ped_deaths.py

import matplotlib.pyplot as plt
# Population data from https://data.worldbank.org/indicator/SP.POP.TOTL
# Ped. death data estimated from Figure 1 in:
# https://international.fhwa.dot.gov/programs/mrp/docs/FHWAPL2-020_GBP_Ped_Safety%20_Desk_Review_final102822.pdf
dates = [2000, 2010, 2019]
dates = [str(date) for date in dates]
AU = [
    (19.15, 282.3104149030503),
    (22.03, 169.25140607847925),
    (25.37, 155.36721318887794)
]
CA = [
    (30.69, 370.9047885795528),
    (34.00, 304.128432300995),
    (37.60, 314.04370335574845)
]
NL = [
    (15.93,  114.37779614311216),
    (16.62, 74.0475215590327),
    (17.34,  53.5518082458118)
]
NO = [
    (4.49, 48.262591906915986), 
    (4.89, 23.797956758847704),
    (5.35, 15.200970627466404)
]
UK = [
    (58.89, 887.929704867958),
    (62.77, 416.5222699218525),
    (66.84, 489.90612746267846)
]
USA = [
    (282.2, 4763.263106861964),
    (309.3, 4296.150145820198),
    (328.3, 6209.18453728149)
]

plt.figure()
plt.plot(dates, [death/pop for (pop, death) in AU], '-y^', label="AU")
plt.plot(dates, [death/pop for (pop, death) in CA], '-y*', label="CA")
plt.plot(dates, [death/pop for (pop, death) in NL], '-gD', label="NL")
plt.plot(dates, [death/pop for (pop, death) in NO], '-m*', label="NO")
plt.plot(dates, [death/pop for (pop, death) in UK], '-rs', label="UK")
plt.plot(dates, [death/pop for (pop, death) in USA], '-rD', label="USA")
plt.xlabel("Year")
plt.ylabel("Fatality Count / Population in Millions")
plt.legend(
    fancybox=True, 
    shadow=True, 
    ncol=6, 
    loc="upper center",
    bbox_to_anchor=(0.5,1.10)
)
plt.savefig("normalized_ped_deaths.png", bbox_inches="tight", dpi=512)
plt.show()