### read in data ###
WC.FL <- read.csv("C:/Users/Lisa/Desktop/677/Pertussis/WC.FL.csv", stringsAsFactors = FALSE)
### this is what the data looks like ###
head(WC.FL)
## YEAR WEEK CASE
## 1 1937 1 -
## 2 1937 2 -
## 3 1937 3 -
## 4 1937 4 -
## 5 1937 5 -
## 6 1937 6 -
### change all unavailalble CASE data (-) to NA ###
for (i in 1:length(WC.FL$CASE)) {
if (WC.FL$CASE[i] == "-") {
WC.FL$CASE[i] <- NA
}
}
WC.FL$CASE <- as.numeric(WC.FL$CASE)
WC.FL$YEAR <- as.numeric(WC.FL$YEAR)
WC.FL$WEEK <- formatC(WC.FL$WEEK, width = 2, flag = "0")
### this is what the data looks like now ###
head(WC.FL)
## YEAR WEEK CASE
## 1 1937 01 NA
## 2 1937 02 NA
## 3 1937 03 NA
## 4 1937 04 NA
## 5 1937 05 NA
## 6 1937 06 NA
### create an ID for YEAR & WEEK together - YEAR.WEEK ###
YR.WK <- as.character(paste(WC.FL[, 1], WC.FL[, 2], sep = "."))
WC.FL <- data.frame(WC.FL, YR.WK)
### find yearly CASE totals ###
WC.FLs <- as.array(split(WC.FL, WC.FL$YEAR))
CASE.YR <- rep(NA, length(unique(WC.FL$YEAR)))
for (i in 1:length(unique(WC.FL$YEAR))) {
CASE.YR[i] <- sum(WC.FLs[[i]][, 3], na.rm = TRUE)
}
CASE.YR <- data.frame(YEAR = c(min(WC.FL$YEAR):max(WC.FL$YEAR)), CASE.YR)
### Merge data into one dataframe containing weekly and yearly CASE
### numbers ### CASE.YR is total of CASEs for that year ###
WC.FL <- merge(WC.FL, CASE.YR)
head(WC.FL, 106)
## YEAR WEEK CASE YR.WK CASE.YR
## 1 1937 01 NA 1937.01 40
## 2 1937 02 NA 1937.02 40
## 3 1937 03 NA 1937.03 40
## 4 1937 04 NA 1937.04 40
## 5 1937 05 NA 1937.05 40
## 6 1937 06 NA 1937.06 40
## 7 1937 07 NA 1937.07 40
## 8 1937 08 NA 1937.08 40
## 9 1937 09 NA 1937.09 40
## 10 1937 10 NA 1937.10 40
## 11 1937 11 NA 1937.11 40
## 12 1937 12 NA 1937.12 40
## 13 1937 13 NA 1937.13 40
## 14 1937 14 NA 1937.14 40
## 15 1937 15 NA 1937.15 40
## 16 1937 16 NA 1937.16 40
## 17 1937 17 NA 1937.17 40
## 18 1937 18 NA 1937.18 40
## 19 1937 19 NA 1937.19 40
## 20 1937 20 NA 1937.20 40
## 21 1937 21 NA 1937.21 40
## 22 1937 22 NA 1937.22 40
## 23 1937 23 NA 1937.23 40
## 24 1937 24 NA 1937.24 40
## 25 1937 25 NA 1937.25 40
## 26 1937 26 NA 1937.26 40
## 27 1937 27 NA 1937.27 40
## 28 1937 28 NA 1937.28 40
## 29 1937 29 NA 1937.29 40
## 30 1937 30 NA 1937.30 40
## 31 1937 31 NA 1937.31 40
## 32 1937 32 NA 1937.32 40
## 33 1937 33 NA 1937.33 40
## 34 1937 34 NA 1937.34 40
## 35 1937 35 NA 1937.35 40
## 36 1937 36 NA 1937.36 40
## 37 1937 37 NA 1937.37 40
## 38 1937 38 NA 1937.38 40
## 39 1937 39 NA 1937.39 40
## 40 1937 40 NA 1937.40 40
## 41 1937 41 NA 1937.41 40
## 42 1937 42 NA 1937.42 40
## 43 1937 43 NA 1937.43 40
## 44 1937 44 3 1937.44 40
## 45 1937 45 5 1937.45 40
## 46 1937 46 8 1937.46 40
## 47 1937 47 1 1937.47 40
## 48 1937 48 7 1937.48 40
## 49 1937 49 1 1937.49 40
## 50 1937 50 6 1937.50 40
## 51 1937 51 9 1937.51 40
## 52 1937 52 NA 1937.52 40
## 53 1938 01 2 1938.01 835
## 54 1938 02 10 1938.02 835
## 55 1938 03 14 1938.03 835
## 56 1938 04 22 1938.04 835
## 57 1938 05 55 1938.05 835
## 58 1938 06 6 1938.06 835
## 59 1938 07 9 1938.07 835
## 60 1938 08 14 1938.08 835
## 61 1938 09 NA 1938.09 835
## 62 1938 10 10 1938.10 835
## 63 1938 11 7 1938.11 835
## 64 1938 12 19 1938.12 835
## 65 1938 13 28 1938.13 835
## 66 1938 14 25 1938.14 835
## 67 1938 15 2 1938.15 835
## 68 1938 16 25 1938.16 835
## 69 1938 17 24 1938.17 835
## 70 1938 18 17 1938.18 835
## 71 1938 19 32 1938.19 835
## 72 1938 20 19 1938.20 835
## 73 1938 21 33 1938.21 835
## 74 1938 22 20 1938.22 835
## 75 1938 23 11 1938.23 835
## 76 1938 24 26 1938.24 835
## 77 1938 25 44 1938.25 835
## 78 1938 26 17 1938.26 835
## 79 1938 27 16 1938.27 835
## 80 1938 28 NA 1938.28 835
## 81 1938 29 19 1938.29 835
## 82 1938 30 9 1938.30 835
## 83 1938 31 17 1938.31 835
## 84 1938 32 12 1938.32 835
## 85 1938 33 NA 1938.33 835
## 86 1938 34 50 1938.34 835
## 87 1938 35 0 1938.35 835
## 88 1938 36 14 1938.36 835
## 89 1938 37 NA 1938.37 835
## 90 1938 38 30 1938.38 835
## 91 1938 39 13 1938.39 835
## 92 1938 40 13 1938.40 835
## 93 1938 41 11 1938.41 835
## 94 1938 42 35 1938.42 835
## 95 1938 43 11 1938.43 835
## 96 1938 44 0 1938.44 835
## 97 1938 45 4 1938.45 835
## 98 1938 46 17 1938.46 835
## 99 1938 47 9 1938.47 835
## 100 1938 48 0 1938.48 835
## 101 1938 49 21 1938.49 835
## 102 1938 50 0 1938.50 835
## 103 1938 51 34 1938.51 835
## 104 1938 52 9 1938.52 835
## 105 1939 01 9 1939.01 1176
## 106 1939 02 14 1939.02 1176
### create plots of weekly and yearly CASE numbers in 'lattice' ###
require(lattice)
## Loading required package: lattice
plot.wk <- barchart(CASE ~ YR.WK, data = WC.FL, horizontal = FALSE, xlab = "WEEK")
plot.yr <- barchart(CASE.YR ~ YEAR, data = WC.FL, 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(WC.FL$YR.WK, WC.FL$CASE, type = "p", pch = ".", xlab = "WEEK")
plot(WC.FL$YEAR, WC.FL$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 ###
WC.FLc <- WC.FL[complete.cases(WC.FL), ]
WC.FLcs <- as.array(split(WC.FLc, WC.FLc$YEAR))
par(mfrow = c(1, 1))
for (i in 1:length(unique(WC.FLc$YEAR))) {
plot(WC.FLcs[[i]][, 2], WC.FLcs[[i]][, 3], type = "b", xlab = WC.FLcs[[i]][1,
1], ylab = "Cases", pch = 16)
}
