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From the table here, I belive these are the right coding for population_by_age:
{'0': 'Under 5', '1': '5 to 9', '2': '10 to 14', '3': '15 to 19',
'4': '20 to 24','5': '25 to 29','6': '30 to 34','7': '35 to 39','8': '40 to 44',
'9': '45 to 49','10': '50 to 54','11': '55 to 59','12': '60 to 64','13': '65 to 69',
'14': '70 to 74','15': '75 to 79','16': '80 to 84','17': 'above 85'}
Describe the problem
I don't know where the data is coming from or when the data was generated
Sample code to reproduce the problem
for zipcode 01827 i am seeing a population_by_age of:
{'0': 67, '1': 130, '2': 172, '3': 164, '4': 64, '5': 44, '6': 37, '7': 64, '8': 146, '9': 188, '10': 158, '11': 113, '12': 99, '13': 72, '14': 35, '15': 26, '16': 12, '17': 7}
Potential Solution
place an object in the elements as the data source, table name, year of source
Maybe you can try talk to the author lively here https://gitter.im/MacHu-GWU-Python-Library-Technical-Support/community
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