DOC: add get_dummies dtype argument description to reshaping.rst

Author: Scorpil

doc/source/reshaping.rst

@@ -240,7 +240,7 @@ values will be set to ``NaN``.
    df3
    df3.unstack()
 
-.. versionadded: 0.18.0
+.. versionadded:: 0.18.0
 
 Alternatively, unstack takes an optional ``fill_value`` argument, for specifying
 the value of missing data.
@@ -634,6 +634,17 @@ When a column contains only one level, it will be omitted in the result.
 
     pd.get_dummies(df, drop_first=True)
 
+By default new columns will have ``np.uint8`` dtype. To choose another dtype use ``dtype`` argument:
+
+.. ipython:: python
+
+    df = pd.DataFrame({'A': list('abc'), 'B': [1.1, 2.2, 3.3]})
+
+    pd.get_dummies(df, dtype=bool).dtypes
+
+.. versionadded:: 0.22.0
+
+
 .. _reshaping.factorize:
 
 Factorizing values

pandas/core/reshape/reshape.py

@@ -729,7 +729,7 @@ def get_dummies(data, prefix=None, prefix_sep='_', dummy_na=False,
         .. versionadded:: 0.18.0
 
     dtype : dtype, default np.uint8
-        Data type to force on a new columns. Only a single dtype is allowed.
+        Data type for new columns. Only a single dtype is allowed.
 
         .. versionadded:: 0.22.0