### read in data ###
TB.IL <- read.csv("C:/Users/Lisa/Desktop/677/TB/TB.IL.csv", stringsAsFactors = FALSE)
### this is what the data looks like ###
head(TB.IL)
## YEAR WEEK CASE
## 1 1975 1 13
## 2 1975 2 30
## 3 1975 3 26
## 4 1975 4 17
## 5 1975 5 12
## 6 1975 6 42
### change all unavailalble CASE data (-) to NA ###
for (i in 1:length(TB.IL$CASE)) {
if (TB.IL$CASE[i] == "-") {
TB.IL$CASE[i] <- NA
}
}
TB.IL$CASE <- as.numeric(TB.IL$CASE)
TB.IL$YEAR <- as.numeric(TB.IL$YEAR)
TB.IL$WEEK <- formatC(TB.IL$WEEK, width = 2, flag = "0")
### this is what the data looks like now ###
head(TB.IL)
## YEAR WEEK CASE
## 1 1975 01 13
## 2 1975 02 30
## 3 1975 03 26
## 4 1975 04 17
## 5 1975 05 12
## 6 1975 06 42
### create an ID for YEAR & WEEK together - YEAR.WEEK ###
YR.WK <- as.character(paste(TB.IL[, 1], TB.IL[, 2], sep = "."))
TB.IL <- data.frame(TB.IL, YR.WK)
### find yearly CASE totals ###
TB.ILs <- as.array(split(TB.IL, TB.IL$YEAR))
CASE.YR <- rep(NA, length(unique(TB.IL$YEAR)))
for (i in 1:length(unique(TB.IL$YEAR))) {
CASE.YR[i] <- sum(TB.ILs[[i]][, 3], na.rm = TRUE)
}
CASE.YR <- data.frame(YEAR = c(min(TB.IL$YEAR):max(TB.IL$YEAR)), CASE.YR)
### Merge data into one dataframe containing weekly and yearly CASE
### numbers ### CASE.YR is total of CASEs for that year ###
TB.IL <- merge(TB.IL, CASE.YR)
head(TB.IL, 106)
## YEAR WEEK CASE YR.WK CASE.YR
## 1 1975 01 13 1975.01 1348
## 2 1975 02 30 1975.02 1348
## 3 1975 03 26 1975.03 1348
## 4 1975 04 17 1975.04 1348
## 5 1975 05 12 1975.05 1348
## 6 1975 06 42 1975.06 1348
## 7 1975 07 14 1975.07 1348
## 8 1975 08 14 1975.08 1348
## 9 1975 09 19 1975.09 1348
## 10 1975 10 25 1975.10 1348
## 11 1975 11 26 1975.11 1348
## 12 1975 12 14 1975.12 1348
## 13 1975 13 25 1975.13 1348
## 14 1975 14 22 1975.14 1348
## 15 1975 15 32 1975.15 1348
## 16 1975 16 28 1975.16 1348
## 17 1975 17 14 1975.17 1348
## 18 1975 18 22 1975.18 1348
## 19 1975 19 13 1975.19 1348
## 20 1975 20 38 1975.20 1348
## 21 1975 21 15 1975.21 1348
## 22 1975 22 15 1975.22 1348
## 23 1975 23 7 1975.23 1348
## 24 1975 24 19 1975.24 1348
## 25 1975 25 28 1975.25 1348
## 26 1975 26 37 1975.26 1348
## 27 1975 27 49 1975.27 1348
## 28 1975 28 34 1975.28 1348
## 29 1975 29 30 1975.29 1348
## 30 1975 30 11 1975.30 1348
## 31 1975 31 22 1975.31 1348
## 32 1975 32 16 1975.32 1348
## 33 1975 33 29 1975.33 1348
## 34 1975 34 55 1975.34 1348
## 35 1975 35 27 1975.35 1348
## 36 1975 36 20 1975.36 1348
## 37 1975 37 40 1975.37 1348
## 38 1975 38 35 1975.38 1348
## 39 1975 39 26 1975.39 1348
## 40 1975 40 34 1975.40 1348
## 41 1975 41 7 1975.41 1348
## 42 1975 42 32 1975.42 1348
## 43 1975 43 43 1975.43 1348
## 44 1975 44 44 1975.44 1348
## 45 1975 45 19 1975.45 1348
## 46 1975 46 37 1975.46 1348
## 47 1975 47 39 1975.47 1348
## 48 1975 48 30 1975.48 1348
## 49 1975 49 25 1975.49 1348
## 50 1975 50 33 1975.50 1348
## 51 1975 51 22 1975.51 1348
## 52 1975 52 22 1975.52 1348
## 53 1975 53 NA 1975.53 1348
## 54 1976 01 2 1976.01 1648
## 55 1976 02 2 1976.02 1648
## 56 1976 03 7 1976.03 1648
## 57 1976 04 14 1976.04 1648
## 58 1976 05 20 1976.05 1648
## 59 1976 06 44 1976.06 1648
## 60 1976 07 24 1976.07 1648
## 61 1976 08 24 1976.08 1648
## 62 1976 09 28 1976.09 1648
## 63 1976 10 16 1976.10 1648
## 64 1976 11 22 1976.11 1648
## 65 1976 12 27 1976.12 1648
## 66 1976 13 21 1976.13 1648
## 67 1976 14 78 1976.14 1648
## 68 1976 15 31 1976.15 1648
## 69 1976 16 29 1976.16 1648
## 70 1976 17 68 1976.17 1648
## 71 1976 18 NA 1976.18 1648
## 72 1976 19 20 1976.19 1648
## 73 1976 20 56 1976.20 1648
## 74 1976 21 24 1976.21 1648
## 75 1976 22 27 1976.22 1648
## 76 1976 23 44 1976.23 1648
## 77 1976 24 42 1976.24 1648
## 78 1976 25 14 1976.25 1648
## 79 1976 26 64 1976.26 1648
## 80 1976 27 65 1976.27 1648
## 81 1976 28 10 1976.28 1648
## 82 1976 29 49 1976.29 1648
## 83 1976 30 42 1976.30 1648
## 84 1976 31 33 1976.31 1648
## 85 1976 32 40 1976.32 1648
## 86 1976 33 24 1976.33 1648
## 87 1976 34 63 1976.34 1648
## 88 1976 35 52 1976.35 1648
## 89 1976 36 26 1976.36 1648
## 90 1976 37 19 1976.37 1648
## 91 1976 38 36 1976.38 1648
## 92 1976 39 18 1976.39 1648
## 93 1976 40 34 1976.40 1648
## 94 1976 41 39 1976.41 1648
## 95 1976 42 44 1976.42 1648
## 96 1976 43 19 1976.43 1648
## 97 1976 44 29 1976.44 1648
## 98 1976 45 44 1976.45 1648
## 99 1976 46 22 1976.46 1648
## 100 1976 47 32 1976.47 1648
## 101 1976 48 40 1976.48 1648
## 102 1976 49 27 1976.49 1648
## 103 1976 50 54 1976.50 1648
## 104 1976 51 21 1976.51 1648
## 105 1976 52 18 1976.52 1648
## 106 1977 01 NA 1977.01 1733
### create plots of weekly and yearly CASE numbers in 'lattice' ###
require(lattice)
## Loading required package: lattice
plot.wk <- barchart(CASE ~ YR.WK, data = TB.IL, horizontal = FALSE, xlab = "WEEK")
plot.yr <- barchart(CASE.YR ~ YEAR, data = TB.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(TB.IL$YR.WK, TB.IL$CASE, type = "p", pch = ".", xlab = "WEEK")
plot(TB.IL$YEAR, TB.IL$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 ###
TB.ILc <- TB.IL[complete.cases(TB.IL), ]
TB.ILcs <- as.array(split(TB.ILc, TB.ILc$YEAR))
par(mfrow = c(1, 1))
for (i in 1:length(unique(TB.ILc$YEAR))) {
plot(TB.ILcs[[i]][, 2], TB.ILcs[[i]][, 3], type = "b", xlab = TB.ILcs[[i]][1,
1], ylab = "Cases", pch = 16)
}
