Error while running make_pipeline_from_data_check_output while applying data checks suggestion

[sainiudit]

actions_pipeline = make_pipeline_from_data_check_output(problem_type, messages)
data_df, y = actions_pipeline.fit(data_df, target)

#################################################
Error Message:
File /anaconda/envs/azureml_py310_sdkv2/lib/python3.10/site-packages/woodwork/logical_types.py:475, in IntegerNullable.transform(self, series, null_invalid_values)
473 if null_invalid_values:
474 series = _coerce_integer(series)
--> 475 return super().transform(series)

File /anaconda/envs/azureml_py310_sdkv2/lib/python3.10/site-packages/woodwork/logical_types.py:76, in LogicalType.transform(self, series, null_invalid_values)
74 series = series.astype(new_dtype)
75 except (TypeError, ValueError):
---> 76 raise TypeConversionError(series, new_dtype, type(self))
77 return series

TypeConversionError: Error converting datatype for LoanAmount from type float64 to type Int64. Please confirm the underlying data is consistent with logical type IntegerNullable.

[sainiudit]

version of library:

import evalml, woodwork
print("evalml : ",evalml.version)
print("woodwork : ",woodwork.version)

evalml : 0.64.0
woodwork : 0.21.2

[gsheni]

@sainiudit would you to provide us with the dataset you used? Or a sample of the dataset? We would like to reproduce this error.