Overlay two plots (ggplot)

Question

How I can overlay the scatter plot of AverageTime2 vs. AverageCost and AverageTime1 vs. AverageCost. (in ggplot)?

Type<-c("a","b","c","d","e","f","g","h","i","j","k")
AverageTime<-c(12,14,66,123,14,33,44,55,55,6,66)
AverageTime2<-c(14,15,66,126,14,100,144,55,55,16,90)
AverageCost<-c(100,10000,400,20000,500000,5000,700,800,400000,500,120000)
AverageCost2<-c(10000,10000,4000,20000,5000,50000,7000,8000,40000,50000,120000)
df<-data.frame(Type,AverageTime,AverageTime2,AverageCost,AverageCost2)

Answer 1

You can simply build your data like this

df<-rbind(data.frame(Type,AverageTime,AT="T1",AverageCost,AverageCost2),
          data.frame(Type,AverageTime=AverageTime2,AT="T2",
                     AverageCost,AverageCost2))

and plot it that way

library(ggplot2)
ggplot(df)+geom_point(aes(AverageTime, AverageCost,color=AT))

Answer 2

You'll need to reshape your data so that the AverageTime and AverageCost are each a column, with a separate column (called something like Type2 ) that distinguishes the two types.

You can accomplish this with dplyr, tidyr, and stringr:

library(dplyr)
library(tidyr)
library(stringr)

df_gather <- df %>%
  gather(column, value, -Type) %>%
  mutate(Type2 = str_detect(column, "2"),
         column = str_replace(column, "2", "")) %>%
  spread(column, value)

The particularly important part of that is to gather all the "Average" columns into one column, then to distinguish them (using the Type2 column), and then to spread them back into separate AverageCost and AverageTime columns.

Afterwards, you can simply do:

ggplot(df_gather, aes(AverageTime, AverageCost, color = Type2)) +
  geom_point()