DOC: update the dtypes/ftypes docstring (Seoul)

pandas/core/generic.py

@@ -4275,16 +4275,82 @@ def get_ftype_counts(self):
 
     @property
     def dtypes(self):
-        """Return the dtypes in this object."""
+        """
+        Return the dtypes in the DataFrame.
+
+        This returns a Series with the data type of each column.
+        The result's index is the original DataFrame's columns. Columns
+        with mixed types are stored with the ``object`` dtype. See
+        :ref:`the User Guide <basics.dtypes>` for more.
+
+        Returns
+        -------
+        pandas.Series
+            The data type of each column.
+
+        See Also
+        --------
+        pandas.DataFrame.ftypes : dtype and sparsity information.
+
+        Examples
+        --------
+        >>> df = pd.DataFrame({'float': [1.0],
+        ...                    'int': [1],
+        ...                    'datetime': [pd.Timestamp('20180310')],
+        ...                    'string': ['foo']})
+        >>> df.dtypes
+        float              float64
+        int                  int64
+        datetime    datetime64[ns]
+        string              object
+        dtype: object
+        """
         from pandas import Series
         return Series(self._data.get_dtypes(), index=self._info_axis,
                       dtype=np.object_)
 
     @property
     def ftypes(self):
         """
-        Return the ftypes (indication of sparse/dense and dtype)
-        in this object.
+        Return the ftypes (indication of sparse/dense and dtype) in DataFrame.
+
+        This returns a Series with the data type of each column.
+        The result's index is the original DataFrame's columns. Columns
+        with mixed types are stored with the ``object`` dtype.  See
+        :ref:`the User Guide <basics.dtypes>` for more.
+
+        Returns
+        -------
+        pandas.Series
+            The data type and indication of sparse/dense of each column.
+
+        See Also
+        --------
+        pandas.DataFrame.dtypes: Series with just dtype information.
+        pandas.SparseDataFrame : Container for sparse tabular data.
+
+        Notes
+        -----
+        Sparse data should have the same dtypes as its dense representation.
+
+        Examples
+        --------
+        >>> import numpy as np
+        >>> arr = np.random.RandomState(0).randn(100, 4)
+        >>> arr[arr < .8] = np.nan
+        >>> pd.DataFrame(arr).ftypes
+        0    float64:dense
+        1    float64:dense
+        2    float64:dense
+        3    float64:dense
+        dtype: object
+
+        >>> pd.SparseDataFrame(arr).ftypes
+        0    float64:sparse
+        1    float64:sparse
+        2    float64:sparse
+        3    float64:sparse
+        dtype: object
         """
         from pandas import Series
         return Series(self._data.get_ftypes(), index=self._info_axis,