How to convert a table into a graph in R

Question

I have a table I want to convert into a graph (bar-graph or line-graph)

The first column has fixed values. Twenty different values are simulated for these fixed values and kept in the next columns. I want to plot a graph of the fixed column against all the different twenty simulated columns.

How do I go about it?

Edit

table name:bygrace

V1    V2   V3   V4   V5                 
100    16   11   -6    1                               
120   -17  -12    7   -2                               
140    18   13   -8    3                              
150   -19  -14    9   -4                              
210    20   15  -10   -5

Actually, my table looks like the one above. The first column V1 represents Premiums charged by an insurance company,say last year (for 5 policyholders/policies) After critical analysis of the portfolio, the company decides to increase or decrease the premium amount for some of the customers. However, the company does not know exactly by how much it should increase of decrease the premiums for fear that it would lose customers. For this reason, four different scenarios/simulations are considered which are represented by the next four columns(V2 through V5) respectively.

Now the task is to plot the premium amounts in V1 against these four different scenarios(bar-graph or line-graph; I think bar will be better).

And my question is can this be done on one graph/at once? If yes, how shoul I go about it? Or do I have to plot the premium against each column separately?

In fact, I have spent the whole of yesterday and today on this but I have not been able to get the desired result.

Someone gave me an answer to try.And I am going to do that because it has given me an idea and I am very thankful to the one!

Many thanks to everyone for their help

Answer 1

Here's a few options using the ggplot2 package. If you haven't started learning much about plotting with R, taking the time now to learn ggplot2 or lattice may be worth the effort.

ggplot requires data to be in "long" format, so the first thing we'll do is reformat to long:

require(ggplot2)

dat <- data.frame(V1 = c(100, 120, 140, 150, 210), V2 = c(16, -17, 18, -19, 20)
, V3 = c(11, -12, 13, -14, 15), V4 = c(-6, 7, -8, 9, -10), V5 = c(1, -2, 3, -4, 5))

dat.m <- melt(dat, "V1")

It sounds like V1 represents discrete levels, and should be treated as categorical data. That is why I treat V1 as a factor. If that's not the case, simply use V1 in the x-axis.

#Bar chart
ggplot(dat.m, aes(x = factor(V1), y = value, fill = variable)) + 
geom_bar(position = "dodge")

#Line chart
ggplot(dat.m, aes(x = factor(V1), y = value, group = variable, colour = variable)) + 
geom_line()

Answer 2

Try this:

#Generate 100 x values.  Then generate 20 random walk y values for each x value
x <- seq(1, 100, 1)  
y <- matrix(20*100, nrow=100, ncol=20)  
for (i in 1:20) {  
  y[, i] <- cumsum(rnorm(100))  
}  

#Build the table  
df <- data.frame(x=x, y=y)  
head(df)  

#Plot the table  
matplot(df[, 1], df[, 2:21],  type="l", main="Twenty Random Walks", xlab="x", ylab="y")    
grid()