sorted_counties_list = list()
# a list of list of dicts
for row in state_list:
# a list of dicts
sorted_counties = sorted(row, key=itemgetter('c'))
sorted_counties_list.append(sorted_counties)
# list of list of dicts
flattened = [val for sublist in sorted_counties_list for val in sublist]
sorted_issuers = sorted(flattened, key=itemgetter('s'))
# find the number of counties w/ only one insurance provider
# first group by county and tally count of insurers
data_grp = collections.defaultdict(list)
for row in sorted_issuers:
data_grp[row['id']].append(row['i'])
issuers_count = list()
for k,v in data_grp.items():
att = dict()
att['Number of Issuers'] = len(v)
att['Issuers'] = v
att['County'] = k
issuers_count.append(att)
# STEP FIVE: Write to file
c.write_dict(sorted_issuers, 'filtered-csvs/2015-issuers-filtered.csv')
c.write_dict(issuers_count, 'filtered-csvs/PROBLEM-count.csv')
sorted_counties_list = list()
# a list of list of dicts
for row in state_list:
# a list of dicts
sorted_counties = sorted(row, key=itemgetter('c'))
sorted_counties_list.append(sorted_counties)
# list of list of dicts
flattened = [val for sublist in sorted_counties_list for val in sublist]
sorted_issuers = sorted(flattened, key=itemgetter('s'))
# find the number of counties w/ only one insurance provider
# first group by county and tally count of insurers
data_grp = collections.defaultdict(list)
for row in sorted_issuers:
data_grp[row['id']].append(row['i'])
issuers_count = list()
for k, v in data_grp.items():
att = dict()
att['Number of Issuers'] = len(v)
att['Issuers'] = v
att['County'] = k
issuers_count.append(att)
# STEP FOUR: Write to file
c.write_dict(sorted_issuers, 'filtered-csvs/test14-issuers-filtered.csv')
c.write_dict(issuers_count, 'filtered-csvs/test14-count.csv')
for row in data:
data_grp[row['f']].append(row['i'])
# get count of issuers by fips code
issuers_by_county = list()
for k, v in data_grp.items():
att = dict()
# all issuers in a county
att['ict'] = len(v)
counter = collections.Counter(v)
# convert counter object to dict
counter_dict = dict(counter.items())
# split dict by key into a list of dicts
chunks = [counter_dict.iteritems()]
split = (dict(ifilter(None, v)) for v in izip_longest(*chunks))
split_list = list(split)
# sort our list of dicts
sorted_split = sorted(split_list)
# split up our dicts into one dict per county
for row in sorted_split:
key = ''.join(row.keys())
value = ''.join(str(v) for v in row.values())
att['f'] = k
issuers_by_county.append(att)
# print issuers_by_county
# STEP TWO: Write to file
c.write_dict(issuers_by_county, '2017-issuers-grouped.csv')
sorted_counties_list = list()
# a list of list of dicts
for row in state_list:
# a list of dicts
sorted_counties = sorted(row, key=itemgetter('c'))
sorted_counties_list.append(sorted_counties)
# list of list of dicts
flattened = [val for sublist in sorted_counties_list for val in sublist]
sorted_issuers = sorted(flattened, key=itemgetter('s'))
# find the number of counties w/ only one insurance provider
# first group by county and tally count of insurers
data_grp = collections.defaultdict(list)
for row in sorted_issuers:
data_grp[row['id']].append(row['i'])
issuers_count = list()
for k, v in data_grp.items():
att = dict()
att['Number of Issuers'] = len(v)
att['Issuers'] = v
att['County'] = k
issuers_count.append(att)
# STEP FIVE: Write to file
c.write_dict(sorted_issuers, 'filtered-csvs/2015-issuers-filtered.csv')
c.write_dict(issuers_count, 'filtered-csvs/PROBLEM-count.csv')
's': fips['s'],
'f': fips['f'],
'id': fips['id']
}
joined_data.append(entry)
# print joined_data
# identify where the join was unsuccessful
joined = list()
for row in joined_data:
joined.append(row['id'])
orig = list()
for row in aca_2017:
orig.append(row['id'])
unmatched = list()
for row in orig:
if row not in joined:
unmatched.append(row)
unmatched_unique = list(set(unmatched))
for row in unmatched_unique:
print row
print len(joined), len(orig)
# STEP THREE: Write to file
c.write_dict(joined_data, 'fips-join/2017-joined.csv')
# a list of list of dicts
for row in state_list:
# a list of dicts
sorted_issuers = sorted(row, key=itemgetter('c'))
sorted_issuers_2017.append(sorted_issuers)
# list of list of dicts
flattened = [val for sublist in sorted_issuers_2017 for val in sublist]
sorted_issuers_2017_list = sorted(flattened, key=itemgetter('s'))
# find the number of counties w/ only one insurance provider
# first group by county and tally count of insurers
data_grp = collections.defaultdict(list)
for row in sorted_issuers_2017_list:
data_grp[row['id']].append(row['i'])
issuers_count = list()
for k,v in data_grp.items():
att = dict()
att['Number of Issuers'] = len(v)
att['Issuers'] = v
att['County'] = k
issuers_count.append(att)
# print issuers_count
# STEP FIVE: Write to file
c.write_dict(sorted_issuers_2017_list, 'filtered-csvs/2017-issuers-filtered.csv')
c.write_dict(issuers_count, 'filtered-csvs/2017-count.csv')
sorted_counties_list = list()
# a list of list of dicts
for row in state_list:
# a list of dicts
sorted_counties = sorted(row, key=itemgetter('c'))
sorted_counties_list.append(sorted_counties)
# list of list of dicts
flattened = [val for sublist in sorted_counties_list for val in sublist]
sorted_issuers = sorted(flattened, key=itemgetter('s'))
# find the number of counties w/ only one insurance provider
# first group by county and tally count of insurers
data_grp = collections.defaultdict(list)
for row in sorted_issuers:
data_grp[row['id']].append(row['i'])
issuers_count = list()
for k,v in data_grp.items():
att = dict()
att['Number of Issuers'] = len(v)
att['Issuers'] = v
att['County'] = k
issuers_count.append(att)
# STEP FOUR: Write to file
c.write_dict(sorted_issuers, 'filtered-csvs/test14-issuers-filtered.csv')
c.write_dict(issuers_count, 'filtered-csvs/test14-count.csv')