Raise type conversion error in datetime

docs/source/release_notes.rst

@@ -9,6 +9,7 @@ Future Release
         * Pass additional progress information in callback functions (:pr:`979`)
         * Add the ability to generate optional extra stats with ``DataFrame.ww.describe_dict`` (:pr:`988`)
     * Fixes
+        * Raise type conversion error in ``Datetime`` logical type (:pr:`1001`)
     * Changes
         * Remove version restriction for dask requirements (:pr:`998`)
     * Documentation Changes

woodwork/exceptions.py

@@ -34,7 +34,11 @@ def get_warning_message(self, attr, invalid_reason, object_type):
 
 
 class TypeConversionError(Exception):
-    pass
+    def __init__(self, series, new_dtype, logical_type):
+        message = f'Error converting datatype for {series.name} from type {str(series.dtype)} '
+        message += f'to type {new_dtype}. Please confirm the underlying data is consistent with '
+        message += f'logical type {logical_type}.'
+        super().__init__(message)
 
 
 class ParametersIgnoredWarning(UserWarning):

woodwork/logical_types.py

@@ -47,17 +47,15 @@ def transform(self, series):
         new_dtype = self._get_valid_dtype(type(series))
         if new_dtype != str(series.dtype):
             # Update the underlying series
-            error_msg = f'Error converting datatype for {series.name} from type {str(series.dtype)} ' \
-                f'to type {new_dtype}. Please confirm the underlying data is consistent with ' \
-                f'logical type {type(self)}.'
+            error = TypeConversionError(series, new_dtype, type(self))
             try:
                 series = series.astype(new_dtype)
                 if str(series.dtype) != new_dtype:
                     # Catch conditions when Panads does not error but did not
                     # convert to the specified dtype (example: 'category' -> 'bool')
-                    raise TypeConversionError(error_msg)
+                    raise error
             except (TypeError, ValueError):
-                raise TypeConversionError(error_msg)
+                raise error
         return series
 
 
@@ -183,14 +181,17 @@ def transform(self, series):
         """Converts the series data to a formatted datetime."""
         new_dtype = self._get_valid_dtype(type(series))
         if new_dtype != str(series.dtype):
-            if dd and isinstance(series, dd.Series):
-                name = series.name
-                series = dd.to_datetime(series, format=self.datetime_format)
-                series.name = name
-            elif ks and isinstance(series, ks.Series):
-                series = ks.Series(ks.to_datetime(series.to_numpy(), format=self.datetime_format), name=series.name)
-            else:
-                series = pd.to_datetime(series, format=self.datetime_format)
+            try:
+                if dd and isinstance(series, dd.Series):
+                    name = series.name
+                    series = dd.to_datetime(series, format=self.datetime_format)
+                    series.name = name
+                elif ks and isinstance(series, ks.Series):
+                    series = ks.Series(ks.to_datetime(series.to_numpy(), format=self.datetime_format), name=series.name)
+                else:
+                    series = pd.to_datetime(series, format=self.datetime_format)
+            except (TypeError, ValueError):
+                raise TypeConversionError(series, new_dtype, type(self))
         return super().transform(series)
 
 

woodwork/tests/logical_types/test_logical_types.py

@@ -3,6 +3,7 @@
 import pandas as pd
 import pytest
 
+from woodwork.exceptions import TypeConversionError
 from woodwork.logical_types import (
     Boolean,
     Categorical,
@@ -110,6 +111,14 @@ def test_datetime_transform(datetimes):
         assert str(transform.dtype) == 'datetime64[ns]'
 
 
+def test_datetime_conversion_error():
+    series = pd.Series(['a', 'b', 'c'], name='series')
+    match = 'Error converting datatype for series from type object to type datetime64[ns]. '
+    match += 'Please confirm the underlying data is consistent with logical type Datetime.'
+    with pytest.raises(TypeConversionError, match=re.escape(match)):
+        Datetime().transform(series)
+
+
 def test_ordinal_transform(sample_series):
     series_type = str(type(sample_series))
     dask = 'dask' in series_type