#!/usr/bin/env python
# coding: utf-8

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import requests
import pandas as pd


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zips = [90049, 60608, 60615]


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API_URL="http://api.censusreporter.org/1.0/data/show/{release}?table_ids={table_ids}&geo_ids={geoids}"


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def get_data(tables=None, geoids=None, release='latest'):
    if geoids is None:
        geoids = ['040|01000US']
    if tables is None:
        tables = ['B01001']

    url = API_URL.format(table_ids=','.join(tables).upper(), 
                         geoids=','.join(geoids), 
                         release=release)
    response = requests.get(url)
    return response.json()


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def prep_for_pandas(json_data,include_moe=False):
    """Given a dict of dicts as they come from a Census Reporter API call, set it up to be amenable 
    to pandas.DataFrame.from_dict"""
    result = {}
    for geoid, tables in json_data.items():
        flat = {}
        for table,values in tables.items():
            for kind, columns in values.items():
                if kind == 'estimate':
                    flat.update(columns)
                elif kind == 'error' and include_moe:
                    renamed = dict((k+"_moe",v) for k,v in columns.items())
                    flat.update(renamed)
        result[geoid] = flat
    return result


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response = get_data(geoids = ["86000US" + str(z) for z in zips], tables = ['B17001'])
df = pd.DataFrame.from_dict(prep_for_pandas(response['data']),orient='index')


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df


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df.describe()


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