I'm iterating through a range from 2010 to 2018. I want to include the results in my api pull for each year as a separate column in my data frame. I'mnot sure how to name the column titles to do so.
I tried using "Population {i}" for the column name.
for i in range(2010,2019):
# Census & gmaps API Keys
from config import (api_key, gkey)
c = Census(api_key, year=i)
# Configure gmaps
gmaps.configure(api_key=gkey)
# Run Census Search to retrieve data on all zip codes (2013 ACS5 Census)
# See: https://github.com/CommerceDataService/census-wrapper for library documentation
# See: https://gist.github.com/afhaque/60558290d6efd892351c4b64e5c01e9b for labels
census_data = c.acs5.get(("NAME", "B19013_001E", "B01003_001E", "B01002_001E",
"B19301_001E",
"B17001_002E"), {'for': 'place:*','in': 'state:51'})
# Convert to DataFrame
census_pd = pd.DataFrame(census_data)
# Column Reordering
census_pd = census_pd.rename(columns={"B01003_001E": "Population[i]",
"B01002_001E": "Median Age [i]",
"B19013_001E": "Household Income [i]",
"B19301_001E": "Per Capita Income [i]",
"B17001_002E": "Poverty Count [i]",
"NAME": "Name", "place": "Place [i]"})
# Add in Poverty Rate (Poverty Count / Population)
#census_pd["Poverty Rate"] = 100 * \
# census_pd["Poverty Count"].astype(int) / census_pd["Population"].astype(int)
# Final DataFrame
#census_pd = census_pd[["City", "Population", "Median Age", "Household Income",
#/ "Per Capita Income", "Poverty Count", "Poverty Rate"]]
# Visualize
print(len(census_pd))
print (i)
census_pd.head()
census_pd.to_csv("test2.csv", index=False)