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blacktwin/botulism.json

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Mapping Infant Botulism Cases in the US from 1975-2017
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botulism.json
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"description" : "The CDC Botulism Consultation Service, the Alaska Division of Public Health, and the California Department of Public Health provide clinical consultations on suspected cases of all types of botulism except infant botulism. These agencies are the only sources of antitoxin for non-infant botulism in the United States. The California Infant Botulism Treatment and Prevention provides clinical consultations on suspected infant botulism cases; it is the only source of antitoxin for infant botulism in the United States. Together, these clinical consultations provide expert guidance to clinicians and support the collection of epidemiologic and medical information for all suspected botulism cases reported in the United States.",
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, [ "row-tid6-bwfg.piga", "00000000-0000-0000-6F1E-814433C6E1EB", 0, 1558625993, null, 1558625993, null, "{ }", "Washington", "2007", "Infant", "A", "1" ]
, [ "row-mexp-xg6x-9qpz", "00000000-0000-0000-1694-0666C1415E53", 0, 1558625993, null, 1558625993, null, "{ }", "Washington", "2007", "Wound", "A", "2" ]
, [ "row-gfi8_kdr4_9yng", "00000000-0000-0000-A65A-A17B01E815C1", 0, 1558625993, null, 1558625993, null, "{ }", "Washington", "2008", "Infant", "A", "1" ]
, [ "row-h9ks.pzzn-ex5a", "00000000-0000-0000-72BB-CFEA265959DE", 0, 1558625993, null, 1558625993, null, "{ }", "Washington", "2008", "Wound", "A", "2" ]
, [ "row-kc4w.ukf3_x2s7", "00000000-0000-0000-FE19-3623F6121D89", 0, 1558625993, null, 1558625993, null, "{ }", "Washington", "2009", "Foodborne", "A", "4" ]
, [ "row-vxkw-cc2q-ss44", "00000000-0000-0000-EB11-1EEEF2ADEA32", 0, 1558625993, null, 1558625993, null, "{ }", "Washington", "2009", "Infant", "A", "2" ]
, [ "row-y6yn_vfpj-4pm6", "00000000-0000-0000-420A-98E189165EDA", 0, 1558625993, null, 1558625993, null, "{ }", "Washington", "2009", "Wound", "A", "4" ]
, [ "row-vivu~9f2d_mzug", "00000000-0000-0000-555C-2ADC59B3E2C8", 0, 1558625993, null, 1558625993, null, "{ }", "Washington", "2010", "Infant", "A", "2" ]
, [ "row-mcpc-32n3_ingv", "00000000-0000-0000-3928-566A4C43F387", 0, 1558625993, null, 1558625993, null, "{ }", "Washington", "2010", "Infant", "B", "1" ]
, [ "row-f3ub_qewd.emyr", "00000000-0000-0000-3602-993BEAEDBE97", 0, 1558625993, null, 1558625993, null, "{ }", "Washington", "2010", "Wound", "A", "1" ]
, [ "row-xiph.2e2q-9rmb", "00000000-0000-0000-1141-CB86809FDD10", 0, 1558625993, null, 1558625993, null, "{ }", "Washington", "2011", "Infant", "A", "3" ]
, [ "row-ftt8_7c6z-fr7p", "00000000-0000-0000-AF48-995512C9E361", 0, 1558625993, null, 1558625993, null, "{ }", "Washington", "2011", "Wound", "A", "2" ]
, [ "row-mfku~5c9d.edh9", "00000000-0000-0000-76F9-890F09CBD772", 0, 1558625993, null, 1558625993, null, "{ }", "Washington", "2012", "Infant", "A", "4" ]
, [ "row-z5a7-aqz5.3ccs", "00000000-0000-0000-5E25-11F5EA4CA1DE", 0, 1558625993, null, 1558625993, null, "{ }", "Washington", "2012", "Wound", "A", "1" ]
, [ "row-hsb3.65ai_ijcx", "00000000-0000-0000-79BC-428D21CC5C54", 0, 1558625993, null, 1558625993, null, "{ }", "Washington", "2013", "Infant", "A", "4" ]
, [ "row-vjnh.v3ab~t66v", "00000000-0000-0000-42FF-0718FDA9AF4C", 0, 1558625993, null, 1558625993, null, "{ }", "Washington", "2014", "Infant", "A", "3" ]
, [ "row-pkb5_iiij~dtxt", "00000000-0000-0000-5EC8-F2D1B0DCD8E3", 0, 1558625993, null, 1558625993, null, "{ }", "Washington", "2015", "Infant", "A", "6" ]
, [ "row-9kra.apwj-d2n6", "00000000-0000-0000-0AE7-7B3BB3FC9D81", 0, 1558625993, null, 1558625993, null, "{ }", "Washington", "2016", "Foodborne", "A", "2" ]
, [ "row-sx24~awmz-bkew", "00000000-0000-0000-C517-8830ED25EB36", 0, 1558625993, null, 1558625993, null, "{ }", "Washington", "2016", "Infant", "A", "1" ]
, [ "row-84pz_tha3~5v69", "00000000-0000-0000-5CB0-EB47A4CECC8B", 0, 1558625993, null, 1558625993, null, "{ }", "Washington", "2017", "Infant", "A", "5" ]
, [ "row-tuzz.j56a~9zss", "00000000-0000-0000-1DCD-59BD50A8712D", 0, 1558625993, null, 1558625993, null, "{ }", "Washington", "2017", "Wound", "A", "1" ]
, [ "row-svgv~6hvx-r737", "00000000-0000-0000-03DB-8F6416DEC1E4", 0, 1558625993, null, 1558625993, null, "{ }", "Wisconsin", "1919", "Foodborne", "Unknown", "3" ]
, [ "row-sm57~psjp-yvxi", "00000000-0000-0000-05A3-3C631D9FA792", 0, 1558625993, null, 1558625993, null, "{ }", "Wisconsin", "1929", "Foodborne", "Unknown", "2" ]
, [ "row-udxy.4xsb-gf87", "00000000-0000-0000-6A06-DAFC6F3CF634", 0, 1558625993, null, 1558625993, null, "{ }", "Wisconsin", "1939", "Foodborne", "Unknown", "1" ]
, [ "row-t9hs~7zur-bi6e", "00000000-0000-0000-55F4-3F698F7AC677", 0, 1558625993, null, 1558625993, null, "{ }", "Wisconsin", "1976", "Foodborne", "A", "1" ]
, [ "row-j4px.sknm_ry78", "00000000-0000-0000-0754-B4F4B14EAA21", 0, 1558625993, null, 1558625993, null, "{ }", "Wisconsin", "1977", "Infant", "B", "1" ]
, [ "row-t5fg_5x85.czf2", "00000000-0000-0000-B314-35C66FFAE6BA", 0, 1558625993, null, 1558625993, null, "{ }", "Wisconsin", "1978", "Foodborne", "B", "1" ]
, [ "row-r6ma-adzk.g3hc", "00000000-0000-0000-3E75-2261673C3165", 0, 1558625993, null, 1558625993, null, "{ }", "Wisconsin", "1980", "Foodborne", "A", "2" ]
, [ "row-2678-ke2u~paer", "00000000-0000-0000-5ADA-7E61F3205640", 0, 1558625993, null, 1558625993, null, "{ }", "Wisconsin", "1981", "Infant", "A", "1" ]
, [ "row-u9tt-pap7-wigg", "00000000-0000-0000-ACEE-0F72C15903AF", 0, 1558625993, null, 1558625993, null, "{ }", "Wisconsin", "1982", "Foodborne", "A", "1" ]
, [ "row-u8nx.7k7i.j7e2", "00000000-0000-0000-FBE6-C9B4F5419EC2", 0, 1558625993, null, 1558625993, null, "{ }", "Wisconsin", "1984", "Foodborne", "Unknown", "1" ]
, [ "row-zytf-u9nf_tx2h", "00000000-0000-0000-4989-F29144687135", 0, 1558625993, null, 1558625993, null, "{ }", "Wisconsin", "1987", "Foodborne", "A", "1" ]
, [ "row-kmu4.93qb.pbhj", "00000000-0000-0000-1528-58811327D442", 0, 1558625993, null, 1558625993, null, "{ }", "Wisconsin", "1989", "Infant", "F", "1" ]
, [ "row-dd6b_7kby.7553", "00000000-0000-0000-D243-9FB67E3AAFFA", 0, 1558625993, null, 1558625993, null, "{ }", "Wisconsin", "1991", "Foodborne", "B", "1" ]
, [ "row-xwqz_uq2a~mgz9", "00000000-0000-0000-3F9F-652090A60359", 0, 1558625993, null, 1558625993, null, "{ }", "Wisconsin", "1995", "Infant", "B", "1" ]
, [ "row-ihzf_paeg~hsiy", "00000000-0000-0000-97AB-ED013B83E68E", 0, 1558625993, null, 1558625993, null, "{ }", "Wisconsin", "1997", "Infant", "A", "2" ]
, [ "row-viq8-ng9d.ywrq", "00000000-0000-0000-DC01-F1631D5F692C", 0, 1558625993, null, 1558625993, null, "{ }", "Wisconsin", "1997", "Infant", "B", "1" ]
, [ "row-qnvz_99c9.ie8e", "00000000-0000-0000-43B2-E1557A595E42", 0, 1558625993, null, 1558625993, null, "{ }", "Wisconsin", "1998", "Infant", "B", "1" ]
, [ "row-p6x8_2hwm.td7b", "00000000-0000-0000-6042-58F1AA50EFAC", 0, 1558625993, null, 1558625993, null, "{ }", "Wisconsin", "1999", "Infant", "A", "1" ]
, [ "row-fuay-n4nq_gkbu", "00000000-0000-0000-184B-5150941BF63D", 0, 1558625993, null, 1558625993, null, "{ }", "Wisconsin", "2000", "Other", "A", "1" ]
, [ "row-xg25-pndj_5y9t", "00000000-0000-0000-FC40-D21EE2D3CF0E", 0, 1558625993, null, 1558625993, null, "{ }", "Wisconsin", "2007", "Foodborne", "A", "1" ]
, [ "row-n993_xbbu~gj9z", "00000000-0000-0000-0399-46EC932CB96E", 0, 1558625993, null, 1558625993, null, "{ }", "Wisconsin", "2009", "Infant", "B", "1" ]
, [ "row-b9hs_2y8s.rwvb", "00000000-0000-0000-7529-6E91D7CF875F", 0, 1558625993, null, 1558625993, null, "{ }", "Wisconsin", "2014", "Infant", "B", "1" ]
, [ "row-9xwz.dmjg_zs2g", "00000000-0000-0000-6DEF-D79758327F89", 0, 1558625993, null, 1558625993, null, "{ }", "West Virginia", "1940", "Foodborne", "Unknown", "3" ]
, [ "row-sya8~rs8q-4vnb", "00000000-0000-0000-6505-A69B7003F2CF", 0, 1558625993, null, 1558625993, null, "{ }", "West Virginia", "1963", "Foodborne", "B", "1" ]
, [ "row-493t.jibj-gygh", "00000000-0000-0000-C387-13E9393E951E", 0, 1558625993, null, 1558625993, null, "{ }", "West Virginia", "1972", "Wound", "Unknown", "1" ]
, [ "row-f544~xk44_hw9f", "00000000-0000-0000-F996-E7382F860FAB", 0, 1558625993, null, 1558625993, null, "{ }", "West Virginia", "1973", "Foodborne", "B", "6" ]
, [ "row-ni6v_cv39.8qrx", "00000000-0000-0000-731D-7AA4AFFB127B", 0, 1558625993, null, 1558625993, null, "{ }", "West Virginia", "1981", "Infant", "B", "2" ]
, [ "row-9xbn.7cvj.54z5", "00000000-0000-0000-068F-C9BF65D67112", 0, 1558625993, null, 1558625993, null, "{ }", "West Virginia", "1982", "Foodborne", "B", "1" ]
, [ "row-8p49.dbwm_7skg", "00000000-0000-0000-0838-D08BD6E4EBE6", 0, 1558625993, null, 1558625993, null, "{ }", "West Virginia", "1984", "Infant", "B", "1" ]
, [ "row-q7ja-m5mh.ibve", "00000000-0000-0000-704D-79842FE64BE5", 0, 1558625993, null, 1558625993, null, "{ }", "West Virginia", "1991", "Infant", "B", "1" ]
, [ "row-bdiy~9fdf_irrc", "00000000-0000-0000-D752-DD33D89C2272", 0, 1558625993, null, 1558625993, null, "{ }", "West Virginia", "1997", "Infant", "A", "1" ]
, [ "row-ixvk-ugpp~xrfa", "00000000-0000-0000-8B80-DB85E30BE8A8", 0, 1558625993, null, 1558625993, null, "{ }", "West Virginia", "1997", "Infant", "B", "1" ]
, [ "row-5vuf_7hkr.qwjb", "00000000-0000-0000-3556-5A8BB6437234", 0, 1558625993, null, 1558625993, null, "{ }", "West Virginia", "2001", "Infant", "B", "1" ]
, [ "row-sr7r~3ix9~jwx3", "00000000-0000-0000-30CA-3E10A60B2F99", 0, 1558625993, null, 1558625993, null, "{ }", "West Virginia", "2004", "Infant", "B", "2" ]
, [ "row-y7h8.vh7u_sjjp", "00000000-0000-0000-F507-767E6E78BCFC", 0, 1558625993, null, 1558625993, null, "{ }", "West Virginia", "2006", "Infant", "B", "1" ]
, [ "row-c96k.fwak-vfnu", "00000000-0000-0000-728D-84DC85A27F60", 0, 1558625993, null, 1558625993, null, "{ }", "West Virginia", "2007", "Infant", "A", "1" ]
, [ "row-k9p9~6wh6-j5zd", "00000000-0000-0000-8E21-A595C5AD6CC0", 0, 1558625993, null, 1558625993, null, "{ }", "West Virginia", "2008", "Foodborne", "A", "1" ]
, [ "row-76f5_3etf.khmg", "00000000-0000-0000-1462-D40142340D7F", 0, 1558625993, null, 1558625993, null, "{ }", "West Virginia", "2008", "Infant", "B", "1" ]
, [ "row-558f~3s3i~swew", "00000000-0000-0000-E71F-33D4FDAA436F", 0, 1558625993, null, 1558625993, null, "{ }", "West Virginia", "2010", "Infant", "A", "1" ]
, [ "row-mxfh.ppdg-vqst", "00000000-0000-0000-8ABD-CFF6870D1602", 0, 1558625993, null, 1558625993, null, "{ }", "West Virginia", "2010", "Infant", "B", "2" ]
, [ "row-4a48.ukt4_5ehu", "00000000-0000-0000-8D12-70E61C2B39E6", 0, 1558625993, null, 1558625993, null, "{ }", "West Virginia", "2013", "Infant", "B", "1" ]
, [ "row-h6e5-hkqw~a7y2", "00000000-0000-0000-A0BF-2920E6BB340F", 0, 1558625993, null, 1558625993, null, "{ }", "West Virginia", "2015", "Infant", "B", "1" ]
, [ "row-8v3i_zz9a-dmbk", "00000000-0000-0000-87CB-DD6F71AE075F", 0, 1558625993, null, 1558625993, null, "{ }", "West Virginia", "2016", "Infant", "B", "2" ]
, [ "row-54zi_677w_6t98", "00000000-0000-0000-D1B1-94A9AB56E07A", 0, 1558625993, null, 1558625993, null, "{ }", "Wyoming", "1924", "Foodborne", "A", "7" ]
, [ "row-96xz~giwm-xcpi", "00000000-0000-0000-547C-DCFB7641E54C", 0, 1558625993, null, 1558625993, null, "{ }", "Wyoming", "1925", "Foodborne", "B", "4" ]
, [ "row-j85n.4ndn-st8u", "00000000-0000-0000-A7FC-A7ED21594450", 0, 1558625993, null, 1558625993, null, "{ }", "Wyoming", "1926", "Foodborne", "Unknown", "3" ]
, [ "row-st2q~s6bj~xw3g", "00000000-0000-0000-D0D9-6E96B9A33A13", 0, 1558625993, null, 1558625993, null, "{ }", "Wyoming", "1929", "Foodborne", "A", "6" ]
, [ "row-bji5~d5nb_mpyy", "00000000-0000-0000-7376-EA9F60272A59", 0, 1558625993, null, 1558625993, null, "{ }", "Wyoming", "1936", "Foodborne", "A", "3" ]
, [ "row-tgnk-jec8.g923", "00000000-0000-0000-2263-A3C45AE7DDDB", 0, 1558625993, null, 1558625993, null, "{ }", "Wyoming", "1936", "Foodborne", "Unknown", "5" ]
, [ "row-p6i7_9ysn~3a5v", "00000000-0000-0000-D827-A236FE109FDC", 0, 1558625993, null, 1558625993, null, "{ }", "Wyoming", "1975", "Foodborne", "A", "1" ]
, [ "row-gza9.k2vf_msna", "00000000-0000-0000-97DD-726E8DEDC90B", 0, 1558625993, null, 1558625993, null, "{ }", "Wyoming", "1982", "Foodborne", "A", "1" ]
, [ "row-v3ft-5hun.a4wk", "00000000-0000-0000-9599-21AC1FD98D02", 0, 1558625993, null, 1558625993, null, "{ }", "Wyoming", "1984", "Infant", "A", "1" ]
, [ "row-tfw9~r9kc~jump", "00000000-0000-0000-5130-3656E0E0CA2D", 0, 1558625993, null, 1558625993, null, "{ }", "Wyoming", "1986", "Wound", "Unknown", "1" ]
, [ "row-hmpb-ejpu_mkkh", "00000000-0000-0000-1840-23D8F330B9C2", 0, 1558625993, null, 1558625993, null, "{ }", "Wyoming", "1990", "Foodborne", "A", "1" ]
, [ "row-zkuq.khjr_8tm3", "00000000-0000-0000-1B1B-344F55CD96E4", 0, 1558625993, null, 1558625993, null, "{ }", "Wyoming", "2006", "Infant", "A", "1" ]
, [ "row-kp45-p65a_pk5a", "00000000-0000-0000-3E10-37DFCBF93812", 0, 1558625993, null, 1558625993, null, "{ }", "Wyoming", "2008", "Infant", "A", "1" ]
, [ "row-97dy.efpn_p399", "00000000-0000-0000-F31C-F9ACFDCAAE11", 0, 1558625993, null, 1558625993, null, "{ }", "Wyoming", "2012", "Infant", "A", "2" ]
, [ "row-4jn5.zbyj_e7b5", "00000000-0000-0000-CFED-417272A70C53", 0, 1558625993, null, 1558625993, null, "{ }", "Wyoming", "2015", "Infant", "A", "1" ]
, [ "row-ddyu_e8zf~iczt", "00000000-0000-0000-EDE1-D95C542445C9", 0, 1558625993, null, 1558625993, null, "{ }", "Wyoming", "2016", "Infant", "A", "1" ]
]
}
Raw
infant_botulism.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as ani
from matplotlib.collections import PatchCollection
from mpl_toolkits.basemap import Basemap
from matplotlib.patches import Polygon
import json
COLOR_COUNT = 5
def divide_chunks(l, n):
# looping till length l
for i in range(0, len(l), n):
yield l[i:i + n]
# Get data from exported json from CDC site
# https://data.cdc.gov/Foodborne-Waterborne-and-Related-Diseases/Botulism/66i6-hisz/data
with open("".join("botulism.json")) as file:
json_data = json.load(file)
# Sort by year
json_data = sorted(json_data["data"], key=lambda k: k[9])
year_data = {}
counts = []
# Pull data to be worked
for row in json_data:
if row[10].lower() == "infant" and row[8] != "NA":
if not year_data.get(row[9]):
year_data[row[9]] = {}
year_data[row[9]].update({row[8]: int(row[12])})
else:
if year_data[row[9]].get(row[8]):
year_data[row[9]][row[8]] += int(row[12])
else:
year_data[row[9]].update({row[8]: int(row[12])})
# Find year range from data
years = [year for year in year_data.keys()]
first_last = years[::len(years)-1]
# Create figure
fig = plt.figure(figsize=(10, 12))
plt.suptitle("Infant Botulism Cases in the US from {}".format("-".join(first_last)), x=0.475,
size=25)
# Create subplots
map_ax = plt.subplot2grid((2, 3), (0, 0), colspan=3)
# Draw map before creating bargraph subplot
bmap = Basemap(llcrnrlon=-119,llcrnrlat=22,urcrnrlon=-64,urcrnrlat=49,
projection='lcc',lat_1=33,lat_2=45,lon_0=-95)
bmap.drawcoastlines()
# Load the shapefile, use the name 'states'
bmap.readshapefile('st99_d00', name='states', drawbounds=True)
# Create list of State names
state_names = []
for shape_dict in bmap.states_info:
state_names.append(shape_dict['NAME'])
# Set color map to red
patches = []
reds = plt.get_cmap('Reds', COLOR_COUNT)
# Work through data collect to create state polygon and red mappings
year_totals = {}
year_poly = {}
for year, data in year_data.items():
yearly_counts = []
year_poly.update({year: []})
for state, count in data.items():
seg = bmap.states[state_names.index(state)]
color = reds(float(count / (10 * COLOR_COUNT)))
poly = Polygon(seg, facecolor=color, edgecolor=color)
patches.append(poly)
counts.append(count)
yearly_counts.append(count)
year_poly[year].append({"state": state,
"count": count,
"poly": poly,
"color": color})
year_totals[year] = sum(yearly_counts)
# Gether information for colorbar for map legend
clean_counts = list(set(counts))
count_max = clean_counts[-1]
clean_range = list(range(count_max))
range_array = np.array(clean_range)
# Compute the indices to split on for colorbar for map legend
splits = np.array_split(range_array, COLOR_COUNT)
clean_labels = ["> {}".format(splits[0][-1])]
for chunk in splits[1:-1]:
clean_labels.append("{}-{}".format(chunk[0], chunk[-1]))
clean_labels.append("< {}".format(splits[-1][0]))
# Create colorbar for map legend
pathcollection = PatchCollection(patches, cmap=reds)
pathcollection.set_array(np.array(clean_counts))
pathcollection.set_clim(-0.5, COLOR_COUNT+0.5)
colorbar = fig.colorbar(pathcollection, ax=map_ax, orientation='vertical')
colorbar.set_ticks(np.linspace(0, COLOR_COUNT, COLOR_COUNT))
colorbar.set_ticklabels(range(COLOR_COUNT))
colorbar.ax.tick_params(labelsize=15)
colorbar.ax.set_yticklabels(clean_labels)
map_ax.set_aspect('auto')
# Create bar chart for top states
bar_ax = plt.subplot2grid((2, 3), (1, 0))
bar_ax.set_xlim(0, count_max + 5)
# Create line graph for yearly occurrences
line_ax = plt.subplot2grid((2, 3), (1, 1), colspan=2)
xlim = [int(x) for x in first_last]
ylim = [0, max(year_totals.values())]
xlim[1] += 2
ylim[1] += 5
year_dates = [int(year)for year in years]
line_ax.set_xticks(year_dates)
# Create writer for creating gif
ImageWriter = ani.writers['imagemagick']
metadata = dict(title='Ani CDC Infant Botulism', artist='Matplotlib',
comment='Gif support!')
writer = ImageWriter(fps=1, metadata=metadata)
counts_lst = []
years_lst = []
# Start writing
with writer.saving(fig, 'infant_botulism_results.gif', 60):
for year, data in year_poly.items():
state_totals = {}
state_colors = {}
# Update states map
for d in data:
map_ax.add_patch(d["poly"])
state_totals.update({d["state"]: d["count"]})
state_colors.update({d["state"]: d["color"]})
# Find top 3 states with most cases
top_counts = sorted(state_totals.items(), key=lambda kv: kv[1], reverse=True)
top_list = list(top_counts)[:3]
top_counts = []
top_states = []
top_colors = []
for state, count in top_list:
top_states.append(state)
top_counts.append(count)
top_colors.append(state_colors.get(state))
x_pos = list(reversed([i for i, _ in enumerate(top_states)]))
# Clear bar chart each year and create
bar_ax.cla()
bar_ax.barh(x_pos, count_max, align='center', color="white", edgecolor="white", height=0.9)
rects = bar_ax.barh(x_pos, top_counts, align='center', color=top_colors, edgecolor="black")
bar_ax.set_yticklabels(top_states)
bar_ax.set_yticks(x_pos)
plt.cla()
year_total = sum(state_totals.values())
years_lst.append(int(year))
counts_lst.append(year_total)
# Plot to line graph
line_ax.plot(years_lst, counts_lst, color="r")
line_ax.set_xlim(xlim)
line_ax.set_ylim(ylim)
# Set updating yearly totals
bar_ax.set_title('Top 3 States', size=20, loc='left')
line_ax.set_title("{} Total: {}".format(year, year_total), size=20, loc='left')
# plt.show()
writer.grab_frame()
writer.grab_frame()
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