### read in data ###
M.IL <- read.csv("C:/Users/Lisa/Desktop/677/Measles/M.IL.csv", stringsAsFactors = FALSE)
### this is what the data looks like ###
head(M.IL)
## YEAR WEEK CASE
## 1 1927 1 -
## 2 1927 2 -
## 3 1927 3 -
## 4 1927 4 -
## 5 1927 5 -
## 6 1927 6 -
### change all unavailalble CASE data (-) to NA ###
for (i in 1:length(M.IL$CASE)) {
if (M.IL$CASE[i] == "-") {
M.IL$CASE[i] <- NA
}
}
M.IL$CASE <- as.numeric(M.IL$CASE)
M.IL$YEAR <- as.numeric(M.IL$YEAR)
M.IL$WEEK <- formatC(M.IL$WEEK, width = 2, flag = "0")
### this is what the data looks like now ###
head(M.IL)
## YEAR WEEK CASE
## 1 1927 01 NA
## 2 1927 02 NA
## 3 1927 03 NA
## 4 1927 04 NA
## 5 1927 05 NA
## 6 1927 06 NA
### create an ID for YEAR & WEEK together - YEAR.WEEK ###
YR.WK <- as.character(paste(M.IL[, 1], M.IL[, 2], sep = "."))
M.IL <- data.frame(M.IL, YR.WK)
### find yearly CASE totals ###
M.ILs <- as.array(split(M.IL, M.IL$YEAR))
CASE.YR <- rep(NA, length(unique(M.IL$YEAR)))
for (i in 1:length(unique(M.IL$YEAR))) {
CASE.YR[i] <- sum(M.ILs[[i]][, 3], na.rm = TRUE)
}
CASE.YR <- data.frame(YEAR = c(min(M.IL$YEAR):max(M.IL$YEAR)), CASE.YR)
### Merge data into one dataframe containing weekly and yearly CASE
### numbers ### CASE.YR is total of CASEs for that year ###
M.IL <- merge(M.IL, CASE.YR)
head(M.IL, 106)
## YEAR WEEK CASE YR.WK CASE.YR
## 1 1927 01 NA 1927.01 138
## 2 1927 02 NA 1927.02 138
## 3 1927 03 NA 1927.03 138
## 4 1927 04 NA 1927.04 138
## 5 1927 05 NA 1927.05 138
## 6 1927 06 NA 1927.06 138
## 7 1927 07 NA 1927.07 138
## 8 1927 08 NA 1927.08 138
## 9 1927 09 NA 1927.09 138
## 10 1927 10 NA 1927.10 138
## 11 1927 11 NA 1927.11 138
## 12 1927 12 NA 1927.12 138
## 13 1927 13 NA 1927.13 138
## 14 1927 14 NA 1927.14 138
## 15 1927 15 NA 1927.15 138
## 16 1927 16 NA 1927.16 138
## 17 1927 17 NA 1927.17 138
## 18 1927 18 NA 1927.18 138
## 19 1927 19 NA 1927.19 138
## 20 1927 20 NA 1927.20 138
## 21 1927 21 NA 1927.21 138
## 22 1927 22 NA 1927.22 138
## 23 1927 23 NA 1927.23 138
## 24 1927 24 NA 1927.24 138
## 25 1927 25 NA 1927.25 138
## 26 1927 26 NA 1927.26 138
## 27 1927 27 NA 1927.27 138
## 28 1927 28 NA 1927.28 138
## 29 1927 29 NA 1927.29 138
## 30 1927 30 NA 1927.30 138
## 31 1927 31 NA 1927.31 138
## 32 1927 32 NA 1927.32 138
## 33 1927 33 NA 1927.33 138
## 34 1927 34 NA 1927.34 138
## 35 1927 35 NA 1927.35 138
## 36 1927 36 NA 1927.36 138
## 37 1927 37 NA 1927.37 138
## 38 1927 38 NA 1927.38 138
## 39 1927 39 NA 1927.39 138
## 40 1927 40 NA 1927.40 138
## 41 1927 41 NA 1927.41 138
## 42 1927 42 NA 1927.42 138
## 43 1927 43 NA 1927.43 138
## 44 1927 44 NA 1927.44 138
## 45 1927 45 NA 1927.45 138
## 46 1927 46 NA 1927.46 138
## 47 1927 47 32 1927.47 138
## 48 1927 48 15 1927.48 138
## 49 1927 49 32 1927.49 138
## 50 1927 50 NA 1927.50 138
## 51 1927 51 33 1927.51 138
## 52 1927 52 26 1927.52 138
## 53 1928 01 38 1928.01 7460
## 54 1928 02 58 1928.02 7460
## 55 1928 03 46 1928.03 7460
## 56 1928 04 61 1928.04 7460
## 57 1928 05 84 1928.05 7460
## 58 1928 06 101 1928.06 7460
## 59 1928 07 103 1928.07 7460
## 60 1928 08 156 1928.08 7460
## 61 1928 09 151 1928.09 7460
## 62 1928 10 149 1928.10 7460
## 63 1928 11 260 1928.11 7460
## 64 1928 12 232 1928.12 7460
## 65 1928 13 180 1928.13 7460
## 66 1928 14 226 1928.14 7460
## 67 1928 15 164 1928.15 7460
## 68 1928 16 234 1928.16 7460
## 69 1928 17 173 1928.17 7460
## 70 1928 18 244 1928.18 7460
## 71 1928 19 275 1928.19 7460
## 72 1928 20 214 1928.20 7460
## 73 1928 21 244 1928.21 7460
## 74 1928 22 268 1928.22 7460
## 75 1928 23 195 1928.23 7460
## 76 1928 24 216 1928.24 7460
## 77 1928 25 186 1928.25 7460
## 78 1928 26 185 1928.26 7460
## 79 1928 27 123 1928.27 7460
## 80 1928 28 90 1928.28 7460
## 81 1928 29 81 1928.29 7460
## 82 1928 30 47 1928.30 7460
## 83 1928 31 49 1928.31 7460
## 84 1928 32 29 1928.32 7460
## 85 1928 33 26 1928.33 7460
## 86 1928 34 24 1928.34 7460
## 87 1928 35 24 1928.35 7460
## 88 1928 36 14 1928.36 7460
## 89 1928 37 23 1928.37 7460
## 90 1928 38 43 1928.38 7460
## 91 1928 39 40 1928.39 7460
## 92 1928 40 38 1928.40 7460
## 93 1928 41 69 1928.41 7460
## 94 1928 42 75 1928.42 7460
## 95 1928 43 92 1928.43 7460
## 96 1928 44 141 1928.44 7460
## 97 1928 45 176 1928.45 7460
## 98 1928 46 116 1928.46 7460
## 99 1928 47 318 1928.47 7460
## 100 1928 48 213 1928.48 7460
## 101 1928 49 331 1928.49 7460
## 102 1928 50 277 1928.50 7460
## 103 1928 51 311 1928.51 7460
## 104 1928 52 247 1928.52 7460
## 105 1929 01 330 1929.01 38503
## 106 1929 02 339 1929.02 38503
### create plots of weekly and yearly CASE numbers in 'lattice' ###
require(lattice)
## Loading required package: lattice
plot.wk <- barchart(CASE ~ YR.WK, data = M.IL, horizontal = FALSE, xlab = "WEEK")
plot.yr <- barchart(CASE.YR ~ YEAR, data = M.IL, horizontal = FALSE, col = "black",
xlab = "YEAR")
print(plot.wk, position = c(0.01, 0.47, 0.65, 0.99), more = TRUE)
print(plot.yr, position = c(0.01, 0, 0.65, 0.5), more = FALSE)
### same plots plotted using 'plot' ###
par(mfrow = c(2, 1), mar = c(4, 4, 1, 1))
plot(M.IL$YR.WK, M.IL$CASE, type = "p", pch = ".", xlab = "WEEK")
plot(M.IL$YEAR, M.IL$CASE.YR, type = "b", pch = 16, xlab = "YEAR")
### split the data by year and plot CASE numbers by week for each year ###
### note that CASEs for each month are NOT plotted on the same scale ###
M.ILc <- M.IL[complete.cases(M.IL), ]
M.ILcs <- as.array(split(M.ILc, M.ILc$YEAR))
par(mfrow = c(1, 1))
for (i in 1:length(unique(M.ILc$YEAR))) {
plot(M.ILcs[[i]][, 2], M.ILcs[[i]][, 3], type = "b", xlab = M.ILcs[[i]][1,
1], ylab = "Cases", pch = 16)
}
