Merge branch 'main' into enh-consistency-interval-range

Author: Khor Chean Wei

doc/source/getting_started/install.rst

@@ -276,7 +276,7 @@ Computation
 ========================= ================== =============================================================
 Dependency                Minimum Version    Notes
 ========================= ================== =============================================================
-SciPy                     1.14.1             Miscellaneous statistical functions
+SciPy                     1.4.1              Miscellaneous statistical functions
 numba                     0.50.1             Alternative execution engine for rolling operations
                                              (see :ref:`Enhancing Performance <enhancingperf.numba>`)
 xarray                    0.15.1             pandas-like API for N-dimensional data

doc/source/whatsnew/v1.5.0.rst

@@ -110,6 +110,13 @@ did not have the same index as the input.
     df.groupby('a', dropna=True).transform(lambda x: x)
     df.groupby('a', dropna=True).transform('sum')
 
+.. _whatsnew_150.notable_bug_fixes.visualization:
+
+Styler
+^^^^^^
+
+- Fix showing "None" as ylabel in :meth:`Series.plot` when not setting ylabel (:issue:`46129`)
+
 .. _whatsnew_150.notable_bug_fixes.notable_bug_fix2:
 
 notable_bug_fix2

pandas/_libs/tslibs/dtypes.pxd

@@ -1,8 +1,11 @@
+from numpy cimport int64_t
+
 from pandas._libs.tslibs.np_datetime cimport NPY_DATETIMEUNIT
 
 
 cdef str npy_unit_to_abbrev(NPY_DATETIMEUNIT unit)
 cdef NPY_DATETIMEUNIT freq_group_code_to_npy_unit(int freq) nogil
+cdef int64_t periods_per_day(NPY_DATETIMEUNIT reso=*)
 
 cdef dict attrname_to_abbrevs
 

pandas/_libs/tslibs/dtypes.pyx

@@ -307,6 +307,36 @@ cdef NPY_DATETIMEUNIT freq_group_code_to_npy_unit(int freq) nogil:
         return NPY_DATETIMEUNIT.NPY_FR_D
 
 
+cdef int64_t periods_per_day(NPY_DATETIMEUNIT reso=NPY_DATETIMEUNIT.NPY_FR_ns):
+    """
+    How many of the given time units fit into a single day?
+    """
+    cdef:
+        int64_t day_units
+
+    if reso == NPY_DATETIMEUNIT.NPY_FR_ps:
+        # pico is the smallest unit for which we don't overflow, so
+        #  we exclude fempto and atto
+        day_units = 24 * 3600 * 1_000_000_000_000
+    elif reso == NPY_DATETIMEUNIT.NPY_FR_ns:
+        day_units = 24 * 3600 * 1_000_000_000
+    elif reso == NPY_DATETIMEUNIT.NPY_FR_us:
+        day_units = 24 * 3600 * 1_000_000
+    elif reso == NPY_DATETIMEUNIT.NPY_FR_ms:
+        day_units = 24 * 3600 * 1_000
+    elif reso == NPY_DATETIMEUNIT.NPY_FR_s:
+        day_units = 24 * 3600
+    elif reso == NPY_DATETIMEUNIT.NPY_FR_m:
+        day_units = 24 * 60
+    elif reso == NPY_DATETIMEUNIT.NPY_FR_h:
+        day_units = 24
+    elif reso == NPY_DATETIMEUNIT.NPY_FR_D:
+        day_units = 1
+    else:
+        raise NotImplementedError(reso)
+    return day_units
+
+
 cdef dict _reso_str_map = {
     Resolution.RESO_NS.value: "nanosecond",
     Resolution.RESO_US.value: "microsecond",

pandas/_libs/tslibs/vectorized.pyx

@@ -21,7 +21,9 @@ cnp.import_array()
 from .conversion cimport normalize_i8_stamp
 
 from .dtypes import Resolution
+
 from .ccalendar cimport DAY_NANOS
+from .dtypes cimport c_Resolution
 from .nattype cimport (
     NPY_NAT,
     c_NaT as NaT,
@@ -168,27 +170,19 @@ def ints_to_pydatetime(
 
 # -------------------------------------------------------------------------
 
-cdef:
-    int RESO_US = Resolution.RESO_US.value
-    int RESO_MS = Resolution.RESO_MS.value
-    int RESO_SEC = Resolution.RESO_SEC.value
-    int RESO_MIN = Resolution.RESO_MIN.value
-    int RESO_HR = Resolution.RESO_HR.value
-    int RESO_DAY = Resolution.RESO_DAY.value
-
 
-cdef inline int _reso_stamp(npy_datetimestruct *dts):
+cdef inline c_Resolution _reso_stamp(npy_datetimestruct *dts):
     if dts.us != 0:
         if dts.us % 1000 == 0:
-            return RESO_MS
-        return RESO_US
+            return c_Resolution.RESO_MS
+        return c_Resolution.RESO_US
     elif dts.sec != 0:
-        return RESO_SEC
+        return c_Resolution.RESO_SEC
     elif dts.min != 0:
-        return RESO_MIN
+        return c_Resolution.RESO_MIN
     elif dts.hour != 0:
-        return RESO_HR
-    return RESO_DAY
+        return c_Resolution.RESO_HR
+    return c_Resolution.RESO_DAY
 
 
 @cython.wraparound(False)
@@ -205,7 +199,7 @@ def get_resolution(const int64_t[:] stamps, tzinfo tz=None) -> Resolution:
         str typ
 
         npy_datetimestruct dts
-        int reso = RESO_DAY, curr_reso
+        c_Resolution reso = c_Resolution.RESO_DAY, curr_reso
 
     if is_utc(tz) or tz is None:
         use_utc = True

pandas/_typing.py

@@ -297,6 +297,9 @@ def closed(self) -> bool:
 else:
     TakeIndexer = Any
 
+# Shared by functions such as drop and astype
+IgnoreRaise = Literal["ignore", "raise"]
+
 # Windowing rank methods
 WindowingRankType = Literal["average", "min", "max"]
 
@@ -311,7 +314,7 @@ def closed(self) -> bool:
 
 # datetime and NaTType
 DatetimeNaTType = Union[datetime, "NaTType"]
-DateTimeErrorChoices = Literal["ignore", "raise", "coerce"]
+DateTimeErrorChoices = Union[IgnoreRaise, Literal["coerce"]]
 
 # sort_index
 SortKind = Literal["quicksort", "mergesort", "heapsort", "stable"]

pandas/core/common.py

@@ -250,7 +250,9 @@ def asarray_tuplesafe(values, dtype: NpDtype | None = None) -> np.ndarray:
     return result
 
 
-def index_labels_to_array(labels, dtype: NpDtype | None = None) -> np.ndarray:
+def index_labels_to_array(
+    labels: np.ndarray | Iterable, dtype: NpDtype | None = None
+) -> np.ndarray:
     """
     Transform label or iterable of labels to array, for use in Index.
 

pandas/core/dtypes/astype.py

@@ -19,6 +19,7 @@
 from pandas._typing import (
     ArrayLike,
     DtypeObj,
+    IgnoreRaise,
 )
 from pandas.errors import IntCastingNaNError
 from pandas.util._exceptions import find_stack_level
@@ -235,7 +236,7 @@ def astype_array(values: ArrayLike, dtype: DtypeObj, copy: bool = False) -> Arra
 
 
 def astype_array_safe(
-    values: ArrayLike, dtype, copy: bool = False, errors: str = "raise"
+    values: ArrayLike, dtype, copy: bool = False, errors: IgnoreRaise = "raise"
 ) -> ArrayLike:
     """
     Cast array (ndarray or ExtensionArray) to the new dtype.

pandas/core/frame.py

@@ -58,6 +58,7 @@
     FloatFormatType,
     FormattersType,
     Frequency,
+    IgnoreRaise,
     IndexKeyFunc,
     IndexLabel,
     Level,
@@ -4831,17 +4832,61 @@ def reindex(self, *args, **kwargs) -> DataFrame:
         kwargs.pop("labels", None)
         return super().reindex(**kwargs)
 
-    @deprecate_nonkeyword_arguments(version=None, allowed_args=["self", "labels"])
+    @overload
+    def drop(
+        self,
+        labels: Hashable | list[Hashable] = ...,
+        *,
+        axis: Axis = ...,
+        index: Hashable | list[Hashable] = ...,
+        columns: Hashable | list[Hashable] = ...,
+        level: Level | None = ...,
+        inplace: Literal[True],
+        errors: IgnoreRaise = ...,
+    ) -> None:
+        ...
+
+    @overload
     def drop(
         self,
-        labels=None,
+        labels: Hashable | list[Hashable] = ...,
+        *,
+        axis: Axis = ...,
+        index: Hashable | list[Hashable] = ...,
+        columns: Hashable | list[Hashable] = ...,
+        level: Level | None = ...,
+        inplace: Literal[False] = ...,
+        errors: IgnoreRaise = ...,
+    ) -> DataFrame:
+        ...
+
+    @overload
+    def drop(
+        self,
+        labels: Hashable | list[Hashable] = ...,
+        *,
+        axis: Axis = ...,
+        index: Hashable | list[Hashable] = ...,
+        columns: Hashable | list[Hashable] = ...,
+        level: Level | None = ...,
+        inplace: bool = ...,
+        errors: IgnoreRaise = ...,
+    ) -> DataFrame | None:
+        ...
+
+    # error: Signature of "drop" incompatible with supertype "NDFrame"
+    # github.com/python/mypy/issues/12387
+    @deprecate_nonkeyword_arguments(version=None, allowed_args=["self", "labels"])
+    def drop(  # type: ignore[override]
+        self,
+        labels: Hashable | list[Hashable] = None,
         axis: Axis = 0,
-        index=None,
-        columns=None,
+        index: Hashable | list[Hashable] = None,
+        columns: Hashable | list[Hashable] = None,
         level: Level | None = None,
         inplace: bool = False,
-        errors: str = "raise",
-    ):
+        errors: IgnoreRaise = "raise",
+    ) -> DataFrame | None:
         """
         Drop specified labels from rows or columns.
 
@@ -11187,7 +11232,7 @@ def where(
         inplace=False,
         axis=None,
         level=None,
-        errors="raise",
+        errors: IgnoreRaise = "raise",
         try_cast=lib.no_default,
     ):
         return super().where(cond, other, inplace, axis, level, errors, try_cast)
@@ -11202,7 +11247,7 @@ def mask(
         inplace=False,
         axis=None,
         level=None,
-        errors="raise",
+        errors: IgnoreRaise = "raise",
         try_cast=lib.no_default,
     ):
         return super().mask(cond, other, inplace, axis, level, errors, try_cast)

pandas/core/generic.py

@@ -44,6 +44,7 @@
     DtypeArg,
     DtypeObj,
     FilePath,
+    IgnoreRaise,
     IndexKeyFunc,
     IndexLabel,
     IntervalClosedType,
@@ -71,6 +72,7 @@
 )
 from pandas.util._decorators import (
     deprecate_kwarg,
+    deprecate_nonkeyword_arguments,
     doc,
     rewrite_axis_style_signature,
 )
@@ -4270,16 +4272,59 @@ def reindex_like(
 
         return self.reindex(**d)
 
+    @overload
     def drop(
         self,
-        labels=None,
-        axis=0,
-        index=None,
-        columns=None,
-        level=None,
+        labels: Hashable | list[Hashable] = ...,
+        *,
+        axis: Axis = ...,
+        index: Hashable | list[Hashable] = ...,
+        columns: Hashable | list[Hashable] = ...,
+        level: Level | None = ...,
+        inplace: Literal[True],
+        errors: IgnoreRaise = ...,
+    ) -> None:
+        ...
+
+    @overload
+    def drop(
+        self: NDFrameT,
+        labels: Hashable | list[Hashable] = ...,
+        *,
+        axis: Axis = ...,
+        index: Hashable | list[Hashable] = ...,
+        columns: Hashable | list[Hashable] = ...,
+        level: Level | None = ...,
+        inplace: Literal[False] = ...,
+        errors: IgnoreRaise = ...,
+    ) -> NDFrameT:
+        ...
+
+    @overload
+    def drop(
+        self: NDFrameT,
+        labels: Hashable | list[Hashable] = ...,
+        *,
+        axis: Axis = ...,
+        index: Hashable | list[Hashable] = ...,
+        columns: Hashable | list[Hashable] = ...,
+        level: Level | None = ...,
+        inplace: bool_t = ...,
+        errors: IgnoreRaise = ...,
+    ) -> NDFrameT | None:
+        ...
+
+    @deprecate_nonkeyword_arguments(version=None, allowed_args=["self", "labels"])
+    def drop(
+        self: NDFrameT,
+        labels: Hashable | list[Hashable] = None,
+        axis: Axis = 0,
+        index: Hashable | list[Hashable] = None,
+        columns: Hashable | list[Hashable] = None,
+        level: Level | None = None,
         inplace: bool_t = False,
-        errors: str = "raise",
-    ):
+        errors: IgnoreRaise = "raise",
+    ) -> NDFrameT | None:
 
         inplace = validate_bool_kwarg(inplace, "inplace")
 
@@ -4312,7 +4357,7 @@ def _drop_axis(
         labels,
         axis,
         level=None,
-        errors: str = "raise",
+        errors: IgnoreRaise = "raise",
         only_slice: bool_t = False,
     ) -> NDFrameT:
         """
@@ -5826,7 +5871,7 @@ def dtypes(self):
         return self._constructor_sliced(data, index=self._info_axis, dtype=np.object_)
 
     def astype(
-        self: NDFrameT, dtype, copy: bool_t = True, errors: str = "raise"
+        self: NDFrameT, dtype, copy: bool_t = True, errors: IgnoreRaise = "raise"
     ) -> NDFrameT:
         """
         Cast a pandas object to a specified dtype ``dtype``.
@@ -9139,7 +9184,7 @@ def _where(
         inplace=False,
         axis=None,
         level=None,
-        errors="raise",
+        errors: IgnoreRaise = "raise",
     ):
         """
         Equivalent to public method `where`, except that `other` is not
@@ -9278,7 +9323,7 @@ def where(
         inplace=False,
         axis=None,
         level=None,
-        errors="raise",
+        errors: IgnoreRaise = "raise",
         try_cast=lib.no_default,
     ):
         """
@@ -9431,7 +9476,7 @@ def mask(
         inplace=False,
         axis=None,
         level=None,
-        errors="raise",
+        errors: IgnoreRaise = "raise",
         try_cast=lib.no_default,
     ):