33 lines
1.1 KiB
R
33 lines
1.1 KiB
R
nw <- read.table('data/2026/algemeen-rang-per-2026.23-1', sep="\t", quote="", encoding="utf-8", col.names=c("f", "word"))
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od <- read.table('data/2026/algemeen-rang-per-2026.22-4', sep="\t", quote="", encoding="utf-8", col.names=c("f", "word"))
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words <- unique(c(od$word, nw$word))
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o <- order(words)
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words <- words[o]
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n <- length(words)
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d <- data.frame(word=words, od=rep(NA, n), nw=rep(NA, n))
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for (word in nw$word) {
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d$nw[d$word==word] <- nw$f[nw$word==word]
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}
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for (word in od$word) {
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d$od[d$word==word] <- od$f[od$word==word]
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}
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d$nw[is.na(d$nw)] <- max(nw$f) + 2
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d$od[is.na(d$od)] <- max(od$f) + 2
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myplot <- function(values, labels, titel="", sub ="") {
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y <- 1:length(values)
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xx <- range(values)
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plot(values, y, xlim=c(xx[1], xx[2] + (xx[2]-xx[1]) / 5), xlab="score", ylab="index", main=titel, sub=sub)
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text(values, y, labels, pos=4)
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}
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nwn <- (d$nw - 1) / (max(nw$f) + 1)
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odn <- (d$od - 1) / (max(od$f) + 1)
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v <- odn - nwn
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o <- order(-v)
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myplot(v[o][1:40], words[o][1:40], titel="score op basis van genormaliseerde rang", "week 23 t.o.v. week 19 t/m 22")
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