Removed data files

diff --git a/euromomo/Estimation_v42.R b/euromomo/Estimation_v42.R
deleted file mode 100644 (file)
index 6200441..0000000
--- a/euromomo/Estimation_v42.R
+++ /dev/null
@@ -1,397 +0,0 @@
-##################################\r
-### Version 4.2 - October 2018 ###\r
-##################################\r
-### Any questions or problems please contact: Jens Nielsen, Phone: +45 32683965 E-mail: nls@ssi.dk\r
-\r
-# Install required packages\r
-#install.packages("ISOweeks")\r
-\r
-ptrend <- 0.05\r
-p26 <- 0.05\r
-p52 <- 0.10\r
-\r
-### START: deaths data ###\r
-if (A_MOMO == 1) {\r
-  deaths <- try(read.table(paste0(indir,"/A-MOMO data.txt"), sep=",", dec=".", header=T)[,c("group","YoDi","WoDi","nb","nbc")])\r
-  if (inherits(deaths,"try-error")) {\r
-    stop(paste0("Error: ",indir,"/A-MOMO data.txt"))\r
-  }\r
-  deaths$deaths <- pmax(deaths$nb, deaths$nbc)\r
-  deaths$agegrp <- match(deaths$group, c("0to4","5to14","15to64","65P","Total")) - 1  # Convert group to integer (0-5)\r
-  deaths <- deaths[!is.na(deaths$agegrp), c("agegrp", "YoDi", "WoDi", "deaths")]\r
-  names(deaths)[2:3] <- c("year","week")\r
-}\r
-if (A_MOMO != 1) {\r
-  deaths <- try(read.table(paste0(indir,"/deaths.txt"), sep=";", dec=".", header=T)[,c("agegrp","year","week","deaths")])\r
-  if (inherits(deaths,"try-error")) {\r
-    stop(paste0("Error: ",indir,"/deaths.txt"))\r
-  }\r
-}\r
-deaths <- subset(deaths, (start_year*100+start_week <= year*100+week) & (year*100+week <= end_year*100+end_week))\r
-deaths[is.na(deaths)] <- 0\r
-deaths <- deaths[order(deaths$agegrp,deaths$year,deaths$week),]\r
-### END: deaths data ###\r
-\r
-### Start: Temperature data ###\r
-\r
-#' Temperature data from WeatherData\r
-#' PARM ET data containing then variables: date, pop3, NUTS3, temp\r
-#' PARM start_year first year to be included. Must be >= 2000\r
-#' PARM start_week first week in start_year to be included\r
-#' PARM end_year last year to be included\r
-#' PARM end_week last week in end_year to be included\r
-TemperatureData <- function(ET, start_year, start_week, end_year, end_week) {\r
-  ET$date <- as.Date(as.character(ET$date,"%Y%m%d"))\r
-  ET$NUTS3 <- as.character(ET$NUTS3)\r
-  ET[is.na(ET$pop3), "pop3"] <- 1\r
-  ET <- ET[order(ET$NUTS3, ET$date),]  # Ordering speeds summarizing a bit\r
-  ET <- aggregate(cbind(temp, pop3) ~ NUTS3 + date, data=ET, function(x) mean(x, na.rm = TRUE))\r
-  ET$pop3.sum <- with(ET, tapply(pop3, date, sum))[as.character(ET$date)]\r
-  ET$temp <- ET$temp * ET$pop3 / ET$pop3.sum\r
-  ET <- aggregate(temp ~ date, data = ET, function(x) sum(x, na.rm = TRUE))\r
-  ET <- merge(ET, data.frame(date = seq.Date(as.Date(paste0(start_year,"/01/01")), as.Date(paste0(end_year+1,"/01/01")), by = "day")), by = "date", all = TRUE)\r
-  ET$ISOweek <- ISOweek::ISOweek(ET$date)\r
-  ET <- subset(ET, (paste0(start_year,"-W",formatC(start_week, width=2, flag="0")) <= ISOweek) &\r
-                   (ISOweek <= paste0(end_year,"-W",formatC(end_week, width=2, flag="0"))))\r
-  ET <- aggregate(temp ~ ISOweek, data = ET, function(x) c(mean(x, na.rm = TRUE), range(x, na.rm = TRUE)))\r
-  ET <- cbind(as.data.frame(ET$ISOweek), as.data.frame(ET$temp))\r
-  colnames(ET) <- c("ISOweek","temp","tmin","tmax")\r
-  ET$wk <- order(ET$ISOweek)\r
-  ET$sin52 <- sin((2*pi/(365.25/7))*ET$wk)\r
-  ET$cos52 <- cos((2*pi/(365.25/7))*ET$wk)\r
-  ET$ptemp <- predict(glm(temp ~ sin52 + cos52, data=ET[!(is.na(ET$temp) | is.infinite(ET$temp)),]), ET)\r
-  ET$ptmin <- predict(glm(tmin ~ sin52 + cos52, data=ET[!(is.na(ET$tmin) | is.infinite(ET$tmin)),]), ET)\r
-  ET$ptmax <- predict(glm(tmax ~ sin52 + cos52, data=ET[!(is.na(ET$tmax) | is.infinite(ET$tmax)),]), ET)\r
-  ET[,c("wk","cos52","sin52")] <- NULL\r
-  ET$t = ifelse(is.na(ET$temp) | is.infinite(ET$temp), ET$ptemp, ET$temp)\r
-  ET$ET <- with(ET, (t-ptmax)*(t>ptmax)+(t-ptmin)*(t<ptmin))\r
-  ET$year <- as.numeric(substr(ET$ISOweek,1,4))\r
-  ET$week <- as.numeric(substr(ET$ISOweek,7,8))\r
-  ET[, c("ISOweek", "t")] <- NULL\r
-  return(ET <- ET[order(ET$year,ET$week),])\r
-}\r
-\r
-# Read weather data\r
-if (WeatherData == 1) {\r
-  ET <- try(read.table(paste0("http://euromomo.eu/methods/weather/wdata_",country.code,".txt"), header = TRUE, sep = ";", dec = ".")[, c("date","pop3","NUTS3","temp")])\r
-  if (inherits(ET,"try-error")) {\r
-    stop(paste0("Cannot download wdata_",country.code,".txt from http://euromomo.eu/methods/weather"))\r
-  }\r
-}\r
-if (WeatherData != 1) {\r
-  ET <- try(read.table(paste0(indir,"/wdata_",country.code,".txt"), header = TRUE, sep = ";", dec = ".")[, c("date","pop3","NUTS3","temp")])\r
-  if (inherits(ET,"try-error")) {\r
-    stop(paste0("Error: ",indir,"/wdata_",country.code,".txt"))\r
-  }\r
-}\r
-\r
-ET <- TemperatureData(ET,start_year,start_week,end_year,end_week)\r
-\r
-write.table(ET, file=paste0(indir,"/temperature.txt"), row.names = FALSE, quote = FALSE, sep =";", dec=".")\r
-\r
-rm(TemperatureData)\r
-### END: Temperature data ###\r
-\r
-### START: Population data ###\r
-if (population) {\r
-  pop_data <- try(read.table(paste0(indir,"/population.txt"), sep=";", dec=".", header=TRUE)[,c("agegrp","year","week","N")])\r
-  if (inherits(pop_data,"try-error")) {\r
-    stop(paste0("Error: ",indir,"/population.txt"))\r
-  }\r
-} \r
-### END: Population data ###\r
-\r
-### START: Merge data ###\r
-results4 <- try(read.table(paste0(indir,"/IA.txt"), sep=";", dec=".", header=TRUE))\r
-if (inherits(results4,"try-error")) {\r
-  stop(paste0("Error: ",indir,"/IA.txt"))\r
-}\r
-results4 <- merge(deaths, results4[,c("agegrp","year","week","IA")],  by=c("agegrp","year","week"), all=FALSE)\r
-results4 <- merge(results4,ET[,c("year","week","ET")], by=c("year","week"), all=FALSE)\r
-if (population) {\r
-  results4 <- merge(results4, pop_data,  by=c("agegrp","year","week"), all=FALSE)\r
-  rm(pop_data)\r
-} else {\r
-  results4$N <- 1\r
-}\r
-rm(deaths, ET)\r
-### END: Merge data ###\r
-\r
-### START: Prepare data ###\r
-\r
-# Function to get lag, forward and backward\r
-vecshift <- function(x, shift=0) {\r
-  if (shift==0) return(x)\r
-  if (shift>0) return(c(x[-(1:shift)], rep(NA,shift)))\r
-  if (shift<0) return(c(rep(NA, -shift), x[1:(length(x)+shift)]))\r
-}\r
-\r
-results4 <- subset(results4, (year*100+week >= start_year*100+start_week) & (year*100+week <= end_year*100+end_week))\r
-results4 <- results4[with(results4, order(agegrp, year, week)),]\r
-\r
-results4$season <- with(results4, year - (week<27))\r
-results4$summer <- with(results4, week>=21 & results4$week<=39)\r
-results4$winter <- !results4$summer\r
-\r
-# lags IA\r
-for (a in 0:4) {\r
-  for (s in sort(unique(results4[results4$agegrp==a, "season"]))) {\r
-    for (d in 0:IAlags) {\r
-      results4[results4$agegrp==a, paste("d", d, "_IA", s, sep="")] <- vecshift(results4[results4$agegrp==a, "IA"], -d) * as.numeric(results4[results4$agegrp==a, "season"]==s)\r
-    }\r
-  }\r
-}\r
-# warm/cold summer/winter and lags\r
-for (s in c("summer","winter")) {\r
-  results4[,paste0("cold_", s)] <- with(results4, -((ET<0) & get(s)) * ET)\r
-  results4[,paste0("warm_", s)] <- with(results4, ((ET>0) & get(s)) * ET)\r
-  for (t in c("cold","warm")) {\r
-    for (d in 0:ETlags) {\r
-      results4[,paste0("d", d, "_", t, "_", s)] <- NA\r
-      for (a in 0:4) {\r
-        results4[results4$agegrp==a,paste0("d", d, "_", t, "_", s)] <- vecshift(results4[results4$agegrp==a,paste0( t, "_", s)], -d)\r
-      }\r
-    }\r
-  }\r
-  results4[,paste0("cold_", s)] <- NULL\r
-  results4[,paste0("warm_", s)] <- NULL\r
-}\r
-rm(a, s, t, d, vecshift)\r
-results4$summer <- NULL\r
-results4$winter <- NULL\r
-\r
-# Create wk\r
-results4 <- results4[with(results4, order(agegrp, year, week)),]\r
-results4$wk <- unlist(lapply(table(results4$agegrp), seq))\r
-\r
-results4$sin52 <- sin((2*pi/(365.25/7)) * results4$wk)\r
-results4$cos52 <- cos((2*pi/(365.25/7)) * results4$wk)\r
-results4$sin26 <- sin((4*pi/(365.25/7)) * results4$wk)\r
-results4$cos26 <- cos((4*pi/(365.25/7)) * results4$wk)\r
-\r
-results4[is.na(results4)] <- 0\r
-### END: Prepare data ###\r
-\r
-### START: Estimation ###\r
-results4$EB <- NA\r
-results4$VlogB <- NA\r
-results4$EIA <- NA\r
-results4$VlogIA <- NA\r
-results4$EET <- NA\r
-results4$VlogET <- NA\r
-results4$Vdeaths <- NA\r
-\r
-for (a in 0:4) {\r
-  print(paste("### Age group ",a,"###"))\r
-  wk = "wk"\r
-  f <- paste(c("deaths ~ ",wk," sin52 + cos52 + sin26 + cos26", \r
-    grep("^d[0-9]", names(results4), value=TRUE)), collapse=" + ")\r
-  m <- try(glm(f, quasipoisson, offset = log(N), data=results4[results4$agegrp==a,]))\r
-  if (!inherits(m,"try-error") & m$converge & (median(results4[results4$agegrp==a, "deaths"]) > 0)) {\r
-    fa <- paste(c("deaths ~ sin52 + cos52 + sin26 + cos26",\r
-                  grep("^d[0-9]", names(results4), value=TRUE)), collapse=" + ")\r
-    ma <- glm(fa, quasipoisson, offset = log(N), data=results4[results4$agegrp==a,])\r
-    if (anova(m, ma, dispersion = max(1,sum(residuals(m, type = "deviance")^2)/df.residual(m)), test="LRT")$`Pr(>Chi)`[2]>ptrend) {\r
-      wk = ""\r
-      m <- ma\r
-    }\r
-    fa <- paste(c("deaths ~ ",wk, grep("^d[0-9]", names(results4), value=TRUE)), collapse=" + ")\r
-    ma <- glm(fa, quasipoisson, offset = log(N), data=results4[results4$agegrp==a,])\r
-    if (anova(m, ma, dispersion = max(1, sum(residuals(m, type = "deviance")^2)/df.residual(m)), test="LRT")$`Pr(>Chi)`[2]>max(p26,p52)) {\r
-      m <- ma\r
-    } else {\r
-      fa <- paste(c("deaths ~ ",wk," + cos52 + sin52", grep("^d[0-9]", names(results4), value=TRUE)), collapse=" + ")\r
-      ma <- glm(fa, quasipoisson, offset = log(N), data=results4[results4$agegrp==a,])\r
-      if (anova(m, ma, dispersion = max(1, sum(residuals(m, type = "deviance")^2)/df.residual(m)), test="LRT")$`Pr(>Chi)`[2]>p26) {\r
-        m <- ma\r
-      } else {\r
-        fa <- paste(c("deaths ~ ",wk, grep("^d[0-9]", names(results4), value=TRUE)), collapse=" + ")\r
-        ma <- glm(fa, quasipoisson, offset = log(N), data=results4[results4$agegrp==a,])\r
-        if (anova(m, ma, dispersion = max(1, sum(residuals(m, type = "deviance")^2)/df.residual(m)), test="LRT")$`Pr(>Chi)`[2]>p52) {\r
-          m <- ma\r
-        }\r
-      }\r
-    }\r
-  } else {\r
-    if (inherits(m,"try-error")) print("### Could not fit model ###")\r
-    if (!m$converge) print("### Model did not converge ###")\r
-    if (median(results4[results4$agegrp==a, "deaths"]) == 0) print("### Zero inflated ###")\r
-    print("### Simple model with only trend used ###")\r
-    f <- paste(c("deaths ~ wk"))\r
-    m <- glm(f, quasipoisson, offset = log(N), data=results4[results4$agegrp==a,])\r
-  }\r
-  print(summary(m, dispersion = max(1, sum(residuals(m, type = "deviance")^2)/df.residual(m))))\r
-  # Baseline\r
-  results4.B <- results4[results4$agegrp==a,]\r
-  for (d in 0:IAlags) {\r
-    for (s in min(results4.B$season):max(results4.B$season)) {\r
-      results4.B[,paste("d", d, "_IA", s, sep="")] <- 0\r
-    }\r
-    for (s in c("summer","winter")) {\r
-      results4.B[,paste("d", d, "_warm_", s, sep="")] <- 0\r
-      results4.B[,paste("d", d, "_cold_", s, sep="")] <- 0\r
-    }\r
-  }\r
-  results4[results4$agegrp==a,]$EB <- exp(predict.glm(m, newdata=results4.B, se.fit=TRUE)$fit)\r
-  results4[results4$agegrp==a,]$VlogB <- predict.glm(m, newdata=results4.B, dispersion = max(1, sum(residuals(m, type = "deviance")^2)/df.residual(m)), se.fit=TRUE)$se.fit^2\r
-  # IA\r
-  results4.IA <- results4[results4$agegrp==a,]\r
-  for (s in c("summer","winter")) {\r
-    for (d in 0:ETlags) {\r
-      results4.IA[,paste("d", d, "_warm_", s, sep="")] <- 0\r
-      results4.IA[,paste("d", d, "_cold_", s, sep="")] <- 0\r
-    }\r
-  }\r
-  results4[results4$agegrp==a,]$EIA <- exp(predict.glm(m, newdata=results4.IA, se.fit=TRUE)$fit)\r
-  results4[results4$agegrp==a,]$VlogIA <- predict.glm(m, newdata=results4.IA, dispersion = max(1, sum(residuals(m, type = "deviance")^2)/df.residual(m)), se.fit=TRUE)$se.fit^2\r
-  # ET\r
-  results4.ET <- results4[results4$agegrp==a,]\r
-  for (d in 0:IAlags) {\r
-    for (s in sort(unique(results4.ET$season))) {\r
-      results4.ET[,paste("d", d, "_IA", s, sep="")] <- 0\r
-    }\r
-  }\r
-  results4[results4$agegrp==a,]$EET <-  exp(predict.glm(m, newdata=results4.ET, se.fit=T)$fit)\r
-  results4[results4$agegrp==a,]$VlogET <- predict.glm(m, newdata=results4.ET, dispersion = max(1, sum(residuals(m, type = "deviance")^2)/df.residual(m)), se.fit=T)$se.fit^2\r
-\r
-  results4[results4$agegrp==a,]$Vdeaths <- with(results4[results4$agegrp==a,], EB * max(1, sum(residuals(m, type = "deviance")^2)/df.residual(m))) \r
-}\r
-\r
-# Delete external objects\r
-rm(a, f, fa, s, d, m, ma, results4.B, results4.ET, results4.IA, ptrend, p26, p52, wk)\r
-### END: Estimation ###\r
-\r
-### START: Post estimation ###\r
-# Keep relevant variables #\r
-results4 <- results4[, c("agegrp", "year", "week", "deaths", "N", "IA", "ET", "Vdeaths", "EB", "VlogB", "EIA", "VlogIA", "EET", "VlogET")]\r
-\r
-# Baseline, EIA and EET estimation variances - not on log scale\r
-results4$VB <- with(results4, (exp(VlogB)-1)*exp(2*log(EB) + VlogB))\r
-results4$VIA <- with(results4, (exp(VlogIA)-1)*exp(2*log(EIA) + VlogIA)) \r
-results4$VET <- with(results4, (exp(VlogET)-1)*exp(2*log(EET) + VlogET))\r
-\r
-# Effects of IA and ET\r
-results4$EdIA <- with(results4, EIA - EB)\r
-results4[is.na(results4$EdIA),"EdIA"] <- 0\r
-results4$EdET <- with(results4, EET - EB)\r
-results4[is.na(results4$EdET),"EdET"] <- 0\r
-# Excess relative to baseline\r
-results4$excess <- with(results4, deaths - EB)\r
-# Unexplained excess\r
-results4$uexcess <- with(results4, deaths - (EB + EdIA + EdET))\r
-# Exclude negative IA effects\r
-if (IArest) results4$uexcess <- with(results4, deaths - (EB + pmax(0,EdIA) + EdET))\r
-\r
-# Baseline 2/3 residual confidence intervals\r
-results4$RVB <- with(results4, ((2/3)*(EB^(2/3-1))^2)*Vdeaths + ((2/3)*(EB^(2/3-1))^2)*VB)\r
-results4[with(results4, is.na(RVB) | is.infinite(RVB)), "RVB"] <- 0\r
-results4$EB_95L <- with(results4, pmax(0,sign((sign(EB)*abs(EB)^(2/3))-1.96*sqrt(RVB))*abs((sign(EB)*abs(EB)^(2/3))-1.96*sqrt(RVB))^(3/2)))\r
-results4$EB_95U <- with(results4, sign((sign(EB)*abs(EB)^(2/3))+1.96*sqrt(RVB))*abs((sign(EB)*abs(EB)^(2/3))+1.96*sqrt(RVB))^(3/2))\r
-\r
-# EdIA 2/3 residual confidence intervals\r
-results4$RVdIA <- with(results4, ((2/3)*(EB^(2/3-1))^2)*VB + ((2/3)*(EIA^(2/3-1))^2)*VIA)\r
-results4[with(results4, is.na(RVdIA) | is.infinite(RVdIA)), "RVdIA"] <- 0\r
-results4$EdIA_95L <- with(results4, sign((sign(EdIA)*abs(EdIA)^(2/3))-1.96*sqrt(RVdIA))*abs((sign(EdIA)*abs(EdIA)^(2/3))-1.96*sqrt(RVdIA))^(3/2))\r
-results4$EdIA_95U <- with(results4, pmax(EdIA_95L,sign((sign(EdIA)*abs(EdIA)^(2/3))+1.96*sqrt(RVdIA))*abs((sign(EdIA)*abs(EdIA)^(2/3))+1.96*sqrt(RVdIA))^(3/2)))\r
-\r
-# EdET 2/3 residual confidence intervals\r
-results4$RVdET <- with(results4, ((2/3)*(EB^(2/3-1))^2)*VB + ((2/3)*(EET^(2/3-1))^2)*VET)\r
-results4[with(results4, is.na(RVdET) | is.infinite(RVdET)), "RVdET"] <- 0\r
-results4$EdET_95L <- with(results4, sign((sign(EdET)*abs(EdET)^(2/3))-1.96*sqrt(RVdET))*abs((sign(EdET)*abs(EdET)^(2/3))-1.96*sqrt(RVdET))^(3/2))\r
-results4$EdET_95U <- with(results4, pmax(EdET_95L,sign((sign(EdET)*abs(EdET)^(2/3))+1.96*sqrt(RVdET))*abs((sign(EdET)*abs(EdET)^(2/3))+1.96*sqrt(RVdET))^(3/2)))\r
-\r
-results4$summer <- with(results4, ifelse(week>=21 & week<=39, year, NA))\r
-results4$winter <- with(results4, ifelse(week<=20 | week>=40, year - (week<=20), NA))\r
-\r
-# Order\r
-results4 <- results4[with(results4, order(agegrp, year, week)),]\r
-\r
-cummulate <- function(x, pos=FALSE) {\r
-  # x = variable, EdIA\r
-  y <- x[,1]\r
-  if (pos) y <- x[,1] * (x[,2] > 0)\r
-  return(cumsum(y))\r
-}\r
-cCI <- function(x) {\r
-  # x = cEB, cVB, cE*, cV*\r
-  colnames(x) <- c("cEB", "cVB", "cE", "cV")\r
-  x$cEd <- x$cE - x$cEB\r
-  x$cRVd <- ((2/3)*(x$cEB^(2/3-1))^2)*x$cVB + ((2/3)*(x$cE^(2/3-1))^2)*x$cV\r
-  x[with(x, is.na(cRVd) | is.infinite(cRVd)), "cRVd"] <- 0\r
-  x$cCI_95L <- with(x, sign((sign(cEd)*abs(cEd)^(2/3))-1.96*sqrt(cRVd))*abs((sign(cEd)*abs(cEd)^(2/3))-1.96*sqrt(cRVd))^(3/2))\r
-  x$cCI_95U <- with(x, sign((sign(cEd)*abs(cEd)^(2/3))+1.96*sqrt(cRVd))*abs((sign(cEd)*abs(cEd)^(2/3))+1.96*sqrt(cRVd))^(3/2))\r
-  return(x[, c("cEd", "cCI_95L", "cCI_95U")])\r
-}\r
-\r
-# EdIA and EdET residual variances\r
-for (s in c("summer", "winter", "year")) {\r
-  nn <- !is.na(results4[,s])  # logical vector indicating season\r
-  for (a in 0:4) {\r
-    ag <- (results4$agegrp==a)\r
-    for (v in c("excess","uexcess")) {\r
-      results4[nn & ag ,paste0("c", v, "_", s)] <- NA\r
-      for (sy in sort(unique(results4[,s]))) {\r
-        results4[(results4[,s]==sy) & nn & ag, paste0("c", v, "_", s)] <-\r
-          cummulate(results4[(results4[,s]==sy) & nn & ag, c(v, "EdIA")], FALSE)\r
-      }\r
-    }\r
-    for (v in c("B","IA")) {\r
-      results4[nn & ag ,paste0("cE", v, "_", s)] <- NA\r
-      results4[nn & ag ,paste0("cV", v, "_", s)] <- NA\r
-      for (sy in sort(unique(results4[,s]))) {\r
-        results4[(results4[,s]==sy) & nn & ag, paste0("cE", v, "_", s)] <-\r
-          cummulate(results4[(results4[,s]==sy) & nn & ag, c(paste0("E",v),"EdIA")], IArest)\r
-        results4[(results4[,s]==sy) & nn & ag, paste0("cV", v, "_", s)] <-\r
-          cummulate(results4[(results4[,s]==sy) & nn & ag, c(paste0("V",v),"EdIA")],  IArest)\r
-      }\r
-    }\r
-    results4[nn & ag, paste0("cEd", v, "_", s)] <- NA\r
-    results4[nn & ag, paste0("cEd", v, "_", s, "_95L")] <- NA\r
-    results4[nn & ag, paste0("cEd", v, "_", s, "_95U")] <- NA\r
-    results4[nn & ag, c(paste0("cEd", v, "_", s), paste0("cEd", v, "_", s, "_95L"), paste0("cEd", v,"_", s, "_95U"))] <-\r
-      cCI(results4[nn & ag, c(paste0("cEB_", s), paste0("cVB_", s), paste0("cE",v,"_", s), paste0("cV",v,"_",s))])\r
-    for (v in c("B","ET")) {\r
-      results4[nn & ag ,paste0("cE", v, "_", s)] <- NA\r
-      results4[nn & ag ,paste0("cV", v, "_", s)] <- NA\r
-      for (sy in sort(unique(results4[,s]))) {\r
-        results4[(results4[,s]==sy) & nn & ag, paste0("cE", v, "_", s)] <-\r
-          cummulate(results4[(results4[,s]==sy) & nn & ag, c(paste0("E",v),"EdIA")], FALSE)\r
-        results4[(results4[,s]==sy) & nn & ag, paste0("cV", v, "_", s)] <-\r
-          cummulate(results4[(results4[,s]==sy) & nn & ag, c(paste0("V",v),"EdIA")],  FALSE)\r
-      }\r
-    }\r
-    results4[nn & ag ,paste0("cEd", v, "_", s)] <- NA\r
-    results4[nn & ag ,paste0("cEd", v, "_", s, "_95L")] <- NA\r
-    results4[nn & ag ,paste0("cEd", v, "_", s, "_95U")] <- NA\r
-    results4[nn & ag ,c(paste0("cEd", v, "_", s), paste0("cEd", v, "_", s, "_95L"), paste0("cEd", v, "_", s, "_95U"))] <-\r
-      cCI(results4[nn & ag , c(paste0("cEB_", s), paste0("cVB_", s), paste0("cE",v,"_", s), paste0("cV",v,"_",s))])\r
-  }\r
-}\r
-\r
-results4$country <- country\r
-results4$IArestricted <- as.integer(IArest)\r
-results4 <- results4[, c("country", "IArestricted", "agegrp", "year", "week", "deaths", "Vdeaths", "N", "IA", "ET",\r
-                         "EB", "EB_95L", "EB_95U", "VB", \r
-                         "EIA", "VIA", "EET", "VET", \r
-                         "EdIA", "EdIA_95L", "EdIA_95U", \r
-                         "EdET", "EdET_95L", "EdET_95U", \r
-                         "cexcess_year", "cuexcess_year", \r
-                         "cEdIA_year", "cEdIA_year_95L", "cEdIA_year_95U", \r
-                         "cEdET_year", "cEdET_year_95L", "cEdET_year_95U", \r
-                         "summer", "cexcess_summer", "cuexcess_summer", \r
-                         "cEdIA_summer", "cEdIA_summer_95L", "cEdIA_summer_95U", \r
-                         "cEdET_summer", "cEdET_summer_95L", "cEdET_summer_95U", \r
-                         "winter", "cexcess_winter", "cuexcess_winter", \r
-                         "cEdIA_winter", "cEdIA_winter_95L", "cEdIA_winter_95U", \r
-                         "cEdET_winter", "cEdET_winter_95L", "cEdET_winter_95U")]\r
-\r
-if (IArest) { \r
-  write.table(results4, file=paste0(outdir,"/",country,"_output_v4_IArestricted.txt"), \r
-      row.names = FALSE, quote = FALSE, sep =";", dec=".", na="") \r
-} else { \r
-  write.table(results4, file=paste0(outdir,"/",country,"_output_v4.txt"), \r
-      row.names = FALSE, quote = FALSE, sep =";", dec=".", na="")\r
-}\r
-\r
-rm(a, s, sy, v, nn, ag, cummulate, cCI, results4)\r
-### END: Post estimation ###\r

diff --git a/euromomo/FluMOMO_v42.R b/euromomo/FluMOMO_v42.R
deleted file mode 100644 (file)
index 3372f23..0000000
--- a/euromomo/FluMOMO_v42.R
+++ /dev/null
@@ -1,77 +0,0 @@
-# Install required packages (if not already installed)\r
-#install.packages("ISOweek")\r
-\r
-\r
-### Clear enviromnet i.e. delete all data and variabels\r
-rm(list = ls())\r
-# Clear console\r
-cat("\014")\r
-\r
-### Country\r
-country <- ""\r
-country.code <- ""\r
-\r
-### Work directory - directory where the R programs are placed\r
-wdir <- "."\r
-\r
-### Period: Start and end (both included)\r
-start_year <- 2013\r
-start_week <- 40\r
-end_year <- 2018\r
-end_week <- 40\r
-\r
-### Deaths data source\r
-### Must be placed in the subdirectory /data in the work directory\r
-# 1 = A-MOMO complete file, renamed to A-MOMO data.txt\r
-# 0 = you provide a ;-separated file: deaths.txt, containing at least the variable: agegrp, year, week, deaths\r
-A_MOMO <- 1\r
-\r
-### Weather data source\r
-# 1 = automatic download from EuroMOMO website\r
-# 0 = you provide a ;-separated file: wdata_'country.code'.txt, containing at least the variables: date, pop3, NUTS3, temp and placed in the subdirectory /data in the work directory\r
-WeatherData <- 1\r
-\r
-### Population data (TRUE/FALSE)\r
-### A ;-separated file: population.txt, must be placed in the subdirectory /data in the work directory\r
-population <- FALSE\r
-\r
-# Restrict IA to only positive (TRUE/FALSE)\r
-IArest <- TRUE\r
-\r
-# Number of IA lags\r
-# 0 = no lag, 1 = one week lag, ...(max=9)\r
-IAlags <- 2\r
-\r
-# Number of OF lags\r
-# 0 = no lag, 1 = one week lag, ...(max=9)\r
-ETlags <- 2\r
-\r
-\r
-### Directory setup ######################################################################\r
-\r
-### Create general output dir\r
-if (!dir.exists(paste0(wdir,"/FluMOMO_",end_year,"w",formatC(end_week, width=2, flag="0")))) {\r
-  dir.create(paste0(wdir,"/FluMOMO_",end_year,"w",formatC(end_week, width=2, flag="0")))\r
-}\r
-### Copy data directory - directory where input data are stored\r
-indir <- paste0(wdir,"/FluMOMO_",end_year,"w",formatC(end_week, width=2, flag="0"),"/data")\r
-if (!dir.exists(indir)) dir.create(indir)\r
-file.copy(from = list.files(paste0(wdir,"/data"), all.files = TRUE, full.names = TRUE, no.. = TRUE),\r
-          to = indir, overwrite = TRUE, recursive = FALSE, copy.mode = TRUE)\r
-#file.remove(list.files(paste0(wdir,"/data"), all.files = TRUE, full.names = TRUE, no.. = TRUE))\r
-\r
-### Create output directory - directory where output are created\r
-outdir <- paste0(wdir,"/FluMOMO_",end_year,"w",formatC(end_week, width=2, flag="0"),"/output")\r
-if (!dir.exists(outdir)) dir.create(outdir)\r
-#########################################################################################\r
-\r
-# Estimation\r
-source(paste0(wdir,"/Estimation_v42.R"), echo = FALSE)\r
-# Output: txt-files\r
-source(paste0(wdir,"/Output_txt_v42.R"))\r
-# Output: graphs IA and ET\r
-source(paste0(wdir,"/Output_IA_ET_v42.R"))\r
-# Output: graphs over calendar time\r
-source(paste0(wdir,"/Output_calendar_v42.R"))\r
-# Output: graphs cumulated IA\r
-source(paste0(wdir,"/Output_cumulated_v42.R"))\r

diff --git a/euromomo/Output_IA_ET_v42.R b/euromomo/Output_IA_ET_v42.R
deleted file mode 100644 (file)
index 64dbe0e..0000000
--- a/euromomo/Output_IA_ET_v42.R
+++ /dev/null
@@ -1,88 +0,0 @@
-### Ambient temperatures ###\r
-ET <- read.table(file=paste0(indir,"/temperature.txt"), header = T, sep =";", dec=".")\r
-ET <- ET[with(ET, order(year, week)),]\r
-ET$t = ifelse((ET$week %% 2) == 0, min(ET$temp, ET$ptmin, na.rm = TRUE), max(ET$temp, ET$ptmax, na.rm = TRUE))\r
-ET$temp = ifelse(is.na(ET$temp), ET$ptemp, ET$temp)\r
-ET$Uexecc <- with(ET, pmax(ptmax,temp))\r
-ET$Lexecc <- with(ET, pmin(ptmin,temp))\r
-ET$wk <- 1:nrow(ET)\r
-ET$yw <- sprintf("%04iw%02d", ET$year, ET$week)\r
-\r
-png(paste0(outdir,"/temperature_v4R.png"), width=1200, height=800, res=130)\r
-par(mar=c(9,4,3,2))\r
-with(ET, {\r
-  plot(x=wk, y=t, type="n", xlab=NA, ylab="Degree Celsius", \r
-      main="Ambient temperatures", bty="l", xaxt="n")\r
-  axis(1, at=wk[as.integer(substr(yw,6,7)) %in% c(1,27)], \r
-      labels=yw[as.integer(substr(yw,6,7)) %in% c(1,27)], las=2, cex.axis=0.9)\r
-  polygon(x=c(wk,rev(wk)), y=c(Uexecc, rev(ptmax)),\r
-    border=do.call(rgb, c(as.list(col2rgb("red")/255), alpha=0.5)),\r
-    col=do.call(rgb, c(as.list(col2rgb("red")/255), alpha=0.5)))\r
-  polygon(x=c(wk,rev(wk)), y=c(Lexecc, rev(ptmin)),\r
-    border=do.call(rgb, c(as.list(col2rgb("blue")/255), alpha=0.5)),\r
-    col=do.call(rgb, c(as.list(col2rgb("blue")/255), alpha=0.5)))\r
-  points(x=wk, y=ptemp, type="l", col="black")\r
-  points(x=wk, y=ptmin, type="l", col="blue")\r
-  points(x=wk, y=ptmax, type="l", col="red")\r
-  points(x=wk, y=temp, pch=19, cex=0.7)\r
-  mtext("Year-week", side=1, line=4.5)\r
-  legend("bottom", c("expected temperature", "max expected temperature", "min expected temperature"),\r
-    lty="solid", col=c("black", "red", "blue"), lwd=2,\r
-    horiz=TRUE, inset=c(0,-0.39), xpd=NA, bty="n", cex=1)\r
-  legend("bottom", c("observed temperature", "extreme heat", "extreme cold"),\r
-    col=c("black", do.call(rgb, c(as.list(col2rgb("red")/255), alpha=0.5)), do.call(rgb, c(as.list(col2rgb("blue")/255), alpha=0.5))), pch=c(19,15,15),\r
-    horiz=TRUE, inset=c(0,-0.46), xpd=NA, bty="n", cex=1, pt.cex=c(1,2,2))  \r
-})\r
-dev.off()\r
-rm(ET)\r
-\r
-\r
-### Influenza Activity ###\r
-\r
-results4 <- read.table(\r
-    file = paste0(outdir, "/", country, "_output_v4", ifelse(IArest, "_IArestricted", ""), ".txt"), \r
-    header = TRUE, sep =";", dec=".") \r
-results4 <- results4[with(results4, order(agegrp, year, week)),]\r
-results4$wk <- unlist(lapply(table(results4$agegrp), seq))\r
-results4$agegrp.labels <- ordered(results4$agegrp, \r
-    labels = c("0-4 years", "5-14 years", "15-64 years", "Aged 65", "Total"))\r
-results4$yw <- sprintf("%04iw%02d", results4$year, results4$week)\r
-\r
-\r
-png(paste0(outdir,"/IA_agegroups_v4R.png"), width=1200, height=1600, res=130)\r
-par(mar=c(3,4,2,2), oma=c(5,2,2,0), mfrow=c(5,1))\r
-for (a in 0:4)\r
-  with(results4[(results4$agegrp==a),], {\r
-    plot(x=wk, y=IA, xaxt="n", ylab=NA, xlab=NA, type="n", bty="l", \r
-        main=unique(results4$agegrp.labels)[a+1])\r
-    if (a==4) {\r
-      axis(1, at=wk[as.integer(substr(yw,6,7)) %in% c(1,27)], \r
-          labels=yw[as.integer(substr(yw,6,7)) %in% c(1,27)], las=2, cex.axis=0.9)\r
-    }\r
-    grid(nx=NA, ny=NULL)\r
-    abline(v=wk[as.integer(substr(yw,6,7)) %in% c(1,27)], col="lightgray", lty="dotted")\r
-    points(x=wk, y=IA, col="red", lwd=2, type="l")\r
-  })\r
-mtext("Influenza Activity per week", side=2, outer=TRUE)\r
-mtext("Influenza Activity by age group", side=3, outer=TRUE, adj=0, cex=1.2)\r
-mtext("year-week", side=1, line=5)\r
-dev.off()\r
-\r
-\r
-for (a in 0:4) {\r
-  png(paste0(outdir,"/IA_agegroup_",a,"_v4R.png"), width=1200, height=800, res=130)\r
-  par(mar=c(6,4,4,2))\r
-    with(results4[(results4$agegrp==a),], {\r
-      plot(x=wk, y=IA, xaxt="n", ylab="Influenza Activity per week", xlab=NA, type="n", bty="l")\r
-      axis(1, at=wk[as.integer(substr(yw,6,7)) %in% c(1,27)], \r
-          labels=yw[as.integer(substr(yw,6,7)) %in% c(1,27)], las=2, cex.axis=0.9)\r
-      grid(nx=NA, ny=NULL)\r
-      abline(v=wk[as.integer(substr(yw,6,7)) %in% c(1,27)], col="lightgray", lty="dotted")\r
-      mtext(paste("Influenza Activity, age group:",unique(results4$agegrp.labels)[a+1]), \r
-          side=3, line=1, adj=0)\r
-      points(x=wk, y=IA, col="red", lwd=2, type="l")\r
-      mtext("year-week", side=1, line=4.5)\r
-    })\r
-  dev.off()\r
-}\r
-rm(a)
\ No newline at end of file

diff --git a/euromomo/Output_calendar_v42.R b/euromomo/Output_calendar_v42.R
deleted file mode 100644 (file)
index 10e3a96..0000000
--- a/euromomo/Output_calendar_v42.R
+++ /dev/null
@@ -1,110 +0,0 @@
-### Graphs - calendar time ###\r
-\r
-if (IArest) {\r
-  results4 <- read.table(file=paste0(outdir,"/",country,"_output_v4_IArestricted.txt"), header = TRUE, sep =";", dec=".")\r
-  results4$EIA <- results4$EB + pmax(0,results4$EdIA)\r
-  results4$EIAET <- results4$EB + pmax(0,results4$EdIA) + results4$EdET\r
-  note <- "Note: Negative effects of IA are not shown"\r
-} else {\r
-  results4 <- read.table(file=paste0(outdir,"/",country,"_output_v4.txt"), header = TRUE, sep =";", dec=".")\r
-  results4$EIA <- results4$EB + results4$EdIA\r
-  results4$EIAET <- results4$EB + results4$EdIA + results4$EdET\r
-  note <- ""\r
-}\r
-results4 <- results4[with(results4, order(agegrp, year, week)),]\r
-results4$wk <- unlist(lapply(table(results4$agegrp), seq))\r
-results4$agegrp.labels <- ordered(results4$agegrp, \r
-    labels = c("0-4 years","5-14 years","15-64 years","Aged 65","Total"))\r
-results4$yw <- sprintf("%04dw%02d", results4$year, results4$week)\r
-\r
-\r
-plotDeaths <- function(a, mortality=FALSE, annot=TRUE) {\r
-  if (mortality) {\r
-    results4[,c("deaths","EB","EB_95L","EB_95U","EIAET","EIA")] <- \r
-      100000 * results4[,c("deaths","EB","EB_95L","EB_95U","EIAET","EIA")] / results4[,"N"]\r
-  }\r
-  with(results4[(results4$agegrp==a),], {\r
-    plot(wk, EB, type="n", xaxt="n", bty="l", xlab=NA, ylab=NA, \r
-        ylim=range(pretty(range(c(EIAET, EIA, EB_95U, EB_95L)))))\r
-    if (annot) {\r
-      axis(1, at=wk[as.integer(substr(yw,6,7)) %in% c(1,27)], \r
-          labels=yw[as.integer(substr(yw,6,7)) %in% c(1,27)], las=2, cex.axis=0.9)\r
-    }\r
-    grid(nx=NA, ny=NULL)\r
-    abline(v=wk[as.integer(substr(yw,6,7)) %in% c(1,27)], col="lightgray", lty="dotted")\r
-    polygon(x=c(wk,rev(wk)), y=c(deaths,rev(EB)), \r
-      col=do.call(rgb, c(as.list(col2rgb("gray")/255), alpha=0.7)),\r
-      border=do.call(rgb, c(as.list(col2rgb("gray")/255), alpha=0.7)))\r
-    points(wk, EIAET, col="darkgreen", lwd=2, type="l")\r
-    points(wk, EIA, col="red", lwd=2, type="l")\r
-    points(wk, EB, lwd=2, type="l")\r
-    points(wk, EB_95L, lty="dashed", lwd=2, type="l")\r
-    points(wk, EB_95U, lty="dashed", lwd=2, type="l")\r
-  })\r
-  if (annot) {\r
-    mtext(sprintf("FluMOMO v4 - week %s, %s", end_week, end_year), side=3, line=1, adj=1, cex=0.8)\r
-    mtext("year-week", side=1, line=4.5)\r
-    if (mortality) {\r
-      mtext(paste("Mortality by age group:",unique(results4$agegrp.labels)[a+1]), side=3, line=1, adj=0, cex=1.2)\r
-      mtext("Deaths / 100.000 per week", side=2, line=2.5)\r
-    } else {\r
-      mtext(paste("Number of deaths, age group:",unique(results4$agegrp.labels)[a+1]), side=3, line=1, adj=0, cex=1.2)\r
-      mtext("Number of deaths per week", side=2, line=2.5)\r
-    }\r
-    legend("bottom", c("Effect of Influenza Activity (IA)",\r
-        "Effect of excess temperature (on top of IA)", "Baseline", "95% confidence interval"), \r
-        lwd=2, col=c("red","darkgreen","black","black"), lty=c(rep("solid",3),"dashed"), \r
-        bty="n", ncol=2, xpd=NA, inset=c(0,-0.5), seg.len=4)\r
-  }\r
-}\r
-\r
-\r
-plotDeathsMultiple <- function(mortality=FALSE) {\r
-  par(mar=c(3,2,3,2), mfrow=c(5,1), oma=c(8,3.5,3,0))\r
-  for(a in 0:4) {\r
-    plotDeaths(a, mortality=mortality, annot=FALSE)\r
-    mtext(unique(results4$agegrp.labels)[a+1], side=3, line=1)\r
-    if (a==4) {\r
-      with(results4[(results4$agegrp==a),], \r
-        axis(1, at=wk[as.integer(substr(yw,6,7)) %in% c(1,27)], \r
-          labels=yw[as.integer(substr(yw,6,7)) %in% c(1,27)], las=2))\r
-    }\r
-  }\r
-  mtext(sprintf("FluMOMO v4 - week %s, %s", end_week, end_year), side=3, line=0, adj=0.9, cex=0.8, outer=TRUE)\r
-  mtext("year-week", side=1, line=5)\r
-  if (mortality) {\r
-    mtext("Mortality by age group", side=3, line=0, adj=0, cex=1.2, outer=TRUE)\r
-    mtext("Deaths / 100.000 per week", side=2.5, line=1, outer=TRUE)\r
-  } else {\r
-    mtext("Number of deaths by age group", side=3, line=0, adj=0, cex=1.2, outer=TRUE)\r
-    mtext("Number of deaths per week", side=2.5, line=1, outer=TRUE)\r
-  }\r
-  legend("bottom", c("Effect of Influenza Activity (IA)",\r
-      "Effect of excess temperature (on top of IA)", "Baseline", "95% confidence interval"), \r
-      lwd=2, col=c("red","darkgreen","black","black"), lty=c(rep("solid",3),"dashed"), \r
-      bty="n", ncol=2, xpd=NA, inset=c(0,-0.9), seg.len=4)\r
-}\r
-\r
-\r
-png(paste0(outdir,"/deaths_agegroups_v4", ifelse(IArest, "_IArestricted", ""), ".png"), width=1200, height=1600, res=130)\r
-plotDeathsMultiple(mortality=FALSE)\r
-dev.off()\r
-for (a in 0:4) {\r
-  png(paste0(outdir, "/deaths_agegroup_", a, "_v4", ifelse(IArest, "_IArestricted", ""), ".png"), width=1200, height=800, res=130)\r
-  par(mar=c(10,4,3,2))\r
-  plotDeaths(a, mortality=FALSE)\r
-  dev.off()\r
-}\r
-\r
-if (population) {\r
-  png(paste0(outdir,"/mr_agegroups_v4", ifelse(IArest, "_IArestricted", ""), ".png"), width=1200, height=1600, res=130)\r
-  plotDeathsMultiple(mortality=TRUE)\r
-  dev.off()  \r
-  for (a in 0:4) {\r
-    png(paste0(outdir,"/mr_agegroup", a, "_v4", ifelse(IArest, "_IArestricted", ""), ".png"), width=1200, height=800, res=130)\r
-    par(mar=c(10,4,3,2))\r
-    plotDeaths(a, mortality=TRUE)\r
-    dev.off()\r
-  }\r
-}\r
-rm(plotDeaths, plotDeathsMultiple, results4, a, note)\r

diff --git a/euromomo/Output_cumulated_v42.R b/euromomo/Output_cumulated_v42.R
deleted file mode 100644 (file)
index 48f3e71..0000000
--- a/euromomo/Output_cumulated_v42.R
+++ /dev/null
@@ -1,115 +0,0 @@
-### Graphs - cumulated ###\r
-\r
-results4 <- read.table(\r
-      paste0(outdir, "/", country, "_output_v4", ifelse(IArest, "_IArestricted", ""), ".txt"), \r
-      header = TRUE, sep =";", dec=".")\r
-note <- ifelse(IArest, "Note: Negative effects of IA are not shown", "")\r
-results4$agegrp.labels <- factor(results4$agegrp, \r
-    labels = c("0-4 years", "5-14 years", "15-64 years", "Aged 65", "Total"))\r
-\r
-\r
-pal <- c("#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#A65628", "#F781BF")\r
-\r
-plotCumulSingle <- function(a, mortality=FALSE, lwd=2, ylab=NULL) {\r
-  if (mortality) {\r
-    yvar <- "cm"\r
-    ylb <- "Deaths / 100,000"\r
-    title <- paste0("Cumulated ",s," mortality attributable to ",t,", age group: ",unique(results4$agegrp.labels)[a+1])\r
-  } else {\r
-    yvar <- "cd"\r
-    ylb <- "Number of deaths"\r
-    title <- paste0("Cumulated ",s," number of deaths attributable to ",t,", age group: ",unique(results4$agegrp.labels)[a+1])\r
-  }\r
-  if (!is.null(ylab)) ylb <- ylab\r
-  xlb <- "Week number"\r
-  if (is.na(ylb)) xlb <- NA\r
-  \r
-  with(out[(out$agegrp==a),], {\r
-    plot(x=wk, y=get(yvar), type="n", xaxt="n", bty="l", \r
-      xlab=xlb, ylab=ylb,\r
-      col=pal[1:length(levels(season))][as.integer(season)]\r
-    )\r
-    if (!is.na(ylb)) {\r
-      mtext(title, side=3, line=2, adj=0)\r
-      mtext(sprintf("FluMOMO v4 - week %s, %s", end_week, end_year), side=3, line=2, adj=1, cex=0.8)\r
-    }\r
-    axis(1, at=seq(1, max(wk), 4), labels = unique(floor(week))[seq(1, max(wk), 4)])\r
-    grid(nx=NA, ny=NULL)\r
-    abline(v=seq(1, max(wk), 4), col="lightgray", lty="dotted")\r
-    mapply(function(s, col, l) {\r
-      points(x=wk[season==s], y=get(yvar)[season==s], col=col, type="l", lty=l, lwd=lwd)\r
-    }, s=levels(season), col=rev(pal[1:length(levels(season))]), \r
-    l=c(rep("dotted", length(levels(season))-1), "solid"))\r
-  })\r
-}\r
-\r
-\r
-plotCumulMultiple <- function(mortality=FALSE, lwd=2, ylab=NULL) {\r
-  par(mfrow=c(5,1), oma=c(6,3,2,0))\r
-  for (a in 0:4) {\r
-    par(mar=c(3,2,3,2))\r
-    plotCumulSingle(a, mortality, ylab=NA)\r
-    legend("topleft", levels(results4$agegrp.labels)[a+1], bty="n", xpd=NA, cex=1.3, inset=c(0,-0.2))\r
-  }\r
-  mtext(paste0("Cumulated ",s, ifelse(mortality, " mortality", " number of deaths"), " attributable to ",t,", age group: ",unique(results4$agegrp.labels)[a+1]), side=3, line=0, adj=0, outer=TRUE)\r
-  mtext(sprintf("FluMOMO v4 - week %s, %s", end_week, end_year), side=3, line=0, adj=0.95, cex=0.8, outer=TRUE)\r
-  mtext(ifelse(mortality, "Deaths / 100,000", "Number of deaths"), side=2, line=1, outer=TRUE)\r
-  mtext("Week number", side=1, line=3, cex=0.8)\r
-  legend("bottom", legend=rev(levels(out$season)),\r
-    lty = c("solid", rep("dotted", length(levels(out$season))-1)),\r
-    col = pal[1:length(levels(out$season))], lwd=2, cex=1.2,\r
-    bty="n", horiz=TRUE, xpd=NA, inset=c(0,-0.59))\r
-}\r
-\r
-\r
-for (s in c("summer","winter","year")) {\r
-  for (t in c("IA")) {\r
-    out <- results4[!is.na(results4[,s]), \r
-        c("agegrp","agegrp.labels","year","week",paste0("cEd",t,"_",s),"N")]\r
-    colnames(out) <- c("agegrp","agegrp.labels","year","week","cd","N")\r
-    out$cm <- 100000 * out$cd / out$N\r
-    out[out$week==53,"week"] <- 52.5\r
-    if (s == "winter") {\r
-      out$wk <- with(out, 1 + (week-40)*(week>=40) + (week+12)*(week<=20))\r
-      out$season <- factor(paste0(as.character(with(out, year*(week>=40) + (year-1)*(week<=20))),"/",substr(as.character(with(out, year*(week>=40) + (year-1)*(week<=20))+1),3,4)))\r
-    }\r
-    if (s == "summer") {\r
-      out$wk <- out$week-20\r
-      out$season <- factor(out$year)\r
-    }\r
-    if (s == "year") {\r
-      out$wk <- out$week\r
-      out$season <- factor(out$year)\r
-    }\r
-    out <- out[with(out, order(agegrp, wk)),]\r
-    png(paste0(outdir,"/cumulated_",t,"_deaths_agegroups_",s,"_v4", ifelse(IArest, "_IArestricted", ""), ".png"), width=1200, height=1600, res=130)\r
-    plotCumulMultiple()\r
-    dev.off()\r
-    if (population) {\r
-      png(paste0(outdir,"/cumulated_",t,"_mr_agegroups_",s,"_v4", ifelse(IArest, "_IArestricted", ""), ".png"), width=1200, height=1600, res=130)\r
-      plotCumulMultiple(mortality=TRUE)\r
-      dev.off()\r
-    }\r
-    for (a in 0:4) {\r
-      png(paste0(outdir,"/cumulated_",t,"_deaths_agegroup_",a,"_",s,"_v4", ifelse(IArest, "_IArestricted", ""), ".png"), width=1200, height=800, res=130)\r
-      par(oma=c(3,0,0,0))\r
-      plotCumulSingle(a)\r
-      legend("bottom", legend=rev(levels(out$season)),\r
-        lty = c("solid", rep("dotted", length(levels(out$season))-1)),\r
-        col = pal[1:length(levels(out$season))], lwd=2,\r
-        bty="n", horiz=TRUE, xpd=NA, inset=c(0,-0.35))\r
-      dev.off()\r
-      if (population) {\r
-        png(paste0(outdir,"/cumulated_",t,"_mr_agegroup_",a,"_",s,"_v4", ifelse(IArest, "_IArestricted", ""), ".png"), width=1200, height=800, res=130)\r
-        par(oma=c(3,0,0,0))\r
-        plotCumulSingle(a, mortality=TRUE)\r
-        legend("bottom", legend=rev(levels(out$season)),\r
-          lty = c("solid", rep("dotted", length(levels(out$season))-1)),\r
-          col = pal[1:length(levels(out$season))], lwd=2,\r
-          bty="n", horiz=TRUE, xpd=NA, inset=c(0,-0.35))\r
-        dev.off()\r
-      }\r
-    }\r
-  }\r
-}\r
-rm(plotCumulSingle, plotCumulMultiple, results4, a, s, t, out, note, pal)\r

diff --git a/euromomo/Output_txt_v42.R b/euromomo/Output_txt_v42.R
deleted file mode 100644 (file)
index 86f2fe7..0000000
--- a/euromomo/Output_txt_v42.R
+++ /dev/null
@@ -1,49 +0,0 @@
-### ;-separated txt files ###\r
-\r
-if (IArest) { \r
-  results4 <- read.table(file=paste0(outdir,"/",country,"_output_v4_IArestricted.txt"), \r
-      header = TRUE, sep =";", dec=".")\r
-} else { \r
-  results4 <- read.table(file=paste0(outdir,"/",country,"_output_v4.txt"), \r
-      header = TRUE, sep =";", dec=".")\r
-}\r
-\r
-csvout <- function(x, s) {\r
-  y <- do.call("rbind", lapply(sort(unique(x[,s])), function(i) {\r
-    cbind(unique(x[,"agegrp"]), min(x[(x[,s]==i),"yw"]), max(x[(x[,s]==i),"yw"]), \r
-        round(tail(\r
-          x[(x[,s]==i), \r
-              c(paste0("cEdIA_",s), paste0("cEdIA_",s,"_95L"), paste0("cEdIA_",s,"_95U"), \r
-              paste0("cEdET_",s), paste0("cEdET_",s,"_95L"), paste0("cEdET_",s,"_95U"), \r
-              paste0("cexcess_",s), paste0("cuexcess_",s), "N")],\r
-          n=1)))\r
-    }))\r
-  colnames(y) <- c("AgeGroup", "Start", "End", "cIA", "cIA_95L", "cIA_95U", \r
-                    "cET", "cET_95L", "cET_95U", "cexcess", "cuexcess", "N")\r
-  return(y)\r
-}\r
-\r
-results4$yw <- sprintf("%04iw%02i",results4$year, results4$week)\r
-\r
-for (s in c("summer","winter","year")) {\r
-  out <- do.call("rbind", lapply(0:4, function(a) {\r
-    csvout(results4[(!is.na(results4[,s])) & (results4$agegrp==a),], s)\r
-  }))\r
-  out$AgeGroup <- factor(out$AgeGroup, levels = c(0,1,2,3,4), \r
-        labels = c("0-4 years","5-14 years","15-64 years","Aged 65","Total"))\r
-  write.table(out[,c("AgeGroup", "Start", "End", "cIA", "cIA_95L", "cIA_95U", \r
-              "cET", "cET_95L", "cET_95U", "cexcess", "cuexcess")], \r
-      file = paste0(outdir, "/", s, "_deaths_v4_IA", ifelse(IArest, "restricted", ""), ".txt" ), \r
-      row.names = FALSE, quote = FALSE, sep =";", dec=".", na="")\r
-  if (population) {\r
-    out[,c("cIA", "cIA_95L", "cIA_95U", "cET", "cET_95L", "cET_95U", "cexcess", "cuexcess")] <-\r
-      round(100000 * out[,c("cIA", "cIA_95L", "cIA_95U", "cET", "cET_95L", "cET_95U", "cexcess", "cuexcess")] / out[,"N"], 2)\r
-    colnames(out) <- c("AgeGroup", "Start", "End", "cmrIA", "cmrIA_95L", "cmrIA_95U", "cmrET", "cmrET_95L", "cmrET_95U", "cexcess", "cuexcess", "N")\r
-    write.table(out[,c("AgeGroup", "Start", "End", "cmrIA", "cmrIA_95L", "cmrIA_95U", \r
-              "cmrET", "cmrET_95L", "cmrET_95U", "cexcess", "cuexcess")],\r
-      file=paste0(outdir,"/",s,"_mr_v4_IA", ifelse(IArest, "restricted", ""), ".txt"), \r
-      row.names = FALSE, quote = FALSE, sep =";", dec=".")\r
-  }\r
-}\r
-\r
-rm(out, s, csvout, results4)\r

diff --git a/euromomo/SOP_v42.pdf b/euromomo/SOP_v42.pdf
deleted file mode 100644 (file)
index d8352c2..0000000
Binary files a/euromomo/SOP_v42.pdf and /dev/null differ

diff --git a/euromomo/euromomo.ipynb b/euromomo/euromomo.ipynb
deleted file mode 100644 (file)
index 2d4218e..0000000
--- a/euromomo/euromomo.ipynb
+++ /dev/null
@@ -1,314 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import json\n",
-    "import requests\n",
-    "from bs4 import BeautifulSoup"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Change this\n",
-    "OUTPUT_FILE = 'euromomo.json'"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Change this if the script breaks\n",
-    "BASE_PAGE = \"https://www.euromomo.eu/graphs-and-maps/\"\n",
-    "JS_FILE_PATTERN = \"src-templates-graphs-and-maps-js\""
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 30,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# First, we need to find the JS link inside the webpage\n",
-    "r = requests.get(BASE_PAGE)\n",
-    "if r.status_code != 200:\n",
-    "    raise Exception(f\"Cannot reach webpage {BASE_PAGE} {r.status_code}\")\n",
-    "soup = BeautifulSoup(r.text, features=\"lxml\")\n",
-    "link_to_file = None\n",
-    "for possible in soup.find_all(\"link\", attrs={\"as\": \"script\"}):\n",
-    "    if JS_FILE_PATTERN in possible['href']:\n",
-    "        link_to_file = \"https://www.euromomo.eu\" + possible['href']\n",
-    "        break"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 31,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[<link as=\"script\" href=\"/50fe40790468168eec944b4bf3a7387c41e08258-80a60393842707b4ef3f.js\" rel=\"preload\"/>,\n",
-       " <link as=\"script\" href=\"/framework-e94c62ba7ecbd1156bac.js\" rel=\"preload\"/>,\n",
-       " <link as=\"script\" href=\"/app-c8f47833a3ed3eeb35b5.js\" rel=\"preload\"/>,\n",
-       " <link as=\"script\" href=\"/component---src-templates-graphs-and-maps-js-4be2e0d0712cbdd396d8.js\" rel=\"preload\"/>,\n",
-       " <link as=\"script\" href=\"/commons-5c085e7cd1a604626d58.js\" rel=\"preload\"/>,\n",
-       " <link as=\"script\" href=\"/5e2a4920-b8478647cb0804da9c90.js\" rel=\"preload\"/>,\n",
-       " <link as=\"script\" href=\"/styles-c41920853eed0685ae46.js\" rel=\"preload\"/>,\n",
-       " <link as=\"script\" href=\"/webpack-runtime-ba300874af730e00e5e4.js\" rel=\"preload\"/>]"
-      ]
-     },
-     "execution_count": 31,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "soup.find_all(\"link\", attrs={\"as\": \"script\"})"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 32,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "if link_to_file is None:\n",
-    "    print(f\"Could not find a JS file with {JS_FILE_PATTERN} in its name :-(\")\n",
-    "    exit(1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 33,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'https://www.euromomo.eu/component---src-templates-graphs-and-maps-js-4be2e0d0712cbdd396d8.js'"
-      ]
-     },
-     "execution_count": 33,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "link_to_file"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 34,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# We need a bit of renaming\n",
-    "def rename_key(key, value):\n",
-    "    print(f'doing {key}')\n",
-    "    if isinstance(value, list):\n",
-    "        if \"Belgium\" in value:\n",
-    "            return \"countries\"\n",
-    "        if \"Total\" in value:\n",
-    "            return \"age_groups\"\n",
-    "    elif isinstance(value, str):\n",
-    "        value = int(value)\n",
-    "        if value <= 52:\n",
-    "            return \"week\"\n",
-    "        if value >= 2020:\n",
-    "            return \"year\"\n",
-    "    elif isinstance(value, dict):\n",
-    "        if set(value.keys()) == {\"counts\", \"zscores\", \"weeks\"}:\n",
-    "            return \"data_totals\"\n",
-    "        if set(value.keys()) == {\"data\", \"years\"}:\n",
-    "            return \"excess_mortality\"\n",
-    "        if set(value.keys()) == {\"data\", \"weeks\"}:\n",
-    "            if len(value[\"data\"]) == 24:\n",
-    "                return \"z_scores_country_age_groups\"\n",
-    "            if len(value[\"data\"]) >= 276:\n",
-    "                return \"z_scores_country\"\n",
-    "    raise Exception(f\"Cannot find valid key name. Key is {key} with value of type {type(value)}\")\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 35,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "js_file: str = requests.get(link_to_file).text"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 36,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "pos = 0\n",
-    "found = []\n",
-    "while True:\n",
-    "    pos = js_file.find(\"JSON.parse('\", pos)\n",
-    "    if pos == -1:\n",
-    "        break\n",
-    "    end_pos = js_file.find(\"')\", pos)\n",
-    "\n",
-    "    content = js_file[pos+len(\"JSON.parse('\"):end_pos]\n",
-    "    assert \"'\" not in content\n",
-    "    found.append(content)\n",
-    "    pos += 1\n",
-    "\n",
-    "# the biggest JSON part in the file is probably the good one ;-)\n",
-    "biggest = max(found, key=lambda x: len(x))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 37,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "raw_data = json.loads(biggest)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 38,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "doing weeks\n"
-     ]
-    },
-    {
-     "ename": "Exception",
-     "evalue": "Cannot find valid key name. Key is weeks with value of type <class 'list'>",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mException\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-38-7fbed730e1a3>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0mrename_key\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mv\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mv\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mraw_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[0;32m<ipython-input-38-7fbed730e1a3>\u001b[0m in \u001b[0;36m<dictcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0mrename_key\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mv\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mv\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mraw_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[0;32m<ipython-input-34-f58db1eb5796>\u001b[0m in \u001b[0;36mrename_key\u001b[0;34m(key, value)\u001b[0m\n\u001b[1;32m     23\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"data\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m>=\u001b[0m \u001b[0;36m276\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     24\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0;34m\"z_scores_country\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 25\u001b[0;31m     \u001b[0;32mraise\u001b[0m \u001b[0mException\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"Cannot find valid key name. Key is {key} with value of type {type(value)}\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[0;31mException\u001b[0m: Cannot find valid key name. Key is weeks with value of type <class 'list'>"
-     ]
-    }
-   ],
-   "source": [
-    "data = {rename_key(k, v): v for k, v in raw_data.items()}"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 39,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "with open('euromomo.json', 'w') as f:\n",
-    "    json.dump(data, f)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "1"
-      ]
-     },
-     "execution_count": 13,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "len(found)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 23,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['weeks', 'ages', 'pooled', 'countries', 'reportYear', 'reportWeek']"
-      ]
-     },
-     "execution_count": 23,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "[k for k in raw_data.keys()]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 26,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "list"
-      ]
-     },
-     "execution_count": 26,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "type([1,2,3])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
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diff --git a/euromomo/euromomo.json b/euromomo/euromomo.json
deleted file mode 100644 (file)
index 68c3034..0000000
--- a/euromomo/euromomo.json
+++ /dev/null
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\ No newline at end of file

diff --git a/uk-deaths-data/Weekly_Deaths - Historical_NI.xls b/uk-deaths-data/Weekly_Deaths - Historical_NI.xls
deleted file mode 100644 (file)
index c6a6f9b..0000000
Binary files a/uk-deaths-data/Weekly_Deaths - Historical_NI.xls and /dev/null differ

diff --git a/uk-deaths-data/Weekly_Deaths_NI_2015.csv b/uk-deaths-data/Weekly_Deaths_NI_2015.csv
deleted file mode 100644 (file)
index 0695211..0000000
--- a/uk-deaths-data/Weekly_Deaths_NI_2015.csv
+++ /dev/null
@@ -1,55 +0,0 @@
-Registration Week,Week Starts (Saturday),Week Ends (Friday),Total Number of Deaths Registered in Week (2015P),Average number of deaths registered in corresponding week in previous 5 years (2010 to 2014P),Range,
-,,,,,Minimum in Previous 5 years,Maximum in Previous 5 years
-1,29/12/14,02/01/15,319,317.2,248,372
-2,03/01/15,09/01/15,373,384,344,421
-3,10/01/15,16/01/15,383,347.8,319,373
-4,17/01/15,23/01/15,397,319,282,353
-5,24/01/15,30/01/15,374,309.2,284,336
-6,31/01/15,06/02/15,347,306.8,280,317
-7,07/02/15,13/02/15,328,305.4,277,340
-8,14/02/15,20/02/15,317,312.8,298,330
-9,21/02/15,27/02/15,401,302.2,285,319
-10,28/02/15,06/03/15,346,308.8,268,345
-11,07/03/15,13/03/15,323,326.8,313,334
-12,14/03/15,20/03/15,310,283.4,261,312
-13,21/03/15,27/03/15,323,305,285,330
-14,28/03/15,03/04/15,221,291.2,268,307
-15,04/04/15,10/04/15,294,306.2,255,390
-16,11/04/15,17/04/15,327,286.4,247,328
-17,18/04/15,24/04/15,316,260.2,199,303
-18,25/04/15,01/05/15,335,290,276,313
-19,01/05/15,07/05/15,256,257.2,215,289
-20,08/05/15,15/05/15,299,280.8,250,323
-21,16/05/15,22/05/15,290,276.4,241,312
-22,23/05/15,29/05/15,258,258.8,241,287
-23,30/05/15,05/06/15,340,246.6,226,276
-24,06/06/15,12/06/15,272,286,270,303
-25,13/06/15,19/06/15,292,245,211,273
-26,20/06/15,26/06/15,303,250.6,235,266
-27,27/06/15,03/07/15,300,255.8,243,268
-28,04/07/15,10/07/15,252,226.4,191,247
-29,11/07/15,17/07/15,203,244.6,208,276
-30,18/07/15,24/07/15,274,261.4,235,296
-31,25/07/15,31/07/15,291,260.4,240,292
-32,01/08/15,07/08/15,248,256,241,265
-33,08/08/15,14/08/15,235,263.2,246,282
-34,15/08/15,21/08/15,251,266.6,255,282
-35,22/08/15,28/08/15,259,241.4,226,260
-36,29/08/15,04/09/15,237,261.2,221,301
-37,05/09/15,11/09/15,324,259.2,226,295
-38,12/09/15,18/09/15,283,252.6,238,271
-39,19/09/15,25/09/15,287,277.6,238,306
-40,26/09/15,02/10/15,282,270,259,277
-41,03/10/15,09/10/15,304,269,241,317
-42,10/10/15,16/10/15,299,276.8,256,293
-43,17/10/15,23/10/15,274,283.4,263,305
-44,24/10/15,30/10/15,292,270.8,257,284
-45,31/10/15,06/11/15,290,276.2,260,298
-46,07/11/15,13/11/15,297,275.4,230,297
-47,14/11/15,20/11/15,294,288.8,269,313
-48,21/11/15,27/11/15,279,280.8,256,293
-49,28/11/15,04/12/15,294,280.8,255,299
-50,05/12/15,11/12/15,343,285.4,263,301
-51,12/12/15,18/12/15,301,297.4,281,313
-52,19/12/15,25/12/15,232,210.4,178,255
-53,26/12/15,01/01/16,232,57.4,287,287

diff --git a/uk-deaths-data/Weekly_Deaths_NI_2016.csv b/uk-deaths-data/Weekly_Deaths_NI_2016.csv
deleted file mode 100644 (file)
index 2216668..0000000
--- a/uk-deaths-data/Weekly_Deaths_NI_2016.csv
+++ /dev/null
@@ -1,54 +0,0 @@
-Registration Week,Week Starts (Saturday),Week Ends (Friday),Total Number of Deaths Registered in Week (2016P),Average number of deaths registered in corresponding week in previous 5 years (2011 to 2015P),Range,
-,,,,,Minimum in Previous 5 years,Maximum in Previous 5 years
-1,02/01/16,08/01/16,424,331.4,294,372
-2,09/01/16,15/01/16,348,374.4,344,392
-3,16/01/16,22/01/16,372,349.8,319,383
-4,23/01/16,29/01/16,355,333.4,282,397
-5,30/01/16,05/02/16,314,318.8,284,374
-6,06/02/16,12/02/16,310,313.6,280,347
-7,13/02/16,19/02/16,217,308.6,277,340
-8,20/02/16,26/02/16,423,314.8,298,330
-9,27/02/16,04/03/16,298,320.4,285,401
-10,05/03/16,11/03/16,309,317,268,346
-11,12/03/16,18/03/16,292,324.8,313,334
-12,19/03/16,25/03/16,306,286.2,261,312
-13,26/03/16,01/04/16,280,309.8,285,330
-14,02/04/16,08/04/16,295,281.8,221,307
-15,09/04/16,15/04/16,292,314,280,390
-16,16/04/16,22/04/16,293,290.4,247,328
-17,23/04/16,29/04/16,306,274.2,199,316
-18,30/04/16,06/05/16,258,300.4,276,335
-19,07/05/16,13/05/16,318,265.4,249,289
-20,14/05/16,20/05/16,259,285.2,250,323
-21,21/05/16,27/05/16,280,283.4,241,312
-22,28/05/16,03/06/16,284,257.6,241,287
-23,04/06/16,10/06/16,275,268.4,226,340
-24,11/06/16,17/06/16,299,286.4,272,303
-25,18/06/16,24/06/16,252,255,211,292
-26,25/06/16,01/07/16,291,260.8,235,303
-27,02/07/16,08/07/16,286,263.2,243,300
-28,09/07/16,15/07/16,237,228.2,191,252
-29,16/07/16,22/07/16,281,243.6,203,276
-30,23/07/16,29/07/16,298,261.8,235,296
-31,30/07/16,05/08/16,264,270.6,252,292
-32,06/08/16,12/08/16,270,257.4,248,265
-33,13/08/16,19/08/16,260,258,235,282
-34,20/08/16,26/08/16,301,264.8,251,282
-35,27/08/16,02/09/16,264,242.2,226,260
-36,03/09/16,09/09/16,275,264.4,237,301
-37,10/09/16,16/09/16,294,269.8,226,324
-38,17/09/16,23/09/16,272,259.8,238,283
-39,24/09/16,30/09/16,275,287.4,261,306
-40,01/10/16,07/10/16,308,273.2,259,282
-41,08/10/16,14/10/16,288,276.6,241,317
-42,15/10/16,21/10/16,296,284.4,256,299
-43,22/10/16,28/10/16,272,277.2,263,300
-44,29/10/16,04/11/16,279,273.2,257,292
-45,05/11/16,11/11/16,290,280.4,260,298
-46,12/11/16,18/11/16,341,275.8,230,297
-47,19/11/16,25/11/16,329,285,269,296
-48,26/11/16,02/12/16,303,285.4,277,293
-49,03/12/16,09/12/16,322,279.8,255,294
-50,10/12/16,16/12/16,324,293.8,263,343
-51,17/12/16,23/12/16,360,297.8,281,313
-52,24/12/16,30/12/16,199,205.8,178,232

diff --git a/uk-deaths-data/Weekly_Deaths_NI_2017.csv b/uk-deaths-data/Weekly_Deaths_NI_2017.csv
deleted file mode 100644 (file)
index a1d109c..0000000
--- a/uk-deaths-data/Weekly_Deaths_NI_2017.csv
+++ /dev/null
@@ -1,54 +0,0 @@
-Registration Week,Week Starts (Saturday),Week Ends (Friday),Total Number of Deaths Registered in Week (2017P),Average number of deaths registered in corresponding week in previous 5 years (2012 to 2016P),Range,
-,,,,,Minimum in Previous 5 years,Maximum in Previous 5 years
-1,31/12/2016,06/01/2017,416,342,294,424
-2,07/01/2017,13/01/2017,434,366,344,382
-3,14/01/2017,20/01/2017,397,353,319,383
-4,21/01/2017,27/01/2017,387,338,282,397
-5,28/01/2017,03/02/2017,371,325,290,374
-6,04/02/2017,10/02/2017,336,312,280,347
-7,11/02/2017,17/02/2017,337,297,217,340
-8,18/02/2017,24/02/2017,351,339,298,423
-9,25/02/2017,03/03/2017,352,320,285,401
-10,04/03/2017,10/03/2017,357,325,308,346
-11,11/03/2017,17/03/2017,251,321,292,334
-12,18/03/2017,24/03/2017,356,293,261,312
-13,25/03/2017,31/03/2017,314,309,280,330
-14,01/04/2017,07/04/2017,306,280,285,307
-15,08/04/2017,14/04/2017,270,316,290,390
-16,15/04/2017,21/04/2017,245,298,247,328
-17,22/04/2017,28/04/2017,327,296,251,316
-18,29/04/2017,05/05/2017,258,293,258,335
-19,06/05/2017,12/05/2017,302,277,249,318
-20,13/05/2017,19/05/2017,315,279,250,323
-21,20/05/2017,26/05/2017,328,284,241,312
-22,27/05/2017,02/06/2017,256,264,241,287
-23,03/06/2017,09/06/2017,292,273,226,340
-24,10/06/2017,16/06/2017,300,290,284,303
-25,17/06/2017,23/06/2017,271,251,211,292
-26,24/06/2017,30/06/2017,296,266,235,303
-27,01/07/2017,07/07/2017,262,272,250,300
-28,08/07/2017,14/07/2017,253,237,211,252
-29,15/07/2017,21/07/2017,288,247,221,281
-30,22/07/2017,28/07/2017,287,274,243,298
-31,29/07/2017,04/08/2017,287,273,257,292
-32,05/08/2017,11/08/2017,238,259,249,270
-33,12/08/2017,18/08/2017,266,256,246,282
-34,19/08/2017,25/08/2017,271,272,255,301
-35,26/08/2017,01/09/2017,243,250,228,264
-36,02/09/2017,08/09/2017,278,269,262,301
-37,09/09/2017,15/09/2017,266,279,226,324
-38,16/09/2017,22/09/2017,292,267,248,283
-39,23/09/2017,29/09/2017,282,290,275,306
-40,30/09/2017,06/10/2017,307,283,272,308
-41,07/10/2017,13/10/2017,284,286,252,317
-42,14/10/2017,20/10/2017,291,292,284,299
-43,21/10/2017,27/10/2017,318,276,263,300
-44,28/10/2017,03/11/2017,320,272,257,292
-45,04/11/2017,10/11/2017,295,286,274,298
-46,11/11/2017,17/11/2017,323,298,267,341
-47,18/11/2017,24/11/2017,303,297,269,329
-48,25/11/2017,01/12/2017,355,289,277,303
-49,02/12/2017,08/12/2017,324,286,255,322
-50,09/12/2017,15/12/2017,372,305,263,343
-51,16/12/2017,22/12/2017,354,309,281,360
-52,23/12/2017,29/12/2017,249,204,178,232

diff --git a/uk-deaths-data/Weekly_Deaths_NI_2018.csv b/uk-deaths-data/Weekly_Deaths_NI_2018.csv
deleted file mode 100644 (file)
index 241e846..0000000
--- a/uk-deaths-data/Weekly_Deaths_NI_2018.csv
+++ /dev/null
@@ -1,54 +0,0 @@
-Registration Week,Week Starts (Saturday),Week Ends (Friday),Total Number of Deaths Registered in Week (2018P),Average number of deaths registered in corresponding week in previous 5 years (2013 to 2017P),Range,
-,,,,,Minimum in Previous 5 years,Maximum in Previous 5 years
-1,30/12/2017,05/01/2018,447,46,0,232
-2,06/01/2018,12/01/2018,481,358,294,424
-3,13/01/2018,19/01/2018,470,384,348,434
-4,20/01/2018,26/01/2018,426,369,331,397
-5,27/01/2018,02/02/2018,433,359,303,397
-6,03/02/2018,09/02/2018,351,337,290,374
-7,10/02/2018,16/02/2018,364,317,280,347
-8,17/02/2018,23/02/2018,366,304,217,340
-9,24/02/2018,02/03/2018,314,349,317,423
-10,03/03/2018,09/03/2018,387,331,285,401
-11,10/03/2018,16/03/2018,359,335,309,357
-12,17/03/2018,23/03/2018,326,305,251,334
-13,24/03/2018,30/03/2018,319,309,261,356
-14,31/03/2018,06/04/2018,286,310,280,330
-15,07/04/2018,13/04/2018,350,279,221,306
-16,14/04/2018,20/04/2018,280,312,270,390
-17,21/04/2018,27/04/2018,282,288,245,328
-18,28/04/2018,04/05/2018,292,301,251,327
-19,05/05/2018,11/05/2018,230,289,258,335
-20,12/05/2018,18/05/2018,268,280,249,318
-21,19/05/2018,25/05/2018,268,278,250,315
-22,26/05/2018,01/06/2018,252,290,241,328
-23,02/06/2018,08/06/2018,276,258,241,284
-24,09/06/2018,15/06/2018,277,286,246,340
-25,16/06/2018,22/06/2018,265,290,272,300
-26,23/06/2018,29/06/2018,271,253,211,292
-27,30/06/2018,06/07/2018,266,272,235,303
-28,07/07/2018,13/07/2018,172,271,250,300
-29,14/07/2018,20/07/2018,298,246,237,253
-30,21/07/2018,27/07/2018,282,250,203,288
-31,28/07/2018,03/08/2018,278,283,261,298
-32,04/08/2018,10/08/2018,270,278,257,292
-33,11/08/2018,17/08/2018,283,253,238,270
-34,18/08/2018,24/08/2018,280,253,235,266
-35,25/08/2018,31/08/2018,251,275,251,301
-36,01/09/2018,07/09/2018,265,251,228,264
-37,08/09/2018,14/09/2018,285,272,237,301
-38,15/09/2018,21/09/2018,247,287,254,324
-39,22/09/2018,28/09/2018,298,271,248,292
-40,29/09/2018,05/10/2018,324,288,275,306
-41,06/10/2018,12/10/2018,318,290,276,308
-42,13/10/2018,19/10/2018,282,289,252,317
-43,20/10/2018,26/10/2018,263,293,284,299
-44,27/10/2018,02/11/2018,252,287,271,318
-45,03/11/2018,09/11/2018,293,285,266,320
-46,10/11/2018,16/11/2018,275,291,280,298
-47,17/11/2018,23/11/2018,274,303,267,341
-48,24/11/2018,30/11/2018,297,298,269,329
-49,01/12/2018,07/12/2018,324,304,279,355
-50,08/12/2018,14/12/2018,316,294,255,324
-51,15/12/2018,21/12/2018,317,320,263,372
-52,22/12/2018,28/12/2018,195,317,281,360

diff --git a/uk-deaths-data/Weekly_Deaths_NI_2019.csv b/uk-deaths-data/Weekly_Deaths_NI_2019.csv
deleted file mode 100644 (file)
index 1e2ef2a..0000000
--- a/uk-deaths-data/Weekly_Deaths_NI_2019.csv
+++ /dev/null
@@ -1,54 +0,0 @@
-Registration Week,Week Starts (Saturday),Week Ends (Friday),Total Number of Deaths Registered in Week (2019P),Average number of deaths registered in corresponding week in previous 5 years (2014 to 2018P),Range,
-,,,,,Minimum in Previous 5 years,Maximum in Previous 5 years
-1,29/12/2018,04/01/2019,365,212,178,249
-2,05/01/2019,11/01/2019,371,387,294,481
-3,12/01/2019,18/01/2019,332,401,348,470
-4,19/01/2019,25/01/2019,335,382,331,426
-5,26/01/2019,01/02/2019,296,385,353,433
-6,02/02/2019,08/02/2019,319,349,314,374
-7,09/02/2019,15/02/2019,342,327,280,364
-8,16/02/2019,22/02/2019,337,309,217,366
-9,23/02/2019,01/03/2019,310,347,314,423
-10,02/03/2019,08/03/2019,342,345,285,401
-11,09/03/2019,15/03/2019,343,338,309,359
-12,16/03/2019,22/03/2019,294,304,251,327
-13,23/03/2019,29/03/2019,307,310,261,356
-14,30/03/2019,05/04/2019,287,301,280,323
-15,06/04/2019,12/04/2019,301,292,221,350
-16,13/04/2019,19/04/2019,316,290,270,316
-17,20/04/2019,26/04/2019,272,279,245,327
-18,27/04/2019,03/05/2019,357,298,251,327
-19,04/05/2019,10/05/2019,288,279,230,335
-20,11/05/2019,17/05/2019,330,279,249,318
-21,18/05/2019,24/05/2019,308,278,250,315
-22,25/05/2019,31/05/2019,245,278,241,328
-23,01/06/2019,07/06/2019,279,263,241,284
-24,08/06/2019,14/06/2019,281,286,246,340
-25,15/06/2019,21/06/2019,296,284,265,300
-26,22/06/2019,28/06/2019,262,259,211,292
-27,29/06/2019,05/07/2019,285,278,235,303
-28,06/07/2019,12/07/2019,256,254,172,300
-29,13/07/2019,19/07/2019,280,256,237,298
-30,20/07/2019,26/07/2019,269,255,203,288
-31,27/07/2019,02/08/2019,273,280,261,298
-32,03/08/2019,09/08/2019,266,281,264,292
-33,10/08/2019,16/08/2019,284,260,238,283
-34,17/08/2019,23/08/2019,274,260,235,280
-35,24/08/2019,30/08/2019,223,271,251,301
-36,31/08/2019,06/09/2019,243,258,243,265
-37,07/09/2019,13/09/2019,305,275,237,301
-38,14/09/2019,20/09/2019,281,285,247,324
-39,21/09/2019,27/09/2019,295,281,259,298
-40,28/09/2019,04/10/2019,263,292,275,324
-41,05/10/2019,11/10/2019,287,298,277,318
-42,12/10/2019,18/10/2019,316,295,282,317
-43,19/10/2019,25/10/2019,279,287,263,299
-44,26/10/2019,01/11/2019,302,283,252,318
-45,02/11/2019,08/11/2019,296,290,267,320
-46,09/11/2019,15/11/2019,336,286,275,295
-47,16/11/2019,22/11/2019,361,305,274,341
-48,23/11/2019,29/11/2019,334,304,294,329
-49,30/11/2019,06/12/2019,351,310,279,355
-50,07/12/2019,13/12/2019,353,306,275,324
-51,14/12/2019,20/12/2019,363,331,298,372
-52,21/12/2019,27/12/2019,194,298,195,360

diff --git a/uk-deaths-data/publishedweek1620201.xlsx b/uk-deaths-data/publishedweek1620201.xlsx
deleted file mode 100644 (file)
index 2c8d723..0000000
Binary files a/uk-deaths-data/publishedweek1620201.xlsx and /dev/null differ

diff --git a/uk-deaths-data/publishedweek172020.csv b/uk-deaths-data/publishedweek172020.csv
deleted file mode 100644 (file)
index 1a04d01..0000000
--- a/uk-deaths-data/publishedweek172020.csv
+++ /dev/null
@@ -1,19 +0,0 @@
-Week number,Week ended,"Total deaths, all ages",Total deaths: average of corresponding week over the previous 5 years 1 (England and Wales),Total deaths: average of corresponding week over the previous 5 years 1 (England),Total deaths: average of corresponding week over the previous 5 years (Wales),,,,Persons,Deaths by age group,,,,,,,,,,,,,,,,,,,,,Males,,,,,,,,,,,,,,,,,,,,,,Females,,,,,,,,,,,,,,,,,,,,,Deaths by region of usual residence,E12000001,E12000002,E12000003,E12000004,E12000005,E12000006,E12000007,E12000008,E12000009,W92000004
-,,,,,,Deaths by cause,Deaths where the underlying cause was respiratory disease (ICD-10 J00-J99),Deaths where COVID-19 was mentioned on the death certificate (ICD-10 U07.1 and U07.2),,<1,1-4,5-9,10-14,15-19,20-24,25-29,30-34,35-39,40-44,45-49,50-54,55-59,60-64,65-69,70-74,75-79,80-84,85-89,90+,,Deaths by age group,<1,1-4,5-9,10-14,15-19,20-24,25-29,30-34,35-39,40-44,45-49,50-54,55-59,60-64,65-69,70-74,75-79,80-84,85-89,90+,,Deaths by age group,<1,1-4,5-9,10-14,15-19,20-24,25-29,30-34,35-39,40-44,45-49,50-54,55-59,60-64,65-69,70-74,75-79,80-84,85-89,90+,,North East,North West,Yorkshire and The Humber,East Midlands,West Midlands,East,London,South East,South West,Wales
-1,03/01/20,12254,12175,11412,756,,2141,0,,48,8,4,4,6,11,17,32,54,69,115,239,361,486,696,1164,1535,2049,2457,2898,,,30,5,2,1,5,7,7,21,32,43,62,137,191,275,415,697,826,1053,1098,982,,,18,3,2,3,1,4,10,11,22,26,53,102,170,211,281,467,709,996,1359,1916,,673,1806,1240,1060,1349,1162,1113,1814,1225,787
-2,10/01/20,14058,13822,12933,856,,2477,0,,50,9,8,9,16,23,37,46,68,85,191,279,426,604,857,1341,1724,2290,2697,3297,,,29,4,4,7,8,14,28,28,46,52,114,156,259,355,509,761,924,1172,1231,1127,,,21,5,4,2,8,9,9,18,22,33,77,123,167,249,348,580,800,1118,1466,2170,,707,1932,1339,1195,1450,1573,1272,2132,1487,939
-3,17/01/20,12990,13216,12370,812,,2189,0,,69,7,5,4,10,25,37,47,77,118,189,306,461,562,803,1210,1612,2103,2421,2924,,,38,4,4,3,5,21,31,29,49,72,106,200,295,338,471,690,886,1080,1117,991,,,31,3,1,1,5,4,6,18,28,46,83,106,166,224,332,520,726,1023,1304,1933,,647,1696,1278,1106,1407,1457,1073,2064,1466,767
-4,24/01/20,11856,12760,11933,802,,1893,0,,53,9,4,8,15,30,36,38,79,116,160,280,381,535,791,1167,1474,1863,2188,2626,,,28,6,4,4,14,23,31,22,45,79,90,181,215,334,482,663,819,951,1014,910,,,25,3,0,4,1,7,5,16,34,37,70,99,166,201,309,504,655,912,1174,1716,,612,1529,1187,1024,1231,1410,1028,1833,1253,723
-5,31/01/20,11612,12206,11419,760,,1746,0,,50,6,5,4,23,23,28,58,76,100,163,278,382,525,732,1196,1445,1811,2124,2583,,,22,4,4,3,17,16,19,40,45,58,107,180,247,324,437,683,827,919,970,872,,,28,2,1,1,6,7,9,18,31,42,56,98,135,201,295,513,618,892,1154,1711,,561,1461,1136,1015,1262,1286,1092,1820,1233,727
-6,07/02/20,10986,11925,11154,729,,1572,0,,30,8,4,4,10,34,23,38,71,95,157,289,371,512,689,1120,1358,1698,2040,2433,,,14,5,2,4,8,23,11,24,53,55,95,175,208,306,423,626,713,875,943,843,,,16,3,2,0,2,11,12,14,18,40,62,114,163,206,266,494,645,823,1097,1590,,564,1529,1072,922,1052,1259,987,1729,1157,690
-7,14/02/20,10944,11627,10876,722,,1602,0,,43,6,2,4,16,26,27,40,85,92,165,288,345,490,641,1113,1305,1704,2039,2517,,,29,4,1,3,9,19,19,27,52,58,99,172,209,287,400,660,726,870,995,852,,,14,2,1,1,7,7,8,13,33,34,66,116,136,203,241,453,579,834,1044,1665,,573,1427,1059,976,1159,1172,967,1688,1169,728
-8,21/02/20,10841,11548,10790,724,,1619,0,,51,5,6,7,20,18,29,60,77,117,182,232,346,511,695,1048,1338,1696,1927,2475,,,32,5,4,2,14,14,17,39,46,72,105,140,195,285,400,598,778,894,906,893,,,19,0,2,5,6,4,12,21,31,45,77,92,151,226,295,450,560,802,1021,1582,,539,1477,1087,924,1116,1167,1032,1675,1118,679
-9,28/02/20,10816,11183,10448,698,,1547,0,,49,7,6,7,24,25,28,50,85,103,155,261,347,494,682,1111,1255,1713,2015,2398,,,30,6,4,5,16,19,21,32,51,64,95,147,189,286,417,647,709,871,956,870,,,19,1,2,2,8,6,7,18,34,39,60,114,158,208,265,464,546,842,1059,1528,,572,1476,1078,919,1174,1115,1085,1587,1133,651
-10,06/03/20,10895,11498,10745,720,,1583,0,,56,11,2,7,21,23,39,53,72,104,155,258,358,481,679,1090,1325,1798,1969,2391,,,31,7,1,2,13,16,27,33,45,69,93,153,220,278,388,646,725,938,932,841,,,25,4,1,5,8,7,12,20,27,35,62,105,138,203,291,444,600,860,1037,1550,,568,1490,1112,930,1098,1149,982,1726,1170,652
-11,13/03/20,11019,11205,10447,727,,1508,5,,53,13,3,6,18,39,29,55,80,90,179,260,401,500,685,1068,1366,1738,1951,2483,,,24,5,1,2,13,26,20,41,48,50,109,168,246,296,424,625,748,904,935,885,,,29,8,2,4,5,13,9,14,32,40,70,92,155,204,261,443,618,834,1016,1598,,590,1472,1053,915,1187,1211,964,1751,1174,675
-12,20/03/20,10645,10573,9841,677,,1541,103,,44,2,6,4,15,22,31,41,66,100,160,245,390,469,686,1094,1373,1694,1902,2302,,,25,2,3,3,11,17,22,25,47,63,99,158,229,281,404,629,763,892,905,820,,,19,0,3,1,4,5,9,16,19,37,61,87,161,188,282,465,610,802,997,1482,,522,1443,1012,947,1115,1043,1008,1657,1156,719
-13,27/03/20,11141,10130,9414,665,,1532,539,,49,8,1,4,12,17,33,55,71,95,163,235,381,522,699,1106,1397,1850,2016,2428,,,27,3,1,1,8,11,22,40,40,65,97,146,235,286,423,666,788,1005,984,883,,,22,5,0,3,4,6,11,15,31,30,66,89,146,236,276,440,609,845,1032,1545,,542,1538,982,922,1035,1182,1297,1822,1092,719
-14,03/04/20,16387,10305,9601,667,,1952,3475,,51,8,5,8,9,20,32,54,67,106,220,376,531,733,1044,1690,2179,2826,3015,3413,,,26,2,2,3,7,12,22,39,36,67,124,244,336,453,662,1039,1303,1570,1520,1327,,,25,6,3,5,2,8,10,15,31,39,96,132,195,280,382,651,876,1256,1495,2086,,770,2137,1436,1246,1812,1717,2511,2294,1520,920
-15,10/04/20,18516,10520,9807,671,,1759,6213,,38,6,4,4,8,16,41,45,108,114,249,412,598,852,1149,1797,2418,3195,3564,3898,,,28,3,3,1,5,12,29,30,60,65,148,247,372,548,706,1098,1451,1795,1826,1521,,,10,3,1,3,3,4,12,15,48,49,101,165,226,304,443,699,967,1400,1738,2377,,849,2597,1503,1452,2182,1984,2832,2604,1560,928
-16,17/04/20,22351,10497,9787,661,,1777,8758,,51,6,5,4,20,17,40,52,92,132,242,428,679,945,1272,2108,2817,3840,4444,5157,,,24,4,2,1,12,12,28,32,56,77,147,229,434,591,791,1280,1635,2100,2111,1879,,,27,2,3,3,8,5,12,20,36,55,95,199,245,354,481,828,1182,1740,2333,3278,,1155,3195,1960,1632,2536,2466,3275,3084,1854,1169
-17,24/04/20,21997,10458,9768,662,,1574,8237,,54,6,3,3,11,25,34,66,98,170,279,438,639,927,1248,1990,2741,3772,4349,5144,,,33,4,3,2,5,11,23,39,62,111,175,274,407,578,795,1220,1614,2007,2085,1780,,,21,2,0,1,6,14,11,27,36,59,104,164,232,349,453,770,1127,1765,2264,3364,,1103,3109,2095,1711,2481,2299,2785,3334,1924,1124

diff --git a/uk-deaths-data/publishedweek172020.ods b/uk-deaths-data/publishedweek172020.ods
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index 68213ab..0000000
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diff --git a/uk-deaths-data/publishedweek172020.xlsx b/uk-deaths-data/publishedweek172020.xlsx
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diff --git a/uk-deaths-data/publishedweek182020.csv b/uk-deaths-data/publishedweek182020.csv
deleted file mode 100644 (file)
index 9f6aa26..0000000
--- a/uk-deaths-data/publishedweek182020.csv
+++ /dev/null
@@ -1,21 +0,0 @@
-Week number,Week ended,"Total deaths, all ages",Total deaths: average of corresponding,,,Persons,,,,,,,,,,,,,,,,,,,,,Male,,,,,,,,,,,,,,,,,,,,,Female,,,,,,,,,,,,,,,,,,,,,Deaths by region of usual residence 7,E12000001,E12000002,E12000003,E12000004,E12000005,E12000006,E12000007,E12000008,E12000009,W92000004
-,,,,Deaths by underlying cause,"All respiratory diseases (ICD-10 J00-J99)
-ICD-10 v 2013 (IRIS)",Deaths by age group,<1,1-4,5-9,10-14,15-19,20-24,25-29,30-34,35-39,40-44,45-49,50-54,55-59,60-64,65-69,70-74,75-79,80-84,85-89,90+,Deaths by age group,<1,1-4,5-9,10-14,15-19,20-24,25-29,30-34,35-39,40-44,45-49,50-54,55-59,60-64,65-69,70-74,75-79,80-84,85-89,90+,Deaths by age group,<1,1-4,5-9,10-14,15-19,20-24,25-29,30-34,35-39,40-44,45-49,50-54,55-59,60-64,65-69,70-74,75-79,80-84,85-89,90+,,North East,North West,Yorkshire and The Humber,East Midlands,West Midlands,East,London,South East,South West,Wales
-1,03/01/20,12254,12175,,2141,,48,8,4,4,6,11,17,32,54,69,115,239,361,486,696,1164,1535,2049,2457,2898,,30,5,2,1,5,7,7,21,32,43,62,137,191,275,415,697,826,1053,1098,982,,18,3,2,3,1,4,10,11,22,26,53,102,170,211,281,467,709,996,1359,1916,,673,1806,1240,1060,1349,1162,1113,1814,1225,787
-2,10/01/20,14058,13822,,2477,,50,9,8,9,16,23,37,46,68,85,191,279,426,604,857,1341,1724,2290,2697,3297,,29,4,4,7,8,14,28,28,46,52,114,156,259,355,509,761,924,1172,1231,1127,,21,5,4,2,8,9,9,18,22,33,77,123,167,249,348,580,800,1118,1466,2170,,707,1932,1339,1195,1450,1573,1272,2132,1487,939
-3,17/01/20,12990,13216,,2189,,69,7,5,4,10,25,37,47,77,118,189,306,461,562,803,1210,1612,2103,2421,2924,,38,4,4,3,5,21,31,29,49,72,106,200,295,338,471,690,886,1080,1117,991,,31,3,1,1,5,4,6,18,28,46,83,106,166,224,332,520,726,1023,1304,1933,,647,1696,1278,1106,1407,1457,1073,2064,1466,767
-4,24/01/20,11856,12760,,1893,,53,9,4,8,15,30,36,38,79,116,160,280,381,535,791,1167,1474,1863,2188,2626,,28,6,4,4,14,23,31,22,45,79,90,181,215,334,482,663,819,951,1014,910,,25,3,0,4,1,7,5,16,34,37,70,99,166,201,309,504,655,912,1174,1716,,612,1529,1187,1024,1231,1410,1028,1833,1253,723
-5,31/01/20,11612,12206,,1746,,50,6,5,4,23,23,28,58,76,100,163,278,382,525,732,1196,1445,1811,2124,2583,,22,4,4,3,17,16,19,40,45,58,107,180,247,324,437,683,827,919,970,872,,28,2,1,1,6,7,9,18,31,42,56,98,135,201,295,513,618,892,1154,1711,,561,1461,1136,1015,1262,1286,1092,1820,1233,727
-6,07/02/20,10986,11925,,1572,,30,8,4,4,10,34,23,38,71,95,157,289,371,512,689,1120,1358,1698,2040,2433,,14,5,2,4,8,23,11,24,53,55,95,175,208,306,423,626,713,875,943,843,,16,3,2,0,2,11,12,14,18,40,62,114,163,206,266,494,645,823,1097,1590,,564,1529,1072,922,1052,1259,987,1729,1157,690
-7,14/02/20,10944,11627,,1602,,43,6,2,4,16,26,27,40,85,92,165,288,345,490,641,1113,1305,1704,2039,2517,,29,4,1,3,9,19,19,27,52,58,99,172,209,287,400,660,726,870,995,852,,14,2,1,1,7,7,8,13,33,34,66,116,136,203,241,453,579,834,1044,1665,,573,1427,1059,976,1159,1172,967,1688,1169,728
-8,21/02/20,10841,11548,,1619,,51,5,6,7,20,18,29,60,77,117,182,232,346,511,695,1048,1338,1696,1927,2475,,32,5,4,2,14,14,17,39,46,72,105,140,195,285,400,598,778,894,906,893,,19,0,2,5,6,4,12,21,31,45,77,92,151,226,295,450,560,802,1021,1582,,539,1477,1087,924,1116,1167,1032,1675,1118,679
-9,28/02/20,10816,11183,,1547,,49,7,6,7,24,25,28,50,85,103,155,261,347,494,682,1111,1255,1713,2015,2398,,30,6,4,5,16,19,21,32,51,64,95,147,189,286,417,647,709,871,956,870,,19,1,2,2,8,6,7,18,34,39,60,114,158,208,265,464,546,842,1059,1528,,572,1476,1078,919,1174,1115,1085,1587,1133,651
-10,06/03/20,10895,11498,,1583,,56,11,2,7,21,23,39,53,72,104,155,258,358,481,679,1090,1325,1798,1969,2391,,31,7,1,2,13,16,27,33,45,69,93,153,220,278,388,646,725,938,932,841,,25,4,1,5,8,7,12,20,27,35,62,105,138,203,291,444,600,860,1037,1550,,568,1490,1112,930,1098,1149,982,1726,1170,652
-11,13/03/20,11019,11205,,1508,,53,13,3,6,18,39,29,55,80,90,179,260,401,500,685,1068,1366,1738,1951,2483,,24,5,1,2,13,26,20,41,48,50,109,168,246,296,424,625,748,904,935,885,,29,8,2,4,5,13,9,14,32,40,70,92,155,204,261,443,618,834,1016,1598,,590,1472,1053,915,1187,1211,964,1751,1174,675
-12,20/03/20,10645,10573,,1546,,44,2,6,4,15,22,31,41,66,100,160,245,390,469,686,1094,1373,1694,1902,2302,,25,2,3,3,11,17,22,25,47,63,99,158,229,281,404,629,763,892,905,820,,19,0,3,1,4,5,9,16,19,37,61,87,161,188,282,465,610,802,997,1482,,522,1443,1012,947,1115,1043,1008,1657,1156,719
-13,27/03/20,11141,10130,,1539,,49,8,1,4,12,17,33,55,71,95,163,235,381,522,699,1106,1397,1850,2016,2428,,27,3,1,1,8,11,22,40,40,65,97,146,235,286,423,666,788,1005,984,883,,22,5,0,3,4,6,11,15,31,30,66,89,146,236,276,440,609,845,1032,1545,,542,1538,982,922,1035,1182,1297,1822,1092,719
-14,03/04/20,16387,10305,,1969,,51,8,5,8,9,20,32,54,67,106,220,376,531,733,1044,1690,2179,2826,3015,3413,,26,2,2,3,7,12,22,39,36,67,124,244,336,453,662,1039,1303,1570,1520,1327,,25,6,3,5,2,8,10,15,31,39,96,132,195,280,382,651,876,1256,1495,2086,,770,2137,1436,1246,1812,1717,2511,2294,1520,920
-15,10/04/20,18516,10520,,1760,,38,6,4,4,8,16,41,45,108,114,249,412,598,852,1149,1797,2418,3195,3564,3898,,28,3,3,1,5,12,29,30,60,65,148,247,372,548,706,1098,1451,1795,1826,1521,,10,3,1,3,3,4,12,15,48,49,101,165,226,304,443,699,967,1400,1738,2377,,849,2597,1503,1452,2182,1984,2832,2604,1560,928
-16,17/04/20,22351,10497,,1777,,51,6,5,4,20,17,40,52,92,132,242,428,679,945,1272,2108,2817,3840,4444,5157,,24,4,2,1,12,12,28,32,56,77,147,229,434,591,791,1280,1635,2100,2111,1879,,27,2,3,3,8,5,12,20,36,55,95,199,245,354,481,828,1182,1740,2333,3278,,1155,3195,1960,1632,2536,2466,3275,3084,1854,1169
-17,24/04/20,21997,10458,,1575,,54,6,3,3,11,25,34,66,98,170,279,438,639,927,1248,1990,2741,3772,4349,5144,,33,4,3,2,5,11,23,39,62,111,175,274,407,578,795,1220,1614,2007,2085,1780,,21,2,0,1,6,14,11,27,36,59,104,164,232,349,453,770,1127,1765,2264,3364,,1103,3109,2095,1711,2481,2299,2785,3334,1924,1124
-18,01/05/20,17953,9941,,1272,,48,8,0,3,14,18,40,59,98,116,235,387,550,725,1023,1578,2155,2987,3514,4395,,30,5,0,0,11,11,23,35,60,73,148,235,347,453,631,940,1205,1555,1588,1507,,18,3,0,3,3,7,17,24,38,43,87,152,203,272,392,638,950,1432,1926,2888,,922,2503,1844,1418,1975,1982,1953,2853,1554,929

diff --git a/uk-deaths-data/publishedweek182020.ods b/uk-deaths-data/publishedweek182020.ods
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diff --git a/uk-deaths-data/publishedweek182020.xlsx b/uk-deaths-data/publishedweek182020.xlsx
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index 4096e81..0000000
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diff --git a/uk-deaths-data/publishedweek192020.csv b/uk-deaths-data/publishedweek192020.csv
deleted file mode 100644 (file)
index 3365db2..0000000
--- a/uk-deaths-data/publishedweek192020.csv
+++ /dev/null
@@ -1,22 +0,0 @@
-Week number,Week ended,"Total deaths, all ages",Total deaths: average of corresponding,,,Persons,,,,,,,,,,,,,,,,,,,,,Male,,,,,,,,,,,,,,,,,,,,,Female,,,,,,,,,,,,,,,,,,,,,Deaths by region of usual residence 7,E12000001,E12000002,E12000003,E12000004,E12000005,E12000006,E12000007,E12000008,E12000009,W92000004
-,,,,Deaths by underlying cause,"All respiratory diseases (ICD-10 J00-J99)
-ICD-10 v 2013 (IRIS)",Deaths by age group,<1,1-4,5-9,10-14,15-19,20-24,25-29,30-34,35-39,40-44,45-49,50-54,55-59,60-64,65-69,70-74,75-79,80-84,85-89,90+,Deaths by age group,<1,1-4,5-9,10-14,15-19,20-24,25-29,30-34,35-39,40-44,45-49,50-54,55-59,60-64,65-69,70-74,75-79,80-84,85-89,90+,Deaths by age group,<1,1-4,5-9,10-14,15-19,20-24,25-29,30-34,35-39,40-44,45-49,50-54,55-59,60-64,65-69,70-74,75-79,80-84,85-89,90+,,North East,North West,Yorkshire and The Humber,East Midlands,West Midlands,East,London,South East,South West,Wales
-1,03/01/20,12254,12175,,2141,,48,8,4,4,6,11,17,32,54,69,115,239,361,486,696,1164,1535,2049,2457,2898,,30,5,2,1,5,7,7,21,32,43,62,137,191,275,415,697,826,1053,1098,982,,18,3,2,3,1,4,10,11,22,26,53,102,170,211,281,467,709,996,1359,1916,,673,1806,1240,1060,1349,1162,1113,1814,1225,787
-2,10/01/20,14058,13822,,2477,,50,9,8,9,16,23,37,46,68,85,191,279,426,604,857,1341,1724,2290,2697,3297,,29,4,4,7,8,14,28,28,46,52,114,156,259,355,509,761,924,1172,1231,1127,,21,5,4,2,8,9,9,18,22,33,77,123,167,249,348,580,800,1118,1466,2170,,707,1932,1339,1195,1450,1573,1272,2132,1487,939
-3,17/01/20,12990,13216,,2189,,69,7,5,4,10,25,37,47,77,118,189,306,461,562,803,1210,1612,2103,2421,2924,,38,4,4,3,5,21,31,29,49,72,106,200,295,338,471,690,886,1080,1117,991,,31,3,1,1,5,4,6,18,28,46,83,106,166,224,332,520,726,1023,1304,1933,,647,1696,1278,1106,1407,1457,1073,2064,1466,767
-4,24/01/20,11856,12760,,1893,,53,9,4,8,15,30,36,38,79,116,160,280,381,535,791,1167,1474,1863,2188,2626,,28,6,4,4,14,23,31,22,45,79,90,181,215,334,482,663,819,951,1014,910,,25,3,0,4,1,7,5,16,34,37,70,99,166,201,309,504,655,912,1174,1716,,612,1529,1187,1024,1231,1410,1028,1833,1253,723
-5,31/01/20,11612,12206,,1746,,50,6,5,4,23,23,28,58,76,100,163,278,382,525,732,1196,1445,1811,2124,2583,,22,4,4,3,17,16,19,40,45,58,107,180,247,324,437,683,827,919,970,872,,28,2,1,1,6,7,9,18,31,42,56,98,135,201,295,513,618,892,1154,1711,,561,1461,1136,1015,1262,1286,1092,1820,1233,727
-6,07/02/20,10986,11925,,1572,,30,8,4,4,10,34,23,38,71,95,157,289,371,512,689,1120,1358,1698,2040,2433,,14,5,2,4,8,23,11,24,53,55,95,175,208,306,423,626,713,875,943,843,,16,3,2,0,2,11,12,14,18,40,62,114,163,206,266,494,645,823,1097,1590,,564,1529,1072,922,1052,1259,987,1729,1157,690
-7,14/02/20,10944,11627,,1602,,43,6,2,4,16,26,27,40,85,92,165,288,345,490,641,1113,1305,1704,2039,2517,,29,4,1,3,9,19,19,27,52,58,99,172,209,287,400,660,726,870,995,852,,14,2,1,1,7,7,8,13,33,34,66,116,136,203,241,453,579,834,1044,1665,,573,1427,1059,976,1159,1172,967,1688,1169,728
-8,21/02/20,10841,11548,,1619,,51,5,6,7,20,18,29,60,77,117,182,232,346,511,695,1048,1338,1696,1927,2475,,32,5,4,2,14,14,17,39,46,72,105,140,195,285,400,598,778,894,906,893,,19,0,2,5,6,4,12,21,31,45,77,92,151,226,295,450,560,802,1021,1582,,539,1477,1087,924,1116,1167,1032,1675,1118,679
-9,28/02/20,10816,11183,,1547,,49,7,6,7,24,25,28,50,85,103,155,261,347,494,682,1111,1255,1713,2015,2398,,30,6,4,5,16,19,21,32,51,64,95,147,189,286,417,647,709,871,956,870,,19,1,2,2,8,6,7,18,34,39,60,114,158,208,265,464,546,842,1059,1528,,572,1476,1078,919,1174,1115,1085,1587,1133,651
-10,06/03/20,10895,11498,,1583,,56,11,2,7,21,23,39,53,72,104,155,258,358,481,679,1090,1325,1798,1969,2391,,31,7,1,2,13,16,27,33,45,69,93,153,220,278,388,646,725,938,932,841,,25,4,1,5,8,7,12,20,27,35,62,105,138,203,291,444,600,860,1037,1550,,568,1490,1112,930,1098,1149,982,1726,1170,652
-11,13/03/20,11019,11205,,1508,,53,13,3,6,18,39,29,55,80,90,179,260,401,500,685,1068,1366,1738,1951,2483,,24,5,1,2,13,26,20,41,48,50,109,168,246,296,424,625,748,904,935,885,,29,8,2,4,5,13,9,14,32,40,70,92,155,204,261,443,618,834,1016,1598,,590,1472,1053,915,1187,1211,964,1751,1174,675
-12,20/03/20,10645,10573,,1546,,44,2,6,4,15,22,31,41,66,100,160,245,390,469,686,1094,1373,1694,1902,2302,,25,2,3,3,11,17,22,25,47,63,99,158,229,281,404,629,763,892,905,820,,19,0,3,1,4,5,9,16,19,37,61,87,161,188,282,465,610,802,997,1482,,522,1443,1012,947,1115,1043,1008,1657,1156,719
-13,27/03/20,11141,10130,,1539,,49,8,1,4,12,17,33,55,71,95,163,235,381,522,699,1106,1397,1850,2016,2428,,27,3,1,1,8,11,22,40,40,65,97,146,235,286,423,666,788,1005,984,883,,22,5,0,3,4,6,11,15,31,30,66,89,146,236,276,440,609,845,1032,1545,,542,1538,982,922,1035,1182,1297,1822,1092,719
-14,03/04/20,16387,10305,,1969,,51,8,5,8,9,20,32,54,67,106,220,376,531,733,1044,1690,2179,2826,3015,3413,,26,2,2,3,7,12,22,39,36,67,124,244,336,453,662,1039,1303,1570,1520,1327,,25,6,3,5,2,8,10,15,31,39,96,132,195,280,382,651,876,1256,1495,2086,,770,2137,1436,1246,1812,1717,2511,2294,1520,920
-15,10/04/20,18516,10520,,1760,,38,6,4,4,8,16,41,45,108,114,249,412,598,852,1149,1797,2418,3195,3564,3898,,28,3,3,1,5,12,29,30,60,65,148,247,372,548,706,1098,1451,1795,1826,1521,,10,3,1,3,3,4,12,15,48,49,101,165,226,304,443,699,967,1400,1738,2377,,849,2597,1503,1452,2182,1984,2832,2604,1560,928
-16,17/04/20,22351,10497,,1777,,51,6,5,4,20,17,40,52,92,132,242,428,679,945,1272,2108,2817,3840,4444,5157,,24,4,2,1,12,12,28,32,56,77,147,229,434,591,791,1280,1635,2100,2111,1879,,27,2,3,3,8,5,12,20,36,55,95,199,245,354,481,828,1182,1740,2333,3278,,1155,3195,1960,1632,2536,2466,3275,3084,1854,1169
-17,24/04/20,21997,10458,,1575,,54,6,3,3,11,25,34,66,98,170,279,438,639,927,1248,1990,2741,3772,4349,5144,,33,4,3,2,5,11,23,39,62,111,175,274,407,578,795,1220,1614,2007,2085,1780,,21,2,0,1,6,14,11,27,36,59,104,164,232,349,453,770,1127,1765,2264,3364,,1103,3109,2095,1711,2481,2299,2785,3334,1924,1124
-18,01/05/20,17953,9941,,1272,,48,8,0,3,14,18,40,59,98,116,235,387,550,725,1023,1578,2155,2987,3514,4395,,30,5,0,0,11,11,23,35,60,73,148,235,347,453,631,940,1205,1555,1588,1507,,18,3,0,3,3,7,17,24,38,43,87,152,203,272,392,638,950,1432,1926,2888,,922,2503,1844,1418,1975,1982,1953,2853,1554,929
-19,08/05/20,12657,9576,,923,,28,6,4,10,9,18,25,33,59,89,165,267,407,531,763,1172,1528,2099,2441,3003,,16,3,3,7,5,11,18,18,33,62,98,160,255,334,447,682,867,1112,1089,989,,12,3,1,3,4,7,7,15,26,27,67,107,152,197,316,490,661,987,1352,2014,,769,1790,1328,1094,1326,1321,1213,1887,1218,692

diff --git a/uk-deaths-data/publishedweek192020.ods b/uk-deaths-data/publishedweek192020.ods
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index bc17d0f..0000000
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diff --git a/uk-deaths-data/publishedweek192020.xlsx b/uk-deaths-data/publishedweek192020.xlsx
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diff --git a/uk-deaths-data/publishedweek2015.csv b/uk-deaths-data/publishedweek2015.csv
deleted file mode 100644 (file)
index 83dbf2e..0000000
--- a/uk-deaths-data/publishedweek2015.csv
+++ /dev/null
@@ -1,56 +0,0 @@
-Week number,Week ended,"Total deaths, all ages",Total deaths: average of corresponding,,,Persons,,,,,,,,Males,,,,,,,,Females,,,,,,,,Deaths by region of usual residence,E12000001,E12000002,E12000003,E12000004,E12000005,E12000006,E12000007,E12000008,E12000009,W92000004
-,,,,Deaths by underlying cause,"All respiratory diseases (ICD-10 J00-J99)
-ICD-10 v 2013 (IRIS)",Deaths by age group,Under 1 year,01-14,15-44,45-64,65-74,75-84,85+,Deaths by age group,Under 1 year,01-14,15-44,45-64,65-74,75-84,85+,Deaths by age group,Under 1 year,01-14,15-44,45-64,65-74,75-84,85+,,North East,North West,Yorkshire and The Humber,East Midlands,West Midlands,East,London,South East,South West,Wales
-1,02/01/15,12286,11837.6,,2418,,56,16,198,1229,1845,3548,5392,,29,9,108,689,1042,1865,1915,,27,7,90,540,803,1683,3477,,699,1718,1261,1012,1296,1221,1233,1811,1272,725
-2,09/01/15,16237,12277,,3521,,80,28,298,1552,2387,4505,7387,,45,15,192,912,1347,2306,2596,,35,13,106,640,1040,2199,4791,,753,2282,1607,1328,1713,1712,1549,2525,1697,1031
-3,16/01/15,14866,11145,,3251,,46,28,316,1393,2107,4191,6785,,25,13,212,813,1205,2104,2443,,21,15,104,580,902,2087,4342,,799,1968,1442,1286,1542,1657,1275,2427,1498,936
-4,23/01/15,13934,10714,,2734,,61,20,318,1387,2019,3964,6165,,34,15,211,837,1105,2030,2215,,27,5,107,550,914,1934,3950,,798,1806,1386,1206,1400,1565,1220,2196,1510,828
-5,30/01/15,12900,10492,,2278,,66,20,329,1368,1869,3685,5563,,42,11,215,799,1100,1908,1986,,24,9,114,569,769,1777,3577,,717,1669,1220,1119,1395,1450,1119,1991,1398,801
-6,06/02/15,12039,10320.4,,2115,,66,30,286,1280,1774,3425,5178,,37,18,173,753,1052,1821,1912,,29,12,113,527,722,1604,3266,,669,1586,1151,1071,1229,1360,1097,1843,1297,720
-7,13/02/15,11822,10325,,1985,,66,18,312,1281,1798,3398,4949,,31,13,204,749,1059,1826,1850,,35,5,108,532,739,1572,3099,,661,1608,1128,1021,1161,1284,1108,1836,1283,710
-8,20/02/15,11434,10429.8,,1994,,47,18,303,1225,1714,3309,4817,,25,7,187,733,973,1713,1809,,22,11,116,492,741,1596,3008,,669,1466,1068,965,1152,1276,1102,1713,1257,739
-9,27/02/15,11472,10313.8,,1931,,48,25,296,1267,1749,3355,4731,,28,14,184,760,997,1749,1749,,20,11,112,507,752,1606,2982,,606,1466,1113,973,1149,1286,1062,1767,1290,736
-10,06/03/15,11469,10203.6,,1806,,44,19,291,1225,1850,3279,4759,,29,11,181,763,1087,1689,1696,,15,8,110,462,763,1590,3063,,622,1559,1106,966,1188,1232,1063,1709,1290,712
-11,13/03/15,10951,10160.2,,1744,,38,17,272,1228,1725,3122,4547,,27,7,158,707,981,1623,1590,,11,10,114,521,744,1499,2957,,573,1462,1040,904,1101,1172,1070,1731,1219,661
-12,20/03/15,10568,10020.6,,1642,,44,20,302,1254,1621,3029,4298,,17,15,194,755,929,1570,1600,,27,5,108,499,692,1459,2698,,566,1401,982,872,1083,1158,1092,1531,1192,680
-13,27/03/15,10493,9169.4,,1550,,45,21,286,1181,1650,3020,4289,,29,11,177,709,926,1576,1595,,16,10,109,472,724,1444,2694,,512,1392,1032,891,1071,1098,1080,1566,1164,666
-14,03/04/15,9062,9734,,1393,,47,17,214,976,1405,2642,3760,,27,12,137,589,819,1364,1410,,20,5,77,387,586,1278,2350,,490,1251,841,784,980,971,877,1352,920,580
-15,10/04/15,10089,10172.6,,1525,,57,18,271,1133,1601,2913,4096,,39,10,160,667,921,1477,1560,,18,8,111,466,680,1436,2536,,533,1384,1023,917,994,1062,1002,1488,1005,660
-16,17/04/15,11639,9666.2,,1730,,47,22,321,1342,1849,3323,4735,,24,17,209,803,1095,1721,1757,,23,5,112,539,754,1602,2978,,626,1521,1103,999,1294,1289,1089,1810,1212,671
-17,24/04/15,10599,9557.6,,1550,,56,20,298,1274,1682,3061,4206,,36,12,197,759,978,1620,1523,,20,8,101,515,704,1441,2683,,601,1405,1009,889,1115,1050,1000,1708,1129,662
-18,01/05/15,10134,9771,,1469,,55,21,277,1162,1628,2928,4040,,36,11,176,696,962,1574,1511,,19,10,101,466,666,1354,2529,,516,1385,950,856,1053,1112,961,1530,1110,628
-19,08/05/15,8862,9182.8,,1250,,35,19,224,954,1499,2625,3505,,18,11,156,554,890,1417,1316,,17,8,68,400,609,1208,2189,,503,1166,895,748,949,910,827,1343,901,589
-20,15/05/15,10290,9479.4,,1404,,50,20,309,1227,1703,2998,3983,,32,11,207,714,1024,1565,1502,,18,9,102,513,679,1433,2481,,544,1404,1038,890,1057,1099,949,1552,1100,622
-21,22/05/15,10005,9414.4,,1325,,57,14,304,1176,1680,2926,3839,,35,7,198,705,987,1605,1419,,22,7,106,471,693,1321,2420,,514,1367,989,870,1018,989,906,1587,1122,614
-22,29/05/15,8213,8410.4,,1074,,53,22,213,1014,1365,2464,3082,,34,11,125,595,791,1303,1184,,19,11,88,419,574,1161,1898,,457,1116,866,663,844,838,793,1216,816,588
-23,05/06/15,10157,8867.4,,1256,,48,23,295,1224,1692,2895,3968,,24,17,175,732,986,1485,1450,,24,6,120,492,706,1410,2518,,472,1337,1024,865,1042,1150,961,1538,1094,648
-24,12/06/15,9548,9181.8,,1242,,52,10,270,1188,1586,2781,3660,,35,5,165,722,934,1475,1391,,17,5,105,466,652,1306,2269,,528,1262,953,817,975,997,880,1483,1022,606
-25,19/06/15,9312,8815.4,,1234,,54,22,279,1163,1536,2652,3602,,38,13,181,695,872,1332,1372,,16,9,98,468,664,1320,2230,,459,1248,896,757,943,1020,892,1496,983,595
-26,26/06/15,9190,8811.8,,1168,,51,19,298,1135,1573,2682,3425,,31,10,188,700,945,1439,1297,,20,9,110,435,628,1243,2128,,514,1254,916,756,927,998,887,1396,916,597
-27,03/07/15,9205,8758,,1121,,49,19,288,1065,1615,2560,3603,,30,10,207,619,909,1301,1372,,19,9,81,446,706,1259,2231,,489,1293,868,750,964,977,901,1382,1017,535
-28,10/07/15,9015,8610.6,,1022,,65,18,272,1151,1548,2568,3393,,29,9,190,682,909,1403,1313,,36,9,82,469,639,1165,2080,,491,1238,851,817,941,939,842,1370,949,554
-29,17/07/15,8802,8667.6,,977,,58,14,268,1128,1438,2486,3405,,34,6,155,688,828,1323,1293,,24,8,113,440,610,1163,2112,,466,1127,855,781,882,952,881,1320,933,574
-30,24/07/15,8791,8606,,960,,57,14,288,1096,1583,2520,3233,,38,10,177,651,912,1346,1249,,19,4,111,445,671,1174,1984,,459,1196,846,734,938,934,833,1382,905,529
-31,31/07/15,8617,8652.2,,940,,51,20,299,1084,1446,2493,3223,,30,12,183,627,839,1350,1195,,21,8,116,457,607,1143,2028,,437,1195,846,715,917,941,780,1217,1000,546
-32,07/08/15,8862,8543,,1006,,54,21,264,1095,1471,2576,3379,,25,13,186,680,886,1349,1340,,29,8,78,415,585,1227,2039,,462,1227,953,664,913,908,858,1388,895,564
-33,14/08/15,9148,8560.2,,1055,,51,15,286,1169,1523,2577,3525,,35,10,185,715,893,1365,1339,,16,5,101,454,630,1212,2186,,458,1250,888,792,950,1014,879,1370,974,548
-34,21/08/15,9121,8689,,978,,66,21,298,1159,1543,2655,3379,,33,14,194,667,896,1434,1289,,33,7,104,492,647,1221,2090,,475,1223,915,747,969,943,901,1364,1000,557
-35,28/08/15,9026,7755.4,,1074,,54,11,314,1100,1530,2621,3393,,37,8,204,668,879,1372,1271,,17,3,110,432,651,1249,2122,,445,1262,896,797,834,981,855,1358,967,603
-36,04/09/15,7878,9031.4,,900,,48,12,224,981,1318,2310,2985,,27,7,148,612,778,1219,1165,,21,5,76,369,540,1091,1820,,438,1044,772,663,774,856,803,1188,825,489
-37,11/09/15,9258,8719.8,,1062,,54,14,278,1177,1537,2571,3623,,25,5,175,678,917,1396,1396,,29,9,103,499,620,1175,2227,,471,1262,931,814,932,922,867,1423,1065,554
-38,18/09/15,9097,8807.6,,1032,,40,18,287,1098,1549,2627,3478,,25,10,182,680,889,1394,1273,,15,8,105,418,660,1233,2205,,462,1175,852,748,973,942,901,1448,1020,555
-39,25/09/15,9529,8954.6,,1117,,56,15,295,1156,1531,2791,3682,,29,11,184,704,922,1475,1399,,27,4,111,452,609,1316,2283,,476,1267,922,795,969,981,917,1540,975,664
-40,02/10/15,9410,9091.4,,1149,,65,18,299,1133,1569,2636,3690,,35,8,184,680,896,1411,1400,,30,10,115,453,673,1225,2290,,495,1260,908,814,957,984,918,1419,1086,552
-41,09/10/15,9776,9098.2,,1198,,43,13,297,1196,1599,2820,3807,,22,7,183,711,931,1471,1416,,21,6,114,485,668,1349,2391,,505,1283,915,821,951,1105,976,1457,1076,652
-42,16/10/15,9511,9181,,1165,,59,26,256,1133,1585,2781,3668,,38,12,177,678,937,1464,1410,,21,14,79,455,648,1317,2258,,494,1291,895,809,997,1030,912,1402,1039,612
-43,23/10/15,9711,9357.6,,1183,,60,22,292,1158,1603,2786,3789,,37,12,188,706,943,1496,1479,,23,10,104,452,660,1290,2310,,480,1276,951,835,1053,1022,921,1461,1079,607
-44,30/10/15,9618,9468.4,,1237,,50,14,277,1137,1565,2671,3879,,23,8,185,695,914,1414,1476,,27,6,92,442,651,1257,2403,,523,1299,886,814,967,1030,969,1506,1003,593
-45,06/11/15,9994,9466.8,,1247,,48,24,304,1275,1654,2853,3826,,22,9,200,760,956,1454,1405,,26,15,104,515,698,1399,2421,,524,1409,1014,883,1084,1011,955,1482,1002,606
-46,13/11/15,9938,9650.8,,1235,,53,26,261,1258,1607,2804,3926,,34,15,179,795,980,1499,1479,,19,11,82,463,627,1305,2447,,530,1376,960,767,1027,1018,993,1544,1081,613
-47,20/11/15,9830,9498,,1317,,56,21,295,1172,1648,2835,3802,,35,15,202,720,950,1554,1445,,21,6,93,452,698,1281,2357,,527,1317,937,844,1071,1043,966,1470,1019,611
-48,27/11/15,9822,9496.8,,1156,,33,21,317,1219,1621,2759,3850,,19,11,206,719,922,1510,1445,,14,10,111,500,699,1249,2405,,512,1322,994,844,990,1066,915,1536,1037,589
-49,04/12/15,10365,10208.2,,1345,,59,25,295,1216,1707,3003,4056,,40,14,194,711,1021,1558,1572,,19,11,101,505,686,1445,2484,,534,1425,1012,919,1087,1065,998,1522,1127,659
-50,11/12/15,10269,10440.4,,1413,,37,25,286,1196,1632,2928,4153,,14,10,192,722,916,1562,1552,,23,15,94,474,716,1366,2601,,540,1400,1050,915,1006,1018,985,1536,1102,688
-51,18/12/15,10689,11221,,1437,,66,28,365,1255,1782,3023,4169,,37,10,234,726,1036,1602,1502,,29,18,131,529,746,1421,2667,,618,1526,1060,897,1101,1086,990,1656,1089,646
-52,25/12/15,8630,8139.2,,1233,,49,26,246,1010,1387,2451,3461,,33,7,151,625,797,1260,1315,,16,19,95,385,590,1191,2146,,480,1167,891,707,826,916,870,1347,877,535
-53,01/01/16,7524,8139,,1128,,39,12,146,882,1259,2197,2988,,25,6,85,510,737,1139,1185,,14,6,61,372,522,1058,1803,,407,1074,755,646,799,653,766,1123,757,516

diff --git a/uk-deaths-data/publishedweek2015.ods b/uk-deaths-data/publishedweek2015.ods
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diff --git a/uk-deaths-data/publishedweek2015.xls b/uk-deaths-data/publishedweek2015.xls
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diff --git a/uk-deaths-data/publishedweek522016.csv b/uk-deaths-data/publishedweek522016.csv
deleted file mode 100644 (file)
index 751d09f..0000000
--- a/uk-deaths-data/publishedweek522016.csv
+++ /dev/null
@@ -1,55 +0,0 @@
-Week number,Week ended,"Total deaths, all ages",Total deaths: average of corresponding,,,Persons,,,,,,,,Males,,,,,,,,Females,,,,,,,,Deaths by region of usual residence,E12000001,E12000002,E12000003,E12000004,E12000005,E12000006,E12000007,E12000008,E12000009,W92000004
-,,,,Deaths by underlying cause,"All respiratory diseases (ICD-10 J00-J99)
-ICD-10 v 2013 (IRIS)",Deaths by age group,Under 1 year,01-14,15-44,45-64,65-74,75-84,85+,Deaths by age group,Under 1 year,01-14,15-44,45-64,65-74,75-84,85+,Deaths by age group,Under 1 year,01-14,15-44,45-64,65-74,75-84,85+,,North East,North West,Yorkshire and The Humber,East Midlands,West Midlands,East,London,South East,South West,Wales
-1,08/01/16,13045,11701.4,,2046,,49,17,299,1482,2179,3727,5292,,31,10,178,867,1246,1897,1982,,18,7,121,615,933,1830,3310,,705,1748,1284,1067,1396,1401,1226,1951,1424,809
-2,15/01/16,11501,13016.4,,1835,,64,24,326,1363,1925,3283,4512,,36,14,221,812,1159,1709,1656,,28,10,105,551,766,1574,2856,,600,1532,1148,956,1208,1237,1048,1771,1263,711
-3,22/01/16,11473,11765.4,,1775,,50,18,345,1293,1831,3327,4606,,32,8,238,791,1079,1734,1750,,18,10,107,502,752,1593,2856,,612,1602,1119,929,1209,1253,1068,1710,1219,720
-4,29/01/16,11317,11289,,1810,,47,14,324,1322,1859,3147,4599,,25,8,217,773,1069,1643,1754,,22,6,107,549,790,1504,2845,,631,1516,1131,858,1195,1236,1065,1730,1207,717
-5,05/02/16,11052,10965.6,,1748,,60,22,314,1281,1779,3181,4405,,35,14,203,767,1040,1683,1655,,25,8,111,514,739,1498,2750,,620,1459,1109,954,1197,1160,1059,1604,1169,690
-6,12/02/16,11170,10704,,1730,,60,21,331,1356,1826,3058,4502,,36,12,203,782,1062,1639,1666,,24,9,128,574,764,1419,2836,,599,1466,1066,917,1262,1155,1040,1718,1222,700
-7,19/02/16,10590,10669.4,,1700,,52,22,305,1333,1720,2982,4175,,27,14,196,803,1015,1616,1577,,25,8,109,530,705,1366,2598,,588,1443,1083,881,1088,1057,999,1596,1171,657
-8,26/02/16,11056,10657.6,,1734,,58,20,267,1294,1774,3127,4516,,34,13,176,733,995,1650,1707,,24,7,91,561,779,1477,2809,,582,1497,1115,930,1087,1180,1021,1707,1215,696
-9,04/03/16,11285,10613,,1774,,39,21,318,1328,1864,3180,4533,,22,13,212,799,1024,1709,1745,,17,8,106,529,840,1471,2788,,582,1505,1107,913,1144,1240,1093,1742,1218,721
-10,11/03/16,11010,10544,,1768,,54,22,273,1340,1755,3171,4390,,27,10,172,795,1030,1713,1711,,27,12,101,545,725,1458,2679,,569,1525,1097,911,1104,1190,1008,1694,1148,734
-11,18/03/16,11022,10405,,1709,,55,22,295,1358,1781,3070,4434,,31,10,194,835,1048,1596,1705,,24,12,101,523,733,1474,2729,,552,1460,1102,917,1136,1143,1058,1595,1292,738
-12,25/03/16,9635,10209.4,,1485,,55,18,247,1148,1567,2713,3878,,32,13,157,683,898,1437,1482,,23,5,90,465,669,1276,2396,,474,1331,937,809,891,923,900,1542,1122,668
-13,01/04/16,10286,9668,,1688,,49,15,264,1184,1698,2992,4079,,26,10,171,662,941,1550,1583,,23,5,93,522,757,1442,2496,,578,1362,968,859,942,1079,1039,1611,1104,712
-14,08/04/16,11599,9592.4,,1971,,53,15,306,1327,1941,3238,4719,,34,7,201,768,1109,1738,1743,,19,8,105,559,832,1500,2976,,606,1514,1128,911,1232,1190,1111,1828,1319,742
-15,15/04/16,11417,10206.2,,1809,,63,18,311,1312,1927,3166,4617,,32,10,189,774,1137,1688,1789,,31,8,122,538,790,1478,2828,,594,1572,1105,900,1183,1217,1007,1785,1282,738
-16,22/04/16,10925,10104.8,,1597,,65,24,319,1292,1816,3085,4324,,40,15,208,766,1039,1613,1647,,25,9,111,526,777,1472,2677,,539,1470,1008,908,1134,1189,999,1683,1250,714
-17,29/04/16,10413,9776.6,,1396,,43,22,327,1301,1694,2927,4098,,22,14,212,792,1003,1534,1548,,21,8,115,509,691,1393,2550,,571,1371,1014,857,1065,1147,969,1634,1128,629
-18,06/05/16,9137,10127.8,,1261,,55,23,348,1075,1490,2583,3559,,34,15,249,629,870,1410,1367,,21,8,99,446,620,1173,2192,,495,1280,941,703,929,954,876,1365,994,569
-19,13/05/16,10637,9058.4,,1447,,49,19,308,1277,1768,2994,4218,,36,5,195,743,1057,1563,1673,,13,14,113,534,711,1431,2545,,547,1420,1055,914,1069,1190,971,1646,1143,652
-20,20/05/16,9953,9699.2,,1328,,61,21,328,1149,1686,2855,3853,,34,12,209,687,960,1532,1464,,27,9,119,462,726,1323,2389,,533,1327,927,862,1013,1147,884,1534,1092,611
-21,27/05/16,9739,9524,,1248,,63,19,326,1185,1681,2697,3767,,36,10,205,716,957,1441,1417,,27,9,121,469,724,1256,2350,,484,1300,936,826,995,1103,884,1489,1082,624
-22,03/06/16,7909,8417.2,,982,,35,19,214,963,1445,2253,2980,,16,9,128,546,827,1188,1180,,19,10,86,417,618,1065,1800,,431,1138,814,680,776,790,710,1242,817,500
-23,10/06/16,9873,9047.2,,1292,,58,21,268,1181,1613,2875,3857,,28,10,167,694,923,1535,1466,,30,11,101,487,690,1340,2391,,542,1306,1038,839,1011,1119,939,1468,1004,584
-24,17/06/16,9386,9388.4,,1225,,49,22,255,1195,1604,2703,3556,,28,13,174,725,931,1463,1367,,21,9,81,470,673,1240,2189,,473,1252,923,858,981,1037,858,1410,993,578
-25,24/06/16,9365,8986,,1206,,57,15,295,1161,1549,2659,3625,,29,9,192,675,909,1443,1454,,28,6,103,486,640,1216,2171,,528,1272,925,804,1015,966,831,1408,1039,558
-26,01/07/16,9228,8852,,1106,,46,13,303,1192,1570,2573,3530,,26,9,204,701,897,1369,1280,,20,4,99,491,673,1204,2250,,488,1157,936,801,954,971,880,1497,964,549
-27,08/07/16,9138,8872.2,,1062,,49,18,287,1176,1552,2567,3489,,30,9,175,698,917,1359,1334,,19,9,112,478,635,1208,2155,,507,1269,910,770,956,950,796,1407,1031,524
-28,15/07/16,9388,8706.8,,1101,,54,15,279,1153,1634,2649,3603,,33,8,186,683,964,1395,1336,,21,7,93,470,670,1254,2267,,485,1242,948,784,943,1054,798,1463,1052,599
-29,22/07/16,9350,8776.2,,1168,,55,18,282,1115,1586,2638,3650,,37,9,192,667,936,1459,1414,,18,9,90,448,650,1179,2236,,538,1295,877,830,914,988,847,1443,1023,560
-30,29/07/16,9335,8712.2,,1190,,39,15,312,1074,1567,2641,3683,,20,8,203,630,924,1433,1389,,19,7,109,444,643,1208,2294,,476,1223,910,762,923,1013,940,1414,1027,610
-31,05/08/16,9182,8682.6,,1112,,56,19,276,1171,1542,2588,3524,,29,11,187,690,923,1416,1302,,27,8,89,481,619,1172,2222,,467,1316,879,739,983,1004,822,1311,1052,580
-32,12/08/16,9172,8651.4,,1065,,57,15,277,1183,1552,2557,3520,,37,9,172,738,902,1364,1288,,20,6,105,445,650,1193,2232,,492,1244,886,780,941,1031,801,1346,974,641
-33,19/08/16,9070,8671.8,,1032,,42,17,276,1078,1610,2624,3423,,26,10,191,653,946,1383,1324,,16,7,85,425,664,1241,2099,,476,1279,887,742,951,1005,831,1317,983,574
-34,26/08/16,9319,8783.4,,1093,,48,16,241,1104,1577,2680,3652,,23,4,157,699,899,1480,1395,,25,12,84,405,678,1200,2257,,499,1250,860,793,1039,991,822,1419,1000,619
-35,02/09/16,7923,8020,,917,,43,14,228,968,1415,2233,3020,,21,9,135,564,825,1204,1196,,22,5,93,404,590,1029,1824,,398,1114,800,626,764,877,795,1251,797,470
-36,09/09/16,9399,8813.2,,1036,,48,23,283,1161,1562,2659,3661,,30,17,185,710,944,1398,1345,,18,6,98,451,618,1261,2316,,478,1312,942,844,974,981,873,1384,1033,552
-37,16/09/16,9124,8825.8,,1027,,56,15,265,1170,1583,2628,3406,,27,6,153,690,900,1397,1338,,29,9,112,480,683,1231,2068,,491,1222,914,736,898,998,839,1433,988,576
-38,23/09/16,8945,8839.4,,1039,,58,15,264,1132,1548,2564,3364,,30,11,173,670,910,1404,1251,,28,4,91,462,638,1160,2113,,435,1230,890,730,892,979,854,1399,941,563
-39,30/09/16,8994,9105.6,,979,,53,15,297,1151,1549,2506,3422,,22,7,194,697,925,1327,1350,,31,8,103,454,624,1179,2072,,481,1219,856,787,971,879,852,1345,987,592
-40,07/10/16,9291,9133.2,,1060,,57,21,275,1115,1647,2641,3531,,30,8,176,637,992,1385,1381,,27,13,99,478,655,1256,2150,,465,1331,907,777,938,945,863,1456,1024,562
-41,14/10/16,9719,9210,,1153,,72,14,272,1145,1633,2746,3835,,41,6,183,674,961,1444,1508,,31,8,89,471,672,1302,2327,,520,1328,940,791,966,1069,919,1524,1056,587
-42,21/10/16,9768,9225.6,,1238,,50,21,276,1158,1652,2724,3887,,25,9,178,687,965,1485,1488,,25,12,98,471,687,1239,2399,,511,1322,919,831,977,1020,931,1542,1078,624
-43,28/10/16,9724,9445.4,,1270,,58,16,271,1239,1567,2800,3773,,25,11,170,741,908,1494,1472,,33,5,101,498,659,1306,2301,,530,1401,914,850,966,1034,860,1472,1043,624
-44,04/11/16,10152,9459,,1276,,52,21,281,1186,1723,2833,4056,,31,11,188,670,1011,1451,1598,,21,10,93,516,712,1382,2458,,535,1351,1041,850,1013,1048,904,1630,1114,644
-45,11/11/16,10470,9584.8,,1342,,54,15,278,1279,1709,2954,4178,,28,6,187,730,1021,1576,1565,,26,9,91,549,688,1378,2613,,546,1390,1017,889,1045,1127,976,1691,1139,626
-46,18/11/16,10694,9751.4,,1374,,57,26,355,1225,1703,2992,4332,,31,18,250,709,1001,1566,1730,,26,8,105,516,702,1426,2602,,547,1513,1025,892,1117,1184,941,1605,1154,681
-47,25/11/16,10603,9572,,1413,,49,26,284,1226,1716,3062,4239,,27,12,174,734,1013,1621,1616,,22,14,110,492,703,1441,2623,,536,1432,1022,887,1090,1131,987,1679,1154,661
-48,02/12/16,10439,9615.4,,1371,,58,15,345,1191,1752,2961,4116,,35,8,225,692,984,1557,1574,,23,7,120,499,768,1404,2542,,550,1491,973,888,1076,1176,936,1578,1112,643
-49,09/12/16,11223,10042,,1591,,57,28,310,1266,1808,3176,4578,,29,13,202,749,1019,1676,1738,,28,15,108,517,789,1500,2840,,589,1529,1193,932,1164,1212,1029,1658,1201,693
-50,16/12/16,10533,10317,,1522,,72,22,281,1219,1675,2943,4316,,36,16,180,748,979,1500,1595,,36,6,101,471,696,1443,2721,,561,1444,1036,893,1098,1107,933,1634,1145,663
-51,23/12/16,11493,11061.8,,1640,,56,16,339,1253,1927,3170,4725,,30,6,218,754,1057,1682,1796,,26,10,121,499,870,1488,2929,,679,1594,1097,981,1149,1207,1052,1784,1223,691
-52,30/12/16,8003,7925,,1312,,41,7,178,849,1269,2294,3364,,24,5,99,451,738,1229,1288,,17,2,79,398,531,1065,2076,,456,1087,794,759,715,774,761,1236,846,558

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diff --git a/uk-deaths-data/publishedweek522016.xls b/uk-deaths-data/publishedweek522016.xls
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diff --git a/uk-deaths-data/publishedweek522017.csv b/uk-deaths-data/publishedweek522017.csv
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--- a/uk-deaths-data/publishedweek522017.csv
+++ /dev/null
@@ -1,55 +0,0 @@
-Week number,Week ended,"Total deaths, all ages",Total deaths: average of corresponding,,,Persons,,,,,,,,Males,,,,,,,,Females,,,,,,,,Deaths by region of usual residence,E12000001,E12000002,E12000003,E12000004,E12000005,E12000006,E12000007,E12000008,E12000009,W92000004
-,,,,Deaths by underlying cause,"All respiratory diseases (ICD-10 J00-J99)
-ICD-10 v 2013 (IRIS)",Deaths by age group,Under 1 year,01-14,15-44,45-64,65-74,75-84,85+,Deaths by age group,Under 1 year,01-14,15-44,45-64,65-74,75-84,85+,Deaths by age group,Under 1 year,01-14,15-44,45-64,65-74,75-84,85+,,North East,North West,Yorkshire and The Humber,East Midlands,West Midlands,East,London,South East,South West,Wales
-1,06/01/17,11991,11782,,2321,,58,18,215,1232,1880,3450,5136,,32,9,143,718,1070,1803,1907,,26,9,72,514,810,1647,3229,,602,1665,1208,1016,1243,1187,1173,1899,1228,744
-2,13/01/17,13715,12692,,2690,,56,18,287,1372,2149,3886,5947,,33,10,199,819,1237,2015,2230,,23,8,88,553,912,1871,3717,,738,1840,1351,1170,1439,1450,1296,2161,1419,825
-3,20/01/17,13610,11773,,2625,,54,19,301,1374,2132,3701,6029,,28,10,183,837,1202,1902,2282,,26,9,118,537,930,1799,3747,,676,1786,1383,1190,1414,1484,1276,2195,1346,835
-4,27/01/17,12877,11441,,2373,,52,16,286,1273,1946,3652,5652,,28,7,189,763,1164,1893,2074,,24,9,97,510,782,1759,3578,,627,1666,1242,1116,1362,1488,1198,1999,1278,881
-5,03/02/17,12485,11128,,2147,,55,14,308,1239,1930,3509,5430,,27,8,209,751,1149,1854,2059,,28,6,99,488,781,1655,3371,,631,1625,1243,1045,1293,1384,1210,1920,1359,749
-6,10/02/17,12269,10935,,2093,,57,17,293,1342,1940,3483,5129,,29,9,196,825,1136,1754,1887,,28,8,97,517,804,1729,3242,,635,1566,1224,1036,1234,1411,1161,1916,1339,723
-7,17/02/17,11644,10835,,1932,,49,18,295,1316,1811,3242,4913,,33,10,176,794,1071,1719,1884,,16,8,119,522,740,1523,3029,,610,1528,1186,964,1243,1253,1095,1847,1217,690
-8,24/02/17,11794,10983,,1872,,47,20,286,1298,1816,3214,5112,,26,8,173,754,1031,1680,1923,,21,12,113,544,785,1534,3189,,636,1519,1159,954,1216,1327,1114,1834,1312,701
-9,03/03/17,11248,10980,,1766,,53,22,254,1252,1823,3142,4699,,32,14,153,733,1039,1646,1768,,21,8,101,519,784,1496,2931,,606,1488,1123,963,1184,1328,930,1673,1221,715
-10,10/03/17,11077,10816,,1660,,54,17,316,1240,1756,3086,4608,,29,5,211,748,1045,1636,1760,,25,12,105,492,711,1450,2848,,570,1464,1110,1038,1163,1230,969,1738,1144,634
-11,17/03/17,10697,10641,,1561,,59,7,274,1260,1722,3015,4360,,38,4,171,744,996,1573,1672,,21,3,103,516,726,1442,2688,,581,1450,1121,963,1140,1150,946,1593,1083,653
-12,24/03/17,10325,10193,,1436,,55,13,268,1256,1739,2940,4054,,27,7,174,762,1000,1612,1512,,28,6,94,494,739,1328,2542,,535,1364,1065,947,1034,1134,930,1557,1107,635
-13,31/03/17,10027,9863,,1324,,65,20,307,1202,1656,2838,3939,,32,12,196,705,969,1519,1455,,33,8,111,497,687,1319,2484,,509,1313,1045,870,1024,1109,888,1520,1064,658
-14,07/04/17,9939,10001,,1378,,59,21,277,1181,1705,2748,3947,,35,8,186,701,1005,1491,1565,,24,13,91,480,700,1257,2382,,523,1373,929,835,1048,1056,905,1522,1075,642
-15,14/04/17,8493,10624,,1143,,38,20,235,1003,1468,2397,3330,,20,8,145,634,849,1255,1250,,18,12,90,369,619,1142,2080,,410,1217,795,708,868,918,801,1316,863,577
-16,21/04/17,9644,10625,,1311,,68,19,280,1130,1585,2834,3721,,39,13,172,658,943,1529,1423,,29,6,108,472,642,1305,2298,,517,1362,1010,812,978,996,896,1409,984,654
-17,28/04/17,10908,10246,,1435,,70,20,273,1315,1822,3132,4276,,41,10,167,784,1104,1687,1655,,29,10,106,531,718,1445,2621,,583,1495,1053,882,1125,1137,1053,1678,1159,727
-18,05/05/17,9064,9984,,1154,,44,18,268,1035,1529,2557,3613,,25,11,167,648,892,1345,1441,,19,7,101,387,637,1212,2172,,479,1279,872,803,902,956,804,1356,997,600
-19,12/05/17,10693,9158,,1423,,41,23,323,1275,1813,3019,4196,,22,11,192,752,1088,1631,1657,,19,12,131,523,725,1388,2539,,551,1368,1053,988,1059,1153,970,1685,1155,687
-20,19/05/17,10288,9902,,1325,,38,18,291,1320,1794,2854,3973,,20,10,192,787,1061,1506,1503,,18,8,99,533,733,1348,2470,,553,1329,1030,817,1079,1124,914,1639,1161,615
-21,26/05/17,10040,9640,,1286,,71,21,307,1187,1722,2744,3983,,40,10,192,737,1022,1448,1553,,31,11,115,450,700,1296,2430,,519,1349,936,802,1088,1118,953,1526,1118,602
-22,02/06/17,8332,8417,,1076,,49,12,223,995,1475,2361,3217,,29,9,141,604,864,1260,1204,,20,3,82,391,611,1101,2013,,408,1208,818,726,849,813,787,1217,897,586
-23,09/06/17,9766,9170,,1229,,57,27,308,1227,1632,2785,3727,,37,20,203,746,950,1486,1477,,20,7,105,481,682,1299,2250,,514,1311,950,841,1060,1016,876,1527,1066,584
-24,16/06/17,9367,9473,,1062,,60,20,259,1188,1663,2554,3619,,30,12,172,726,949,1372,1400,,30,8,87,462,714,1182,2219,,499,1272,918,819,1016,990,829,1380,1015,599
-25,23/06/17,9627,9117,,1215,,65,17,300,1175,1570,2715,3785,,36,12,194,698,905,1490,1465,,29,5,106,477,665,1225,2320,,509,1328,901,841,991,991,902,1473,1058,608
-26,30/06/17,9334,8956,,1170,,54,13,275,1121,1656,2676,3536,,36,7,166,672,982,1405,1314,,18,6,109,449,674,1271,2222,,451,1174,914,804,996,1028,903,1456,1038,546
-27,07/07/17,9263,8959,,1012,,60,23,293,1202,1622,2584,3477,,33,15,182,731,984,1397,1391,,27,8,111,471,638,1187,2086,,495,1278,904,802,985,1010,820,1395,996,556
-28,14/07/17,9376,8893,,1141,,56,23,270,1144,1660,2694,3528,,30,11,158,690,982,1446,1398,,26,12,112,454,678,1248,2130,,502,1225,953,862,973,1005,843,1393,1031,564
-29,21/07/17,9113,8946,,959,,64,19,331,1210,1541,2531,3415,,31,12,224,727,938,1331,1358,,33,7,107,483,603,1200,2057,,514,1196,856,809,947,970,867,1389,979,551
-30,28/07/17,8882,8889,,1004,,37,15,280,1184,1539,2439,3388,,20,10,170,704,931,1289,1304,,17,5,110,480,608,1150,2084,,456,1174,881,738,941,949,783,1381,963,586
-31,04/08/17,8941,8762,,1009,,47,12,269,1131,1510,2542,3427,,27,6,170,700,887,1356,1304,,20,6,99,431,623,1186,2123,,507,1192,891,784,911,955,792,1345,946,590
-32,11/08/17,9038,8772,,937,,55,17,257,1141,1580,2620,3368,,26,8,179,685,946,1393,1326,,29,9,78,456,634,1227,2042,,479,1171,882,772,943,1005,858,1346,982,572
-33,18/08/17,9299,8802,,1081,,50,20,293,1146,1568,2601,3617,,27,11,196,678,927,1381,1414,,23,9,97,468,641,1220,2203,,464,1260,849,747,936,1018,929,1481,998,592
-34,25/08/17,9382,8953,,1121,,51,11,286,1095,1549,2667,3723,,29,9,182,665,894,1439,1452,,22,2,104,430,655,1228,2271,,482,1299,848,783,966,1002,907,1502,1001,570
-35,01/09/17,8149,8062,,940,,45,18,211,997,1448,2279,3148,,26,6,126,611,845,1222,1221,,19,12,85,386,603,1057,1927,,434,1117,836,667,780,853,766,1205,908,555
-36,08/09/17,9497,8940,,1058,,53,17,273,1190,1613,2644,3703,,34,11,197,690,968,1432,1451,,19,6,76,500,645,1212,2252,,512,1307,921,808,1017,1066,866,1445,993,542
-37,15/09/17,9454,8929,,1022,,48,18,277,1207,1641,2628,3634,,23,12,189,707,949,1432,1452,,25,6,88,500,692,1196,2182,,539,1285,877,758,1001,990,871,1493,1006,609
-38,22/09/17,9534,8923,,1088,,49,21,294,1157,1614,2623,3776,,29,13,196,694,944,1426,1488,,20,8,98,463,670,1197,2288,,504,1221,919,814,978,1096,900,1422,1074,585
-39,29/09/17,9689,9120,,1153,,45,27,243,1160,1686,2698,3830,,21,16,161,669,952,1438,1532,,24,11,82,491,734,1260,2298,,507,1305,957,782,990,1071,882,1468,1109,593
-40,06/10/17,9778,9248,,1208,,66,20,284,1171,1677,2677,3881,,38,10,192,672,964,1403,1568,,28,10,92,499,713,1274,2313,,501,1289,946,818,1003,1057,923,1521,1063,631
-41,13/10/17,9940,9411,,1219,,48,11,245,1185,1678,2846,3926,,27,5,149,706,965,1534,1519,,21,6,96,479,713,1312,2407,,513,1340,1011,827,1001,1085,928,1497,1068,640
-42,20/10/17,10031,9452,,1199,,62,13,293,1165,1731,2836,3929,,30,7,191,717,1022,1504,1545,,32,6,102,448,709,1332,2384,,550,1359,1019,806,997,1056,934,1541,1098,650
-43,27/10/17,9739,9563,,1144,,54,25,269,1166,1658,2765,3802,,34,14,168,712,975,1452,1494,,20,11,101,454,683,1313,2308,,509,1375,903,743,1058,1037,931,1539,1020,608
-44,03/11/17,9984,9562,,1244,,40,18,288,1243,1659,2875,3860,,30,14,181,737,977,1563,1454,,10,4,107,506,682,1312,2406,,536,1356,1006,850,1014,1129,897,1473,1105,595
-45,10/11/17,10346,9871,,1314,,47,20,322,1251,1734,2889,4081,,26,14,212,736,1057,1583,1608,,21,6,110,515,677,1306,2473,,510,1365,1042,931,1117,1132,931,1572,1117,598
-46,17/11/17,10275,10030,,1362,,48,9,308,1242,1682,2901,4084,,26,8,208,723,963,1557,1616,,22,1,100,519,719,1344,2468,,502,1381,1027,898,1096,1091,949,1539,1103,666
-47,24/11/17,10621,9861,,1319,,50,20,310,1308,1728,2962,4234,,24,11,220,763,1016,1596,1624,,26,9,90,545,712,1366,2610,,550,1419,1089,862,1080,1148,1038,1623,1151,639
-48,01/12/17,10538,9858,,1436,,56,21,295,1216,1737,2945,4266,,33,10,200,735,991,1585,1633,,23,11,95,481,746,1360,2633,,562,1453,1045,878,1065,1168,972,1608,1123,636
-49,08/12/17,10781,10322,,1497,,58,20,268,1224,1761,3027,4423,,38,13,168,760,1029,1619,1736,,20,7,100,464,732,1408,2687,,612,1538,1013,970,1066,1139,1008,1649,1140,630
-50,15/12/17,11217,10353,,1603,,39,19,267,1282,1776,3176,4658,,23,10,173,753,1048,1690,1791,,16,9,94,529,728,1486,2867,,595,1509,1048,971,1128,1226,1042,1765,1204,708
-51,22/12/17,12517,11130,,1905,,52,20,307,1397,1995,3523,5220,,25,10,188,849,1114,1796,2004,,27,10,119,548,881,1727,3216,,719,1709,1181,1039,1318,1322,1153,1961,1332,762
-52,29/12/17,8487,7831,,1431,,23,18,172,895,1275,2444,3654,,15,12,97,529,665,1289,1410,,8,6,75,366,610,1155,2244,,500,1194,840,685,844,878,814,1305,863,541

diff --git a/uk-deaths-data/publishedweek522017.ods b/uk-deaths-data/publishedweek522017.ods
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index 58c17bd..0000000
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diff --git a/uk-deaths-data/publishedweek522017.xls b/uk-deaths-data/publishedweek522017.xls
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index 31b2070..0000000
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diff --git a/uk-deaths-data/publishedweek522018.csv b/uk-deaths-data/publishedweek522018.csv
deleted file mode 100644 (file)
index 747d4f2..0000000
--- a/uk-deaths-data/publishedweek522018.csv
+++ /dev/null
@@ -1,55 +0,0 @@
-Week number,Week ended,"Total deaths, all ages",Total deaths: average of corresponding,,,Persons,,,,,,,,Males,,,,,,,,Females,,,,,,,,Deaths by region of usual residence,E12000001,E12000002,E12000003,E12000004,E12000005,E12000006,E12000007,E12000008,E12000009,W92000004
-,,,,Deaths by underlying cause,"All respiratory diseases (ICD-10 J00-J99)
-ICD-10 v 2013 (IRIS)",Deaths by age group,Under 1 year,01-14,15-44,45-64,65-74,75-84,85+,Deaths by age group,Under 1 year,01-14,15-44,45-64,65-74,75-84,85+,Deaths by age group,Under 1 year,01-14,15-44,45-64,65-74,75-84,85+,,North East,North West,Yorkshire and The Humber,East Midlands,West Midlands,East,London,South East,South West,Wales
-1,05/01/18,12723,12079,,2361,,52,18,208,1290,1976,3612,5565,,32,11,118,748,1120,1865,2080,,20,7,90,542,856,1747,3485,,640,1747,1300,1085,1313,1404,1130,1902,1393,783
-2,12/01/18,15050,13167,,3075,,73,17,302,1561,2321,4155,6621,,42,5,186,918,1347,2120,2499,,31,12,116,643,974,2035,4122,,837,2113,1481,1266,1468,1677,1342,2371,1552,904
-3,19/01/18,14256,12418,,2829,,59,22,286,1507,2191,3866,6325,,33,12,185,888,1268,2009,2390,,26,10,101,619,923,1857,3935,,783,1828,1387,1175,1544,1562,1239,2287,1535,885
-4,26/01/18,13935,11954,,2672,,50,25,298,1459,2157,3824,6122,,26,18,219,889,1273,1978,2264,,24,7,79,570,884,1846,3858,,779,1855,1363,1165,1433,1553,1264,2184,1460,850
-5,02/02/18,13285,11605,,2479,,41,14,339,1404,1988,3661,5838,,24,8,216,809,1186,1960,2204,,17,6,123,595,802,1701,3634,,740,1728,1285,1154,1441,1468,1208,2046,1382,815
-6,09/02/18,12495,11333,,2197,,45,23,293,1347,2032,3376,5374,,26,13,190,816,1183,1786,2043,,19,10,103,531,849,1590,3331,,663,1615,1206,1109,1335,1359,1041,1867,1378,801
-7,16/02/18,12246,11059,,2081,,48,17,318,1377,1953,3492,5041,,24,11,196,836,1168,1851,1999,,24,6,122,541,785,1641,3042,,612,1665,1230,1024,1285,1307,1171,1810,1283,803
-8,23/02/18,12142,11125,,2128,,26,13,294,1378,1896,3398,5137,,18,7,206,840,1067,1731,1915,,8,6,88,538,829,1667,3222,,671,1677,1196,1034,1251,1300,1105,1757,1314,789
-9,02/03/18,10854,11037,,1900,,45,11,254,1229,1728,3028,4559,,25,6,168,745,998,1579,1751,,20,5,86,484,730,1449,2808,,551,1485,1125,907,1308,1088,1060,1611,997,634
-10,09/03/18,12997,10935,,2302,,47,27,287,1362,2019,3691,5564,,26,16,195,806,1158,1945,2142,,21,11,92,556,861,1746,3422,,677,1690,1192,1072,1390,1390,1177,1919,1560,896
-11,16/03/18,12788,10774,,2271,,47,17,329,1316,1989,3594,5496,,25,7,219,798,1157,1879,2075,,22,10,110,518,832,1715,3421,,614,1690,1203,1116,1343,1358,1121,1954,1414,918
-12,23/03/18,11913,10289,,1946,,46,15,278,1349,1917,3342,4966,,35,5,182,810,1133,1732,1885,,11,10,96,539,784,1610,3081,,576,1516,1124,1038,1263,1251,1095,1853,1283,774
-13,30/03/18,9941,9944,,1657,,43,20,261,1065,1586,2884,4082,,21,7,179,674,921,1580,1505,,22,13,82,391,665,1304,2577,,498,1335,973,819,1019,1074,910,1518,1047,633
-14,06/04/18,10794,10286,,1761,,46,22,260,1229,1764,3013,4460,,28,13,167,718,1029,1605,1699,,18,9,93,511,735,1408,2761,,534,1470,1105,886,1054,1196,1014,1578,1142,730
-15,13/04/18,12301,10328,,1971,,36,25,337,1382,2053,3442,5026,,19,14,220,812,1197,1870,1974,,17,11,117,570,856,1572,3052,,631,1613,1199,1068,1228,1425,1133,1883,1293,743
-16,20/04/18,11223,10395,,1641,,54,21,301,1386,1880,3109,4472,,29,10,191,830,1106,1678,1722,,25,11,110,556,774,1431,2750,,559,1456,1037,986,1170,1248,1039,1743,1212,688
-17,27/04/18,10306,10381,,1426,,57,12,340,1213,1707,2906,4071,,32,6,227,731,980,1522,1566,,25,6,113,482,727,1384,2505,,516,1391,987,904,969,1209,947,1613,1117,614
-18,04/05/18,10153,9807,,1369,,51,21,308,1363,1725,2907,3778,,29,14,201,815,1008,1539,1511,,22,7,107,548,717,1368,2267,,534,1347,922,892,1113,1117,917,1570,1082,633
-19,11/05/18,8624,9526,,1055,,48,21,247,1115,1437,2384,3372,,26,12,163,648,841,1280,1343,,22,9,84,467,596,1104,2029,,510,1116,886,740,823,937,841,1294,929,530
-20,18/05/18,10141,9978,,1248,,52,24,300,1330,1760,2791,3884,,29,16,205,791,1017,1509,1543,,23,8,95,539,743,1282,2341,,504,1390,888,943,1105,1125,913,1511,1068,667
-21,25/05/18,9636,9727,,1179,,60,13,294,1258,1659,2687,3665,,33,8,170,731,994,1431,1509,,27,5,124,527,665,1256,2156,,501,1278,913,828,983,1053,932,1512,997,603
-22,01/06/18,8147,8163,,1065,,46,18,250,998,1431,2330,3074,,27,14,171,581,845,1259,1210,,19,4,79,417,586,1071,1864,,458,1142,769,716,859,839,784,1187,830,538
-23,08/06/18,9950,9767,,1270,,46,19,298,1195,1700,2881,3811,,32,9,193,723,968,1510,1524,,14,10,105,472,732,1371,2287,,548,1309,985,884,1065,1157,890,1435,1057,607
-24,15/06/18,9343,9313,,1150,,60,17,286,1199,1607,2670,3504,,33,7,182,698,949,1479,1368,,27,10,104,501,658,1191,2136,,454,1167,947,777,967,991,921,1442,1085,561
-25,22/06/18,9256,9232,,1103,,55,21,308,1161,1613,2550,3548,,27,13,203,696,994,1382,1447,,28,8,105,465,619,1168,2101,,475,1217,944,764,971,985,855,1448,1019,562
-26,29/06/18,9212,9052,,1055,,43,22,306,1184,1652,2508,3497,,23,15,193,726,936,1346,1393,,20,7,113,458,716,1162,2104,,484,1214,882,822,954,1011,824,1408,983,599
-27,06/07/18,9258,9030,,1086,,50,23,286,1150,1548,2611,3590,,26,15,181,697,892,1418,1443,,24,8,105,453,656,1193,2147,,477,1280,895,788,998,940,814,1426,991,625
-28,13/07/18,9293,9018,,1123,,48,21,304,1140,1600,2633,3547,,25,15,204,677,957,1421,1388,,23,6,100,463,643,1212,2159,,470,1239,901,758,961,993,941,1403,1025,583
-29,20/07/18,9127,9032,,1107,,45,15,304,1166,1577,2484,3536,,28,8,187,703,925,1333,1455,,17,7,117,463,652,1151,2081,,471,1229,942,730,949,953,905,1373,971,548
-30,27/07/18,9141,8890,,1019,,59,13,291,1193,1566,2628,3391,,36,10,197,727,922,1417,1277,,23,3,94,466,644,1211,2114,,477,1219,907,762,897,1008,955,1374,941,560
-31,03/08/18,9161,8763,,1005,,62,18,286,1155,1536,2620,3484,,33,12,190,685,863,1357,1388,,29,6,96,470,673,1263,2096,,486,1228,817,830,961,1010,883,1396,957,574
-32,10/08/18,9319,8818,,1019,,59,18,328,1175,1608,2563,3568,,30,11,237,725,960,1439,1378,,29,7,91,450,648,1124,2190,,448,1231,913,793,946,1028,947,1453,997,537
-33,17/08/18,8830,8905,,941,,64,11,253,1130,1558,2489,3325,,38,7,161,669,918,1311,1339,,26,4,92,461,640,1178,1986,,446,1171,880,742,910,991,870,1361,902,518
-34,24/08/18,8978,9033,,921,,44,22,250,1083,1601,2560,3418,,30,8,165,659,901,1381,1365,,14,14,85,424,700,1179,2053,,477,1134,913,780,983,993,808,1392,900,565
-35,31/08/18,7865,8162,,827,,51,11,233,1017,1442,2150,2961,,30,8,151,575,815,1123,1177,,21,3,82,442,627,1027,1784,,437,1058,779,630,793,877,741,1170,845,511
-36,07/09/18,9445,9069,,1098,,45,20,323,1196,1621,2638,3602,,27,9,194,709,985,1361,1475,,18,11,129,487,636,1277,2127,,534,1152,956,804,1005,996,904,1464,1000,594
-37,14/09/18,9191,9091,,999,,55,18,275,1180,1600,2576,3487,,29,9,179,722,922,1353,1387,,26,9,96,458,678,1223,2100,,465,1231,865,814,956,999,834,1440,986,579
-38,21/09/18,9305,9063,,1034,,69,18,292,1171,1623,2601,3531,,42,11,179,709,945,1373,1431,,27,7,113,462,678,1228,2100,,475,1226,912,776,947,990,865,1503,986,598
-39,28/09/18,9150,9285,,987,,50,10,270,1083,1607,2629,3501,,29,6,184,652,929,1443,1397,,21,4,86,431,678,1186,2104,,483,1262,904,766,965,957,868,1375,965,560
-40,05/10/18,9503,9388,,1050,,40,17,287,1200,1627,2696,3636,,16,7,173,709,965,1461,1443,,24,10,114,491,662,1235,2193,,514,1302,948,781,1020,990,898,1387,1020,595
-41,12/10/18,9649,9511,,1124,,47,20,328,1212,1607,2741,3694,,23,14,229,699,987,1451,1437,,24,6,99,513,620,1290,2257,,486,1291,963,832,980,1071,860,1491,1043,606
-42,19/10/18,9864,9602,,1141,,43,18,301,1209,1654,2769,3870,,26,14,195,760,965,1493,1549,,17,4,106,449,689,1276,2321,,527,1274,968,815,979,1045,941,1570,1088,640
-43,26/10/18,9603,9601,,1154,,65,24,309,1200,1657,2642,3706,,34,15,202,702,953,1474,1466,,31,9,107,498,704,1168,2240,,526,1215,956,880,1079,993,905,1376,1004,633
-44,02/11/18,9529,9692,,1090,,46,24,289,1151,1569,2700,3750,,27,15,192,677,937,1448,1530,,19,9,97,474,632,1252,2220,,511,1330,964,810,890,1042,896,1465,988,604
-45,09/11/18,10151,10003,,1295,,44,12,308,1157,1666,2949,4015,,24,7,195,687,971,1589,1549,,20,5,113,470,695,1360,2466,,520,1403,981,813,1081,1094,925,1543,1106,642
-46,16/11/18,10193,10104,,1268,,47,29,292,1238,1716,2819,4052,,24,15,196,734,986,1519,1684,,23,14,96,504,730,1300,2368,,490,1408,969,899,1047,1128,940,1538,1077,656
-47,23/11/18,9957,10050,,1240,,62,22,312,1223,1700,2766,3872,,35,8,197,700,982,1455,1568,,27,14,115,523,718,1311,2304,,511,1357,1013,848,1001,1071,903,1503,1062,657
-48,30/11/18,10033,10087,,1224,,58,20,317,1246,1658,2829,3905,,32,5,205,733,953,1504,1531,,26,15,112,513,705,1325,2374,,505,1330,998,838,1076,1077,948,1523,1040,673
-49,07/12/18,10287,10509,,1341,,45,15,326,1218,1696,2965,4022,,24,9,220,701,991,1573,1532,,21,6,106,517,705,1392,2490,,539,1377,1006,830,1098,1106,958,1594,1076,674
-50,14/12/18,10550,10519,,1386,,51,13,295,1265,1814,2962,4150,,26,9,190,747,1057,1576,1598,,25,4,105,518,757,1386,2552,,561,1422,1108,873,1034,1130,1007,1573,1106,708
-51,21/12/18,11116,11343,,1509,,41,23,333,1306,1867,3136,4410,,24,15,222,810,1112,1680,1708,,17,8,111,496,755,1456,2702,,625,1439,1148,930,1145,1124,1035,1688,1225,724
-52,28/12/18,7131,7909,,1053,,22,11,166,792,1205,2013,2922,,10,7,103,450,694,1051,1146,,12,4,63,342,511,962,1776,,459,1020,688,651,660,695,655,1062,756,461

diff --git a/uk-deaths-data/publishedweek522018.ods b/uk-deaths-data/publishedweek522018.ods
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diff --git a/uk-deaths-data/publishedweek522018withupdatedrespiratoryrow.xls b/uk-deaths-data/publishedweek522018withupdatedrespiratoryrow.xls
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index 9c895bd..0000000
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diff --git a/uk-deaths-data/publishedweek522019.csv b/uk-deaths-data/publishedweek522019.csv
deleted file mode 100644 (file)
index 584bc15..0000000
--- a/uk-deaths-data/publishedweek522019.csv
+++ /dev/null
@@ -1,55 +0,0 @@
-Week number,Week ended,"Total deaths, all ages",Total deaths: average of corresponding,,,Persons,,,,,,,,Males,,,,,,,,Females,,,,,,,,Deaths by region of usual residence,E12000001,E12000002,E12000003,E12000004,E12000005,E12000006,E12000007,E12000008,E12000009,W92000004
-,,,,Deaths by underlying cause,"All respiratory diseases (ICD-10 J00-J99)
-ICD-10 v 2013 (IRIS)",Deaths by age group,Under 1 year,01-14,15-44,45-64,65-74,75-84,85+,Deaths by age group,Under 1 year,01-14,15-44,45-64,65-74,75-84,85+,Deaths by age group,Under 1 year,01-14,15-44,45-64,65-74,75-84,85+,,North East,North West,Yorkshire and The Humber,East Midlands,West Midlands,East,London,South East,South West,Wales
-1,04/01/19,10955,12273,,1736,,43,15,215,1199,1766,3078,4639,,28,5,128,693,992,1590,1758,,15,10,87,506,774,1488,2881,,574,1456,1148,964,1180,1136,1021,1586,1136,718
-2,11/01/19,12609,13670,,2214,,50,20,280,1419,2179,3590,5071,,20,13,168,852,1265,1857,1997,,30,7,112,567,914,1733,3074,,643,1612,1279,1089,1299,1386,1137,1927,1394,809
-3,18/01/19,11860,13056,,1972,,59,29,319,1373,2004,3414,4662,,39,14,211,831,1131,1837,1828,,20,15,108,542,873,1577,2834,,627,1566,1197,979,1187,1344,1073,1936,1236,683
-4,25/01/19,11740,12486,,1942,,42,22,339,1438,1936,3266,4697,,26,10,225,860,1154,1766,1862,,16,12,114,578,782,1500,2835,,640,1593,1137,1037,1131,1291,1045,1875,1229,734
-5,01/02/19,11297,11998,,1931,,57,15,307,1367,1852,3126,4573,,38,10,208,805,1045,1664,1834,,19,5,99,562,807,1462,2739,,618,1485,1131,963,1150,1202,1066,1718,1191,745
-6,08/02/19,11660,11623,,1918,,54,25,267,1387,1955,3251,4721,,36,17,152,869,1100,1718,1895,,18,8,115,518,855,1533,2826,,608,1595,1133,988,1241,1283,1088,1738,1251,701
-7,15/02/19,11824,11301,,1931,,49,17,305,1372,1911,3392,4778,,27,8,201,799,1117,1776,1932,,22,9,104,573,794,1616,2846,,569,1618,1189,1033,1231,1342,1061,1802,1207,748
-8,22/02/19,11295,11383,,1890,,59,30,276,1395,1824,3169,4542,,30,16,159,850,1088,1696,1804,,29,14,117,545,736,1473,2738,,610,1495,1124,928,1143,1218,1045,1777,1234,695
-9,01/03/19,11044,11051,,1786,,52,20,288,1264,1826,3117,4477,,24,10,182,745,1059,1656,1787,,28,10,106,519,767,1461,2690,,572,1425,1109,927,1188,1214,1009,1712,1178,684
-10,08/03/19,10898,11286,,1657,,45,16,303,1342,1857,3042,4293,,32,10,197,839,1112,1664,1689,,13,6,106,503,745,1378,2604,,582,1463,1083,946,1150,1116,1004,1708,1198,622
-11,15/03/19,10567,11095,,1559,,57,24,299,1311,1718,2933,4225,,30,11,194,788,1043,1531,1633,,27,13,105,523,675,1402,2592,,527,1393,1054,879,1092,1198,975,1601,1149,666
-12,22/03/19,10402,10456,,1486,,49,24,293,1249,1713,2948,4126,,29,9,200,774,965,1596,1630,,20,15,93,475,748,1352,2496,,532,1437,1087,890,1062,1066,925,1640,1089,628
-13,29/03/19,9867,10076,,1314,,45,17,289,1222,1643,2794,3857,,26,8,205,728,978,1470,1501,,19,9,84,494,665,1324,2356,,529,1278,943,875,930,1136,910,1540,1047,654
-14,05/04/19,10126,10268,,1412,,41,13,296,1232,1614,2937,3993,,21,8,184,725,930,1589,1592,,20,5,112,507,684,1348,2401,,518,1277,959,876,1050,1224,928,1582,1039,642
-15,12/04/19,10291,10362,,1396,,47,23,288,1265,1712,2907,4049,,31,14,194,783,995,1543,1629,,16,9,94,482,717,1364,2420,,510,1341,1034,858,1084,1188,937,1623,1037,637
-16,19/04/19,9025,10291,,1262,,48,21,251,1100,1446,2547,3612,,24,11,146,644,852,1420,1430,,24,10,105,456,594,1127,2182,,459,1225,910,759,928,1014,834,1350,919,580
-17,26/04/19,10059,10317,,1406,,34,18,273,1207,1730,2811,3986,,16,9,171,724,970,1543,1588,,18,9,102,483,760,1268,2398,,551,1365,996,856,1008,1084,951,1495,1053,678
-18,03/05/19,11207,9804,,1581,,46,18,297,1334,1869,3207,4436,,26,14,207,821,1089,1709,1725,,20,4,90,513,780,1498,2711,,541,1493,1125,986,1136,1139,1040,1782,1251,688
-19,10/05/19,9055,9488,,1239,,56,17,262,1094,1513,2579,3534,,34,9,159,624,868,1362,1411,,22,8,103,470,645,1217,2123,,484,1214,924,776,906,943,807,1456,922,600
-20,17/05/19,10272,10036,,1355,,44,14,304,1274,1650,2864,4122,,24,7,192,795,977,1528,1685,,20,7,112,479,673,1336,2437,,548,1402,980,887,1082,1112,927,1570,1078,658
-21,24/05/19,10284,9747,,1324,,51,21,309,1262,1765,2946,3930,,29,12,193,751,1044,1564,1532,,22,9,116,511,721,1382,2398,,530,1397,1024,888,1070,1097,876,1620,1126,627
-22,31/05/19,8260,8125,,1105,,45,16,239,991,1382,2403,3184,,22,11,147,565,784,1247,1287,,23,5,92,426,598,1156,1897,,436,1176,782,699,840,842,809,1252,886,518
-23,07/06/19,10140,9860,,1290,,48,18,306,1223,1741,2846,3958,,26,9,199,757,1015,1599,1614,,22,9,107,466,726,1247,2344,,554,1349,1025,880,1082,982,919,1516,1182,626
-24,14/06/19,9445,9408,,1134,,46,18,298,1149,1658,2672,3604,,22,11,198,673,963,1464,1442,,24,7,100,476,695,1208,2162,,507,1313,889,817,950,1012,900,1452,986,598
-25,21/06/19,9458,9302,,1134,,46,20,279,1150,1625,2711,3627,,25,11,196,714,963,1480,1427,,21,9,83,436,662,1231,2200,,478,1344,931,751,938,1011,900,1510,1032,542
-26,28/06/19,9511,9177,,1143,,39,21,273,1214,1605,2692,3667,,22,9,186,738,969,1509,1503,,17,12,87,476,636,1183,2164,,475,1250,984,790,1013,1028,892,1481,1005,564
-27,05/07/19,9062,9123,,1076,,33,26,255,1112,1561,2650,3425,,24,17,170,637,910,1420,1318,,9,9,85,475,651,1230,2107,,437,1269,896,750,940,981,833,1431,962,534
-28,12/07/19,9179,9170,,1081,,44,16,259,1140,1564,2616,3540,,23,7,174,698,900,1394,1471,,21,9,85,442,664,1222,2069,,458,1272,932,747,949,995,875,1357,972,588
-29,19/07/19,9080,9100,,1024,,45,14,279,1136,1500,2610,3496,,31,10,180,683,863,1380,1426,,14,4,99,453,637,1230,2070,,478,1287,841,809,962,994,829,1328,981,553
-30,26/07/19,9112,9023,,996,,57,14,267,1117,1598,2580,3479,,36,7,165,660,951,1374,1351,,21,7,102,457,647,1206,2128,,534,1237,895,774,882,1024,833,1376,982,543
-31,02/08/19,9271,8963,,1116,,57,11,265,1123,1597,2664,3554,,30,6,164,702,921,1445,1455,,27,5,101,421,676,1219,2099,,536,1234,936,782,929,988,911,1424,926,570
-32,09/08/19,9122,9026,,1048,,57,12,245,1095,1578,2575,3560,,26,9,156,662,938,1410,1387,,31,3,89,433,640,1165,2173,,530,1149,867,795,953,1026,891,1334,1010,542
-33,16/08/19,9093,9025,,1033,,54,24,277,1244,1573,2530,3391,,28,13,197,743,927,1371,1436,,26,11,80,501,646,1159,1955,,497,1237,857,749,969,933,892,1355,978,589
-34,23/08/19,8994,9113,,981,,47,8,264,1127,1582,2479,3487,,31,4,169,681,942,1357,1439,,16,4,95,446,640,1122,2048,,505,1203,927,726,918,964,826,1389,963,553
-35,30/08/19,8242,8197,,854,,45,16,224,1026,1419,2319,3193,,23,10,138,629,846,1240,1232,,22,6,86,397,573,1079,1961,,466,1153,832,697,826,838,784,1245,814,558
-36,06/09/19,9695,9177,,1125,,54,19,268,1199,1643,2775,3737,,29,9,183,715,955,1487,1480,,25,10,85,484,688,1288,2257,,473,1248,937,867,939,1115,976,1518,1014,582
-37,13/09/19,9513,9260,,1028,,60,12,297,1169,1617,2654,3704,,31,3,178,709,946,1421,1547,,29,9,119,460,671,1233,2157,,482,1328,916,774,1001,1088,916,1399,1020,567
-38,20/09/19,9440,9197,,1056,,45,18,264,1174,1592,2695,3652,,23,11,165,716,918,1412,1463,,22,7,99,458,674,1283,2189,,494,1283,954,827,974,1049,889,1385,982,572
-39,27/09/19,9517,9283,,1045,,55,14,269,1197,1547,2760,3675,,28,8,174,704,922,1514,1527,,27,6,95,493,625,1246,2148,,538,1299,906,842,1027,1014,840,1404,1017,611
-40,04/10/19,9799,9450,,1114,,68,15,325,1189,1665,2780,3757,,37,7,218,705,950,1489,1508,,31,8,107,484,715,1291,2249,,491,1322,948,875,1008,1059,846,1573,1059,597
-41,11/10/19,9973,9651,,1209,,46,16,302,1137,1595,2869,4008,,26,10,208,686,966,1525,1609,,20,6,94,451,629,1344,2399,,527,1400,1005,847,1027,1073,887,1557,1026,590
-42,18/10/19,10156,9726,,1236,,54,14,303,1154,1628,2920,4083,,32,10,193,676,937,1551,1641,,22,4,110,478,691,1369,2442,,567,1400,1019,863,1093,1083,886,1556,1040,622
-43,25/10/19,10021,9674,,1252,,49,14,281,1198,1663,2799,4017,,23,6,186,699,963,1550,1617,,26,8,95,499,700,1249,2400,,540,1361,1001,846,1019,1063,895,1491,1107,670
-44,01/11/19,10164,9777,,1333,,45,19,289,1196,1663,2938,4014,,27,9,176,682,980,1501,1573,,18,10,113,514,683,1437,2441,,537,1338,1033,877,967,1100,976,1547,1118,642
-45,08/11/19,10697,10142,,1363,,52,7,314,1236,1676,2998,4414,,29,3,199,738,991,1616,1737,,23,4,115,498,685,1382,2677,,553,1455,1053,880,1110,1181,974,1701,1102,653
-46,15/11/19,10650,10226,,1451,,46,19,271,1254,1673,3070,4317,,19,9,172,739,980,1635,1692,,27,10,99,515,693,1435,2625,,607,1402,1070,889,1080,1090,1041,1690,1083,674
-47,22/11/19,10882,10124,,1423,,57,19,283,1225,1743,3163,4392,,32,9,168,724,1042,1724,1776,,25,10,115,501,701,1439,2616,,582,1464,1039,931,1138,1166,1023,1618,1203,699
-48,29/11/19,10958,10164,,1566,,56,14,312,1237,1751,3142,4446,,35,10,209,739,1008,1746,1808,,21,4,103,498,743,1396,2638,,563,1469,1139,935,1184,1116,1025,1648,1166,689
-49,06/12/19,10816,10585,,1505,,50,17,315,1275,1689,3078,4392,,32,11,204,756,985,1639,1748,,18,6,111,519,704,1439,2644,,558,1477,1011,958,1083,1184,986,1647,1157,737
-50,13/12/19,11188,10622,,1637,,52,32,315,1313,1793,3215,4468,,29,16,187,746,1028,1711,1772,,23,16,128,567,765,1504,2696,,585,1637,1102,973,1130,1176,1044,1690,1130,699
-51,20/12/19,11926,11499,,1839,,53,19,368,1316,1903,3299,4968,,25,9,229,768,1095,1733,1995,,28,10,139,548,808,1566,2973,,670,1712,1173,1050,1269,1238,1028,1709,1288,767
-52,27/12/19,7533,8014,,1166,,34,13,148,773,1185,2231,3149,,20,6,85,448,666,1123,1218,,14,7,63,325,519,1108,1931,,411,1200,737,729,720,716,653,1094,766,496

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diff --git a/uk-deaths-data/scotland-deaths-2020.csv b/uk-deaths-data/scotland-deaths-2020.csv
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@@ -1,21 +0,0 @@
-Week number3,Week beginning,,,Total deaths from all causes,Total deaths females,Total deaths males,Total deaths: average of corresponding,week over the previous 5 years4,,,,,,,,,,,,Females,,,,,,,Males,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
-,,,,,,,,,,Persons,Deaths by age group,Under 1 year,01-14,15-44,45-64,65-74,75-84,85+,,Under 1 year,01-14,15-44,45-64,65-74,75-84,85+,Under 1 year,01-14,15-44,45-64,65-74,75-84,85+,Deaths by NHS Board of usual residence 5,Ayrshire and Arran,Borders,Dumfries and Galloway,Fife,Forth Valley,Grampian,Greater Glasgow and Clyde,Highland,Lanarkshire,Lothian,Orkney,Shetland,Tayside,Western Isles,,Deaths by Council Area of usual residence5,Aberdeen City,Aberdeenshire,Angus,Argyll and Bute,City of Edinburgh,Clackmannanshire,Dumfries and Galloway,Dundee City,East Ayrshire,East Dunbartonshire,East Lothian,East Renfrewshire,Falkirk,Fife,Glasgow City,Highland,Inverclyde,Midlothian,Moray,Na h-Eileanan Siar,North Ayrshire,North Lanarkshire,Orkney Islands,Perth and Kinross,Renfrewshire,Scottish Borders,Shetland Islands,South Ayrshire,South Lanarkshire,Stirling,West Dunbartonshire,West Lothian,,Deaths by location6,Care Home,Home / Non-institution,Hospital,Other institution
-1,30/12/19,,,1161,616,545,1276,,,,,3,1,24,153,197,372,411,,1,1,11,61,81,195,266,2,0,13,92,116,177,145,,105,20,37,70,76,113,250,75,138,166,1,5,96,9,,,38,48,26,16,87,11,37,35,25,21,23,13,45,70,123,59,25,20,27,9,38,75,1,35,43,20,5,42,63,20,25,36,,,305,306,548,2
-2,06/01/20,,,1567,817,750,1559.6,,,,,0,3,59,215,288,428,574,,0,1,17,95,127,220,357,0,2,42,120,161,208,217,,121,41,58,96,92,148,353,95,194,196,5,4,156,8,,,56,69,34,35,107,13,58,60,37,25,34,26,61,96,189,60,24,20,23,8,43,103,5,62,55,41,4,41,91,18,34,35,,,356,413,790,8
-3,13/01/20,,,1322,671,651,1382,,,,,3,0,36,193,239,385,466,,1,0,9,80,107,186,288,2,0,27,113,132,199,178,,114,38,42,96,68,122,296,94,165,155,2,2,118,10,,,46,56,29,30,86,18,42,50,40,31,26,23,36,96,143,64,28,14,20,10,38,83,2,39,46,38,2,36,82,14,25,29,,,318,366,632,6
-4,20/01/20,,,1226,627,599,1316.6,,,,,1,3,50,171,231,343,427,,1,0,14,80,104,155,273,0,3,36,91,127,188,154,,103,29,42,96,78,117,235,77,161,165,4,2,107,10,,,39,55,24,25,89,16,42,40,26,16,24,24,40,96,114,52,18,19,23,10,37,86,4,43,43,29,2,40,75,22,20,33,,,292,333,596,5
-5,27/01/20,,,1188,580,608,1279.6,,,,,3,3,31,174,214,368,395,,2,2,12,63,96,173,232,1,1,19,111,118,195,163,,96,27,43,79,67,109,264,82,151,154,2,5,99,10,,,49,45,29,23,77,17,43,36,26,29,17,18,29,79,139,59,23,20,15,10,39,83,2,34,33,27,5,31,68,21,22,40,,,279,313,590,6
-6,03/02/20,,,1216,616,600,1253.8,,,,,6,4,31,170,211,378,416,,1,2,15,64,92,191,251,5,2,16,106,119,187,165,,88,24,44,81,55,131,245,69,169,191,5,6,97,11,,,47,54,34,25,106,7,44,28,30,21,28,20,31,81,130,44,23,17,30,11,24,82,5,35,35,24,6,34,87,17,16,40,,,285,321,604,6
-7,10/02/20,,,1162,544,618,1259.2,,,,,4,1,39,166,240,328,384,,0,0,8,64,96,143,233,4,1,31,102,144,185,151,,76,25,43,80,73,119,243,68,155,171,3,4,99,3,,,41,60,26,26,88,20,43,32,24,31,22,24,32,80,113,42,20,17,18,3,29,70,3,41,39,25,4,23,85,21,16,44,,,258,350,552,2
-8,17/02/20,,,1162,596,566,1246.8,,,,,2,2,45,151,224,354,384,,1,1,17,65,101,172,239,1,1,28,86,123,182,145,,105,23,39,88,65,131,238,66,144,152,1,4,98,8,,,49,63,29,17,82,12,39,41,24,16,19,18,35,88,119,49,20,17,19,8,46,66,1,28,41,23,4,35,78,18,24,34,,,266,337,552,7
-9,24/02/20,,,1171,591,580,1164.8,,,,,2,3,47,165,214,333,407,,0,2,16,73,95,152,253,2,1,31,92,119,181,154,,99,35,37,79,57,111,255,78,136,171,4,3,96,10,,,50,47,19,15,91,9,37,42,34,29,23,16,31,79,126,63,26,21,14,10,30,65,4,35,37,35,3,35,71,17,21,36,,,266,362,539,4
-10,02/03/20,,,1208,623,585,1228.6,,,,,3,0,48,173,217,360,407,,3,0,21,71,86,178,264,0,0,27,102,131,182,143,,105,32,40,79,75,106,283,70,151,166,5,4,86,6,,,55,31,23,22,102,11,40,28,35,25,23,19,48,79,154,48,21,13,20,6,40,81,5,35,43,32,4,30,70,16,21,28,,,288,347,567,6
-11,09/03/20,,,1156,570,586,1169,,,,,5,2,49,168,219,318,395,,3,0,23,70,85,159,230,2,2,26,98,134,159,165,,109,29,36,80,55,128,204,77,142,182,6,3,94,11,,,43,64,29,22,106,10,36,26,37,18,23,9,28,80,100,55,15,13,21,11,36,76,6,39,39,29,3,36,66,17,23,40,,,248,351,552,5
-12,16/03/20,,,1196,580,616,1120.4,,,,,4,0,41,189,228,363,371,,3,0,11,81,91,171,223,1,0,30,108,137,192,148,,101,36,41,70,66,132,264,72,138,169,7,3,92,5,,,47,58,33,16,93,15,41,31,39,41,18,14,31,70,117,56,23,19,27,5,36,71,7,28,44,36,3,26,67,20,25,39,,,273,368,544,11
-13,23/03/20,,,1079,578,501,1118.2,,,,,5,1,26,146,202,317,382,,4,0,10,56,89,171,248,1,1,16,90,113,146,134,,108,23,28,98,74,112,167,70,137,144,8,9,96,5,,,38,53,22,29,83,14,28,30,47,10,15,20,48,98,77,41,13,16,21,5,30,78,8,44,26,23,9,31,59,12,21,30,,,261,354,463,1
-14,30/03/20,,,1744,837,907,1098.4,,,,,3,2,61,226,333,542,577,,2,1,18,101,127,251,337,1,1,43,125,206,291,240,,121,42,73,82,96,141,479,102,231,228,9,8,126,6,,,62,54,37,34,124,16,73,46,26,44,26,20,48,82,234,68,63,33,25,6,52,117,9,43,75,42,8,43,114,32,43,45,,,442,571,724,7
-15,06/04/20,,,1978,927,1051,1099.8,,,,,6,2,55,241,330,641,703,,1,1,22,78,122,300,403,5,1,33,163,208,341,300,,131,37,53,109,110,158,499,100,274,313,11,8,167,8,,,56,85,42,29,174,19,53,71,38,32,55,32,57,109,257,71,64,33,17,8,46,133,11,54,71,37,8,47,141,34,43,51,,,599,601,769,9
-16,13/04/20,,,1916,938,978,1067.2,,,,,3,0,47,214,295,606,751,,3,0,15,75,115,283,447,0,0,32,139,180,323,304,,158,31,42,113,85,169,482,107,272,271,4,3,171,8,,,64,76,46,41,158,11,42,78,47,35,36,39,47,113,224,66,62,34,29,8,58,141,4,47,81,31,3,53,131,27,41,43,,,681,531,701,3
-17,20/04/20,,,1836,961,875,1086.8,,,,,2,1,54,230,309,578,662,,1,0,19,84,134,285,438,1,1,35,146,175,293,224,,139,30,43,102,97,147,518,94,238,258,6,2,152,10,,,45,84,50,35,152,13,43,51,42,48,36,28,61,102,271,59,43,29,18,10,58,115,6,51,97,30,2,39,123,23,31,41,,,688,510,635,3
-18,27/04/20,,,1679,854,825,1079.4,,,,,1,1,51,207,270,479,670,,1,1,16,61,126,230,419,0,0,35,146,144,249,251,,122,27,45,110,107,139,410,78,207,280,3,6,140,5,,,56,69,34,31,154,21,45,63,36,39,25,27,63,110,191,47,36,50,14,5,48,107,3,43,75,27,6,38,100,23,42,51,,,638,506,529,6
-19,04/05/20,,,1434,746,688,1034.2,,,,,2,2,39,182,241,467,501,,1,0,17,80,97,246,305,1,2,22,102,144,221,196,,100,24,35,91,104,128,343,83,207,207,2,6,102,2,,,37,63,26,24,114,21,35,41,33,39,23,34,54,91,162,59,27,28,28,2,40,103,2,35,53,24,6,27,104,29,28,42,,,488,440,506,0

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