Merge branch 'master' into cln-arith

Author: jreback

doc/source/user_guide/merging.rst

@@ -18,6 +18,7 @@ Fixed regressions
 - Fixed regression where attempting to mutate a :class:`DateOffset` object would no longer raise an ``AttributeError`` (:issue:`36940`)
 - Fixed regression where :meth:`DataFrame.agg` would fail with :exc:`TypeError` when passed positional arguments to be passed on to the aggregation function (:issue:`36948`).
 - Fixed regression in :class:`RollingGroupby` with ``sort=False`` not being respected (:issue:`36889`)
+- Fixed regression in :meth:`Series.astype` converting ``None`` to ``"nan"`` when casting to string (:issue:`36904`)
 
 .. ---------------------------------------------------------------------------
 

doc/source/whatsnew/v1.1.4.rst

@@ -363,6 +363,7 @@ Numeric
 - Bug in :class:`IntegerArray` multiplication with ``timedelta`` and ``np.timedelta64`` objects (:issue:`36870`)
 - Bug in :meth:`DataFrame.diff` with ``datetime64`` dtypes including ``NaT`` values failing to fill ``NaT`` results correctly (:issue:`32441`)
 - Bug in :class:`IntervalArray` comparisons with :class:`Series` not returning :class:`Series` (:issue:`36908`)
+- Bug in :class:`DataFrame` arithmetic ops incorrectly accepting keyword arguments (:issue:`36843`)
 
 Conversion
 ^^^^^^^^^^
@@ -476,7 +477,7 @@ Other
 
 - Bug in :meth:`DataFrame.replace` and :meth:`Series.replace` incorrectly raising ``AssertionError`` instead of ``ValueError`` when invalid parameter combinations are passed (:issue:`36045`)
 - Bug in :meth:`DataFrame.replace` and :meth:`Series.replace` with numeric values and string ``to_replace`` (:issue:`34789`)
-- Fixed metadata propagation in the :class:`Series.dt` accessor (:issue:`28283`)
+- Fixed metadata propagation in the :class:`Series.dt` and :class:`Series.str` accessors (:issue:`28283`)
 - Bug in :meth:`Index.union` behaving differently depending on whether operand is a :class:`Index` or other list-like (:issue:`36384`)
 - Passing an array with 2 or more dimensions to the :class:`Series` constructor now raises the more specific ``ValueError``, from a bare ``Exception`` previously (:issue:`35744`)
 

doc/source/whatsnew/v1.2.0.rst

@@ -1,7 +1,5 @@
 from copy import copy
 
-from cython import Py_ssize_t
-
 from libc.stdlib cimport free, malloc
 
 import numpy as np
@@ -11,14 +9,14 @@ from numpy cimport int64_t, ndarray
 
 cnp.import_array()
 
-from pandas._libs cimport util
+from pandas._libs.util cimport is_array, set_array_not_contiguous
 
 from pandas._libs.lib import is_scalar, maybe_convert_objects
 
 
 cpdef check_result_array(object obj, Py_ssize_t cnt):
 
-    if (util.is_array(obj) or
+    if (is_array(obj) or
             (isinstance(obj, list) and len(obj) == cnt) or
             getattr(obj, 'shape', None) == (cnt,)):
         raise ValueError('Must produce aggregated value')
@@ -33,7 +31,7 @@ cdef class _BaseGrouper:
         if (dummy.dtype != self.arr.dtype
                 and values.dtype != self.arr.dtype):
             raise ValueError('Dummy array must be same dtype')
-        if util.is_array(values) and not values.flags.contiguous:
+        if is_array(values) and not values.flags.contiguous:
             # e.g. Categorical has no `flags` attribute
             values = values.copy()
         index = dummy.index.values
@@ -106,7 +104,7 @@ cdef class SeriesBinGrouper(_BaseGrouper):
         self.f = f
 
         values = series.values
-        if util.is_array(values) and not values.flags.c_contiguous:
+        if is_array(values) and not values.flags.c_contiguous:
             # e.g. Categorical has no `flags` attribute
             values = values.copy('C')
         self.arr = values
@@ -204,7 +202,7 @@ cdef class SeriesGrouper(_BaseGrouper):
         self.f = f
 
         values = series.values
-        if util.is_array(values) and not values.flags.c_contiguous:
+        if is_array(values) and not values.flags.c_contiguous:
             # e.g. Categorical has no `flags` attribute
             values = values.copy('C')
         self.arr = values
@@ -288,9 +286,9 @@ cpdef inline extract_result(object res, bint squeeze=True):
         res = res._values
         if squeeze and res.ndim == 1 and len(res) == 1:
             res = res[0]
-    if hasattr(res, 'values') and util.is_array(res.values):
+    if hasattr(res, 'values') and is_array(res.values):
         res = res.values
-    if util.is_array(res):
+    if is_array(res):
         if res.ndim == 0:
             res = res.item()
         elif squeeze and res.ndim == 1 and len(res) == 1:
@@ -304,7 +302,7 @@ cdef class Slider:
     """
     cdef:
         ndarray values, buf
-        Py_ssize_t stride, orig_len, orig_stride
+        Py_ssize_t stride
         char *orig_data
 
     def __init__(self, ndarray values, ndarray buf):
@@ -316,11 +314,9 @@ cdef class Slider:
 
         self.values = values
         self.buf = buf
-        self.stride = values.strides[0]
 
+        self.stride = values.strides[0]
         self.orig_data = self.buf.data
-        self.orig_len = self.buf.shape[0]
-        self.orig_stride = self.buf.strides[0]
 
         self.buf.data = self.values.data
         self.buf.strides[0] = self.stride
@@ -333,10 +329,8 @@ cdef class Slider:
         self.buf.shape[0] = end - start
 
     cdef reset(self):
-
-        self.buf.shape[0] = self.orig_len
         self.buf.data = self.orig_data
-        self.buf.strides[0] = self.orig_stride
+        self.buf.shape[0] = 0
 
 
 class InvalidApply(Exception):
@@ -408,39 +402,34 @@ cdef class BlockSlider:
     """
     Only capable of sliding on axis=0
     """
-
-    cdef public:
-        object frame, dummy, index
-        int nblocks
-        Slider idx_slider
-        list blocks
-
     cdef:
+        object frame, dummy, index, block
+        list blk_values
+        ndarray values
+        Slider idx_slider
         char **base_ptrs
+        int nblocks
+        Py_ssize_t i
 
     def __init__(self, object frame):
-        cdef:
-            Py_ssize_t i
-            object b
-
         self.frame = frame
         self.dummy = frame[:0]
         self.index = self.dummy.index
 
-        self.blocks = [b.values for b in self.dummy._mgr.blocks]
+        self.blk_values = [block.values for block in self.dummy._mgr.blocks]
 
-        for x in self.blocks:
-            util.set_array_not_contiguous(x)
+        for values in self.blk_values:
+            set_array_not_contiguous(values)
 
-        self.nblocks = len(self.blocks)
+        self.nblocks = len(self.blk_values)
         # See the comment in indexes/base.py about _index_data.
         # We need this for EA-backed indexes that have a reference to a 1-d
         # ndarray like datetime / timedelta / period.
         self.idx_slider = Slider(
             self.frame.index._index_data, self.dummy.index._index_data)
 
-        self.base_ptrs = <char**>malloc(sizeof(char*) * len(self.blocks))
-        for i, block in enumerate(self.blocks):
+        self.base_ptrs = <char**>malloc(sizeof(char*) * self.nblocks)
+        for i, block in enumerate(self.blk_values):
             self.base_ptrs[i] = (<ndarray>block).data
 
     def __dealloc__(self):
@@ -450,10 +439,9 @@ cdef class BlockSlider:
         cdef:
             ndarray arr
             Py_ssize_t i
-
         # move blocks
         for i in range(self.nblocks):
-            arr = self.blocks[i]
+            arr = self.blk_values[i]
 
             # axis=1 is the frame's axis=0
             arr.data = self.base_ptrs[i] + arr.strides[1] * start
@@ -470,10 +458,8 @@ cdef class BlockSlider:
         cdef:
             ndarray arr
             Py_ssize_t i
-
-        # reset blocks
         for i in range(self.nblocks):
-            arr = self.blocks[i]
+            arr = self.blk_values[i]
 
             # axis=1 is the frame's axis=0
             arr.data = self.base_ptrs[i]

pandas/_libs/reduction.pyx

@@ -723,8 +723,8 @@ def as_ordered(self, inplace=False):
 
         Returns
         -------
-        Categorical
-            Ordered Categorical.
+        Categorical or None
+            Ordered Categorical or None if ``inplace=True``.
         """
         inplace = validate_bool_kwarg(inplace, "inplace")
         return self.set_ordered(True, inplace=inplace)
@@ -741,8 +741,8 @@ def as_unordered(self, inplace=False):
 
         Returns
         -------
-        Categorical
-            Unordered Categorical.
+        Categorical or None
+            Unordered Categorical or None if ``inplace=True``.
         """
         inplace = validate_bool_kwarg(inplace, "inplace")
         return self.set_ordered(False, inplace=inplace)
@@ -848,8 +848,7 @@ def rename_categories(self, new_categories, inplace=False):
         Returns
         -------
         cat : Categorical or None
-           With ``inplace=False``, the new categorical is returned.
-           With ``inplace=True``, there is no return value.
+            Categorical with removed categories or None if ``inplace=True``.
 
         Raises
         ------
@@ -917,7 +916,8 @@ def reorder_categories(self, new_categories, ordered=None, inplace=False):
 
         Returns
         -------
-        cat : Categorical with reordered categories or None if inplace.
+        cat : Categorical or None
+            Categorical with removed categories or None if ``inplace=True``.
 
         Raises
         ------
@@ -957,7 +957,8 @@ def add_categories(self, new_categories, inplace=False):
 
         Returns
         -------
-        cat : Categorical with new categories added or None if inplace.
+        cat : Categorical or None
+            Categorical with new categories added or None if ``inplace=True``.
 
         Raises
         ------
@@ -1007,7 +1008,8 @@ def remove_categories(self, removals, inplace=False):
 
         Returns
         -------
-        cat : Categorical with removed categories or None if inplace.
+        cat : Categorical or None
+            Categorical with removed categories or None if ``inplace=True``.
 
         Raises
         ------
@@ -1054,7 +1056,8 @@ def remove_unused_categories(self, inplace=False):
 
         Returns
         -------
-        cat : Categorical with unused categories dropped or None if inplace.
+        cat : Categorical or None
+            Categorical with unused categories dropped or None if ``inplace=True``.
 
         See Also
         --------