ENH: astype() allows col label -> dtype mapping as arg

closes #7271
closes #13375

Author: StephenKappel

doc/source/whatsnew/v0.19.0.txt

@@ -331,6 +331,8 @@ API changes
 - Passing ``Period`` with multiple frequencies to normal ``Index`` now returns ``Index`` with ``object`` dtype (:issue:`13664`)
 - ``PeriodIndex.fillna`` with ``Period`` has different freq now coerces to ``object`` dtype (:issue:`13664`)
 - More informative exceptions are passed through the csv parser. The exception type would now be the original exception type instead of ``CParserError``. (:issue:`13652`)
+- ``astype()`` will now accept a dict of column name to data types mapping as the ``dtype`` argument. (:issue:`12086`)
+
 
 .. _whatsnew_0190.api.tolist:
 

pandas/core/generic.py

@@ -1,4 +1,5 @@
 # pylint: disable=W0231,E1101
+import collections
 import warnings
 import operator
 import weakref
@@ -161,7 +162,7 @@ def _init_mgr(self, mgr, axes=None, dtype=None, copy=False):
 
     @property
     def _constructor(self):
-        """Used when a manipulation result has the same dimesions as the
+        """Used when a manipulation result has the same dimensions as the
         original.
         """
         raise AbstractMethodError(self)
@@ -3000,18 +3001,48 @@ def astype(self, dtype, copy=True, raise_on_error=True, **kwargs):
 
         Parameters
         ----------
-        dtype : numpy.dtype or Python type
+        dtype : data type, or dict of column name -> data type
+            Use a numpy.dtype or Python type to cast entire pandas object to
+            the same type. Alternatively, use {col: dtype, ...}, where col is a
+            column label and dtype is a numpy.dtype or Python type to cast one
+            or more of the DataFrame's columns to column-specific types.
         raise_on_error : raise on invalid input
         kwargs : keyword arguments to pass on to the constructor
 
         Returns
         -------
         casted : type of caller
         """
+        if isinstance(dtype, collections.Mapping):
+            if self.ndim == 1:  # i.e. Series
+                if len(dtype) > 1 or list(dtype.keys())[0] != self.name:
+                    raise KeyError('Only the Series name can be used for '
+                                   'the key in Series dtype mappings.')
+                new_type = list(dtype.values())[0]
+                return self.astype(new_type, copy, raise_on_error, **kwargs)
+            elif self.ndim > 2:
+                raise NotImplementedError(
+                    'astype() only accepts a dtype arg of type dict when '
+                    'invoked on Series and DataFrames. A single dtype must be '
+                    'specified when invoked on a Panel.'
+                )
+            for col_name in dtype.keys():
+                if col_name not in self:
+                    raise KeyError('Only a column name can be used for the '
+                                   'key in a dtype mappings argument.')
+            from pandas import concat
+            results = []
+            for col_name, col in self.iteritems():
+                if col_name in dtype:
+                    results.append(col.astype(dtype[col_name], copy=copy))
+                else:
+                    results.append(results.append(col.copy() if copy else col))
+            return concat(results, axis=1, copy=False)
 
-        mgr = self._data.astype(dtype=dtype, copy=copy,
-                                raise_on_error=raise_on_error, **kwargs)
-        return self._constructor(mgr).__finalize__(self)
+        # else, only a single dtype is given
+        new_data = self._data.astype(dtype=dtype, copy=copy,
+                                     raise_on_error=raise_on_error, **kwargs)
+        return self._constructor(new_data).__finalize__(self)
 
     def copy(self, deep=True):
         """

pandas/tests/frame/test_dtypes.py

@@ -5,7 +5,7 @@
 
 import numpy as np
 from pandas import (DataFrame, Series, date_range, Timedelta, Timestamp,
-                    compat, option_context)
+                    compat, concat, option_context)
 from pandas.compat import u
 from pandas.types.dtypes import DatetimeTZDtype
 from pandas.tests.frame.common import TestData
@@ -396,6 +396,69 @@ def test_astype_str(self):
             expected = DataFrame(['1.12345678901'])
             assert_frame_equal(result, expected)
 
+    def test_astype_dict(self):
+        # GH7271
+        a = Series(date_range('2010-01-04', periods=5))
+        b = Series(range(5))
+        c = Series([0.0, 0.2, 0.4, 0.6, 0.8])
+        d = Series(['1.0', '2', '3.14', '4', '5.4'])
+        df = DataFrame({'a': a, 'b': b, 'c': c, 'd': d})
+        original = df.copy(deep=True)
+
+        # change type of a subset of columns
+        result = df.astype({'b': 'str', 'd': 'float32'})
+        expected = DataFrame({
+            'a': a,
+            'b': Series(['0', '1', '2', '3', '4']),
+            'c': c,
+            'd': Series([1.0, 2.0, 3.14, 4.0, 5.4], dtype='float32')})
+        assert_frame_equal(result, expected)
+        assert_frame_equal(df, original)
+
+        result = df.astype({'b': np.float32, 'c': 'float32', 'd': np.float64})
+        expected = DataFrame({
+            'a': a,
+            'b': Series([0.0, 1.0, 2.0, 3.0, 4.0], dtype='float32'),
+            'c': Series([0.0, 0.2, 0.4, 0.6, 0.8], dtype='float32'),
+            'd': Series([1.0, 2.0, 3.14, 4.0, 5.4], dtype='float64')})
+        assert_frame_equal(result, expected)
+        assert_frame_equal(df, original)
+
+        # change all columns
+        assert_frame_equal(df.astype({'a': str, 'b': str, 'c': str, 'd': str}),
+                           df.astype(str))
+        assert_frame_equal(df, original)
+
+        # error should be raised when using something other than column labels
+        # in the keys of the dtype dict
+        self.assertRaises(KeyError, df.astype, {'b': str, 2: str})
+        self.assertRaises(KeyError, df.astype, {'e': str})
+        assert_frame_equal(df, original)
+
+        # if the dtypes provided are the same as the original dtypes, the
+        # resulting DataFrame should be the same as the original DataFrame
+        equiv = df.astype({col: df[col].dtype for col in df.columns})
+        assert_frame_equal(df, equiv)
+        assert_frame_equal(df, original)
+
+    def test_astype_duplicate_col(self):
+        a1 = Series([1, 2, 3, 4, 5], name='a')
+        b = Series([0.1, 0.2, 0.4, 0.6, 0.8], name='b')
+        a2 = Series([0, 1, 2, 3, 4], name='a')
+        df = concat([a1, b, a2], axis=1)
+
+        result = df.astype(str)
+        a1_str = Series(['1', '2', '3', '4', '5'], dtype='str', name='a')
+        b_str = Series(['0.1', '0.2', '0.4', '0.6', '0.8'], dtype=str,
+                       name='b')
+        a2_str = Series(['0', '1', '2', '3', '4'], dtype='str', name='a')
+        expected = concat([a1_str, b_str, a2_str], axis=1)
+        assert_frame_equal(result, expected)
+
+        result = df.astype({'a': 'str'})
+        expected = concat([a1_str, b, a2_str], axis=1)
+        assert_frame_equal(result, expected)
+
     def test_timedeltas(self):
         df = DataFrame(dict(A=Series(date_range('2012-1-1', periods=3,
                                                 freq='D')),

pandas/tests/series/test_dtypes.py

@@ -133,6 +133,22 @@ def test_astype_unicode(self):
             reload(sys)  # noqa
             sys.setdefaultencoding(former_encoding)
 
+    def test_astype_dict(self):
+        # GH7271
+        s = Series(range(0, 10, 2), name='abc')
+
+        result = s.astype({'abc': str})
+        expected = Series(['0', '2', '4', '6', '8'], name='abc')
+        assert_series_equal(result, expected)
+
+        result = s.astype({'abc': 'float64'})
+        expected = Series([0.0, 2.0, 4.0, 6.0, 8.0], dtype='float64',
+                          name='abc')
+        assert_series_equal(result, expected)
+
+        self.assertRaises(KeyError, s.astype, {'abc': str, 'def': str})
+        self.assertRaises(KeyError, s.astype, {0: str})
+
     def test_complexx(self):
         # GH4819
         # complex access for ndarray compat

pandas/tests/test_panel.py

@@ -1231,6 +1231,18 @@ def test_dtypes(self):
         expected = Series(np.dtype('float64'), index=self.panel.items)
         assert_series_equal(result, expected)
 
+    def test_astype(self):
+        # GH7271
+        data = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]])
+        panel = Panel(data, ['a', 'b'], ['c', 'd'], ['e', 'f'])
+
+        str_data = np.array([[['1', '2'], ['3', '4']],
+                             [['5', '6'], ['7', '8']]])
+        expected = Panel(str_data, ['a', 'b'], ['c', 'd'], ['e', 'f'])
+        assert_panel_equal(panel.astype(str), expected)
+
+        self.assertRaises(NotImplementedError, panel.astype, {0: str})
+
     def test_apply(self):
         # GH1148