Leon Moya
2020-12-03 10:06:36
You can iterate over the dataframe rows, transform each row to json and then convert it to a dict using json.loads, this will also avoid the numpy data type errors.
you can try this:
import json
from decimal import Decimal
DL_dt = DL_dt.rename(columns={
'director_name': 'Director',
'original_language': 'Language'
})
with table.batch_writer() as batch:
for index, row in DL_dt.iterrows():
batch.put_item(json.loads(row.to_json(), parse_float=Decimal))
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