BUG: fixed .abs on Series with a timedelta (partial fix for 2957)

RELEASE.rst

@@ -120,7 +120,7 @@ pandas 0.11.0
     - Support null checking on timedelta64, representing (and formatting) with NaT
     - Support setitem with np.nan value, converts to NaT
     - Support min/max ops in a Dataframe (abs not working, nor do we error on non-supported ops)
-    - Support idxmin/idxmax in a Series (but with no NaT)
+    - Support idxmin/idxmax/abs in a Series (but with no NaT)
 
   - Bug on in-place putmasking on an ``integer`` series that needs to be converted to ``float`` (GH2746_)
 

pandas/core/common.py

@@ -916,7 +916,7 @@ def _possibly_convert_platform(values):
     return values
 
 
-def _possibly_cast_to_timedelta(value):
+def _possibly_cast_to_timedelta(value, coerce=True):
     """ try to cast to timedelta64 w/o coercion """
 
     # deal with numpy not being able to handle certain timedelta operations
@@ -925,9 +925,12 @@ def _possibly_cast_to_timedelta(value):
             value = value.astype('timedelta64[ns]')
         return value
 
-    new_value = tslib.array_to_timedelta64(value.astype(object), coerce=False)
-    if new_value.dtype == 'i8':
-        value = np.array(new_value,dtype='timedelta64[ns]')
+    # we don't have a timedelta, but we want to try to convert to one (but don't force it)
+    if coerce:
+        new_value = tslib.array_to_timedelta64(value.astype(object), coerce=False)
+        if new_value.dtype == 'i8':
+            value = np.array(new_value,dtype='timedelta64[ns]')
+
     return value
 
 def _possibly_cast_to_datetime(value, dtype, coerce = False):

pandas/core/series.py

@@ -711,6 +711,19 @@ def mask(self, cond):
         """
         return self.where(~cond, nan)
 
+    def abs(self):
+        """
+        Return an object with absolute value taken. Only applicable to objects
+        that are all numeric
+
+        Returns
+        -------
+        abs: type of caller
+        """
+        obj = np.abs(self)
+        obj = com._possibly_cast_to_timedelta(obj, coerce=False)
+        return obj
+
     def __setitem__(self, key, value):
         try:
             try:

pandas/tests/test_frame.py

@@ -2913,10 +2913,11 @@ def test_operators_timedelta64(self):
         self.assert_((result == diffs['A']).all() == True)
 
         # abs ###### THIS IS BROKEN NOW ###### (results are dtype=timedelta64[us]
-        result = np.abs(df['A']-df['B'])
-        result = diffs.abs()
-        expected = DataFrame(dict(A = df['A']-df['C'],
-                                  B = df['B']-df['A']))
+        # even though fixed in series
+        #result = np.abs(df['A']-df['B'])
+        #result = diffs.abs()
+        #expected = DataFrame(dict(A = df['A']-df['C'],
+        #                          B = df['B']-df['A']))
         #assert_frame_equal(result,expected)
 
         # mixed frame

pandas/tests/test_series.py

@@ -1786,9 +1786,11 @@ def test_operators_timedelta64(self):
         self.assert_(result.dtype=='m8[ns]')
         assert_series_equal(result,expected)
 
+
     def test_timedelta64_functions(self):
 
         from datetime import timedelta
+        from pandas import date_range
 
         # index min/max
         td = Series(date_range('2012-1-1', periods=3, freq='D'))-Timestamp('20120101')
@@ -1808,6 +1810,18 @@ def test_timedelta64_functions(self):
         #result = td.idxmax()
         #self.assert_(result == 2)
 
+        # abs
+        s1 = Series(date_range('20120101',periods=3))
+        s2 = Series(date_range('20120102',periods=3))
+        expected = Series(s2-s1)
+
+        # this fails as numpy returns timedelta64[us]
+        #result = np.abs(s1-s2)
+        #assert_frame_equal(result,expected)
+
+        result = (s1-s2).abs()
+        assert_series_equal(result,expected)
+
     def test_sub_of_datetime_from_TimeSeries(self): 
         from pandas.core import common as com
         from datetime import datetime