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					@ -251,13 +251,16 @@ class Components :
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									_value = 0
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									_value = 0
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									if _item['type'] in ['DATE','TIMESTAMP','DATETIMESTAMP','DATETIME'] :
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									if _item['type'] in ['DATE','TIMESTAMP','DATETIMESTAMP','DATETIME'] :
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										if _item['type'] == 'DATE' :
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										if _item['type'] == 'DATE' :
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											_df[name] = _df[name].dt.date
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											#
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											_df[name] = pd.to_datetime(_df[name],errors='coerce')
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											# There is an issue with missing dates that needs to be resolved.
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											# for some reason a missing date/time here will cause the types to turn into timestamp (problem)
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											#	The following is a hack to address the issue (alas) assuming 10 digit dates and 'NaT' replaces missing date values (pandas specifications)
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											#
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											_df[name] = _df[name].apply(lambda value: '' if str(value) == 'NaT' else str(value)[:10])
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											#_df[name] = _df[name].dt.date
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											# _df[name] = pd.to_datetime(_df[name].fillna(''),errors='coerce')
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										else:
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											print ([' ** ',name,_item['type']])
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									else:
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									else:
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										if _item['type'] == 'INTEGER' :
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										if _item['type'] == 'INTEGER' :
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											_type = np.int64
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											_type = np.int64
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