Merge branch 'main' of https://github.com/Tirthchoksi22/pandas

ci/code_checks.sh

@@ -148,7 +148,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.Series.cat.set_categories PR01,PR02" \
         -i "pandas.Series.dt.as_unit PR01,PR02" \
         -i "pandas.Series.dt.ceil PR01,PR02" \
-        -i "pandas.Series.dt.components SA01" \
         -i "pandas.Series.dt.day_name PR01,PR02" \
         -i "pandas.Series.dt.floor PR01,PR02" \
         -i "pandas.Series.dt.freq GL08" \
@@ -165,12 +164,8 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.Series.dt.tz_convert PR01,PR02" \
         -i "pandas.Series.dt.tz_localize PR01,PR02" \
         -i "pandas.Series.dt.unit GL08" \
-        -i "pandas.Series.eq SA01" \
         -i "pandas.Series.ge SA01" \
         -i "pandas.Series.gt SA01" \
-        -i "pandas.Series.kurt RT03,SA01" \
-        -i "pandas.Series.kurtosis RT03,SA01" \
-        -i "pandas.Series.le SA01" \
         -i "pandas.Series.list.__getitem__ SA01" \
         -i "pandas.Series.list.flatten SA01" \
         -i "pandas.Series.list.len SA01" \
@@ -248,20 +243,15 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.TimedeltaIndex.nanoseconds SA01" \
         -i "pandas.TimedeltaIndex.seconds SA01" \
         -i "pandas.TimedeltaIndex.to_pytimedelta RT03,SA01" \
-        -i "pandas.Timestamp.astimezone SA01" \
-        -i "pandas.Timestamp.ceil SA01" \
         -i "pandas.Timestamp.combine PR01,SA01" \
         -i "pandas.Timestamp.ctime SA01" \
         -i "pandas.Timestamp.date SA01" \
         -i "pandas.Timestamp.day GL08" \
-        -i "pandas.Timestamp.dst SA01" \
         -i "pandas.Timestamp.floor SA01" \
         -i "pandas.Timestamp.fold GL08" \
         -i "pandas.Timestamp.fromordinal SA01" \
         -i "pandas.Timestamp.fromtimestamp PR01,SA01" \
         -i "pandas.Timestamp.hour GL08" \
-        -i "pandas.Timestamp.is_leap_year SA01" \
-        -i "pandas.Timestamp.isocalendar SA01" \
         -i "pandas.Timestamp.isoweekday SA01" \
         -i "pandas.Timestamp.max PR02" \
         -i "pandas.Timestamp.microsecond GL08" \
@@ -288,7 +278,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.Timestamp.today SA01" \
         -i "pandas.Timestamp.toordinal SA01" \
         -i "pandas.Timestamp.tz SA01" \
-        -i "pandas.Timestamp.tz_convert SA01" \
         -i "pandas.Timestamp.tz_localize SA01" \
         -i "pandas.Timestamp.tzinfo GL08" \
         -i "pandas.Timestamp.tzname SA01" \
@@ -299,7 +288,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.Timestamp.value GL08" \
         -i "pandas.Timestamp.weekday SA01" \
         -i "pandas.Timestamp.year GL08" \
-        -i "pandas.api.extensions.ExtensionArray._from_sequence_of_strings SA01" \
         -i "pandas.api.extensions.ExtensionArray._hash_pandas_object RT03,SA01" \
         -i "pandas.api.extensions.ExtensionArray._pad_or_backfill PR01,RT03,SA01" \
         -i "pandas.api.extensions.ExtensionArray._reduce RT03,SA01" \
@@ -308,7 +296,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.api.extensions.ExtensionArray.dropna RT03,SA01" \
         -i "pandas.api.extensions.ExtensionArray.dtype SA01" \
         -i "pandas.api.extensions.ExtensionArray.duplicated RT03,SA01" \
-        -i "pandas.api.extensions.ExtensionArray.equals SA01" \
         -i "pandas.api.extensions.ExtensionArray.fillna SA01" \
         -i "pandas.api.extensions.ExtensionArray.insert PR07,RT03,SA01" \
         -i "pandas.api.extensions.ExtensionArray.interpolate PR01,SA01" \
@@ -324,7 +311,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.api.extensions.ExtensionArray.view SA01" \
         -i "pandas.api.indexers.VariableOffsetWindowIndexer PR01,SA01" \
         -i "pandas.api.interchange.from_dataframe RT03,SA01" \
-        -i "pandas.api.types.infer_dtype PR07,SA01" \
         -i "pandas.api.types.is_any_real_numeric_dtype SA01" \
         -i "pandas.api.types.is_bool PR01,SA01" \
         -i "pandas.api.types.is_bool_dtype SA01" \
@@ -353,7 +339,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.api.types.is_period_dtype SA01" \
         -i "pandas.api.types.is_re PR07,SA01" \
         -i "pandas.api.types.is_re_compilable PR07,SA01" \
-        -i "pandas.api.types.is_scalar SA01" \
         -i "pandas.api.types.is_signed_integer_dtype SA01" \
         -i "pandas.api.types.is_sparse SA01" \
         -i "pandas.api.types.is_string_dtype SA01" \
@@ -528,7 +513,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.testing.assert_index_equal PR07,SA01" \
         -i "pandas.testing.assert_series_equal PR07,SA01" \
         -i "pandas.timedelta_range SA01" \
-        -i "pandas.tseries.api.guess_datetime_format SA01" \
         -i "pandas.tseries.offsets.BDay PR02,SA01" \
         -i "pandas.tseries.offsets.BMonthBegin PR02" \
         -i "pandas.tseries.offsets.BQuarterBegin PR02" \
@@ -651,7 +635,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.tseries.offsets.DateOffset.nanos GL08" \
         -i "pandas.tseries.offsets.DateOffset.normalize GL08" \
         -i "pandas.tseries.offsets.DateOffset.rule_code GL08" \
-        -i "pandas.tseries.offsets.Day PR02" \
         -i "pandas.tseries.offsets.Day.freqstr SA01" \
         -i "pandas.tseries.offsets.Day.is_on_offset GL08" \
         -i "pandas.tseries.offsets.Day.n GL08" \

doc/source/whatsnew/v3.0.0.rst

@@ -221,6 +221,7 @@ Removal of prior version deprecations/changes
 - :func:`read_excel`, :func:`read_json`, :func:`read_html`, and :func:`read_xml` no longer accept raw string or byte representation of the data. That type of data must be wrapped in a :py:class:`StringIO` or :py:class:`BytesIO` (:issue:`53767`)
 - :func:`to_datetime` with a ``unit`` specified no longer parses strings into floats, instead parses them the same way as without ``unit`` (:issue:`50735`)
 - :meth:`DataFrame.groupby` with ``as_index=False`` and aggregation methods will no longer exclude from the result the groupings that do not arise from the input (:issue:`49519`)
+- :meth:`ExtensionArray._reduce` now requires a ``keepdims: bool = False`` parameter in the signature (:issue:`52788`)
 - :meth:`Series.dt.to_pydatetime` now returns a :class:`Series` of :py:class:`datetime.datetime` objects (:issue:`52459`)
 - :meth:`SeriesGroupBy.agg` no longer pins the name of the group to the input passed to the provided ``func`` (:issue:`51703`)
 - All arguments except ``name`` in :meth:`Index.rename` are now keyword only (:issue:`56493`)
@@ -246,6 +247,7 @@ Removal of prior version deprecations/changes
 - Removed the "closed" and "normalize" keywords in :meth:`DatetimeIndex.__new__` (:issue:`52628`)
 - Removed the deprecated ``delim_whitespace`` keyword in :func:`read_csv` and :func:`read_table`, use ``sep=r"\s+"`` instead (:issue:`55569`)
 - Require :meth:`SparseDtype.fill_value` to be a valid value for the :meth:`SparseDtype.subtype` (:issue:`53043`)
+- Stopped automatically casting non-datetimelike values (mainly strings) in :meth:`Series.isin` and :meth:`Index.isin` with ``datetime64``, ``timedelta64``, and :class:`PeriodDtype` dtypes (:issue:`53111`)
 - Stopped performing dtype inference when setting a :class:`Index` into a :class:`DataFrame` (:issue:`56102`)
 - Stopped performing dtype inference with in :meth:`Index.insert` with object-dtype index; this often affects the index/columns that result when setting new entries into an empty :class:`Series` or :class:`DataFrame` (:issue:`51363`)
 - Removed the "closed" and "unit" keywords in :meth:`TimedeltaIndex.__new__` (:issue:`52628`, :issue:`55499`)
@@ -461,6 +463,7 @@ Plotting
 
 Groupby/resample/rolling
 ^^^^^^^^^^^^^^^^^^^^^^^^
+- Bug in :meth:`.DataFrameGroupBy.__len__` and :meth:`.SeriesGroupBy.__len__` would raise when the grouping contained NA values and ``dropna=False`` (:issue:`58644`)
 - Bug in :meth:`.DataFrameGroupBy.groups` and :meth:`.SeriesGroupby.groups` that would not respect groupby argument ``dropna`` (:issue:`55919`)
 - Bug in :meth:`.DataFrameGroupBy.median` where nat values gave an incorrect result. (:issue:`57926`)
 - Bug in :meth:`.DataFrameGroupBy.quantile` when ``interpolation="nearest"`` is inconsistent with :meth:`DataFrame.quantile` (:issue:`47942`)

pandas/_config/__init__.py

@@ -15,7 +15,6 @@
     "describe_option",
     "option_context",
     "options",
-    "using_copy_on_write",
 ]
 from pandas._config import config
 from pandas._config import dates  # pyright: ignore[reportUnusedImport]  # noqa: F401
@@ -31,10 +30,6 @@
 from pandas._config.display import detect_console_encoding
 
 
-def using_copy_on_write() -> bool:
-    return True
-
-
 def using_pyarrow_string_dtype() -> bool:
     _mode_options = _global_config["future"]
     return _mode_options["infer_string"]

pandas/_libs/lib.pyx

@@ -184,6 +184,13 @@ def is_scalar(val: object) -> bool:
     bool
         Return True if given object is scalar.
 
+    See Also
+    --------
+    api.types.is_list_like : Check if the input is list-like.
+    api.types.is_integer : Check if the input is an integer.
+    api.types.is_float : Check if the input is a float.
+    api.types.is_bool : Check if the input is a boolean.
+
     Examples
     --------
     >>> import datetime
@@ -1442,6 +1449,7 @@ def infer_dtype(value: object, skipna: bool = True) -> str:
     Parameters
     ----------
     value : scalar, list, ndarray, or pandas type
+        The input data to infer the dtype.
     skipna : bool, default True
         Ignore NaN values when inferring the type.
 
@@ -1476,6 +1484,14 @@ def infer_dtype(value: object, skipna: bool = True) -> str:
     TypeError
         If ndarray-like but cannot infer the dtype
 
+    See Also
+    --------
+    api.types.is_scalar : Check if the input is a scalar.
+    api.types.is_list_like : Check if the input is list-like.
+    api.types.is_integer : Check if the input is an integer.
+    api.types.is_float : Check if the input is a float.
+    api.types.is_bool : Check if the input is a boolean.
+
     Notes
     -----
     - 'mixed' is the catchall for anything that is not otherwise

pandas/_libs/tslibs/nattype.pyx

@@ -528,6 +528,12 @@ class NaTType(_NaT):
         """
         Return a named tuple containing ISO year, week number, and weekday.
 
+        See Also
+        --------
+        DatetimeIndex.isocalendar : Return a 3-tuple containing ISO year,
+            week number, and weekday for the given DatetimeIndex object.
+        datetime.date.isocalendar : The equivalent method for `datetime.date` objects.
+
         Examples
         --------
         >>> ts = pd.Timestamp('2023-01-01 10:00:00')
@@ -542,6 +548,14 @@ class NaTType(_NaT):
         """
         Return the daylight saving time (DST) adjustment.
 
+        This method returns the DST adjustment as a `datetime.timedelta` object
+        if the Timestamp is timezone-aware and DST is applicable.
+
+        See Also
+        --------
+        Timestamp.tz_localize : Localize the Timestamp to a timezone.
+        Timestamp.tz_convert : Convert timezone-aware Timestamp to another time zone.
+
         Examples
         --------
         >>> ts = pd.Timestamp('2000-06-01 00:00:00', tz='Europe/Brussels')
@@ -814,6 +828,11 @@ class NaTType(_NaT):
         """
         Convert timezone-aware Timestamp to another time zone.
 
+        This method is used to convert a timezone-aware Timestamp object to a
+        different time zone. The original UTC time remains the same; only the
+        time zone information is changed. If the Timestamp is timezone-naive, a
+        TypeError is raised.
+
         Parameters
         ----------
         tz : str, pytz.timezone, dateutil.tz.tzfile or None
@@ -829,6 +848,13 @@ class NaTType(_NaT):
         TypeError
             If Timestamp is tz-naive.
 
+        See Also
+        --------
+        Timestamp.tz_localize : Localize the Timestamp to a timezone.
+        DatetimeIndex.tz_convert : Convert a DatetimeIndex to another time zone.
+        DatetimeIndex.tz_localize : Localize a DatetimeIndex to a specific time zone.
+        datetime.datetime.astimezone : Convert a datetime object to another time zone.
+
         Examples
         --------
         Create a timestamp object with UTC timezone:
@@ -1196,6 +1222,12 @@ timedelta}, default 'raise'
         ------
         ValueError if the freq cannot be converted.
 
+        See Also
+        --------
+        Timestamp.floor : Round down a Timestamp to the specified resolution.
+        Timestamp.round : Round a Timestamp to the specified resolution.
+        Series.dt.ceil : Ceil the datetime values in a Series.
+
         Notes
         -----
         If the Timestamp has a timezone, ceiling will take place relative to the
@@ -1256,6 +1288,11 @@ timedelta}, default 'raise'
         """
         Convert timezone-aware Timestamp to another time zone.
 
+        This method is used to convert a timezone-aware Timestamp object to a
+        different time zone. The original UTC time remains the same; only the
+        time zone information is changed. If the Timestamp is timezone-naive, a
+        TypeError is raised.
+
         Parameters
         ----------
         tz : str, pytz.timezone, dateutil.tz.tzfile or None
@@ -1271,6 +1308,13 @@ timedelta}, default 'raise'
         TypeError
             If Timestamp is tz-naive.
 
+        See Also
+        --------
+        Timestamp.tz_localize : Localize the Timestamp to a timezone.
+        DatetimeIndex.tz_convert : Convert a DatetimeIndex to another time zone.
+        DatetimeIndex.tz_localize : Localize a DatetimeIndex to a specific time zone.
+        datetime.datetime.astimezone : Convert a datetime object to another time zone.
+
         Examples
         --------
         Create a timestamp object with UTC timezone:

pandas/_libs/tslibs/offsets.pyx

@@ -1104,7 +1104,7 @@ cdef class Day(Tick):
     """
     Offset ``n`` days.
 
-    Parameters
+    Attributes
     ----------
     n : int, default 1
         The number of days represented.

pandas/_libs/tslibs/parsing.pyx

@@ -859,6 +859,10 @@ def guess_datetime_format(dt_str: str, bint dayfirst=False) -> str | None:
     """
     Guess the datetime format of a given datetime string.
 
+    This function attempts to deduce the format of a given datetime string. It is
+    useful for situations where the datetime format is unknown and needs to be
+    determined for proper parsing. The function is not guaranteed to return a format.
+
     Parameters
     ----------
     dt_str : str
@@ -876,6 +880,12 @@ def guess_datetime_format(dt_str: str, bint dayfirst=False) -> str | None:
         datetime format string (for `strftime` or `strptime`),
         or None if it can't be guessed.
 
+    See Also
+    --------
+    to_datetime : Convert argument to datetime.
+    Timestamp : Pandas replacement for python datetime.datetime object.
+    DatetimeIndex : Immutable ndarray-like of datetime64 data.
+
     Examples
     --------
     >>> from pandas.tseries.api import guess_datetime_format

pandas/_libs/tslibs/timestamps.pyx

@@ -820,9 +820,20 @@ cdef class _Timestamp(ABCTimestamp):
         """
         Return True if year is a leap year.
 
+        A leap year is a year, which has 366 days (instead of 365) including 29th of
+        February as an intercalary day. Leap years are years which are multiples of
+        four with the exception of years divisible by 100 but not by 400.
+
         Returns
         -------
         bool
+            True if year is a leap year, else False
+
+        See Also
+        --------
+        Period.is_leap_year : Return True if the period’s year is in a leap year.
+        DatetimeIndex.is_leap_year : Boolean indicator if the date belongs to a
+            leap year.
 
         Examples
         --------
@@ -1658,6 +1669,14 @@ class Timestamp(_Timestamp):
         """
         Return the daylight saving time (DST) adjustment.
 
+        This method returns the DST adjustment as a `datetime.timedelta` object
+        if the Timestamp is timezone-aware and DST is applicable.
+
+        See Also
+        --------
+        Timestamp.tz_localize : Localize the Timestamp to a timezone.
+        Timestamp.tz_convert : Convert timezone-aware Timestamp to another time zone.
+
         Examples
         --------
         >>> ts = pd.Timestamp('2000-06-01 00:00:00', tz='Europe/Brussels')
@@ -1672,6 +1691,12 @@ class Timestamp(_Timestamp):
         """
         Return a named tuple containing ISO year, week number, and weekday.
 
+        See Also
+        --------
+        DatetimeIndex.isocalendar : Return a 3-tuple containing ISO year,
+            week number, and weekday for the given DatetimeIndex object.
+        datetime.date.isocalendar : The equivalent method for `datetime.date` objects.
+
         Examples
         --------
         >>> ts = pd.Timestamp('2023-01-01 10:00:00')
@@ -2266,6 +2291,12 @@ timedelta}, default 'raise'
         ------
         ValueError if the freq cannot be converted.
 
+        See Also
+        --------
+        Timestamp.floor : Round down a Timestamp to the specified resolution.
+        Timestamp.round : Round a Timestamp to the specified resolution.
+        Series.dt.ceil : Ceil the datetime values in a Series.
+
         Notes
         -----
         If the Timestamp has a timezone, ceiling will take place relative to the
@@ -2451,6 +2482,11 @@ default 'raise'
         """
         Convert timezone-aware Timestamp to another time zone.
 
+        This method is used to convert a timezone-aware Timestamp object to a
+        different time zone. The original UTC time remains the same; only the
+        time zone information is changed. If the Timestamp is timezone-naive, a
+        TypeError is raised.
+
         Parameters
         ----------
         tz : str, pytz.timezone, dateutil.tz.tzfile or None
@@ -2466,6 +2502,13 @@ default 'raise'
         TypeError
             If Timestamp is tz-naive.
 
+        See Also
+        --------
+        Timestamp.tz_localize : Localize the Timestamp to a timezone.
+        DatetimeIndex.tz_convert : Convert a DatetimeIndex to another time zone.
+        DatetimeIndex.tz_localize : Localize a DatetimeIndex to a specific time zone.
+        datetime.datetime.astimezone : Convert a datetime object to another time zone.
+
         Examples
         --------
         Create a timestamp object with UTC timezone: