH44190)
+ * Fixed regression in merge_asof() raising error when array was
+ supplied as join key (GH42844)
+ * Fixed regression when resampling DataFrame with DateTimeIndex
+ with empty groups and uint8, uint16 or uint32 columns
+ incorrectly raising RuntimeError (GH43329)
+ * Fixed regression in creating a DataFrame from a timezone-aware
+ Timestamp scalar near a Daylight Savings Time transition
+ (GH42505)
+ * Fixed performance regression in read_csv() (GH44106)
+ * Fixed regression in Series.duplicated() and
+ Series.drop_duplicates() when Series has Categorical dtype with
+ boolean categories (GH44351)
+ * Fixed regression in GroupBy.sum() with timedelta64[ns] dtype
+ containing NaT failing to treat that value as NA (GH42659)
+ * Fixed regression in RollingGroupby.cov() and
+ RollingGroupby.corr() when other had the same shape as each
+ group would incorrectly return superfluous groups in the result
+ (GH42915)
+
+-------------------------------------------------------------------
Old:
----
pandas-1.3.4.tar.gz
New:
----
pandas-1.3.5.tar.gz
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Other differences:
------------------
++++++ python-pandas.spec ++++++
--- /var/tmp/diff_new_pack.6VeBgd/_old 2022-01-07 12:45:14.783798175 +0100
+++ /var/tmp/diff_new_pack.6VeBgd/_new 2022-01-07 12:45:14.787798178 +0100
@@ -1,7 +1,7 @@
#
# spec file
#
-# Copyright (c) 2021 SUSE LLC
+# Copyright (c) 2022 SUSE LLC
#
# All modifications and additions to the file contributed by third parties
# remain the property of their copyright owners, unless otherwise agreed
@@ -28,7 +28,7 @@
%bcond_with test
%endif
Name: python-pandas%{psuffix}
-Version: 1.3.4
+Version: 1.3.5
Release: 0
Summary: Python data structures for data analysis, time series, and
statistics
License: BSD-3-Clause
@@ -88,12 +88,14 @@
BuildRequires: %{python_module beautifulsoup4 >= 4.6.0}
BuildRequires: %{python_module hypothesis}
BuildRequires: %{python_module lxml >= 4.3.0}
+BuildRequires: %{python_module matplotlib}
BuildRequires: %{python_module numexpr >= 2.7.0}
BuildRequires: %{python_module openpyxl >= 3.0.0}
BuildRequires: %{python_module pandas = %{version}}
BuildRequires: %{python_module pytest >= 6.0}
BuildRequires: %{python_module pytest-mock}
BuildRequires: %{python_module pytest-xdist}
+BuildRequires: %{python_module scipy}
BuildRequires: %{python_module xlrd >= 1.2.0}
BuildRequires: xclip
BuildRequires: xvfb-run
++++++ pandas-1.3.4.tar.gz -> pandas-1.3.5.tar.gz ++++++
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/pandas-1.3.4/PKG-INFO new/pandas-1.3.5/PKG-INFO
--- old/pandas-1.3.4/PKG-INFO 2021-10-17 14:40:38.766444700 +0200
+++ new/pandas-1.3.5/PKG-INFO 2021-12-12 11:23:38.180560000 +0100
@@ -1,6 +1,6 @@
Metadata-Version: 2.1
Name: pandas
-Version: 1.3.4
+Version: 1.3.5
Summary: Powerful data structures for data analysis, time series, and
statistics
Home-page: https://pandas.pydata.org
Author: The Pandas Development Team
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/pandas-1.3.4/doc/source/reference/io.rst
new/pandas-1.3.5/doc/source/reference/io.rst
--- old/pandas-1.3.4/doc/source/reference/io.rst 2021-10-17
14:27:28.000000000 +0200
+++ new/pandas-1.3.5/doc/source/reference/io.rst 2021-12-12
11:15:39.000000000 +0100
@@ -57,7 +57,7 @@
ExcelWriter
-.. currentmodule:: pandas.io.json
+.. currentmodule:: pandas
JSON
~~~~
@@ -65,7 +65,10 @@
:toctree: api/
read_json
- to_json
+ json_normalize
+ DataFrame.to_json
+
+.. currentmodule:: pandas.io.json
.. autosummary::
:toctree: api/
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/pandas-1.3.4/doc/source/user_guide/io.rst
new/pandas-1.3.5/doc/source/user_guide/io.rst
--- old/pandas-1.3.4/doc/source/user_guide/io.rst 2021-10-17
14:27:57.000000000 +0200
+++ new/pandas-1.3.5/doc/source/user_guide/io.rst 2021-12-12
11:20:47.000000000 +0100
@@ -2977,6 +2977,7 @@
Even read XML from AWS S3 buckets such as Python Software Foundation's IRS 990
Form:
.. ipython:: python
+ :okwarning:
df = pd.read_xml(
"s3://irs-form-990/201923199349319487_public.xml",
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/pandas-1.3.4/doc/source/whatsnew/index.rst
new/pandas-1.3.5/doc/source/whatsnew/index.rst
--- old/pandas-1.3.4/doc/source/whatsnew/index.rst 2021-10-17
14:27:57.000000000 +0200
+++ new/pandas-1.3.5/doc/source/whatsnew/index.rst 2021-12-12
11:20:47.000000000 +0100
@@ -16,6 +16,7 @@
.. toctree::
:maxdepth: 2
+ v1.3.5
v1.3.4
v1.3.3
v1.3.2
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/pandas-1.3.4/doc/source/whatsnew/v1.3.4.rst
new/pandas-1.3.5/doc/source/whatsnew/v1.3.4.rst
--- old/pandas-1.3.4/doc/source/whatsnew/v1.3.4.rst 2021-10-17
14:27:28.000000000 +0200
+++ new/pandas-1.3.5/doc/source/whatsnew/v1.3.4.rst 2021-12-12
11:15:39.000000000 +0100
@@ -54,4 +54,4 @@
Contributors
~~~~~~~~~~~~
-.. contributors:: v1.3.3..v1.3.4|HEAD
+.. contributors:: v1.3.3..v1.3.4
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/pandas-1.3.4/doc/source/whatsnew/v1.3.5.rst
new/pandas-1.3.5/doc/source/whatsnew/v1.3.5.rst
--- old/pandas-1.3.4/doc/source/whatsnew/v1.3.5.rst 1970-01-01
01:00:00.000000000 +0100
+++ new/pandas-1.3.5/doc/source/whatsnew/v1.3.5.rst 2021-12-12
11:15:39.000000000 +0100
@@ -0,0 +1,33 @@
+.. _whatsnew_135:
+
+What's new in 1.3.5 (December 12, 2021)
+---------------------------------------
+
+These are the changes in pandas 1.3.5. See :ref:`release` for a full changelog
+including other versions of pandas.
+
+{{ header }}
+
+.. ---------------------------------------------------------------------------
+
+.. _whatsnew_135.regressions:
+
+Fixed regressions
+~~~~~~~~~~~~~~~~~
+- Fixed regression in :meth:`Series.equals` when comparing floats with dtype
object to None (:issue:`44190`)
+- Fixed regression in :func:`merge_asof` raising error when array was supplied
as join key (:issue:`42844`)
+- Fixed regression when resampling :class:`DataFrame` with
:class:`DateTimeIndex` with empty groups and ``uint8``, ``uint16`` or
``uint32`` columns incorrectly raising ``RuntimeError`` (:issue:`43329`)
+- Fixed regression in creating a :class:`DataFrame` from a timezone-aware
:class:`Timestamp` scalar near a Daylight Savings Time transition
(:issue:`42505`)
+- Fixed performance regression in :func:`read_csv` (:issue:`44106`)
+- Fixed regression in :meth:`Series.duplicated` and
:meth:`Series.drop_duplicates` when Series has :class:`Categorical` dtype with
boolean categories (:issue:`44351`)
+- Fixed regression in :meth:`.GroupBy.sum` with ``timedelta64[ns]`` dtype
containing ``NaT`` failing to treat that value as NA (:issue:`42659`)
+- Fixed regression in :meth:`.RollingGroupby.cov` and
:meth:`.RollingGroupby.corr` when ``other`` had the same shape as each group
would incorrectly return superfluous groups in the result (:issue:`42915`)
+
+.. ---------------------------------------------------------------------------
+
+.. _whatsnew_135.contributors:
+
+Contributors
+~~~~~~~~~~~~
+
+.. contributors:: v1.3.4..v1.3.5|HEAD
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/pandas-1.3.4/pandas/_libs/groupby.pyi
new/pandas-1.3.5/pandas/_libs/groupby.pyi
--- old/pandas-1.3.4/pandas/_libs/groupby.pyi 2021-10-17 14:27:57.000000000
+0200
+++ new/pandas-1.3.5/pandas/_libs/groupby.pyi 2021-12-12 11:20:47.000000000
+0100
@@ -53,6 +53,7 @@
values: np.ndarray, # ndarray[complexfloating_t, ndim=2]
labels: np.ndarray, # const intp_t[:]
min_count: int = ...,
+ datetimelike: bool = ...,
) -> None: ...
def group_prod(
out: np.ndarray, # floating[:, ::1]
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/pandas-1.3.4/pandas/_libs/groupby.pyx
new/pandas-1.3.5/pandas/_libs/groupby.pyx
--- old/pandas-1.3.4/pandas/_libs/groupby.pyx 2021-10-17 14:27:57.000000000
+0200
+++ new/pandas-1.3.5/pandas/_libs/groupby.pyx 2021-12-12 11:20:47.000000000
+0100
@@ -483,7 +483,8 @@
int64_t[::1] counts,
ndarray[add_t, ndim=2] values,
const intp_t[:] labels,
- Py_ssize_t min_count=0) -> None:
+ Py_ssize_t min_count=0,
+ bint datetimelike=False) -> None:
"""
Only aggregates on axis=0 using Kahan summation
"""
@@ -545,7 +546,14 @@
val = values[i, j]
# not nan
- if val == val:
+ # With dt64/td64 values, values have been cast to float64
+ # instead if int64 for group_add, but the logic
+ # is otherwise the same as in _treat_as_na
+ if val == val and not (
+ add_t is float64_t
+ and datetimelike
+ and val == <float64_t>NPY_NAT
+ ):
nobs[lab, j] += 1
y = val - compensation[lab, j]
t = sumx[lab, j] + y
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/pandas-1.3.4/pandas/_libs/missing.pyx
new/pandas-1.3.5/pandas/_libs/missing.pyx
--- old/pandas-1.3.4/pandas/_libs/missing.pyx 2021-10-17 14:27:28.000000000
+0200
+++ new/pandas-1.3.5/pandas/_libs/missing.pyx 2021-12-12 11:20:47.000000000
+0100
@@ -64,7 +64,7 @@
elif left is NaT:
return right is NaT
elif util.is_float_object(left):
- if nan_matches_none and right is None:
+ if nan_matches_none and right is None and util.is_nan(left):
return True
return (
util.is_nan(left)
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/pandas-1.3.4/pandas/_libs/ops_dispatch.pyx
new/pandas-1.3.5/pandas/_libs/ops_dispatch.pyx
--- old/pandas-1.3.4/pandas/_libs/ops_dispatch.pyx 2021-10-17
14:27:57.000000000 +0200
+++ new/pandas-1.3.5/pandas/_libs/ops_dispatch.pyx 2021-12-12
11:20:47.000000000 +0100
@@ -26,7 +26,7 @@
"true_divide": "truediv",
"power": "pow",
"remainder": "mod",
- "divide": "div",
+ "divide": "truediv",
"equal": "eq",
"not_equal": "ne",
"less": "lt",
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/pandas-1.3.4/pandas/_version.py
new/pandas-1.3.5/pandas/_version.py
--- old/pandas-1.3.4/pandas/_version.py 2021-10-17 14:40:38.766444700 +0200
+++ new/pandas-1.3.5/pandas/_version.py 2021-12-12 11:23:38.190560000 +0100
@@ -8,11 +8,11 @@
version_json = '''
{
- "date": "2021-10-17T13:27:58+0100",
+ "date": "2021-12-12T10:20:48+0000",
"dirty": false,
"error": null,
- "full-revisionid": "945c9ed766a61c7d2c0a7cbb251b6edebf9cb7d5",
- "version": "1.3.4"
+ "full-revisionid": "66e3805b8cabe977f40c05259cc3fcf7ead5687d",
+ "version": "1.3.5"
}
''' # END VERSION_JSON
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/pandas-1.3.4/pandas/compat/numpy/__init__.py
new/pandas-1.3.5/pandas/compat/numpy/__init__.py
--- old/pandas-1.3.4/pandas/compat/numpy/__init__.py 2021-10-17
14:27:57.000000000 +0200
+++ new/pandas-1.3.5/pandas/compat/numpy/__init__.py 2021-12-12
11:20:47.000000000 +0100
@@ -12,9 +12,15 @@
np_version_under1p18 = _nlv < Version("1.18")
np_version_under1p19 = _nlv < Version("1.19")
np_version_under1p20 = _nlv < Version("1.20")
+np_version_under1p22 = _nlv < Version("1.22")
is_numpy_dev = _nlv.dev is not None
_min_numpy_ver = "1.17.3"
+if is_numpy_dev or not np_version_under1p22:
+ np_percentile_argname = "method"
+else:
+ np_percentile_argname = "interpolation"
+
if _nlv < Version(_min_numpy_ver):
raise ImportError(
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/pandas-1.3.4/pandas/core/algorithms.py
new/pandas-1.3.5/pandas/core/algorithms.py
--- old/pandas-1.3.4/pandas/core/algorithms.py 2021-10-17 14:27:57.000000000
+0200
+++ new/pandas-1.3.5/pandas/core/algorithms.py 2021-12-12 11:20:47.000000000
+0100
@@ -139,7 +139,7 @@
# i.e. all-bool Categorical, BooleanArray
try:
return np.asarray(values).astype("uint8", copy=False),
values.dtype
- except TypeError:
+ except (TypeError, ValueError):
# GH#42107 we have pd.NAs present
return np.asarray(values), values.dtype
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/pandas-1.3.4/pandas/core/arrays/datetimes.py
new/pandas-1.3.5/pandas/core/arrays/datetimes.py
--- old/pandas-1.3.4/pandas/core/arrays/datetimes.py 2021-10-17
14:27:57.000000000 +0200
+++ new/pandas-1.3.5/pandas/core/arrays/datetimes.py 2021-12-12
11:20:47.000000000 +0100
@@ -2067,8 +2067,13 @@
)
if tz and inferred_tz:
# two timezones: convert to intended from base UTC repr
- data = tzconversion.tz_convert_from_utc(data.view("i8"), tz)
- data = data.view(DT64NS_DTYPE)
+ if data.dtype == "i8":
+ # GH#42505
+ # by convention, these are _already_ UTC, e.g
+ return data.view(DT64NS_DTYPE), tz, None
+
+ utc_vals = tzconversion.tz_convert_from_utc(data.view("i8"),
tz)
+ data = utc_vals.view(DT64NS_DTYPE)
elif inferred_tz:
tz = inferred_tz
elif allow_object and data.dtype == object:
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore'
old/pandas-1.3.4/pandas/core/arrays/sparse/scipy_sparse.py
new/pandas-1.3.5/pandas/core/arrays/sparse/scipy_sparse.py
--- old/pandas-1.3.4/pandas/core/arrays/sparse/scipy_sparse.py 2021-10-17
14:27:57.000000000 +0200
+++ new/pandas-1.3.5/pandas/core/arrays/sparse/scipy_sparse.py 2021-12-12
11:20:47.000000000 +0100
@@ -122,7 +122,7 @@
Parameters
----------
- A : scipy.sparse.coo.coo_matrix
+ A : scipy.sparse.coo_matrix
dense_index : bool, default False
Returns
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/pandas-1.3.4/pandas/core/dtypes/cast.py
new/pandas-1.3.5/pandas/core/dtypes/cast.py
--- old/pandas-1.3.4/pandas/core/dtypes/cast.py 2021-10-17 14:27:57.000000000
+0200
+++ new/pandas-1.3.5/pandas/core/dtypes/cast.py 2021-12-12 11:20:47.000000000
+0100
@@ -908,9 +908,9 @@
"""
new_dtype, fill_value = maybe_promote(values.dtype, fill_value)
# We get a copy in all cases _except_ (values.dtype == new_dtype and not
copy)
- values = values.astype(new_dtype, copy=copy)
+ upcast_values = values.astype(new_dtype, copy=copy)
- return values, fill_value
+ return upcast_values, fill_value # type: ignore[return-value]
def invalidate_string_dtypes(dtype_set: set[DtypeObj]):
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/pandas-1.3.4/pandas/core/groupby/ops.py
new/pandas-1.3.5/pandas/core/groupby/ops.py
--- old/pandas-1.3.4/pandas/core/groupby/ops.py 2021-10-17 14:27:57.000000000
+0200
+++ new/pandas-1.3.5/pandas/core/groupby/ops.py 2021-12-12 11:20:47.000000000
+0100
@@ -546,9 +546,10 @@
elif is_bool_dtype(dtype):
values = values.astype("int64")
elif is_integer_dtype(dtype):
- # e.g. uint8 -> uint64, int16 -> int64
- dtype_str = dtype.kind + "8"
- values = values.astype(dtype_str, copy=False)
+ # GH#43329 If the dtype is explicitly of type uint64 the type is
not
+ # changed to prevent overflow.
+ if dtype != np.uint64:
+ values = values.astype(np.int64, copy=False)
elif is_numeric:
if not is_complex_dtype(dtype):
values = ensure_float64(values)
@@ -574,6 +575,16 @@
min_count,
is_datetimelike=is_datetimelike,
)
+ elif self.how in ["add"]:
+ # We support datetimelike
+ func(
+ result,
+ counts,
+ values,
+ comp_ids,
+ min_count,
+ datetimelike=is_datetimelike,
+ )
else:
func(result, counts, values, comp_ids, min_count)
else:
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/pandas-1.3.4/pandas/core/nanops.py
new/pandas-1.3.5/pandas/core/nanops.py
--- old/pandas-1.3.4/pandas/core/nanops.py 2021-10-17 14:27:57.000000000
+0200
+++ new/pandas-1.3.5/pandas/core/nanops.py 2021-12-12 11:20:47.000000000
+0100
@@ -29,6 +29,7 @@
Shape,
)
from pandas.compat._optional import import_optional_dependency
+from pandas.compat.numpy import np_percentile_argname
from pandas.core.dtypes.common import (
get_dtype,
@@ -1667,7 +1668,7 @@
if len(values) == 0:
return np.array([na_value] * len(q), dtype=values.dtype)
- return np.percentile(values, q, interpolation=interpolation)
+ return np.percentile(values, q, **{np_percentile_argname: interpolation})
def nanpercentile(
@@ -1720,7 +1721,9 @@
result = np.array(result, dtype=values.dtype, copy=False).T
return result
else:
- return np.percentile(values, q, axis=1, interpolation=interpolation)
+ return np.percentile(
+ values, q, axis=1, **{np_percentile_argname: interpolation}
+ )
def na_accum_func(values: ArrayLike, accum_func, *, skipna: bool) -> ArrayLike:
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/pandas-1.3.4/pandas/core/reshape/merge.py
new/pandas-1.3.5/pandas/core/reshape/merge.py
--- old/pandas-1.3.4/pandas/core/reshape/merge.py 2021-10-17
14:27:57.000000000 +0200
+++ new/pandas-1.3.5/pandas/core/reshape/merge.py 2021-12-12
11:20:47.000000000 +0100
@@ -1781,21 +1781,27 @@
# GH#29130 Check that merge keys do not have dtype object
if not self.left_index:
left_on = self.left_on[0]
- lo_dtype = (
- self.left[left_on].dtype
- if left_on in self.left.columns
- else self.left.index.get_level_values(left_on)
- )
+ if is_array_like(left_on):
+ lo_dtype = left_on.dtype
+ else:
+ lo_dtype = (
+ self.left[left_on].dtype
+ if left_on in self.left.columns
+ else self.left.index.get_level_values(left_on)
+ )
else:
lo_dtype = self.left.index.dtype
if not self.right_index:
right_on = self.right_on[0]
- ro_dtype = (
- self.right[right_on].dtype
- if right_on in self.right.columns
- else self.right.index.get_level_values(right_on)
- )
+ if is_array_like(right_on):
+ ro_dtype = right_on.dtype
+ else:
+ ro_dtype = (
+ self.right[right_on].dtype
+ if right_on in self.right.columns
+ else self.right.index.get_level_values(right_on)
+ )
else:
ro_dtype = self.right.index.dtype
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/pandas-1.3.4/pandas/core/window/rolling.py
new/pandas-1.3.5/pandas/core/window/rolling.py
--- old/pandas-1.3.4/pandas/core/window/rolling.py 2021-10-17
14:27:57.000000000 +0200
+++ new/pandas-1.3.5/pandas/core/window/rolling.py 2021-12-12
11:20:47.000000000 +0100
@@ -658,8 +658,11 @@
target = self._create_data(target)
result = super()._apply_pairwise(target, other, pairwise, func)
# 1) Determine the levels + codes of the groupby levels
- if other is not None:
- # When we have other, we must reindex (expand) the result
+ if other is not None and not all(
+ len(group) == len(other) for group in
self._grouper.indices.values()
+ ):
+ # GH 42915
+ # len(other) != len(any group), so must reindex (expand) the result
# from flex_binary_moment to a "transform"-like result
# per groupby combination
old_result_len = len(result)
@@ -681,10 +684,9 @@
codes, levels = factorize(labels)
groupby_codes.append(codes)
groupby_levels.append(levels)
-
else:
- # When we evaluate the pairwise=True result, repeat the groupby
- # labels by the number of columns in the original object
+ # pairwise=True or len(other) == len(each group), so repeat
+ # the groupby labels by the number of columns in the original
object
groupby_codes = self._grouper.codes
# error: Incompatible types in assignment (expression has type
# "List[Index]", variable has type "List[Union[ndarray, Index]]")
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/pandas-1.3.4/pandas/io/parsers/c_parser_wrapper.py
new/pandas-1.3.5/pandas/io/parsers/c_parser_wrapper.py
--- old/pandas-1.3.4/pandas/io/parsers/c_parser_wrapper.py 2021-10-17
14:27:57.000000000 +0200
+++ new/pandas-1.3.5/pandas/io/parsers/c_parser_wrapper.py 2021-12-12
11:20:47.000000000 +0100
@@ -206,9 +206,10 @@
"""
assert self.orig_names is not None
# error: Cannot determine type of 'names'
- col_indices = [
- self.orig_names.index(x) for x in self.names # type:
ignore[has-type]
- ]
+
+ # much faster than using orig_names.index(x) xref GH#44106
+ names_dict = {x: i for i, x in enumerate(self.orig_names)}
+ col_indices = [names_dict[x] for x in self.names] # type:
ignore[has-type]
# error: Cannot determine type of 'names'
noconvert_columns = self._set_noconvert_dtype_columns(
col_indices,
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/pandas-1.3.4/pandas/plotting/_matplotlib/compat.py
new/pandas-1.3.5/pandas/plotting/_matplotlib/compat.py
--- old/pandas-1.3.4/pandas/plotting/_matplotlib/compat.py 2021-10-17
14:27:28.000000000 +0200
+++ new/pandas-1.3.5/pandas/plotting/_matplotlib/compat.py 2021-12-12
11:15:39.000000000 +0100
@@ -24,3 +24,4 @@
mpl_ge_3_2_0 = _mpl_version("3.2.0", operator.ge)
mpl_ge_3_3_0 = _mpl_version("3.3.0", operator.ge)
mpl_ge_3_4_0 = _mpl_version("3.4.0", operator.ge)
+mpl_ge_3_5_0 = _mpl_version("3.5.0", operator.ge)
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore'
old/pandas-1.3.4/pandas/plotting/_matplotlib/converter.py
new/pandas-1.3.5/pandas/plotting/_matplotlib/converter.py
--- old/pandas-1.3.4/pandas/plotting/_matplotlib/converter.py 2021-10-17
14:27:57.000000000 +0200
+++ new/pandas-1.3.5/pandas/plotting/_matplotlib/converter.py 2021-12-12
11:20:47.000000000 +0100
@@ -353,8 +353,8 @@
locator = MilliSecondLocator(self.tz)
locator.set_axis(self.axis)
- locator.set_view_interval(*self.axis.get_view_interval())
- locator.set_data_interval(*self.axis.get_data_interval())
+ locator.axis.set_view_interval(*self.axis.get_view_interval())
+ locator.axis.set_data_interval(*self.axis.get_data_interval())
return locator
return dates.AutoDateLocator.get_locator(self, dmin, dmax)
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore'
old/pandas-1.3.4/pandas/tests/arrays/sparse/test_array.py
new/pandas-1.3.5/pandas/tests/arrays/sparse/test_array.py
--- old/pandas-1.3.4/pandas/tests/arrays/sparse/test_array.py 2021-10-17
14:27:57.000000000 +0200
+++ new/pandas-1.3.5/pandas/tests/arrays/sparse/test_array.py 2021-12-12
11:20:47.000000000 +0100
@@ -1204,7 +1204,7 @@
dtype="Sparse[int]",
)
A, _, _ = ser.sparse.to_coo()
- assert isinstance(A, scipy.sparse.coo.coo_matrix)
+ assert isinstance(A, scipy.sparse.coo_matrix)
def test_non_sparse_raises(self):
ser = pd.Series([1, 2, 3])
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore'
old/pandas-1.3.4/pandas/tests/frame/constructors/test_from_records.py
new/pandas-1.3.5/pandas/tests/frame/constructors/test_from_records.py
--- old/pandas-1.3.4/pandas/tests/frame/constructors/test_from_records.py
2021-10-17 14:27:57.000000000 +0200
+++ new/pandas-1.3.5/pandas/tests/frame/constructors/test_from_records.py
2021-12-12 11:20:47.000000000 +0100
@@ -34,10 +34,7 @@
arrdata = [np.array([datetime(2005, 3, 1, 0, 0), None])]
dtypes = [("EXPIRY", "<M8[ns]")]
- try:
- recarray = np.core.records.fromarrays(arrdata, dtype=dtypes)
- except (ValueError):
- pytest.skip("known failure of numpy rec array creation")
+ recarray = np.core.records.fromarrays(arrdata, dtype=dtypes)
result = DataFrame.from_records(recarray)
tm.assert_frame_equal(result, expected)
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore'
old/pandas-1.3.4/pandas/tests/frame/methods/test_quantile.py
new/pandas-1.3.5/pandas/tests/frame/methods/test_quantile.py
--- old/pandas-1.3.4/pandas/tests/frame/methods/test_quantile.py
2021-10-17 14:27:28.000000000 +0200
+++ new/pandas-1.3.5/pandas/tests/frame/methods/test_quantile.py
2021-12-12 11:20:47.000000000 +0100
@@ -1,6 +1,8 @@
import numpy as np
import pytest
+from pandas.compat.numpy import np_percentile_argname
+
import pandas as pd
from pandas import (
DataFrame,
@@ -153,7 +155,10 @@
# cross-check interpolation=nearest results in original dtype
exp = np.percentile(
- np.array([[1, 2, 3], [2, 3, 4]]), 0.5, axis=0,
interpolation="nearest"
+ np.array([[1, 2, 3], [2, 3, 4]]),
+ 0.5,
+ axis=0,
+ **{np_percentile_argname: "nearest"},
)
expected = Series(exp, index=[1, 2, 3], name=0.5, dtype="int64")
tm.assert_series_equal(result, expected)
@@ -167,7 +172,7 @@
np.array([[1.0, 2.0, 3.0], [2.0, 3.0, 4.0]]),
0.5,
axis=0,
- interpolation="nearest",
+ **{np_percentile_argname: "nearest"},
)
expected = Series(exp, index=[1, 2, 3], name=0.5, dtype="float64")
tm.assert_series_equal(result, expected)
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/pandas-1.3.4/pandas/tests/frame/test_constructors.py
new/pandas-1.3.5/pandas/tests/frame/test_constructors.py
--- old/pandas-1.3.4/pandas/tests/frame/test_constructors.py 2021-10-17
14:27:57.000000000 +0200
+++ new/pandas-1.3.5/pandas/tests/frame/test_constructors.py 2021-12-12
11:20:47.000000000 +0100
@@ -68,6 +68,19 @@
class TestDataFrameConstructors:
+ def test_constructor_dict_with_tzaware_scalar(self):
+ # GH#42505
+ dt = Timestamp("2019-11-03
01:00:00-0700").tz_convert("America/Los_Angeles")
+
+ df = DataFrame({"dt": dt}, index=[0])
+ expected = DataFrame({"dt": [dt]})
+ tm.assert_frame_equal(df, expected)
+
+ # Non-homogeneous
+ df = DataFrame({"dt": dt, "value": [1]})
+ expected = DataFrame({"dt": [dt], "value": [1]})
+ tm.assert_frame_equal(df, expected)
+
def test_construct_ndarray_with_nas_and_int_dtype(self):
# GH#26919 match Series by not casting np.nan to meaningless int
arr = np.array([[1, np.nan], [2, 3]])
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/pandas-1.3.4/pandas/tests/groupby/test_function.py
new/pandas-1.3.5/pandas/tests/groupby/test_function.py
--- old/pandas-1.3.4/pandas/tests/groupby/test_function.py 2021-10-17
14:27:57.000000000 +0200
+++ new/pandas-1.3.5/pandas/tests/groupby/test_function.py 2021-12-12
11:20:47.000000000 +0100
@@ -1105,3 +1105,27 @@
result = grouped.sum(min_count=2)
expected = DataFrame({"b": [pd.NA] * 3, "c": [pd.NA] * 3}, dtype="Int64",
index=idx)
tm.assert_frame_equal(result, expected)
+
+
+def test_groupby_sum_timedelta_with_nat():
+ # GH#42659
+ df = DataFrame(
+ {
+ "a": [1, 1, 2, 2],
+ "b": [pd.Timedelta("1d"), pd.Timedelta("2d"), pd.Timedelta("3d"),
pd.NaT],
+ }
+ )
+ td3 = pd.Timedelta(days=3)
+
+ gb = df.groupby("a")
+
+ res = gb.sum()
+ expected = DataFrame({"b": [td3, td3]}, index=Index([1, 2], name="a"))
+ tm.assert_frame_equal(res, expected)
+
+ res = gb["b"].sum()
+ tm.assert_series_equal(res, expected["b"])
+
+ res = gb["b"].sum(min_count=2)
+ expected = Series([td3, pd.NaT], dtype="m8[ns]", name="b",
index=expected.index)
+ tm.assert_series_equal(res, expected)
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore'
old/pandas-1.3.4/pandas/tests/indexes/datetimes/test_indexing.py
new/pandas-1.3.5/pandas/tests/indexes/datetimes/test_indexing.py
--- old/pandas-1.3.4/pandas/tests/indexes/datetimes/test_indexing.py
2021-10-17 14:27:57.000000000 +0200
+++ new/pandas-1.3.5/pandas/tests/indexes/datetimes/test_indexing.py
2021-12-12 11:20:47.000000000 +0100
@@ -652,10 +652,6 @@
([date(9999, 1, 1), date(9999, 1, 1)], [-1, -1]),
],
)
- # FIXME: these warnings are flaky GH#36131
- @pytest.mark.filterwarnings(
- "ignore:Comparison of Timestamp with datetime.date:FutureWarning"
- )
def test_get_indexer_out_of_bounds_date(self, target, positions):
values = DatetimeIndex([Timestamp("2020-01-01"),
Timestamp("2020-01-02")])
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/pandas-1.3.4/pandas/tests/indexes/test_engines.py
new/pandas-1.3.5/pandas/tests/indexes/test_engines.py
--- old/pandas-1.3.4/pandas/tests/indexes/test_engines.py 2021-10-17
14:27:57.000000000 +0200
+++ new/pandas-1.3.5/pandas/tests/indexes/test_engines.py 2021-12-12
11:20:47.000000000 +0100
@@ -61,13 +61,7 @@
@pytest.mark.parametrize(
"scalar",
[
- # error: Argument 1 to "Timestamp" has incompatible type
"timedelta64";
- # expected "Union[integer[Any], float, str, date, datetime64]"
- pd.Timestamp(
- pd.Timedelta(days=42).asm8.view(
- "datetime64[ns]"
- ) # type: ignore[arg-type]
- ),
+ pd.Timestamp(pd.Timedelta(days=42).asm8.view("datetime64[ns]")),
pd.Timedelta(days=42).value,
pd.Timedelta(days=42).to_pytimedelta(),
pd.Timedelta(days=42).to_timedelta64(),
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/pandas-1.3.4/pandas/tests/io/parser/test_quoting.py
new/pandas-1.3.5/pandas/tests/io/parser/test_quoting.py
--- old/pandas-1.3.4/pandas/tests/io/parser/test_quoting.py 2021-10-17
14:27:57.000000000 +0200
+++ new/pandas-1.3.5/pandas/tests/io/parser/test_quoting.py 2021-12-12
11:20:47.000000000 +0100
@@ -22,7 +22,7 @@
{"quotechar": None, "quoting": csv.QUOTE_MINIMAL},
"quotechar must be set if quoting enabled",
),
- ({"quotechar": 2}, '"quotechar" must be string, not int'),
+ ({"quotechar": 2}, '"quotechar" must be string( or None)?, not int'),
],
)
def test_bad_quote_char(all_parsers, kwargs, msg):
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/pandas-1.3.4/pandas/tests/plotting/common.py
new/pandas-1.3.5/pandas/tests/plotting/common.py
--- old/pandas-1.3.4/pandas/tests/plotting/common.py 2021-10-17
14:27:28.000000000 +0200
+++ new/pandas-1.3.5/pandas/tests/plotting/common.py 2021-12-12
11:15:39.000000000 +0100
@@ -45,6 +45,8 @@
from pandas.plotting._matplotlib import compat
+ self.compat = compat
+
mpl.rcdefaults()
self.start_date_to_int64 = 812419200000000000
@@ -550,7 +552,7 @@
obj.plot(kind=kind, grid=False, **kws)
assert not is_grid_on()
- if kind != "pie":
+ if kind not in ["pie", "hexbin", "scatter"]:
self.plt.subplot(1, 4 * len(kinds), spndx)
spndx += 1
mpl.rc("axes", grid=True)
@@ -569,6 +571,12 @@
"""
return [v[field] for v in rcParams["axes.prop_cycle"]]
+ def get_x_axis(self, ax):
+ return ax._shared_axes["x"] if self.compat.mpl_ge_3_5_0() else
ax._shared_x_axes
+
+ def get_y_axis(self, ax):
+ return ax._shared_axes["y"] if self.compat.mpl_ge_3_5_0() else
ax._shared_y_axes
+
def _check_plot_works(f, filterwarnings="always", default_axes=False,
**kwargs):
"""
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore'
old/pandas-1.3.4/pandas/tests/plotting/frame/test_frame.py
new/pandas-1.3.5/pandas/tests/plotting/frame/test_frame.py
--- old/pandas-1.3.4/pandas/tests/plotting/frame/test_frame.py 2021-10-17
14:27:28.000000000 +0200
+++ new/pandas-1.3.5/pandas/tests/plotting/frame/test_frame.py 2021-12-12
11:15:39.000000000 +0100
@@ -525,8 +525,8 @@
df.plot(ax=ax1, kind="area")
df.plot(ax=ax2, kind="area")
- assert ax1._shared_y_axes.joined(ax1, ax2)
- assert ax2._shared_y_axes.joined(ax1, ax2)
+ assert self.get_y_axis(ax1).joined(ax1, ax2)
+ assert self.get_y_axis(ax2).joined(ax1, ax2)
def test_bar_linewidth(self):
df = DataFrame(np.random.randn(5, 5))
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/pandas-1.3.4/pandas/tests/plotting/test_common.py
new/pandas-1.3.5/pandas/tests/plotting/test_common.py
--- old/pandas-1.3.4/pandas/tests/plotting/test_common.py 2021-10-17
14:27:28.000000000 +0200
+++ new/pandas-1.3.5/pandas/tests/plotting/test_common.py 2021-12-12
11:15:39.000000000 +0100
@@ -39,4 +39,6 @@
next(gen)
axes = fig.get_axes()
assert len(axes) == 1
- assert axes[0].get_geometry() == (2, 1, 2)
+ subplot_geometry = list(axes[0].get_subplotspec().get_geometry()[:-1])
+ subplot_geometry[-1] += 1
+ assert subplot_geometry == [2, 1, 2]
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore'
old/pandas-1.3.4/pandas/tests/plotting/test_datetimelike.py
new/pandas-1.3.5/pandas/tests/plotting/test_datetimelike.py
--- old/pandas-1.3.4/pandas/tests/plotting/test_datetimelike.py 2021-10-17
14:27:28.000000000 +0200
+++ new/pandas-1.3.5/pandas/tests/plotting/test_datetimelike.py 2021-12-12
11:20:47.000000000 +0100
@@ -180,12 +180,7 @@
first_line = ax.get_lines()[0]
first_x = first_line.get_xdata()[0].ordinal
first_y = first_line.get_ydata()[0]
- try:
- assert expected_string == ax.format_coord(first_x, first_y)
- except (ValueError):
- pytest.skip(
- "skipping test because issue forming test comparison
GH7664"
- )
+ assert expected_string == ax.format_coord(first_x, first_y)
annual = Series(1, index=date_range("2014-01-01", periods=3,
freq="A-DEC"))
_, ax = self.plt.subplots()
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore'
old/pandas-1.3.4/pandas/tests/plotting/test_hist_method.py
new/pandas-1.3.5/pandas/tests/plotting/test_hist_method.py
--- old/pandas-1.3.4/pandas/tests/plotting/test_hist_method.py 2021-10-17
14:27:28.000000000 +0200
+++ new/pandas-1.3.5/pandas/tests/plotting/test_hist_method.py 2021-12-12
11:15:39.000000000 +0100
@@ -728,35 +728,35 @@
ax1, ax2 = df.hist(column="height", by=df.gender, sharex=True)
# share x
- assert ax1._shared_x_axes.joined(ax1, ax2)
- assert ax2._shared_x_axes.joined(ax1, ax2)
+ assert self.get_x_axis(ax1).joined(ax1, ax2)
+ assert self.get_x_axis(ax2).joined(ax1, ax2)
# don't share y
- assert not ax1._shared_y_axes.joined(ax1, ax2)
- assert not ax2._shared_y_axes.joined(ax1, ax2)
+ assert not self.get_y_axis(ax1).joined(ax1, ax2)
+ assert not self.get_y_axis(ax2).joined(ax1, ax2)
def test_axis_share_y(self):
df = self.hist_df
ax1, ax2 = df.hist(column="height", by=df.gender, sharey=True)
# share y
- assert ax1._shared_y_axes.joined(ax1, ax2)
- assert ax2._shared_y_axes.joined(ax1, ax2)
+ assert self.get_y_axis(ax1).joined(ax1, ax2)
+ assert self.get_y_axis(ax2).joined(ax1, ax2)
# don't share x
- assert not ax1._shared_x_axes.joined(ax1, ax2)
- assert not ax2._shared_x_axes.joined(ax1, ax2)
+ assert not self.get_x_axis(ax1).joined(ax1, ax2)
+ assert not self.get_x_axis(ax2).joined(ax1, ax2)
def test_axis_share_xy(self):
df = self.hist_df
ax1, ax2 = df.hist(column="height", by=df.gender, sharex=True,
sharey=True)
# share both x and y
- assert ax1._shared_x_axes.joined(ax1, ax2)
- assert ax2._shared_x_axes.joined(ax1, ax2)
+ assert self.get_x_axis(ax1).joined(ax1, ax2)
+ assert self.get_x_axis(ax2).joined(ax1, ax2)
- assert ax1._shared_y_axes.joined(ax1, ax2)
- assert ax2._shared_y_axes.joined(ax1, ax2)
+ assert self.get_y_axis(ax1).joined(ax1, ax2)
+ assert self.get_y_axis(ax2).joined(ax1, ax2)
@pytest.mark.parametrize(
"histtype, expected",
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/pandas-1.3.4/pandas/tests/plotting/test_series.py
new/pandas-1.3.5/pandas/tests/plotting/test_series.py
--- old/pandas-1.3.4/pandas/tests/plotting/test_series.py 2021-10-17
14:27:28.000000000 +0200
+++ new/pandas-1.3.5/pandas/tests/plotting/test_series.py 2021-12-12
11:20:47.000000000 +0100
@@ -154,8 +154,8 @@
abs(self.ts).plot(ax=ax1, kind="area")
abs(self.ts).plot(ax=ax2, kind="area")
- assert ax1._shared_y_axes.joined(ax1, ax2)
- assert ax2._shared_y_axes.joined(ax1, ax2)
+ assert self.get_y_axis(ax1).joined(ax1, ax2)
+ assert self.get_y_axis(ax2).joined(ax1, ax2)
def test_label(self):
s = Series([1, 2])
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore'
old/pandas-1.3.4/pandas/tests/resample/test_datetime_index.py
new/pandas-1.3.5/pandas/tests/resample/test_datetime_index.py
--- old/pandas-1.3.4/pandas/tests/resample/test_datetime_index.py
2021-10-17 14:27:57.000000000 +0200
+++ new/pandas-1.3.5/pandas/tests/resample/test_datetime_index.py
2021-12-12 11:20:47.000000000 +0100
@@ -1827,3 +1827,27 @@
index=DatetimeIndex(["2020-03-31"], dtype="datetime64[ns]",
freq="Q-DEC"),
)
tm.assert_series_equal(result, expected)
+
+
+def test_resample_unsigned_int(uint_dtype):
+ # gh-43329
+ df = DataFrame(
+ index=date_range(start="2000-01-01", end="2000-01-03 23", freq="12H"),
+ columns=["x"],
+ data=[0, 1, 0] * 2,
+ dtype=uint_dtype,
+ )
+ df = df.loc[(df.index < "2000-01-02") | (df.index > "2000-01-03"), :]
+
+ if uint_dtype == "uint64":
+ with pytest.raises(RuntimeError, match="empty group with uint64_t"):
+ result = df.resample("D").max()
+ else:
+ result = df.resample("D").max()
+
+ expected = DataFrame(
+ [1, np.nan, 0],
+ columns=["x"],
+ index=date_range(start="2000-01-01", end="2000-01-03 23",
freq="D"),
+ )
+ tm.assert_frame_equal(result, expected)
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore'
old/pandas-1.3.4/pandas/tests/reshape/merge/test_merge_asof.py
new/pandas-1.3.5/pandas/tests/reshape/merge/test_merge_asof.py
--- old/pandas-1.3.4/pandas/tests/reshape/merge/test_merge_asof.py
2021-10-17 14:27:57.000000000 +0200
+++ new/pandas-1.3.5/pandas/tests/reshape/merge/test_merge_asof.py
2021-12-12 11:20:47.000000000 +0100
@@ -1484,3 +1484,44 @@
match=r"Incompatible merge dtype, .*, both sides must have numeric
dtype",
):
merge_asof(left, right, left_on="a", right_on="a")
+
+
+def test_merge_asof_array_as_on():
+ # GH#42844
+ right = pd.DataFrame(
+ {
+ "a": [2, 6],
+ "ts": [pd.Timestamp("2021/01/01 00:37"), pd.Timestamp("2021/01/01
01:40")],
+ }
+ )
+ ts_merge = pd.date_range(
+ start=pd.Timestamp("2021/01/01 00:00"), periods=3, freq="1h"
+ )
+ left = pd.DataFrame({"b": [4, 8, 7]})
+ result = merge_asof(
+ left,
+ right,
+ left_on=ts_merge,
+ right_on="ts",
+ allow_exact_matches=False,
+ direction="backward",
+ )
+ expected = pd.DataFrame({"b": [4, 8, 7], "a": [np.nan, 2, 6], "ts":
ts_merge})
+ tm.assert_frame_equal(result, expected)
+
+ result = merge_asof(
+ right,
+ left,
+ left_on="ts",
+ right_on=ts_merge,
+ allow_exact_matches=False,
+ direction="backward",
+ )
+ expected = pd.DataFrame(
+ {
+ "a": [2, 6],
+ "ts": [pd.Timestamp("2021/01/01 00:37"), pd.Timestamp("2021/01/01
01:40")],
+ "b": [4, 8],
+ }
+ )
+ tm.assert_frame_equal(result, expected)
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore'
old/pandas-1.3.4/pandas/tests/series/methods/test_drop_duplicates.py
new/pandas-1.3.5/pandas/tests/series/methods/test_drop_duplicates.py
--- old/pandas-1.3.4/pandas/tests/series/methods/test_drop_duplicates.py
2021-10-17 14:27:28.000000000 +0200
+++ new/pandas-1.3.5/pandas/tests/series/methods/test_drop_duplicates.py
2021-12-12 11:20:47.000000000 +0100
@@ -2,6 +2,7 @@
import pytest
from pandas import (
+ NA,
Categorical,
Series,
)
@@ -224,6 +225,20 @@
assert return_value is None
tm.assert_series_equal(sc, tc[~expected])
+ def test_drop_duplicates_categorical_bool_na(self):
+ # GH#44351
+ ser = Series(
+ Categorical(
+ [True, False, True, False, NA], categories=[True, False],
ordered=True
+ )
+ )
+ result = ser.drop_duplicates()
+ expected = Series(
+ Categorical([True, False, np.nan], categories=[True, False],
ordered=True),
+ index=[0, 1, 4],
+ )
+ tm.assert_series_equal(result, expected)
+
def test_drop_duplicates_pos_args_deprecation():
# GH#41485
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore'
old/pandas-1.3.4/pandas/tests/series/methods/test_duplicated.py
new/pandas-1.3.5/pandas/tests/series/methods/test_duplicated.py
--- old/pandas-1.3.4/pandas/tests/series/methods/test_duplicated.py
2021-10-17 14:27:28.000000000 +0200
+++ new/pandas-1.3.5/pandas/tests/series/methods/test_duplicated.py
2021-12-12 11:20:47.000000000 +0100
@@ -1,7 +1,11 @@
import numpy as np
import pytest
-from pandas import Series
+from pandas import (
+ NA,
+ Categorical,
+ Series,
+)
import pandas._testing as tm
@@ -33,3 +37,15 @@
result = ser.duplicated(keep=keep)
tm.assert_series_equal(result, expected)
+
+
+def test_duplicated_categorical_bool_na():
+ # GH#44351
+ ser = Series(
+ Categorical(
+ [True, False, True, False, NA], categories=[True, False],
ordered=True
+ )
+ )
+ result = ser.duplicated()
+ expected = Series([False, False, True, True, False])
+ tm.assert_series_equal(result, expected)
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore'
old/pandas-1.3.4/pandas/tests/series/methods/test_equals.py
new/pandas-1.3.5/pandas/tests/series/methods/test_equals.py
--- old/pandas-1.3.4/pandas/tests/series/methods/test_equals.py 2021-10-17
14:27:57.000000000 +0200
+++ new/pandas-1.3.5/pandas/tests/series/methods/test_equals.py 2021-12-12
11:20:47.000000000 +0100
@@ -125,3 +125,18 @@
assert ser.equals(ser2)
assert Index(ser).equals(Index(ser2))
assert ser.array.equals(ser2.array)
+
+
+def test_equals_None_vs_float():
+ # GH#44190
+ left = Series([-np.inf, np.nan, -1.0, 0.0, 1.0, 10 / 3, np.inf],
dtype=object)
+ right = Series([None] * len(left))
+
+ # these series were found to be equal due to a bug, check that they are
correctly
+ # found to not equal
+ assert not left.equals(right)
+ assert not right.equals(left)
+ assert not left.to_frame().equals(right.to_frame())
+ assert not right.to_frame().equals(left.to_frame())
+ assert not Index(left, dtype="object").equals(Index(right, dtype="object"))
+ assert not Index(right, dtype="object").equals(Index(left, dtype="object"))
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/pandas-1.3.4/pandas/tests/window/test_groupby.py
new/pandas-1.3.5/pandas/tests/window/test_groupby.py
--- old/pandas-1.3.4/pandas/tests/window/test_groupby.py 2021-10-17
14:27:57.000000000 +0200
+++ new/pandas-1.3.5/pandas/tests/window/test_groupby.py 2021-12-12
11:20:47.000000000 +0100
@@ -122,8 +122,33 @@
expected.index = expected_index
tm.assert_frame_equal(result, expected)
+ @pytest.mark.parametrize("f, expected_val", [["corr", 1], ["cov", 0.5]])
+ def test_rolling_corr_cov_other_same_size_as_groups(self, f, expected_val):
+ # GH 42915
+ df = DataFrame(
+ {"value": range(10), "idx1": [1] * 5 + [2] * 5, "idx2": [1, 2, 3,
4, 5] * 2}
+ ).set_index(["idx1", "idx2"])
+ other = DataFrame({"value": range(5), "idx2": [1, 2, 3, 4,
5]}).set_index(
+ "idx2"
+ )
+ result = getattr(df.groupby(level=0).rolling(2), f)(other)
+ expected_data = ([np.nan] + [expected_val] * 4) * 2
+ expected = DataFrame(
+ expected_data,
+ columns=["value"],
+ index=MultiIndex.from_arrays(
+ [
+ [1] * 5 + [2] * 5,
+ [1] * 5 + [2] * 5,
+ list(range(1, 6)) * 2,
+ ],
+ names=["idx1", "idx1", "idx2"],
+ ),
+ )
+ tm.assert_frame_equal(result, expected)
+
@pytest.mark.parametrize("f", ["corr", "cov"])
- def test_rolling_corr_cov(self, f):
+ def test_rolling_corr_cov_other_diff_size_as_groups(self, f):
g = self.frame.groupby("A")
r = g.rolling(window=4)
@@ -138,6 +163,11 @@
expected["A"] = np.nan
tm.assert_frame_equal(result, expected)
+ @pytest.mark.parametrize("f", ["corr", "cov"])
+ def test_rolling_corr_cov_pairwise(self, f):
+ g = self.frame.groupby("A")
+ r = g.rolling(window=4)
+
result = getattr(r.B, f)(pairwise=True)
def func(x):
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/pandas-1.3.4/pandas.egg-info/PKG-INFO
new/pandas-1.3.5/pandas.egg-info/PKG-INFO
--- old/pandas-1.3.4/pandas.egg-info/PKG-INFO 2021-10-17 14:40:38.000000000
+0200
+++ new/pandas-1.3.5/pandas.egg-info/PKG-INFO 2021-12-12 11:23:37.000000000
+0100
@@ -1,6 +1,6 @@
Metadata-Version: 2.1
Name: pandas
-Version: 1.3.4
+Version: 1.3.5
Summary: Powerful data structures for data analysis, time series, and
statistics
Home-page: https://pandas.pydata.org
Author: The Pandas Development Team
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/pandas-1.3.4/pandas.egg-info/SOURCES.txt
new/pandas-1.3.5/pandas.egg-info/SOURCES.txt
--- old/pandas-1.3.4/pandas.egg-info/SOURCES.txt 2021-10-17
14:40:38.000000000 +0200
+++ new/pandas-1.3.5/pandas.egg-info/SOURCES.txt 2021-12-12
11:23:37.000000000 +0100
@@ -246,6 +246,7 @@
doc/source/whatsnew/v1.3.2.rst
doc/source/whatsnew/v1.3.3.rst
doc/source/whatsnew/v1.3.4.rst
+doc/source/whatsnew/v1.3.5.rst
doc/sphinxext/README.rst
doc/sphinxext/announce.py
doc/sphinxext/contributors.py
