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plotting 2 datasets with unequal lengths using ggplot2

Tags:

r

ggplot2

I have 2 datasets with unequal lengths for plotting using ggplots2:

Data A;

column x column y
0.23     1.54    
0.44     1.46
0.69     1.37
0.70     1.21
0.75     1.01
0.88     0.91 

Data B:

column x column y
0.13     1.24    
0.34     1.16
0.49     1.07
0.54     0.99
0.69     1.01

I'm sure of how to write a code in ggplot2 for plotting these two data sets together. In both cases, plots shown as x axis = column x and y axis= column y. Can someone help me please?

James

like image 748
James Johnson Avatar asked Jan 14 '23 21:01

James Johnson


2 Answers

Suppose you have datasets A and B as a data.frame:

A <- data.frame(x=1:5, y=11:15)
B <- data.frame(x=1:10, y=20:11)

You have to join them together:

df <- rbind(A, B) # Join A and B together.
df
    x  y
1   1 11
2   2 12
3   3 13
4   4 14
5   5 15
6   1 20
7   2 19
8   3 18
9   4 17
10  5 16
11  6 15
12  7 14
13  8 13
14  9 12
15 10 11

Then you can plot it:

ggplot(data=df, aes(x=x, y=y)) + geom_point()

If you want to distinguish points from dataset A and B by color:

df$dataset <- c(rep("A", nrow(A)), rep("B", nrow(B)))
df
    x  y dataset
1   1 11       A
2   2 12       A
3   3 13       A
4   4 14       A
5   5 15       A
6   1 20       B
7   2 19       B
8   3 18       B
9   4 17       B
10  5 16       B
11  6 15       B
12  7 14       B
13  8 13       B
14  9 12       B
15 10 11       B

ggplot(data=df, aes(x=x, y=y, col=dataset)) + geom_point()

If you want to distinguish points from dataset A and B by color and size and change axis labels:

ggplot(data=df, aes(x=x, y=y, col=dataset, size=dataset)) + geom_point() +
scale_color_manual(name="Dataset", labels = c("Data A","Data B"), values=c("red", "blue")) + 
scale_size_manual(name="Dataset", labels = c("Data A","Data B"), values=c(10, 5)) + 
xlab("xxxx") + ylab("yyyy")

See Tutorial or use google :).

like image 75
user2194122 Avatar answered Jan 19 '23 12:01

user2194122


I know this comes up all the time when looking to plot data points (which are sparse) and a a line from a theoretical curve (which has lots of data points)

In this case you can give the different aesthetic mappings to each piece of ggplot's geometries, individually.

E.g. [EDITED HERE TO MAKE THE BEST EXAMPLE BE FIRST]

ggplot() +
  geom_point(data = df_A, aes(x, y)) + 
  geom_line(data = df_B, aes(x, y), color = "red") +
  theme_minimal() 

or

ggplot() +
  with(df_A, geom_point(aes(x, y))) + 
  with(df_B, geom_line(aes(x, y)), color = "red") +
  theme_minimal() 
like image 20
Ken Osborne Avatar answered Jan 19 '23 12:01

Ken Osborne