BUG: ignore errors for invalid dates in to_datetime() with errors=coerce (#25512)

doc/source/whatsnew/v0.25.0.rst

@@ -359,6 +359,7 @@ Datetimelike
 - Bug in :class:`Series` and :class:`DataFrame` repr where ``np.datetime64('NaT')`` and ``np.timedelta64('NaT')`` with ``dtype=object`` would be represented as ``NaN`` (:issue:`25445`)
 - Bug in :func:`to_datetime` which does not replace the invalid argument with ``NaT`` when error is set to coerce (:issue:`26122`)
 - Bug in adding :class:`DateOffset` with nonzero month to :class:`DatetimeIndex` would raise ``ValueError`` (:issue:`26258`)
+- Bug in :func:`to_datetime` which raises unhandled ``OverflowError`` when called with mix of invalid dates and ``NaN`` values with ``format='%Y%m%d'`` and ``error='coerce'`` (:issue:`25512`)
 
 Timedelta
 ^^^^^^^^^

pandas/core/tools/datetimes.py

@@ -775,21 +775,21 @@ def calc_with_mask(carg, mask):
  # try intlike / strings that are ints
  try:
  return calc(arg.astype(np.int64))
- except ValueError:
+ except (ValueError, OverflowError):
  pass
 
  # a float with actual np.nan
  try:
  carg = arg.astype(np.float64)
  return calc_with_mask(carg, notna(carg))
- except ValueError:
+ except (ValueError, OverflowError):
  pass
 
  # string with NaN-like
  try:
  mask = ~algorithms.isin(arg, list(tslib.nat_strings))
  return calc_with_mask(arg, mask)
- except ValueError:
+ except (ValueError, OverflowError):
  pass
 
  return None

pandas/tests/indexes/datetimes/test_tools.py

@@ -96,6 +96,25 @@ def test_to_datetime_format_YYYYMMDD(self, cache):
  result = pd.to_datetime(s, format='%Y%m%d', errors='coerce',
  cache=cache)
  expected = Series(['20121231', '20141231', 'NaT'], dtype='M8[ns]')
+ tm.assert_series_equal(result, expected)
+
+ @pytest.mark.parametrize("input_s, expected", [
+ # NaN before strings with invalid date values
+ [Series(['19801222', np.nan, '20010012', '10019999']),
+ Series([Timestamp('19801222'), np.nan, np.nan, np.nan])],
+ # NaN after strings with invalid date values
+ [Series(['19801222', '20010012', '10019999', np.nan]),
+ Series([Timestamp('19801222'), np.nan, np.nan, np.nan])],
+ # NaN before integers with invalid date values
+ [Series([20190813, np.nan, 20010012, 20019999]),
+ Series([Timestamp('20190813'), np.nan, np.nan, np.nan])],
+ # NaN after integers with invalid date values
+ [Series([20190813, 20010012, np.nan, 20019999]),
+ Series([Timestamp('20190813'), np.nan, np.nan, np.nan])]])
+ def test_to_datetime_format_YYYYMMDD_overflow(self, input_s, expected):
+ # GH 25512
+ # format='%Y%m%d', errors='coerce'
+ result = pd.to_datetime(input_s, format='%Y%m%d', errors='coerce')
  assert_series_equal(result, expected)
 
  @pytest.mark.parametrize('cache', [True, False])