Merge pull request pandas-dev#11809 from Dr-Irv/rounding

ENH: Using built-in round on a series pandas-dev#11763

Author: jreback

doc/source/whatsnew/v0.18.0.txt

@@ -34,6 +34,8 @@ Other enhancements
 - Handle truncated floats in SAS xport files (:issue:`11713`)
 - Added option to hide index in ``Series.to_string`` (:issue:`11729`)
 - ``read_excel`` now supports s3 urls of the format ``s3://bucketname/filename`` (:issue:`11447`)
+- A simple version of ``Panel.round()`` is now implemented (:issue:`11763`)
+- For Python 3.x, ``round(DataFrame)``, ``round(Series)``, ``round(Panel)`` will work (:issue:`11763`)
 
 .. _whatsnew_0180.enhancements.rounding:
 
@@ -90,6 +92,8 @@ In addition, ``.round()`` will be available thru the ``.dt`` accessor of ``Serie
 Backwards incompatible API changes
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
+- The parameter ``out`` has been removed from the ``Series.round()`` method. (:issue:`11763`) 
+
 Bug in QuarterBegin with n=0
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 

pandas/core/frame.py

@@ -4376,13 +4376,17 @@ def round(self, decimals=0, out=None):
         Returns
         -------
         DataFrame object
+        
+        See Also
+        --------
+        numpy.around
         """
         from pandas.tools.merge import concat
 
         def _dict_round(df, decimals):
             for col, vals in df.iteritems():
                 try:
-                    yield np.round(vals, decimals[col])
+                    yield vals.round(decimals[col])
                 except KeyError:
                     yield vals
 
@@ -4392,8 +4396,8 @@ def _dict_round(df, decimals):
                     raise ValueError("Index of decimals must be unique")
             new_cols = [col for col in _dict_round(self, decimals)]
         elif com.is_integer(decimals):
-            # Dispatch to numpy.round
-            new_cols = [np.round(v, decimals) for _, v in self.iteritems()]
+            # Dispatch to Series.round
+            new_cols = [v.round(decimals) for _, v in self.iteritems()]
         else:
             raise TypeError("decimals must be an integer, a dict-like or a Series")
 

pandas/core/generic.py

@@ -749,7 +749,10 @@ def bool(self):
 
     def __abs__(self):
         return self.abs()
-
+    
+    def __round__(self,decimals=0):
+        return self.round(decimals)
+ 
     #----------------------------------------------------------------------
     # Array Interface
 

pandas/core/panel.py

@@ -624,6 +624,33 @@ def head(self, n=5):
 
     def tail(self, n=5):
         raise NotImplementedError
+    
+    def round(self, decimals=0):
+        """
+        Round each value in Panel to a specified number of decimal places.
+        
+        .. versionadded:: 0.18.0
+        
+        Parameters
+        ----------
+        decimals : int
+            Number of decimal places to round to (default: 0). 
+            If decimals is negative, it specifies the number of 
+            positions to the left of the decimal point.
+                
+        Returns
+        -------
+        Panel object
+        
+        See Also
+        --------
+        numpy.around
+        """
+        if com.is_integer(decimals):
+            result = np.apply_along_axis(np.round, 0, self.values)
+            return self._wrap_result(result, axis=0)
+        raise TypeError("decimals must be an integer")
+        
 
     def _needs_reindex_multi(self, axes, method, level):
         """ don't allow a multi reindex on Panel or above ndim """

pandas/core/series.py

@@ -1235,15 +1235,29 @@ def idxmax(self, axis=None, out=None, skipna=True):
     argmin = idxmin
     argmax = idxmax
 
-    @Appender(np.ndarray.round.__doc__)
-    def round(self, decimals=0, out=None):
+    def round(self, decimals=0):
         """
+        Round each value in a Series to the given number of decimals.
+        
+        Parameters
+        ----------
+        decimals : int
+            Number of decimal places to round to (default: 0). 
+            If decimals is negative, it specifies the number of 
+            positions to the left of the decimal point.
+        
+        Returns
+        -------
+        Series object
+        
+        See Also
+        --------
+        numpy.around
 
         """
-        result = _values_from_object(self).round(decimals, out=out)
-        if out is None:
-            result = self._constructor(result,
-                                       index=self.index).__finalize__(self)
+        result = _values_from_object(self).round(decimals)
+        result = self._constructor(result,
+                                   index=self.index).__finalize__(self)
 
         return result
 

pandas/tests/test_format.py

@@ -1,4 +1,4 @@
-# -*- coding: utf-8 -*-
+# -*- coding: utf-8 -*-
 from __future__ import print_function
 from distutils.version import LooseVersion
 import re
@@ -2969,128 +2969,6 @@ def test_to_csv_engine_kw_deprecation(self):
             df = DataFrame({'col1' : [1], 'col2' : ['a'], 'col3' : [10.1] })
             df.to_csv(engine='python')
 
-    def test_round_dataframe(self):
-
-        # GH 2665
-
-        # Test that rounding an empty DataFrame does nothing
-        df = DataFrame()
-        tm.assert_frame_equal(df, df.round())
-
-        # Here's the test frame we'll be working with
-        df = DataFrame(
-            {'col1': [1.123, 2.123, 3.123], 'col2': [1.234, 2.234, 3.234]})
-
-        # Default round to integer (i.e. decimals=0)
-        expected_rounded = DataFrame(
-            {'col1': [1., 2., 3.], 'col2': [1., 2., 3.]})
-        tm.assert_frame_equal(df.round(), expected_rounded)
-
-        # Round with an integer
-        decimals = 2
-        expected_rounded = DataFrame(
-            {'col1': [1.12, 2.12, 3.12], 'col2': [1.23, 2.23, 3.23]})
-        tm.assert_frame_equal(df.round(decimals), expected_rounded)
-
-        # This should also work with np.round (since np.round dispatches to
-        # df.round)
-        tm.assert_frame_equal(np.round(df, decimals), expected_rounded)
-
-        # Round with a list
-        round_list = [1, 2]
-        with self.assertRaises(TypeError):
-            df.round(round_list)
-
-        # Round with a dictionary
-        expected_rounded = DataFrame(
-            {'col1': [1.1, 2.1, 3.1], 'col2': [1.23, 2.23, 3.23]})
-        round_dict = {'col1': 1, 'col2': 2}
-        tm.assert_frame_equal(df.round(round_dict), expected_rounded)
-
-        # Incomplete dict
-        expected_partially_rounded = DataFrame(
-            {'col1': [1.123, 2.123, 3.123], 'col2': [1.2, 2.2, 3.2]})
-        partial_round_dict = {'col2': 1}
-        tm.assert_frame_equal(
-            df.round(partial_round_dict), expected_partially_rounded)
-
-        # Dict with unknown elements
-        wrong_round_dict = {'col3': 2, 'col2': 1}
-        tm.assert_frame_equal(
-            df.round(wrong_round_dict), expected_partially_rounded)
-
-        # float input to `decimals`
-        non_int_round_dict = {'col1': 1, 'col2': 0.5}
-        if sys.version < LooseVersion('2.7'):
-            # np.round([1.123, 2.123], 0.5) is only a warning in Python 2.6
-            with self.assert_produces_warning(DeprecationWarning, check_stacklevel=False):
-                df.round(non_int_round_dict)
-        else:
-            with self.assertRaises(TypeError):
-                df.round(non_int_round_dict)
-
-        # String input
-        non_int_round_dict = {'col1': 1, 'col2': 'foo'}
-        with self.assertRaises(TypeError):
-            df.round(non_int_round_dict)
-
-        non_int_round_Series = Series(non_int_round_dict)
-        with self.assertRaises(TypeError):
-            df.round(non_int_round_Series)
-
-        # List input
-        non_int_round_dict = {'col1': 1, 'col2': [1, 2]}
-        with self.assertRaises(TypeError):
-            df.round(non_int_round_dict)
-
-        non_int_round_Series = Series(non_int_round_dict)
-        with self.assertRaises(TypeError):
-            df.round(non_int_round_Series)
-
-        # Non integer Series inputs
-        non_int_round_Series = Series(non_int_round_dict)
-        with self.assertRaises(TypeError):
-            df.round(non_int_round_Series)
-
-        non_int_round_Series = Series(non_int_round_dict)
-        with self.assertRaises(TypeError):
-            df.round(non_int_round_Series)
-
-        # Negative numbers
-        negative_round_dict = {'col1': -1, 'col2': -2}
-        big_df = df * 100
-        expected_neg_rounded = DataFrame(
-                {'col1':[110., 210, 310], 'col2':[100., 200, 300]})
-        tm.assert_frame_equal(
-            big_df.round(negative_round_dict), expected_neg_rounded)
-
-        # nan in Series round
-        nan_round_Series = Series({'col1': nan, 'col2':1})
-        expected_nan_round = DataFrame(
-                {'col1': [1.123, 2.123, 3.123], 'col2': [1.2, 2.2, 3.2]})
-        if sys.version < LooseVersion('2.7'):
-            # Rounding with decimal is a ValueError in Python < 2.7
-            with self.assertRaises(ValueError):
-                df.round(nan_round_Series)
-        else:
-            with self.assertRaises(TypeError):
-                df.round(nan_round_Series)
-
-        # Make sure this doesn't break existing Series.round
-        tm.assert_series_equal(df['col1'].round(1), expected_rounded['col1'])
-
-    def test_round_issue(self):
-        # GH11611
-
-        df = pd.DataFrame(np.random.random([3, 3]), columns=['A', 'B', 'C'],
-                          index=['first', 'second', 'third'])
-
-        dfs = pd.concat((df, df), axis=1)
-        rounded = dfs.round()
-        self.assertTrue(rounded.index.equals(dfs.index))
-
-        decimals = pd.Series([1, 0, 2], index=['A', 'B', 'A'])
-        self.assertRaises(ValueError, df.round, decimals)
 
 class TestSeriesFormatting(tm.TestCase):
     _multiprocess_can_split_ = True