break
if re.findall(r'\b(' + abbrev + r')\b', location, re.IGNORECASE):
states_freqs[abbrev] += 1
break
return states_freqs
Q = ' '.join(sys.argv[1:])
# Don't forget to pass in keyword parameters if you don't have
# a token file stored to disk
t = oauth_login()
_, screen_name_to_location, _ = analyze_users_in_search_results(t, q=Q, max_batches=5, count=100)
locations = screen_name_to_location.values()
# Resolve state abbreviations to the number of times these states appear
states_freqs = get_state_frequencies(locations)
# Munge the data to the format expected by Protovis for Dorling Cartogram
json_data = {}
for state, freq in states_freqs.items():
json_data[state] = {'value': freq}
# Copy over some scripts for Protovis...
# Our html template references some Protovis scripts, which we can
# simply copy into out/
Q = ' '.join(sys.argv[2:])
MAX_HTTP_ERRORS = 100
g = geopy.geocoders.Google(GEOCODING_API_KEY)
# Don't forget to pass in keyword parameters if you don't have
# a token file stored to disk
t = oauth_login()
# This function returns a few useful maps. Let's use the
# screen_name => location map and geocode the locations
_, screen_name_to_location, _ = analyze_users_in_search_results(
t, Q, max_pages=1)
locations = screen_name_to_location.values()
location2coords, location2description = geocode_locations(g, locations)
# Doing something interesting like building up some KML to visualize in Google Earth/Maps
# just involves some simple string munging...
kml = build_kml(
"Geocoded user profiles for Twitter search results for " + Q,
location2coords)
if not os.path.isdir('out'):
os.mkdir('out')
f = open(os.path.join(os.getcwd(), 'out', Q + ".kml"), 'w')
f.write(kml)
break
if re.findall(r'\b(' + abbrev + r')\b', location, re.IGNORECASE):
states_freqs[abbrev] += 1
break
return states_freqs
Q = ' '.join(sys.argv[1:])
# Don't forget to pass in keyword parameters if you don't have
# a token file stored to disk
t = oauth_login()
_, screen_name_to_location, _ = analyze_users_in_search_results(t, Q)
locations = screen_name_to_location.values()
# Resolve state abbreviations to the number of times these states appear
states_freqs = get_state_frequencies(locations)
# Munge the data to the format expected by Protovis for Dorling Cartogram
json_data = {}
for state, freq in states_freqs.items():
json_data[state] = {'value': freq}
# Copy over some scripts for Protovis...
# Our html template references some Protovis scripts, which we can
# simply copy into out/
