Bug: OverflowError in resample.agg with tz data (pandas-dev#25297)

Pingviinituutti · Feb 28, 2019 · 0a88ee7 · 0a88ee7
1 parent 8e04e37
commit 0a88ee7
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diff --git a/doc/source/whatsnew/v0.25.0.rst b/doc/source/whatsnew/v0.25.0.rst
@@ -172,7 +172,7 @@ Plotting
 Groupby/Resample/Rolling
 ^^^^^^^^^^^^^^^^^^^^^^^^
 
--
+- Bug in :meth:`pandas.core.resample.Resampler.agg` with a timezone aware index where ``OverflowError`` would raise when passing a list of functions (:issue:`22660`)
 -
 -
 

diff --git a/pandas/core/indexes/datetimes.py b/pandas/core/indexes/datetimes.py
@@ -1010,7 +1010,7 @@ def get_loc(self, key, method=None, tolerance=None):
         except (KeyError, ValueError, TypeError):
             try:
                 return self._get_string_slice(key)
-            except (TypeError, KeyError, ValueError):
+            except (TypeError, KeyError, ValueError, OverflowError):
                 pass
 
             try:

diff --git a/pandas/tests/resample/test_resample_api.py b/pandas/tests/resample/test_resample_api.py
@@ -549,3 +549,25 @@ def test_selection_api_validation():
 
     exp.index.name = 'd'
     assert_frame_equal(exp, df.resample('2D', level='d').sum())
+
+
+@pytest.mark.parametrize('col_name', ['t2', 't2x', 't2q', 'T_2M',
+                                      't2p', 't2m', 't2m1', 'T2M'])
+def test_agg_with_datetime_index_list_agg_func(col_name):
+    # GH 22660
+    # The parametrized column names would get converted to dates by our
+    # date parser. Some would result in OutOfBoundsError (ValueError) while
+    # others would result in OverflowError when passed into Timestamp.
+    # We catch these errors and move on to the correct branch.
+    df = pd.DataFrame(list(range(200)),
+                      index=pd.date_range(start='2017-01-01', freq='15min',
+                                          periods=200, tz='Europe/Berlin'),
+                      columns=[col_name])
+    result = df.resample('1d').aggregate(['mean'])
+    expected = pd.DataFrame([47.5, 143.5, 195.5],
+                            index=pd.date_range(start='2017-01-01', freq='D',
+                                                periods=3, tz='Europe/Berlin'),
+                            columns=pd.MultiIndex(levels=[[col_name],
+                                                          ['mean']],
+                                                  codes=[[0], [0]]))
+    assert_frame_equal(result, expected)