diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index f0147859cae97..d5c3a95fa3b6a 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -5447,7 +5447,7 @@ def astype(
         """
         if is_dict_like(dtype):
             if self.ndim == 1:  # i.e. Series
-                if len(dtype) > 1 or self.name not in dtype:
+                if len(dtype) > 1 or self.name not in dtype and errors == "raise":
                     raise KeyError(
                         "Only the Series name can be used for "
                         "the key in Series dtype mappings."
@@ -5456,7 +5456,7 @@ def astype(
                 return self.astype(new_type, copy, errors)
 
             for col_name in dtype.keys():
-                if col_name not in self:
+                if col_name not in self and errors == "raise":
                     raise KeyError(
                         "Only a column name can be used for the "
                         "key in a dtype mappings argument."
diff --git a/pandas/tests/frame/test_dtypes.py b/pandas/tests/frame/test_dtypes.py
index 713d8f3ceeedb..4e048f02582fc 100644
--- a/pandas/tests/frame/test_dtypes.py
+++ b/pandas/tests/frame/test_dtypes.py
@@ -276,7 +276,7 @@ def test_astype_str_float(self):
 
     @pytest.mark.parametrize("dtype_class", [dict, Series])
     def test_astype_dict_like(self, dtype_class):
-        # GH7271 & GH16717
+        # GH7271 & GH16717 & GH30324
         a = Series(date_range("2010-01-04", periods=5))
         b = Series(range(5))
         c = Series([0.0, 0.2, 0.4, 0.6, 0.8])
@@ -342,6 +342,15 @@ def test_astype_dict_like(self, dtype_class):
         tm.assert_frame_equal(df, equiv)
         tm.assert_frame_equal(df, original)
 
+        # GH 30324
+        # If errors=='ignore' than the resulting DataFrame
+        # should be the same as the original DataFrame
+        dt8 = dtype_class({"b": str, 2: str})
+        dt9 = dtype_class({"e": str})
+        df.astype(dt8, errors="ignore")
+        df.astype(dt9, errors="ignore")
+        tm.assert_frame_equal(df, original)
+
     def test_astype_duplicate_col(self):
         a1 = Series([1, 2, 3, 4, 5], name="a")
         b = Series([0.1, 0.2, 0.4, 0.6, 0.8], name="b")