Plot two graphs in the same plot [duplicate]

This question already has an answer here:

Plotting two variables as lines using ggplot2 on the same graph 6 answers

The solution with ggplot in this question worked really well for my data. However, I am trying to add a legend and everything that I tried does not work...

For example, in the ggplot example in the above question, how I can add a legend to show that the red curve is related to "Ocean" and the green curve is related to "Soil"? Yes, I want to add text that I will define and it is not related to any other variable in my data.frame.

The example below is some of my own data...

Rate     Probability      Stats
1.0e-04    1e-04          891.15 
1.0e-05    1e-04          690
...

etc (it's about 400 rows). And I have two data frames similar to the above one. So My code is

g <- ggplot(Master1MY, aes(Probability))
g <- g + geom_point(aes(y=Master1MY$Stats), colour="red", size=1)
g <- g + geom_point(aes(y=Transposon1MY$Stats), colour="blue", size=1)
g + labs(title= "10,000bp and 1MY", x = "Probability", y = "Stats")

The plot looks like

I just want a red and blue legend saying "Master" and "Transposon"

Thanks!

In ggplot it is generally most convenient to keep the data in a 'long' format. Here I use the function melt from the reshape2 package to convert your data from wide to long format. Depending how you specify different aesthetics (size, shape, colour et c), corresponding legends will appear.

library(ggplot2)
library(reshape2)

# data from the example you were referring to, in a 'wide' format.
x  <- seq(-2, 2, 0.05)
ocean <- pnorm(x)
soil <- pnorm(x, 1, 1)
df <- data.frame(x, ocean, soil)

# melt the data to a long format
df2 <- melt(data = df, id.vars = "x")

# plot, using the aesthetics argument 'colour'
ggplot(data = df2, aes(x = x, y = value, colour = variable)) + geom_line()

Edit, set name and labels of legend

# Manually set name of the colour scale and labels for the different colours
ggplot(data = df2, aes(x = x, y = value, colour = variable)) +
 geom_line() +
 scale_colour_discrete(name = "Type of sample", labels = c("Sea water", "Soil"))

Edit2, following new sample data Convert your data, assuming its organization from your update, to a long format. Again, I believe you make your ggplot life easier if you keep your data in a long format. I relate every step with the simple example data which I used in my first answer. Please note that there are many alternative ways to rearrange your data. This is one way, based on the small (non-reproducible) parts of your data you provided in the update.

# x  <- seq(-2, 2, 0.05)
# Master1MY$Probability
Probability <- 1:100

# ocean <- pnorm(x)
# Master1MY$Stats
Master1MY <- rnorm(100, mean = 600, sd = 20)

# soil <- pnorm(x,1,1)
# Transposon1MY$Stats
Transposon1MY <- rnorm(100, mean = 100, sd = 10)

# df <- data.frame(x, ocean, soil)
df <- data.frame(Probability, Master1MY, Transposon1MY)

# df2 <- melt(df, id.var = "x")
df2 <- melt(df, id.var = "Probability")

# default
ggplot(data = df2, aes(x = Probability, y = value, col = variable)) +
  geom_point()

# change legend name and labels, see previous edit using 'scale_colour_discrete'

# set manual colours scale using 'scale_colour_manual'.

ggplot(data = df2, aes(x = Probability, y = value, col = variable)) +
  geom_point() +
  scale_colour_manual(values = c("red","blue"), name = "Type of sample", labels = c("Master", "Transposon"))