DEPR: deprecate get_ftype_counts (GH18243)

doc/source/whatsnew/v0.23.0.txt

@@ -741,6 +741,7 @@ Deprecations
 
 - ``pandas.tseries.plotting.tsplot`` is deprecated. Use :func:`Series.plot` instead (:issue:`18627`)
 - ``Index.summary()`` is deprecated and will be removed in a future version (:issue:`18217`)
+- ``NDFrame.get_ftype_counts()`` is deprecated and will be removed in a future version (:issue:`18243`)
 
 .. _whatsnew_0230.prior_deprecations:
 

pandas/core/generic.py

@@ -4677,6 +4677,8 @@ def get_ftype_counts(self):
         """
         Return counts of unique ftypes in this object.
 
+        .. deprecated:: 0.23.0
+
         This is useful for SparseDataFrame or for DataFrames containing
         sparse arrays.
 
@@ -4707,6 +4709,10 @@ def get_ftype_counts(self):
         object:dense     1
         dtype: int64
         """
+        warnings.warn("get_ftype_counts is deprecated and will "
+                      "be removed in a future version",
+                      FutureWarning, stacklevel=2)
+
         from pandas import Series
         return Series(self._data.get_ftype_counts())
 

pandas/core/indexes/base.py

@@ -3396,11 +3396,8 @@ def map(self, mapper, na_action=None):
 
     def isin(self, values, level=None):
         """
-        Return a boolean array where the index values are in `values`.
-
         Compute boolean array of whether each index value is found in the
-        passed set of values. The length of the returned boolean array matches
-        the length of the index.
+        passed set of values.
 
         Parameters
         ----------
@@ -3409,74 +3406,23 @@ def isin(self, values, level=None):
 
             .. versionadded:: 0.18.1
 
-               Support for values as a set.
+            Support for values as a set
 
         level : str or int, optional
             Name or position of the index level to use (if the index is a
-            `MultiIndex`).
-
-        Returns
-        -------
-        is_contained : ndarray
-            NumPy array of boolean values.
-
-        See also
-        --------
-        Series.isin : Same for Series.
-        DataFrame.isin : Same method for DataFrames.
+            MultiIndex).
 
         Notes
         -----
-        In the case of `MultiIndex` you must either specify `values` as a
-        list-like object containing tuples that are the same length as the
-        number of levels, or specify `level`. Otherwise it will raise a
-        ``ValueError``.
-
         If `level` is specified:
 
         - if it is the name of one *and only one* index level, use that level;
         - otherwise it should be a number indicating level position.
 
-        Examples
-        --------
-        >>> idx = pd.Index([1,2,3])
-        >>> idx
-        Int64Index([1, 2, 3], dtype='int64')
-
-        Check whether each index value in a list of values.
-        >>> idx.isin([1, 4])
-        array([ True, False, False])
-
-        >>> midx = pd.MultiIndex.from_arrays([[1,2,3],
-        ...                                  ['red', 'blue', 'green']],
-        ...                                  names=('number', 'color'))
-        >>> midx
-        MultiIndex(levels=[[1, 2, 3], ['blue', 'green', 'red']],
-                   labels=[[0, 1, 2], [2, 0, 1]],
-                   names=['number', 'color'])
-
-        Check whether the strings in the 'color' level of the MultiIndex
-        are in a list of colors.
-
-        >>> midx.isin(['red', 'orange', 'yellow'], level='color')
-        array([ True, False, False])
-
-        To check across the levels of a MultiIndex, pass a list of tuples:
-
-        >>> midx.isin([(1, 'red'), (3, 'red')])
-        array([ True, False, False])
-
-        For a DatetimeIndex, string values in `values` are converted to
-        Timestamps.
-
-        >>> dates = ['2000-03-11', '2000-03-12', '2000-03-13']
-        >>> dti = pd.to_datetime(dates)
-        >>> dti
-        DatetimeIndex(['2000-03-11', '2000-03-12', '2000-03-13'],
-        dtype='datetime64[ns]', freq=None)
+        Returns
+        -------
+        is_contained : ndarray (boolean dtype)
 
-        >>> dti.isin(['2000-03-11'])
-        array([ True, False, False])
         """
         if level is not None:
             self._validate_index_level(level)

pandas/tests/series/test_dtypes.py

@@ -64,8 +64,10 @@ def test_dtype(self):
         assert self.ts.ftypes == 'float64:dense'
         tm.assert_series_equal(self.ts.get_dtype_counts(),
                                Series(1, ['float64']))
-        tm.assert_series_equal(self.ts.get_ftype_counts(),
-                               Series(1, ['float64:dense']))
+        # GH18243 - Assert .get_ftype_counts is deprecated
+        with tm.assert_produces_warning(FutureWarning):
+            tm.assert_series_equal(self.ts.get_ftype_counts(),
+                                   Series(1, ['float64:dense']))
 
     @pytest.mark.parametrize("value", [np.nan, np.inf])
     @pytest.mark.parametrize("dtype", [np.int32, np.int64])