from getdata import load_jobs, get_average_prices_data
from getscores import get_state_scores
from plotchoropleth import choropleth_usa_states
"""
Generate (and save) choropleths of available jobs (scaled by house prices)
"""
prices = get_average_prices_data()
profession_keys = ["data-science", "financial-services", "information-technology", "mobile-app"]
for pk in profession_keys:
jobs = load_jobs(pk)
scores = get_state_scores(jobs, prices)
choropleth_usa_states(scores, "templates/jobsdata_%s.html" % pk, title="")
jobs = pd.concat((jobs, new_jobs), ignore_index=True)
jobs_per_state = jobs.groupby(['state'])['id'].count().to_dict()
prices = get_average_prices_data()
# Add state abbreviations to prices dataframe
fips = get_fips_data()
prices = pd.merge(prices, fips.groupby(['state_long','state']).count().reset_index()[['state_long','state']], how='left', on=['state_long'])
for p in range(12):
max_price = 150000. + float(p)*50000
prices_per_state = prices.loc[prices['average_price'] < max_price, ['state','average_price']].set_index('state').to_dict()['average_price']
if len(prices_per_state) > 0:
counts = []
for state in prices_per_state:
try:
counts.append(float(jobs_per_state[state]))
except KeyError:
continue
max_jobs = max(counts)
counts = [v/max_jobs for v in counts]
scores = dict(zip(jobs_per_state.keys(), counts))
else:
scores = {}
choropleth_usa_states(scores, 'templates/pricedata_%s.html' % int(max_price), title='')
fips = get_fips_data()
prices = pd.merge(
prices,
fips.groupby(['state_long',
'state']).count().reset_index()[['state_long', 'state']],
how='left',
on=['state_long'])
for p in range(12):
max_price = 150000. + float(p) * 50000
prices_per_state = prices.loc[prices['average_price'] < max_price,
['state', 'average_price']].set_index(
'state').to_dict()['average_price']
if len(prices_per_state) > 0:
counts = []
for state in prices_per_state:
try:
counts.append(float(jobs_per_state[state]))
except KeyError:
continue
max_jobs = max(counts)
counts = [v / max_jobs for v in counts]
scores = dict(zip(jobs_per_state.keys(), counts))
else:
scores = {}
choropleth_usa_states(scores,
'templates/pricedata_%s.html' % int(max_price),
title='')
