TST: add tests for keeping dtype in Series.update

pandas/tests/series/test_combine_concat.py

@@ -10,10 +10,10 @@
 import pandas as pd
 from pandas import DataFrame, DatetimeIndex, Series, compat, date_range
 import pandas.util.testing as tm
-from pandas.util.testing import assert_series_equal
+from pandas.util.testing import assert_frame_equal, assert_series_equal
 
 
-class TestSeriesCombine():
+class TestSeriesCombine(object):
 
  def test_append(self, datetime_series, string_series, object_series):
  appendedSeries = string_series.append(object_series)
@@ -116,8 +116,32 @@ def test_update(self):
  df = DataFrame([{"a": 1}, {"a": 3, "b": 2}])
  df['c'] = np.nan
 
- # this will fail as long as series is a sub-class of ndarray
- # df['c'].update(Series(['foo'],index=[0])) #####
+ df['c'].update(Series(['foo'], index=[0]))
+ expected = DataFrame([[1, np.nan, 'foo'], [3, 2., np.nan]],
+ columns=['a', 'b', 'c'])
+ assert_frame_equal(df, expected)
+
+ @pytest.mark.parametrize('other_values', [
+ [61, 63], # int
+ [61., 63.], # float, but can be cast to int
+ [61.1, 63.1], # float, cannot be cast to int
+ [(61,), (63,)] # object
+ ], ids=['int', 'float_castable', 'float', 'object'])
+ @pytest.mark.parametrize('caller_dtype', ['int', 'float', object])
+ def test_update_dtypes(self, caller_dtype, other_values):
+ caller_values = [10, 11, 12]
+ s = Series(caller_values, dtype=caller_dtype)
+ other = Series(other_values, index=[1, 3])
+ s.update(other)
+
+ expected_values = [caller_values[0], other_values[0], caller_values[2]]
+ try:
+ # we keep original dtype whenever possible
+ expected = Series(expected_values, dtype=caller_dtype)
+ except ValueError:
+ expected = Series(expected_values)
+ print(s, expected)
+ assert_series_equal(s, expected)
 
  def test_concat_empty_series_dtypes_roundtrips(self):