Work internally only with nullable pandas integers

data_models/schemas.py

@@ -115,6 +115,11 @@ def read_schema(schema_name = None, ext_schema_path = None):
             if not schema['sections'][section]['header'].get('field_layout'):
                 delimiter = schema['sections'][section]['header'].get('delimiter')
                 schema['sections'][section]['header']['field_layout'] = 'delimited' if delimiter else 'fixed_width'
+            for element in schema['sections'][section]['elements'].keys():
+                if schema['sections'][section]['elements'][element].get('column_type') in properties.numpy_integers:
+                    np_integer = schema['sections'][section]['elements'][element].get('column_type') 
+                    pd_integer = properties.pandas_nan_integers.get(np_integer)
+                    schema['sections'][section]['elements'][element].update({'column_type':pd_integer})
         return schema
     else:
         logging.error('Multile reports per line data model: not yet supported')

properties.py

@@ -17,8 +17,14 @@ supported_data_models = [ os.path.basename(x).split(".")[0] for x in glob.glob(s
 # Data types ------------------------------------------------------------------
 numpy_integers = ['int8','int16','int32','int64','uint8','uint16','uint32','uint64']
 numpy_floats = ['float16','float32','float64']
+
+pandas_nan_integers = {'int8':'Int8','int16':'Int16','int32':'Int32',
+                       'int64':'Int64','uint8':'UInt8','uint16':'UInt16',
+                       'uint32':'UInt32','uint64':'UInt64'}
+
 numeric_types = numpy_integers.copy()
 numeric_types.extend(numpy_floats)
+numeric_types.extend(pandas_nan_integers.values())
 
 object_types = ['str','object','key','datetime']