Pass the errors and kwargs arguments through to astype in the columns…

doc/source/whatsnew/v0.25.0.rst

@@ -275,7 +275,7 @@ Numeric
 Conversion
 ^^^^^^^^^^
 
--
+- Bug in :func:`DataFrame.astype()` when passing a dict of columns and types the `errors` parameter was ignored. (:issue:`25905`)
 -
 -
 

pandas/core/generic.py

@@ -5716,7 +5716,8 @@ def astype(self, dtype, copy=True, errors='raise', **kwargs):
             results = []
             for col_name, col in self.iteritems():
                 if col_name in dtype:
-                    results.append(col.astype(dtype[col_name], copy=copy))
+                    results.append(col.astype(dtype=dtype[col_name], copy=copy,
+                                              errors=errors, **kwargs))
                 else:
                     results.append(results.append(col.copy() if copy else col))
 

pandas/tests/frame/common.py

@@ -1,3 +1,6 @@
+from contextlib import contextmanager
+from typing import Optional
+
 import numpy as np
 
 from pandas.util._decorators import cache_readonly

pandas/tests/frame/test_dtypes.py

@@ -850,6 +850,35 @@ def test_arg_for_errors_in_astype(self):
 
         df.astype(np.int8, errors='ignore')
 
+    def test_arg_for_errors_in_astype_dictlist(self):
+        """Test that the errors=ignore argument silences the exception that is
+        thrown by default for data that cannot be converted to the specified
+        type with astype.
+
+        Test for GH-25905
+        """
+        data_df = pd.DataFrame([{'a': '1',
+                                 'b': '16.5%',
+                                 'c': 'test'},
+                                {'a': '2.2',
+                                 'b': '15.3',
+                                 'c': 'another_test'}
+                                ])
+        expected = pd.DataFrame([{'a': '1',
+                                  'b': '16.5%',
+                                  'c': 'test'},
+                                 {'a': '2.2',
+                                  'b': '15.3',
+                                  'c': 'another_test'}
+                                 ], dtype='float64')
+        type_dict = {'a': 'float64',
+                     'b': 'float64',
+                     'c': 'object'}
+
+        result = data_df.astype(dtype=type_dict, errors='ignore')
+
+        tm.assert_frame_equal(expected, result)
+
     @pytest.mark.parametrize('input_vals', [
         ([1, 2]),
         (['1', '2']),