DEPR: Enforce deprecation of mad and tshift (#49252)

Author: rhshadrach

asv_bench/benchmarks/groupby.py

@@ -35,7 +35,6 @@
         "pct_change",
         "min",
         "var",
-        "mad",
         "describe",
         "std",
         "quantile",
@@ -52,7 +51,6 @@
         "cummax",
         "pct_change",
         "var",
-        "mad",
         "describe",
         "std",
     },
@@ -437,7 +435,6 @@ class GroupByMethods:
             "first",
             "head",
             "last",
-            "mad",
             "max",
             "min",
             "median",
@@ -483,7 +480,7 @@ def setup(self, dtype, method, application, ncols):
 
         if method == "describe":
             ngroups = 20
-        elif method in ["mad", "skew"]:
+        elif method == "skew":
             ngroups = 100
         else:
             ngroups = 1000

asv_bench/benchmarks/stat_ops.py

@@ -2,7 +2,7 @@
 
 import pandas as pd
 
-ops = ["mean", "sum", "median", "std", "skew", "kurt", "mad", "prod", "sem", "var"]
+ops = ["mean", "sum", "median", "std", "skew", "kurt", "prod", "sem", "var"]
 
 
 class FrameOps:
@@ -11,9 +11,6 @@ class FrameOps:
     param_names = ["op", "dtype", "axis"]
 
     def setup(self, op, dtype, axis):
-        if op == "mad" and dtype == "Int64":
-            # GH-33036, GH#33600
-            raise NotImplementedError
         values = np.random.randn(100000, 4)
         if dtype == "Int64":
             values = values.astype(int)

doc/redirects.csv

@@ -186,7 +186,6 @@ generated/pandas.core.groupby.DataFrameGroupBy.filter,../reference/api/pandas.co
 generated/pandas.core.groupby.DataFrameGroupBy.hist,../reference/api/pandas.core.groupby.DataFrameGroupBy.hist
 generated/pandas.core.groupby.DataFrameGroupBy.idxmax,../reference/api/pandas.core.groupby.DataFrameGroupBy.idxmax
 generated/pandas.core.groupby.DataFrameGroupBy.idxmin,../reference/api/pandas.core.groupby.DataFrameGroupBy.idxmin
-generated/pandas.core.groupby.DataFrameGroupBy.mad,../reference/api/pandas.core.groupby.DataFrameGroupBy.mad
 generated/pandas.core.groupby.DataFrameGroupBy.pct_change,../reference/api/pandas.core.groupby.DataFrameGroupBy.pct_change
 generated/pandas.core.groupby.DataFrameGroupBy.plot,../reference/api/pandas.core.groupby.DataFrameGroupBy.plot
 generated/pandas.core.groupby.DataFrameGroupBy.quantile,../reference/api/pandas.core.groupby.DataFrameGroupBy.quantile
@@ -196,7 +195,6 @@ generated/pandas.core.groupby.DataFrameGroupBy.shift,../reference/api/pandas.cor
 generated/pandas.core.groupby.DataFrameGroupBy.size,../reference/api/pandas.core.groupby.DataFrameGroupBy.size
 generated/pandas.core.groupby.DataFrameGroupBy.skew,../reference/api/pandas.core.groupby.DataFrameGroupBy.skew
 generated/pandas.core.groupby.DataFrameGroupBy.take,../reference/api/pandas.core.groupby.DataFrameGroupBy.take
-generated/pandas.core.groupby.DataFrameGroupBy.tshift,../reference/api/pandas.core.groupby.DataFrameGroupBy.tshift
 generated/pandas.core.groupby.GroupBy.agg,../reference/api/pandas.core.groupby.GroupBy.agg
 generated/pandas.core.groupby.GroupBy.aggregate,../reference/api/pandas.core.groupby.GroupBy.aggregate
 generated/pandas.core.groupby.GroupBy.all,../reference/api/pandas.core.groupby.GroupBy.all
@@ -415,7 +413,6 @@ generated/pandas.DataFrame.le,../reference/api/pandas.DataFrame.le
 generated/pandas.DataFrame.loc,../reference/api/pandas.DataFrame.loc
 generated/pandas.DataFrame.lookup,../reference/api/pandas.DataFrame.lookup
 generated/pandas.DataFrame.lt,../reference/api/pandas.DataFrame.lt
-generated/pandas.DataFrame.mad,../reference/api/pandas.DataFrame.mad
 generated/pandas.DataFrame.mask,../reference/api/pandas.DataFrame.mask
 generated/pandas.DataFrame.max,../reference/api/pandas.DataFrame.max
 generated/pandas.DataFrame.mean,../reference/api/pandas.DataFrame.mean
@@ -528,7 +525,6 @@ generated/pandas.DataFrame.transform,../reference/api/pandas.DataFrame.transform
 generated/pandas.DataFrame.transpose,../reference/api/pandas.DataFrame.transpose
 generated/pandas.DataFrame.truediv,../reference/api/pandas.DataFrame.truediv
 generated/pandas.DataFrame.truncate,../reference/api/pandas.DataFrame.truncate
-generated/pandas.DataFrame.tshift,../reference/api/pandas.DataFrame.tshift
 generated/pandas.DataFrame.tz_convert,../reference/api/pandas.DataFrame.tz_convert
 generated/pandas.DataFrame.tz_localize,../reference/api/pandas.DataFrame.tz_localize
 generated/pandas.DataFrame.unstack,../reference/api/pandas.DataFrame.unstack
@@ -1097,7 +1093,6 @@ generated/pandas.Series.last_valid_index,../reference/api/pandas.Series.last_val
 generated/pandas.Series.le,../reference/api/pandas.Series.le
 generated/pandas.Series.loc,../reference/api/pandas.Series.loc
 generated/pandas.Series.lt,../reference/api/pandas.Series.lt
-generated/pandas.Series.mad,../reference/api/pandas.Series.mad
 generated/pandas.Series.map,../reference/api/pandas.Series.map
 generated/pandas.Series.mask,../reference/api/pandas.Series.mask
 generated/pandas.Series.max,../reference/api/pandas.Series.max
@@ -1266,7 +1261,6 @@ generated/pandas.Series.transform,../reference/api/pandas.Series.transform
 generated/pandas.Series.transpose,../reference/api/pandas.Series.transpose
 generated/pandas.Series.truediv,../reference/api/pandas.Series.truediv
 generated/pandas.Series.truncate,../reference/api/pandas.Series.truncate
-generated/pandas.Series.tshift,../reference/api/pandas.Series.tshift
 generated/pandas.Series.tz_convert,../reference/api/pandas.Series.tz_convert
 generated/pandas.Series.tz_localize,../reference/api/pandas.Series.tz_localize
 generated/pandas.Series.unique,../reference/api/pandas.Series.unique

doc/source/reference/frame.rst

@@ -151,7 +151,6 @@ Computations / descriptive stats
    DataFrame.eval
    DataFrame.kurt
    DataFrame.kurtosis
-   DataFrame.mad
    DataFrame.max
    DataFrame.mean
    DataFrame.median
@@ -268,7 +267,6 @@ Time Series-related
    DataFrame.asof
    DataFrame.shift
    DataFrame.slice_shift
-   DataFrame.tshift
    DataFrame.first_valid_index
    DataFrame.last_valid_index
    DataFrame.resample

doc/source/reference/groupby.rst

@@ -84,7 +84,6 @@ Function application
    DataFrameGroupBy.idxmax
    DataFrameGroupBy.idxmin
    DataFrameGroupBy.last
-   DataFrameGroupBy.mad
    DataFrameGroupBy.max
    DataFrameGroupBy.mean
    DataFrameGroupBy.median
@@ -108,7 +107,6 @@ Function application
    DataFrameGroupBy.var
    DataFrameGroupBy.tail
    DataFrameGroupBy.take
-   DataFrameGroupBy.tshift
    DataFrameGroupBy.value_counts
 
 ``SeriesGroupBy`` computations / descriptive stats
@@ -138,7 +136,6 @@ Function application
    SeriesGroupBy.idxmin
    SeriesGroupBy.is_monotonic_increasing
    SeriesGroupBy.is_monotonic_decreasing
-   SeriesGroupBy.mad
    SeriesGroupBy.max
    SeriesGroupBy.mean
    SeriesGroupBy.median
@@ -165,7 +162,6 @@ Function application
    SeriesGroupBy.var
    SeriesGroupBy.tail
    SeriesGroupBy.take
-   SeriesGroupBy.tshift
    SeriesGroupBy.value_counts
 
 Plotting and visualization

doc/source/reference/series.rst

@@ -148,7 +148,6 @@ Computations / descriptive stats
    Series.diff
    Series.factorize
    Series.kurt
-   Series.mad
    Series.max
    Series.mean
    Series.median
@@ -269,7 +268,6 @@ Time Series-related
    Series.tz_localize
    Series.at_time
    Series.between_time
-   Series.tshift
    Series.slice_shift
 
 Accessors

doc/source/user_guide/basics.rst

@@ -556,7 +556,6 @@ optional ``level`` parameter which applies only if the object has a
     ``count``, Number of non-NA observations
     ``sum``, Sum of values
     ``mean``, Mean of values
-    ``mad``, Mean absolute deviation
     ``median``, Arithmetic median of values
     ``min``, Minimum
     ``max``, Maximum

doc/source/whatsnew/v2.0.0.rst

@@ -200,7 +200,8 @@ Removal of prior version deprecations/changes
 - Removed ``pandas.SparseSeries`` and ``pandas.SparseDataFrame`` (:issue:`30642`)
 - Enforced disallowing a string column label into ``times`` in :meth:`DataFrame.ewm` (:issue:`43265`)
 - Enforced :meth:`Rolling.count` with ``min_periods=None`` to default to the size of the window (:issue:`31302`)
--
+- Removed the deprecated method ``mad`` from pandas classes (:issue:`11787`)
+- Removed the deprecated method ``tshift`` from pandas classes (:issue:`11631`)
 
 .. ---------------------------------------------------------------------------
 .. _whatsnew_200.performance:

pandas/core/apply.py

@@ -557,7 +557,7 @@ def apply_str(self) -> DataFrame | Series:
             sig = inspect.getfullargspec(func)
             arg_names = (*sig.args, *sig.kwonlyargs)
             if self.axis != 0 and (
-                "axis" not in arg_names or f in ("corrwith", "mad", "skew")
+                "axis" not in arg_names or f in ("corrwith", "skew")
             ):
                 raise ValueError(f"Operation {f} does not support axis=1")
             elif "axis" in arg_names:

pandas/core/generic.py

@@ -250,7 +250,7 @@ class NDFrame(PandasObject, indexing.IndexingMixin):
     _internal_names_set: set[str] = set(_internal_names)
     _accessors: set[str] = set()
     _hidden_attrs: frozenset[str] = frozenset(
-        ["_AXIS_NAMES", "_AXIS_NUMBERS", "get_values", "tshift"]
+        ["_AXIS_NAMES", "_AXIS_NUMBERS", "get_values"]
     )
     _metadata: list[str] = []
     _is_copy: weakref.ReferenceType[NDFrame] | None = None
@@ -10122,8 +10122,6 @@ def shift(
         Index.shift : Shift values of Index.
         DatetimeIndex.shift : Shift values of DatetimeIndex.
         PeriodIndex.shift : Shift values of PeriodIndex.
-        tshift : Shift the time index, using the index's frequency if
-            available.
 
         Examples
         --------
@@ -10272,49 +10270,6 @@ def slice_shift(self: NDFrameT, periods: int = 1, axis: Axis = 0) -> NDFrameT:
         new_obj = new_obj.set_axis(shifted_axis, axis=axis, copy=False)
         return new_obj.__finalize__(self, method="slice_shift")
 
-    @final
-    def tshift(self: NDFrameT, periods: int = 1, freq=None, axis: Axis = 0) -> NDFrameT:
-        """
-        Shift the time index, using the index's frequency if available.
-
-        .. deprecated:: 1.1.0
-            Use `shift` instead.
-
-        Parameters
-        ----------
-        periods : int
-            Number of periods to move, can be positive or negative.
-        freq : DateOffset, timedelta, or str, default None
-            Increment to use from the tseries module
-            or time rule expressed as a string (e.g. 'EOM').
-        axis : {0 or ‘index’, 1 or ‘columns’, None}, default 0
-            Corresponds to the axis that contains the Index.
-            For `Series` this parameter is unused and defaults to 0.
-
-        Returns
-        -------
-        shifted : Series/DataFrame
-
-        Notes
-        -----
-        If freq is not specified then tries to use the freq or inferred_freq
-        attributes of the index. If neither of those attributes exist, a
-        ValueError is thrown
-        """
-        warnings.warn(
-            (
-                "tshift is deprecated and will be removed in a future version. "
-                "Please use shift instead."
-            ),
-            FutureWarning,
-            stacklevel=find_stack_level(),
-        )
-
-        if freq is None:
-            freq = "infer"
-
-        return self.shift(periods, freq, axis)
-
     def truncate(
         self: NDFrameT,
         before=None,
@@ -11544,70 +11499,6 @@ def prod(
 
     product = prod
 
-    def mad(
-        self,
-        axis: Axis | None = None,
-        skipna: bool_t = True,
-        level: Level | None = None,
-    ) -> Series | float:
-        """
-        {desc}
-
-        .. deprecated:: 1.5.0
-            mad is deprecated.
-
-        Parameters
-        ----------
-        axis : {axis_descr}
-            Axis for the function to be applied on.
-            For `Series` this parameter is unused and defaults to 0.
-        skipna : bool, default True
-            Exclude NA/null values when computing the result.
-        level : int or level name, default None
-            If the axis is a MultiIndex (hierarchical), count along a
-            particular level, collapsing into a {name1}.
-
-        Returns
-        -------
-        {name1} or {name2} (if level specified)\
-        {see_also}\
-        {examples}
-        """
-        msg = (
-            "The 'mad' method is deprecated and will be removed in a future version. "
-            "To compute the same result, you may do `(df - df.mean()).abs().mean()`."
-        )
-        warnings.warn(msg, FutureWarning, stacklevel=find_stack_level())
-
-        if not is_bool(skipna):
-            warnings.warn(
-                "Passing None for skipna is deprecated and will raise in a future"
-                "version. Pass True instead. Only boolean values will be allowed "
-                "in the future.",
-                FutureWarning,
-                stacklevel=find_stack_level(),
-            )
-            skipna = True
-        if axis is None:
-            axis = self._stat_axis_number
-        if level is not None:
-            warnings.warn(
-                "Using the level keyword in DataFrame and Series aggregations is "
-                "deprecated and will be removed in a future version. Use groupby "
-                "instead. df.mad(level=1) should use df.groupby(level=1).mad()",
-                FutureWarning,
-                stacklevel=find_stack_level(),
-            )
-            return self._agg_by_level("mad", axis=axis, level=level, skipna=skipna)
-
-        data = self._get_numeric_data()
-        if axis == 0:
-            # error: Unsupported operand types for - ("NDFrame" and "float")
-            demeaned = data - data.mean(axis=0)  # type: ignore[operator]
-        else:
-            demeaned = data.sub(data.mean(axis=1), axis=0)
-        return np.abs(demeaned).mean(axis=axis, skipna=skipna)
-
     @classmethod
     def _add_numeric_operations(cls) -> None:
         """
@@ -11664,21 +11555,6 @@ def all(
 
         setattr(cls, "all", all)
 
-        @doc(
-            NDFrame.mad.__doc__,
-            desc="Return the mean absolute deviation of the values "
-            "over the requested axis.",
-            name1=name1,
-            name2=name2,
-            axis_descr=axis_descr,
-            see_also="",
-            examples="",
-        )
-        def mad(self, axis: Axis | None = None, skipna: bool_t = True, level=None):
-            return NDFrame.mad(self, axis, skipna, level)
-
-        setattr(cls, "mad", mad)
-
         @doc(
             _num_ddof_doc,
             desc="Return unbiased standard error of the mean over requested "

pandas/core/groupby/base.py

@@ -36,7 +36,6 @@ class OutputKey:
         "idxmax",
         "idxmin",
         "last",
-        "mad",
         "max",
         "mean",
         "median",
@@ -86,7 +85,6 @@ def maybe_normalize_deprecated_kernels(kernel) -> Literal["bfill", "ffill"]:
         "pct_change",
         "rank",
         "shift",
-        "tshift",
     ]
 )