thoughtfulbloke/AgeRates.csv

## AgeRates.csv
"Age-specific death rates by sex, December years (total population) (Annual-Dec)","","","","","","","","","","","","","","","","","","",""
"","Total Population","","","","","","","","","","","","","","","","","",""
" ","0-4 Years","5-9 Years","10-14 Years","15-19 Years","20-24 Years","25-29 Years","30-34 Years","35-39 Years","40-44 Years","45-49 Years","50-54 Years","55-59 Years","60-64 Years","65-69 Years","70-74 Years","75-79 Years","80-84 Years","85-89 Years","90 Years and Over"
1971,4.31,0.39,0.35,0.96,1.06,0.97,1.29,1.81,2.93,4.70,7.50,12.19,19.17,29.34,44.81,71.51,118.74,192.62,280.73
1972,4.04,0.37,0.33,1.16,1.13,0.89,1.19,1.71,2.65,4.51,7.33,11.72,19.32,29.64,45.89,74.35,118.35,187.90,309.62
1973,3.99,0.42,0.35,1.22,1.24,0.98,1.17,1.86,2.70,4.76,7.26,12.57,18.57,30.31,45.92,72.05,114.84,190.45,320.67
1974,3.68,0.38,0.43,1.16,1.06,1.04,1.15,1.76,2.96,4.74,7.51,11.68,19.02,28.10,46.32,70.63,111.84,190.96,314.86
1975,3.78,0.46,0.34,1.02,1.11,1.01,1.17,1.75,2.64,4.60,7.39,11.07,19.04,27.29,45.13,65.78,106.28,186.23,317.53
1976,3.24,0.31,0.37,1.07,1.21,0.92,1.00,1.58,2.89,4.62,7.08,11.66,17.77,27.99,46.15,69.86,103.70,175.67,313.66
1977,3.36,0.41,0.38,1.30,1.41,1.22,1.23,1.62,2.97,4.76,7.26,11.25,18.00,28.07,44.99,68.86,103.68,170.02,311.36
1978,3.16,0.31,0.34,1.05,1.20,1.01,1.04,1.60,2.72,4.73,6.93,10.82,17.72,26.51,43.33,64.53,93.57,158.39,288.91
1979,3.06,0.32,0.32,1.01,1.15,1.03,1.01,1.51,2.42,4.38,7.01,10.84,17.74,27.03,43.65,67.42,99.84,153.49,302.65
1980,3.07,0.33,0.32,0.97,1.28,1.21,1.07,1.43,2.23,4.27,6.40,10.97,17.59,28.72,42.98,70.96,108.41,162.38,362.58
1981,2.99,0.27,0.32,1.03,1.20,0.90,1.08,1.34,2.51,4.09,6.43,10.69,15.98,26.51,40.62,62.22,97.34,152.78,254.43
1982,2.88,0.30,0.24,0.95,1.23,0.98,1.13,1.47,2.26,4.08,6.24,10.69,16.37,26.07,40.33,60.81,99.23,149.58,251.72
1983,2.97,0.30,0.30,0.93,1.31,0.91,1.03,1.34,2.19,3.81,5.90,10.17,16.24,25.81,40.13,63.60,100.46,149.75,247.94
1984,2.85,0.28,0.28,0.91,1.09,0.90,1.14,1.22,2.17,3.38,6.17,9.98,15.23,24.18,39.16,61.48,92.86,145.21,234.52
1985,2.67,0.33,0.32,1.01,1.12,1.09,0.97,1.27,2.15,3.76,6.10,10.15,16.13,25.08,39.83,64.46,99.45,165.65,286.28
1986,2.89,0.26,0.34,1.03,1.25,1.08,1.13,1.44,2.00,3.24,6.13,9.73,15.90,24.11,39.43,62.27,96.59,143.03,245.88
1987,2.59,0.28,0.34,1.06,1.34,1.11,1.12,1.35,1.88,3.38,6.39,9.69,15.20,24.23,39.41,60.71,95.43,149.66,243.71
1988,2.81,0.27,0.29,0.98,1.34,1.11,1.12,1.37,2.03,3.22,5.56,9.06,15.21,23.48,36.92,60.05,95.38,154.18,245.90
1989,2.64,0.27,0.27,1.12,1.34,1.02,1.06,1.29,2.01,3.23,5.70,8.41,14.72,22.62,36.16,57.66,91.72,143.29,249.75
1990,2.27,0.22,0.24,1.03,1.38,1.09,1.05,1.26,1.93,3.20,5.34,8.95,14.00,22.10,35.52,54.05,87.56,131.95,232.98
1991,2.06,0.24,0.26,0.83,1.12,0.94,1.01,1.44,1.95,2.99,4.84,7.97,13.20,21.07,32.48,51.72,85.23,132.42,231.06
1992,1.80,0.26,0.29,0.87,1.13,0.98,0.95,1.30,1.67,2.85,4.94,8.09,12.85,20.94,32.37,51.75,87.75,139.42,231.53
1993,1.80,0.16,0.21,0.91,1.15,0.92,0.88,1.23,1.91,2.59,4.88,7.83,12.56,19.92,31.67,52.59,83.03,136.12,231.29
1994,1.68,0.19,0.19,0.74,0.95,0.95,1.01,1.17,1.68,2.46,4.67,7.25,12.24,19.48,31.32,49.51,82.05,133.33,234.08
1995,1.60,0.19,0.22,0.83,1.15,1.04,0.97,1.12,1.64,2.74,4.82,7.40,12.01,19.68,30.93,50.13,79.73,134.30,246.35
1996,1.71,0.18,0.25,0.95,0.95,0.96,1.02,1.14,1.37,2.77,4.38,7.08,12.55,19.35,30.56,48.44,82.04,135.07,246.72
1997,1.63,0.16,0.22,0.88,0.88,0.99,0.99,1.06,1.69,2.49,4.34,6.90,11.07,18.78,28.76,44.42,78.83,127.62,235.86
1998,1.35,0.17,0.26,0.77,0.84,0.87,0.93,1.12,1.71,2.26,3.71,6.63,10.99,17.33,26.53,43.22,71.66,117.11,216.60
1999,1.37,0.13,0.23,0.73,0.85,0.87,0.87,1.09,1.59,2.39,3.83,6.76,11.13,17.02,28.06,45.85,74.54,127.90,244.23
2000,1.52,0.16,0.21,0.61,0.74,0.88,0.91,0.99,1.53,2.36,3.65,6.14,9.56,16.44,25.85,42.52,69.84,116.31,214.01
2001,1.32,0.16,0.21,0.69,0.81,0.76,0.91,0.99,1.46,2.13,3.64,5.68,9.98,16.12,26.45,41.44,70.73,125.53,234.40
2002,1.35,0.16,0.18,0.58,0.72,0.81,0.85,1.08,1.45,2.25,3.48,5.88,9.25,15.36,25.43,41.84,68.58,124.70,236.02
2003,1.26,0.13,0.18,0.72,0.67,0.73,0.87,1.06,1.47,2.27,3.59,5.51,8.93,14.82,24.69,39.74,68.61,120.74,229.86
2004,1.36,0.11,0.17,0.65,0.67,0.69,0.72,1.09,1.36,2.30,3.45,5.19,8.73,14.41,23.78,39.28,68.87,124.05,232.43
2005,1.25,0.15,0.16,0.66,0.74,0.65,0.78,1.03,1.50,2.16,3.23,5.18,8.23,12.97,21.28,35.79,64.97,109.58,214.40
2006,1.25,0.12,0.14,0.64,0.61,0.65,0.73,0.95,1.36,2.15,3.23,5.13,8.19,13.00,22.33,36.97,62.66,114.60,231.16
2007,1.36,0.13,0.18,0.58,0.70,0.60,0.81,1.07,1.45,2.07,3.23,5.03,7.75,12.83,21.73,36.08,62.79,111.68,222.69
2008,1.34,0.13,0.17,0.62,0.72,0.64,0.69,1.03,1.35,1.89,2.97,5.22,7.86,12.76,21.17,36.18,63.49,113.76,224.52
2009,1.24,0.11,0.18,0.58,0.68,0.63,0.84,0.93,1.39,2.04,3.29,4.49,7.51,12.39,20.53,33.91,61.21,109.99,222.50
2010,1.24,0.06,0.14,0.53,0.63,0.55,0.65,0.93,1.37,2.11,3.04,4.64,6.99,11.68,18.98,32.23,59.59,105.67,210.76
2011,1.09,0.06,0.14,0.55,0.72,0.64,0.76,0.90,1.39,1.91,2.89,4.75,7.18,12.03,19.13,33.33,59.87,112.03,225.83
2012,1.01,0.11,0.15,0.55,0.61,0.55,0.64,0.82,1.32,2.11,3.05,4.26,6.82,11.25,18.74,32.25,58.77,111.38,224.15
2013,0.99,0.08,0.10,0.49,0.54,0.51,0.58,0.87,1.26,1.99,3.09,4.41,6.81,10.62,18.18,31.46,56.03,107.22,206.35
2014,1.24,0.13,0.10,0.38,0.48,0.51,0.59,0.83,1.23,1.87,3.06,4.48,6.80,10.69,17.84,31.65,59.02,107.49,221.73
2015,1.00,0.10,0.12,0.46,0.53,0.53,0.61,0.75,1.18,1.96,2.91,4.33,6.63,10.74,18.33,31.27,58.31,105.40,220.90
2016,0.83,0.11,0.11,0.39,0.49,0.55,0.64,0.76,1.26,1.83,2.98,4.56,6.53,10.38,16.61,28.99,55.25,102.72,210.68
2017,0.90,0.09,0.11,0.41,0.60,0.61,0.67,0.89,1.16,1.90,2.94,4.37,6.91,10.53,17.49,30.96,57.41,108.74,216.10
2018,0.90,0.09,0.14,0.44,0.56,0.56,0.67,0.83,1.22,1.73,2.92,4.58,6.75,10.20,16.71,29.33,55.74,103.81,214.78
2019,1.07,0.08,0.17,0.41,0.60,0.56,0.73,0.83,1.21,1.95,3.07,4.45,6.49,10.27,16.69,29.17,53.51,107.54,215.10
2020,0.86,0.07,0.14,0.40,0.50,0.53,0.54,0.77,1.15,1.80,2.81,4.27,6.22,9.75,15.39,27.47,49.80,95.40,194.56
2021,1.05,0.08,0.13,0.41,0.53,0.52,0.63,0.84,1.24,1.69,2.92,4.31,6.45,9.86,15.93,27.77,51.26,100.22,207.38
2022,0.82,0.07,0.11,0.34,0.55,0.61,0.66,0.83,1.18,1.94,2.97,4.73,7.07,10.55,16.74,30.04,54.69,107.50,234.89
"Table information:"
"Units:"
"/ 1000, Magnitude = Units"
""
"Footnotes:"
"Rates from 1991 onward are based on the resident population concept. Before 1991, rates are based on the de facto population concept. Vitals data (births, deaths and marriages) is based on date of registration (not date of occurrence)."
"Deaths per 1,000 mean estimated population in each age group."
" "
"Symbols:"
".. figure not available"
"C: Confidential"
"E: Early Estimate"
"P: Provisional"
"R: Revised"
"S: Suppressed"
""
"Status flags are not displayed"
""
"Table reference: "
"DMM001AA"
""
"Last updated:"
"16 November 2023 10:45am"
""
"Source: Statistics New Zealand"
"Contact: Information Centre"
"Telephone: 0508 525 525"
"Email:info@stats.govt.nz"
""
""
""

## NZstandardpop.R
# Death rates by age
# https://infoshare.stats.govt.nz : Death Rates DMM : Age-specific death rates by sex, December years (total population) (Annual-Dec)
# Total population, All Ages, All Years
# Saved as AgeRates.csv
library(dplyr)
library(tidyr)

AR <- read.csv("AgeRates.csv", skip=2) |>
  gather(key="Age", value="per1k", 2:20) |>
  mutate(low_n = as.numeric(gsub("[^0123456789]","", substr(Age,2,3))),
  Year = as.numeric(X.)) |>
  filter(!.is.na(per1k))

#Standard Population from https://seer.cancer.gov/stdpopulations/stdpop.singleages.html
# US 2000 single years to 99, 100+
# to make 5 years to 89 then 90+ as an exact match to the data

library("rvest")
url <- "https://seer.cancer.gov/stdpopulations/stdpop.singleages.html"
population <- read_html(url) |>
  html_table()
StndPops <- population[[1]]
US <- StndPops[2:102,1:2]
US_clean <- US |>
  mutate(age_n = floor(as.numeric(gsub("[^0123456789]","", US$Age))/5),
         age_n = ifelse(age_n > 18,18,age_n),
         pop_n = as.numeric(gsub(",","", `2000 U.S. Standard Population (Census P25-1130)`))) |>
  summarise(.by=age_n,
            Pop = sum(pop_n)) |>
  mutate(low_n = age_n*5) |>
  select(low_n, Pop)

combo <- AR |> inner_join(US_clean, by="low_n") |>
  summarise(.by=Year, Standard_Deaths = sum(Pop * per1k / 1000))
precovid <- combo[combo$Year < 2020,]
plot(precovid$Year, precovid$Standard_Deaths)
	"Age-specific death rates by sex, December years (total population) (Annual-Dec)","","","","","","","","","","","","","","","","","","",""
	"","Total Population","","","","","","","","","","","","","","","","","",""
	" ","0-4 Years","5-9 Years","10-14 Years","15-19 Years","20-24 Years","25-29 Years","30-34 Years","35-39 Years","40-44 Years","45-49 Years","50-54 Years","55-59 Years","60-64 Years","65-69 Years","70-74 Years","75-79 Years","80-84 Years","85-89 Years","90 Years and Over"
	1971,4.31,0.39,0.35,0.96,1.06,0.97,1.29,1.81,2.93,4.70,7.50,12.19,19.17,29.34,44.81,71.51,118.74,192.62,280.73
	1972,4.04,0.37,0.33,1.16,1.13,0.89,1.19,1.71,2.65,4.51,7.33,11.72,19.32,29.64,45.89,74.35,118.35,187.90,309.62
	1973,3.99,0.42,0.35,1.22,1.24,0.98,1.17,1.86,2.70,4.76,7.26,12.57,18.57,30.31,45.92,72.05,114.84,190.45,320.67
	1974,3.68,0.38,0.43,1.16,1.06,1.04,1.15,1.76,2.96,4.74,7.51,11.68,19.02,28.10,46.32,70.63,111.84,190.96,314.86
	1975,3.78,0.46,0.34,1.02,1.11,1.01,1.17,1.75,2.64,4.60,7.39,11.07,19.04,27.29,45.13,65.78,106.28,186.23,317.53
	1976,3.24,0.31,0.37,1.07,1.21,0.92,1.00,1.58,2.89,4.62,7.08,11.66,17.77,27.99,46.15,69.86,103.70,175.67,313.66
	1977,3.36,0.41,0.38,1.30,1.41,1.22,1.23,1.62,2.97,4.76,7.26,11.25,18.00,28.07,44.99,68.86,103.68,170.02,311.36
	1978,3.16,0.31,0.34,1.05,1.20,1.01,1.04,1.60,2.72,4.73,6.93,10.82,17.72,26.51,43.33,64.53,93.57,158.39,288.91
	1979,3.06,0.32,0.32,1.01,1.15,1.03,1.01,1.51,2.42,4.38,7.01,10.84,17.74,27.03,43.65,67.42,99.84,153.49,302.65
	1980,3.07,0.33,0.32,0.97,1.28,1.21,1.07,1.43,2.23,4.27,6.40,10.97,17.59,28.72,42.98,70.96,108.41,162.38,362.58
	1981,2.99,0.27,0.32,1.03,1.20,0.90,1.08,1.34,2.51,4.09,6.43,10.69,15.98,26.51,40.62,62.22,97.34,152.78,254.43
	1982,2.88,0.30,0.24,0.95,1.23,0.98,1.13,1.47,2.26,4.08,6.24,10.69,16.37,26.07,40.33,60.81,99.23,149.58,251.72
	1983,2.97,0.30,0.30,0.93,1.31,0.91,1.03,1.34,2.19,3.81,5.90,10.17,16.24,25.81,40.13,63.60,100.46,149.75,247.94
	1984,2.85,0.28,0.28,0.91,1.09,0.90,1.14,1.22,2.17,3.38,6.17,9.98,15.23,24.18,39.16,61.48,92.86,145.21,234.52
	1985,2.67,0.33,0.32,1.01,1.12,1.09,0.97,1.27,2.15,3.76,6.10,10.15,16.13,25.08,39.83,64.46,99.45,165.65,286.28
	1986,2.89,0.26,0.34,1.03,1.25,1.08,1.13,1.44,2.00,3.24,6.13,9.73,15.90,24.11,39.43,62.27,96.59,143.03,245.88
	1987,2.59,0.28,0.34,1.06,1.34,1.11,1.12,1.35,1.88,3.38,6.39,9.69,15.20,24.23,39.41,60.71,95.43,149.66,243.71
	1988,2.81,0.27,0.29,0.98,1.34,1.11,1.12,1.37,2.03,3.22,5.56,9.06,15.21,23.48,36.92,60.05,95.38,154.18,245.90
	1989,2.64,0.27,0.27,1.12,1.34,1.02,1.06,1.29,2.01,3.23,5.70,8.41,14.72,22.62,36.16,57.66,91.72,143.29,249.75
	1990,2.27,0.22,0.24,1.03,1.38,1.09,1.05,1.26,1.93,3.20,5.34,8.95,14.00,22.10,35.52,54.05,87.56,131.95,232.98
	1991,2.06,0.24,0.26,0.83,1.12,0.94,1.01,1.44,1.95,2.99,4.84,7.97,13.20,21.07,32.48,51.72,85.23,132.42,231.06
	1992,1.80,0.26,0.29,0.87,1.13,0.98,0.95,1.30,1.67,2.85,4.94,8.09,12.85,20.94,32.37,51.75,87.75,139.42,231.53
	1993,1.80,0.16,0.21,0.91,1.15,0.92,0.88,1.23,1.91,2.59,4.88,7.83,12.56,19.92,31.67,52.59,83.03,136.12,231.29
	1994,1.68,0.19,0.19,0.74,0.95,0.95,1.01,1.17,1.68,2.46,4.67,7.25,12.24,19.48,31.32,49.51,82.05,133.33,234.08
	1995,1.60,0.19,0.22,0.83,1.15,1.04,0.97,1.12,1.64,2.74,4.82,7.40,12.01,19.68,30.93,50.13,79.73,134.30,246.35
	1996,1.71,0.18,0.25,0.95,0.95,0.96,1.02,1.14,1.37,2.77,4.38,7.08,12.55,19.35,30.56,48.44,82.04,135.07,246.72
	1997,1.63,0.16,0.22,0.88,0.88,0.99,0.99,1.06,1.69,2.49,4.34,6.90,11.07,18.78,28.76,44.42,78.83,127.62,235.86
	1998,1.35,0.17,0.26,0.77,0.84,0.87,0.93,1.12,1.71,2.26,3.71,6.63,10.99,17.33,26.53,43.22,71.66,117.11,216.60
	1999,1.37,0.13,0.23,0.73,0.85,0.87,0.87,1.09,1.59,2.39,3.83,6.76,11.13,17.02,28.06,45.85,74.54,127.90,244.23
	2000,1.52,0.16,0.21,0.61,0.74,0.88,0.91,0.99,1.53,2.36,3.65,6.14,9.56,16.44,25.85,42.52,69.84,116.31,214.01
	2001,1.32,0.16,0.21,0.69,0.81,0.76,0.91,0.99,1.46,2.13,3.64,5.68,9.98,16.12,26.45,41.44,70.73,125.53,234.40
	2002,1.35,0.16,0.18,0.58,0.72,0.81,0.85,1.08,1.45,2.25,3.48,5.88,9.25,15.36,25.43,41.84,68.58,124.70,236.02
	2003,1.26,0.13,0.18,0.72,0.67,0.73,0.87,1.06,1.47,2.27,3.59,5.51,8.93,14.82,24.69,39.74,68.61,120.74,229.86
	2004,1.36,0.11,0.17,0.65,0.67,0.69,0.72,1.09,1.36,2.30,3.45,5.19,8.73,14.41,23.78,39.28,68.87,124.05,232.43
	2005,1.25,0.15,0.16,0.66,0.74,0.65,0.78,1.03,1.50,2.16,3.23,5.18,8.23,12.97,21.28,35.79,64.97,109.58,214.40
	2006,1.25,0.12,0.14,0.64,0.61,0.65,0.73,0.95,1.36,2.15,3.23,5.13,8.19,13.00,22.33,36.97,62.66,114.60,231.16
	2007,1.36,0.13,0.18,0.58,0.70,0.60,0.81,1.07,1.45,2.07,3.23,5.03,7.75,12.83,21.73,36.08,62.79,111.68,222.69
	2008,1.34,0.13,0.17,0.62,0.72,0.64,0.69,1.03,1.35,1.89,2.97,5.22,7.86,12.76,21.17,36.18,63.49,113.76,224.52
	2009,1.24,0.11,0.18,0.58,0.68,0.63,0.84,0.93,1.39,2.04,3.29,4.49,7.51,12.39,20.53,33.91,61.21,109.99,222.50
	2010,1.24,0.06,0.14,0.53,0.63,0.55,0.65,0.93,1.37,2.11,3.04,4.64,6.99,11.68,18.98,32.23,59.59,105.67,210.76
	2011,1.09,0.06,0.14,0.55,0.72,0.64,0.76,0.90,1.39,1.91,2.89,4.75,7.18,12.03,19.13,33.33,59.87,112.03,225.83
	2012,1.01,0.11,0.15,0.55,0.61,0.55,0.64,0.82,1.32,2.11,3.05,4.26,6.82,11.25,18.74,32.25,58.77,111.38,224.15
	2013,0.99,0.08,0.10,0.49,0.54,0.51,0.58,0.87,1.26,1.99,3.09,4.41,6.81,10.62,18.18,31.46,56.03,107.22,206.35
	2014,1.24,0.13,0.10,0.38,0.48,0.51,0.59,0.83,1.23,1.87,3.06,4.48,6.80,10.69,17.84,31.65,59.02,107.49,221.73
	2015,1.00,0.10,0.12,0.46,0.53,0.53,0.61,0.75,1.18,1.96,2.91,4.33,6.63,10.74,18.33,31.27,58.31,105.40,220.90
	2016,0.83,0.11,0.11,0.39,0.49,0.55,0.64,0.76,1.26,1.83,2.98,4.56,6.53,10.38,16.61,28.99,55.25,102.72,210.68
	2017,0.90,0.09,0.11,0.41,0.60,0.61,0.67,0.89,1.16,1.90,2.94,4.37,6.91,10.53,17.49,30.96,57.41,108.74,216.10
	2018,0.90,0.09,0.14,0.44,0.56,0.56,0.67,0.83,1.22,1.73,2.92,4.58,6.75,10.20,16.71,29.33,55.74,103.81,214.78
	2019,1.07,0.08,0.17,0.41,0.60,0.56,0.73,0.83,1.21,1.95,3.07,4.45,6.49,10.27,16.69,29.17,53.51,107.54,215.10
	2020,0.86,0.07,0.14,0.40,0.50,0.53,0.54,0.77,1.15,1.80,2.81,4.27,6.22,9.75,15.39,27.47,49.80,95.40,194.56
	2021,1.05,0.08,0.13,0.41,0.53,0.52,0.63,0.84,1.24,1.69,2.92,4.31,6.45,9.86,15.93,27.77,51.26,100.22,207.38
	2022,0.82,0.07,0.11,0.34,0.55,0.61,0.66,0.83,1.18,1.94,2.97,4.73,7.07,10.55,16.74,30.04,54.69,107.50,234.89
	"Table information:"
	"Units:"
	"/ 1000, Magnitude = Units"
	""
	"Footnotes:"
	"Rates from 1991 onward are based on the resident population concept. Before 1991, rates are based on the de facto population concept. Vitals data (births, deaths and marriages) is based on date of registration (not date of occurrence)."
	"Deaths per 1,000 mean estimated population in each age group."
	" "
	"Symbols:"
	".. figure not available"
	"C: Confidential"
	"E: Early Estimate"
	"P: Provisional"
	"R: Revised"
	"S: Suppressed"
	""
	"Status flags are not displayed"
	""
	"Table reference: "
	"DMM001AA"
	""
	"Last updated:"
	"16 November 2023 10:45am"
	""
	"Source: Statistics New Zealand"
	"Contact: Information Centre"
	"Telephone: 0508 525 525"
	"Email:info@stats.govt.nz"
	""
	""
	""
	# Death rates by age
	# https://infoshare.stats.govt.nz : Death Rates DMM : Age-specific death rates by sex, December years (total population) (Annual-Dec)
	# Total population, All Ages, All Years
	# Saved as AgeRates.csv
	library(dplyr)
	library(tidyr)

	AR <- read.csv("AgeRates.csv", skip=2) \|>
	gather(key="Age", value="per1k", 2:20) \|>
	mutate(low_n = as.numeric(gsub("[^0123456789]","", substr(Age,2,3))),
	Year = as.numeric(X.)) \|>
	filter(!.is.na(per1k))

	#Standard Population from https://seer.cancer.gov/stdpopulations/stdpop.singleages.html
	# US 2000 single years to 99, 100+
	# to make 5 years to 89 then 90+ as an exact match to the data

	library("rvest")
	url <- "https://seer.cancer.gov/stdpopulations/stdpop.singleages.html"
	population <- read_html(url) \|>
	html_table()
	StndPops <- population[[1]]
	US <- StndPops[2:102,1:2]
	US_clean <- US \|>
	mutate(age_n = floor(as.numeric(gsub("[^0123456789]","", US$Age))/5),
	age_n = ifelse(age_n > 18,18,age_n),
	pop_n = as.numeric(gsub(",","", `2000 U.S. Standard Population (Census P25-1130)`))) \|>
	summarise(.by=age_n,
	Pop = sum(pop_n)) \|>
	mutate(low_n = age_n*5) \|>
	select(low_n, Pop)

	combo <- AR \|> inner_join(US_clean, by="low_n") \|>
	summarise(.by=Year, Standard_Deaths = sum(Pop * per1k / 1000))
	precovid <- combo[combo$Year < 2020,]
	plot(precovid$Year, precovid$Standard_Deaths)