add more tests

tests/system/small/test_dataframe.py

@@ -3687,6 +3687,12 @@ def test_df_add_suffix(scalars_df_index, scalars_pandas_df_index, axis):
     )
 
 
+def test_df_astype_error_error(session):
+    input = pd.DataFrame(["hello", "world", "3.11", "4000"])
+    with pytest.raises(ValueError):
+        session.read_pandas(input).astype("Float64", errors="bad_value")
+
+
 def test_df_columns_filter_items(scalars_df_index, scalars_pandas_df_index):
     if pd.__version__.startswith("2.0") or pd.__version__.startswith("1."):
         pytest.skip("pandas filter items behavior different pre-2.1")

tests/system/small/test_index.py

@@ -123,6 +123,12 @@ def test_index_astype(scalars_df_index, scalars_pandas_df_index):
     pd.testing.assert_index_equal(bf_result, pd_result)
 
 
+def test_index_astype_error_error(session):
+    input = pd.Index(["hello", "world", "3.11", "4000"])
+    with pytest.raises(ValueError):
+        session.read_pandas(input).astype("Float64", errors="bad_value")
+
+
 def test_index_any(scalars_df_index, scalars_pandas_df_index):
     bf_result = scalars_df_index.set_index("int64_col").index.any()
     pd_result = scalars_pandas_df_index.set_index("int64_col").index.any()

tests/system/small/test_series.py

@@ -3103,6 +3103,7 @@ def foo(x):
         ("int64_col", "time64[us][pyarrow]"),
         ("bool_col", "Int64"),
         ("bool_col", "string[pyarrow]"),
+        ("bool_col", "Float64"),
         ("string_col", "binary[pyarrow]"),
         ("bytes_col", "string[pyarrow]"),
         # pandas actually doesn't let folks convert to/from naive timestamp and
@@ -3155,6 +3156,12 @@ def test_astype_safe(session):
     pd.testing.assert_series_equal(result, exepcted)
 
 
+def test_series_astype_error_error(session):
+    input = pd.Series(["hello", "world", "3.11", "4000"])
+    with pytest.raises(ValueError):
+        session.read_pandas(input).astype("Float64", errors="bad_value")
+
+
 @skip_legacy_pandas
 def test_astype_numeric_to_int(scalars_df_index, scalars_pandas_df_index):
     column = "numeric_col"