ggplot2 plot table as lines

Question

I would like to plot the following dataset

structure(list(X = structure(c(3L, 12L, 11L, 7L, 13L, 2L, 1L, 
10L, 5L, 4L, 8L, 14L, 9L, 6L), .Label = c(\"BUM\", \"DD         


        

Answer 1

This is an extension to @Andrie's solution. It combines the faceting idea with that of overplotting (stolen liberally from the learnr blog, which I find results in a cool visualization. Here is the code and the resulting output. Comments are welcome

mdf <- melt(df, id.vars="X")
mdf = transform(mdf, variable = reorder(variable, value, mean), Y = X)

ggplot(mdf, aes(x = variable, y = value)) + 
  geom_line(data = transform(mdf, X = NULL), aes(group = Y), colour = "grey80") +
  geom_line(aes(group = X)) +
  facet_wrap(~X) +
  opts(axis.text.x = theme_text(angle=90, hjust=1))

EDIT: If you have groupings of milieus, then a better way to present might be the following

mycols = c(brewer.pal(4, 'Oranges'), brewer.pal(4, 'Greens'), 
           brewer.pal(3, 'Blues'), brewer.pal(3, 'PuRd'))
mdf2 = read.table(textConnection("
  V1,  V2
  ETB, LEIT
  PMA, LEIT
  PER, LEIT
  LEIT, LEIT
  KON, TRADITION
  TRA, TRADITION
  DDR, TRADITION
  TRADITION, TRADITION
  BUM, MAIN
  MAT, MAIN
  MAIN, MAIN
  EXP, HEDOS
  HED, HEDOS
  HEDOS, HEDOS"), sep = ",", header = T, stringsAsFactors = F)

mdf2 = data.frame(mdf2, mycols = mycols)
mdf3 = merge(mdf, mdf2, by.x = 'X', by.y = "V1")

p1 = ggplot(mdf3, aes(x = variable, y = value, group = X, colour = mycols)) + 
  geom_line(subset = .(nchar(as.character(X)) == 3)) +
  geom_line(subset = .(nchar(as.character(X)) != 3), size = 1.5) +
  facet_wrap(~ V2) +
  scale_color_identity(name = 'Milieus', breaks = mdf2$mycols, labels = mdf2$V1) +
  theme_bw() + 
  opts(axis.text.x = theme_text(angle=90, hjust=1)) 

Answer 2

First, melt the data to put it in a long format.

melted_data <- melt(the_data, id.vars = "X")

Now draw the plot with a numeric x axis, and fix up the labels.

p <- ggplot(melted_data, aes(as.numeric(variable), value, colour = X)) + 
  geom_line() + 
  scale_x_continuous(
    breaks = seq_len(nlevels(melted_data$variable)), 
    labels = levels(melted_data$variable)
  ) +
  opts(axis.text.x = theme_text(angle = 90))
p

---

Having answered this, I'm not sure what the plot tells you &ndahs; it's just a jumble of lines to me. You might be better greying out most of the lines, and highlighting one or two interesting ones.

Add a column that picks out, e.g., EXP.

melted_data$is_EXP <- with(melted_data, X == "EXP")

Ignore my previous anser; Andrie's is better. Use manual colour and size scales to highlight your new column.

p <- ggplot(melted_data, aes(variable, value, colour = is_EXP, size = is_EXP, group = X)) + 
  geom_line() + 
  scale_colour_manual(values = c("grey80", "black")) + 
  scale_size_manual(values = c(0.5, 1.5)) +
  opts(axis.text.x = theme_text(angle = 90, hjust=1))
p

Answer 3

The trick is to reshape your data into tall format before you pass it to ggplot. This is easy when using the melt function in package reshape2:

Assuming your data is a variable called df:

library(reshape2)
library(ggplot2)

mdf <- melt(df, id.vars="X")
str(mdf)
ggplot(mdf, aes(x=variable, y=value, colour=X, group=X)) + geom_line() +
    opts(axis.text.x = theme_text(angle=90, hjust=1))

---

Edit As @Chase suggests, you can use facetting to make the plot more readable:

ggplot(mdf, aes(x=X, y=value)) + geom_point() +
    opts(axis.text.x = theme_text(angle=90, hjust=1)) + facet_wrap(~variable)