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Last active September 8, 2017 15:09
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Analyze Swedish cause-of-death and population data (assumed to be in data/2017-9-10-4Amod.csv and data/mfsv16.csv) transformed to CSV files.
using DataFrames
deaths = readtable(normpath("data", "2017-9-10-4Amod.csv"))
ages = DataFrame(age = collect(0:20),
agest = [0;0;1;collect(5:5:90)],
age2 =[0;1;fill(2,3);fill(3,6);fill(4,4);fill(5,2);fill(6,4)])
ages2 = by(ages[:,[:agest, :age2]], :age2,
df -> DataFrame(agest=minimum(df[:agest])))
pop = DataFrame()
pop1 = readtable(normpath("data", "mfsv16.csv"))
ages1 = DataFrame(age1 = collect(0:101),
age = [0;1;fill(2,4);map((x)->fld(x,5)+2, collect(5:89));fill(20,11)])
pop1_age = join(pop1, ages1, on = :age1)
for sex in ["Kv"; "M"]
pop1_sex = pop1_age[pop1_age[:sex].==sex, [:n, :age]]
pop_sex = by(pop1_sex, :age, df -> DataFrame(sex = sex, n = sum(df[:n])))
pop = vcat(pop, pop_sex)
function df_reg(sex, caexpr, ageaggr = false)
if caexpr == "pop"
df_sub = pop[pop[:sex].==sex, [:age, :n]]
df_sub = deaths[((map((x)->ismatch(Regex(caexpr), x),
convert(Vector{AbstractString}, deaths[:icd10]))) & (deaths[:sex].==sex)),
[:age, :n]]
df_aggr = by(df_sub, :age, df -> DataFrame(n=sum(df[:n])))
df_aggr_age = join(df_aggr, ages, on = :age)
if ageaggr
df_aggr_age2 = by(df_aggr_age[:, [:n, :age2]], :age2,
df -> DataFrame(n=sum(df[:n])))
return join(df_aggr_age2, ages2, on = :age2)
return df_aggr_age
function propframe(sex, ca1, ca2 = "A00-Y98", ageaggr = false)
ca1frame = df_reg(sex, ca1, ageaggr)
ca2frame = df_reg(sex, ca2, ageaggr)
propframe = DataFrame(age = ca1frame[1], agest = ca1frame[:agest],
prop = ca1frame[:n]./ca2frame[:n])
return Dict(:sex => sex, :ca1 => ca1, :ca2 => ca2, :frame => propframe)
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