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Use ACS 2016 5 year data #84

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Use ACS 2016 5 year data #84

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2 changes: 1 addition & 1 deletion scripts/create_block_groups.py
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Original file line number Diff line number Diff line change
Expand Up @@ -65,7 +65,7 @@ def block_groups_10(state, county):
acs_df = pd.DataFrame(c.acs5.get(
ACS_VARS,
{'for': 'block group:*', 'in': 'county:{} state:{}'.format(county, state)},
year=2015
year=2016
))

census_df.rename(columns=CENSUS_10_VAR_MAP, inplace=True)
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8 changes: 4 additions & 4 deletions scripts/create_data_demographics.py
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Original file line number Diff line number Diff line change
Expand Up @@ -254,7 +254,7 @@ def get_10_data(geo_str):
ACS_12_VARS, {'for': 'state:*'}, year=2012
))
acs_df = pd.DataFrame(c.acs5.get(
ACS_VARS, {'for': 'state:*'}, year=2015
ACS_VARS, {'for': 'state:*'}, year=2016
))
elif geo_str == 'counties':
census_df = pd.DataFrame(c.sf1.get(
Expand All @@ -264,7 +264,7 @@ def get_10_data(geo_str):
ACS_12_VARS, {'for': 'county:*', 'in': 'state:*'}, year=2012
))
acs_df = pd.DataFrame(c.acs5.get(
ACS_VARS, {'for': 'county:*', 'in': 'state:*'}, year=2015
ACS_VARS, {'for': 'county:*', 'in': 'state:*'}, year=2016
))
elif geo_str == 'cities':
census_df = pd.DataFrame(c.sf1.get(
Expand All @@ -274,14 +274,14 @@ def get_10_data(geo_str):
ACS_12_VARS, {'for': 'place:*', 'in': 'state:*'}, year=2012
))
acs_df = pd.DataFrame(c.acs5.get(
ACS_VARS, {'for': 'place:*', 'in': 'state:*'}, year=2015
ACS_VARS, {'for': 'place:*', 'in': 'state:*'}, year=2016
))
# Handle ACS var difference
acs_df['NAME'] = acs_df['NAME'].apply(lambda x: ','.join(x.split(',')[:-1]).strip())
else:
census_df = state_county_sub_data(c.sf1, geo_str, CENSUS_10_VARS, 2010)
acs_12_df = state_county_sub_data(c.acs5, geo_str, ACS_12_VARS, 2012)
acs_df = state_county_sub_data(c.acs5, geo_str, ACS_VARS, 2015)
acs_df = state_county_sub_data(c.acs5, geo_str, ACS_VARS, 2016)

census_df.rename(columns=CENSUS_10_VAR_MAP, inplace=True)
acs_12_df.rename(columns=ACS_12_VAR_MAP, inplace=True)
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