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This repository has been archived by the owner on Aug 2, 2019. It is now read-only.
I do not want to export my records if they are null. This bit of code actually does that, but i image you would want something like use_nulls as an input variable. Basically if you dont want the nulls to be there, that should be an option :). This is part of the data.py file.
elif isinstance(pd_obj, pd.DataFrame):
# We have to explicitly convert the column names to strings
# because the json serializer doesn't allow for integer keys.
for i, row in pd_obj.iterrows():
for num, (k, v) in enumerate(row.iteritems()):
value = {}
if pd.notnull(v) == True and use_nulls = False:
value['idx'] = cls.serialize(i)
value['col'] = cls.serialize(k)
value['val'] = cls.serialize(v)
if grouped:
value['group'] = num
vega_data.values.append(value)
elif use_null = True:
vega_data.values.append(value)
The text was updated successfully, but these errors were encountered:
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I do not want to export my records if they are null. This bit of code actually does that, but i image you would want something like use_nulls as an input variable. Basically if you dont want the nulls to be there, that should be an option :). This is part of the data.py file.
The text was updated successfully, but these errors were encountered: