Plot Multiple Datasets with Ggplot

Plot multiple datasets with ggplot

Here's a template for plotting two data frame in the same figure:

A = data.frame(x = rnorm(10),y=rnorm(10))
B = data.frame(x = rnorm(10),y=rnorm(10))
ggplot(A,aes(x,y)) +geom_point() +geom_point(data=B,colour='red') + xlim(0, 10) 

or equivalently:

qplot(x,y,data=A)  +geom_point(data=B,colour='red') + xlim(0, 10) 

If you want to plot to figures side by side, see ?par and look for the descriptions of 'mfcol' and 'mfrow'

In addition to ggsave, see ?pdf.

How to plot plots using different datasets using ggplot2

Given the careful and reproducible way you created your question I am not just referring to the old answer as it may be harder to transfer the subsetting etc.

You initialize a new ggplot object whenever you run ggplot(...).

If you want to add a layer on top of an existing plot you have to operate on the same object, something like this:

ggplot(data=df, aes(x=Credible, y=len, group=1)) +
  geom_line(color="red")+
  geom_point()+
  labs(x = "Credible", y = "") +
  geom_point(data=zero, color="green", aes(x=x0, y=y0, group=1))

Note how in the second geom_point the data source and aesthetics are explicitly specified instead to prevent them being inherited from the initial object.

Plotting multiple grouped variable datasets in ggplot

You could try this

library(ggplot2)
library(dplyr)
df_melted <- bind_rows(df.1.melted, df.2.melted)
df_melted %>% 
 mutate(df = rep(c('df.1', 'df.2'), each = nrow(df_melted) / 2)) %>% 
 ggplot(aes(x = variable,
            y = value,
            col = df)) +
 geom_line(aes(group = name)) +
 geom_point() +
 scale_y_log10(limits = c( 1, 10), 
               breaks = c(1, 10)) +
 scale_color_manual(values = c('df.1' = "forestgreen",
                               'df.2' = "orange"))

The idea is to create one data frame, df_melted, and add the column df that indicates from which data frame the observations came from. Then you can map variable df to the colour aesthetic. As suggested in the comment you can change the default colours using scale_colour_manual.

How can I create a loop in R for plotting multiple datasets in sequence?

for (MyFile in list.files()){
    print(MyFile)
    ## do other stuff
}

One ggplot with multiple data sets

A solution is described here and here.

Install ggnewscale and then add a new scale using new_scale:

library(ggplot2)
library(ggnewscale)

dta1 = data.frame(storename = c(letters[1:5]),
                      storesize = c("small","small","medium","large","large"),
                      lon = c(10,11.2,15,19,22),
                      lat = c(5,5.8,5.6,6.1,3.4))
dta2 = data.frame(population = sample(100,100,replace = T),
                      lon = runif(100,10,22),
                      lat = runif(100,3.5,6))

ggplot() + 
geom_point(data=dta1,  aes(x=lon, y=lat,size=storesize), shape=23, fill="blue") + 
scale_size_manual(values = c(1,2,3)) +
new_scale("size") +
geom_point(data=dta2, aes(x=lon, y=lat, size=population), shape=21, fill="orange")

plot multiple datasets and compare categories with barplots

Here's code that may help you reach your goal. Note that I took some liberties with your input data because it seems to be incomplete in your question.

library(ggplot2)

List_before <- data.frame(
  list_id = "list_before",
  name = c("Tracker1", "Tracker2", "Tracker3", "Tracker4","Tracker5","Tracker6"),
  number_trackers = sample(c(1, 2, 3, 4, 5, 6)), 
  category = c("Ads", "Analytics", "Other 1", "Other 2", "Other 3", "Other 4"), 
  c4 = c("url1.com","ur2.com","url3.com","url4.com","url5.com","url6.com"))

List_short_after <- data.frame(
  list_id = "list_short_after",
  name = c("Tracker1", "Tracker2", "Tracker3", "Tracker4","Tracker5","Tracker6"),
  number_trackers = sample(c(1, 2, 3, 4, 5, 6)), 
  category = c("Ads", "Analytics", "Other 1", "Other 2", "Other 3", "Other 4"), 
  c4 = c("url1.com","ur2.com","url3.com","url4.com","url5.com","url6.com"))

List_after <- data.frame(
  list_id = "list_after",
  name = c("Tracker1", "Tracker2", "Tracker3", "Tracker4","Tracker5","Tracker6"),
  number_trackers = sample(c(1, 2, 3, 4, 5, 6)),
  category = c("Ads", "Analytics", "Other 1", "Other 2", "Other 3", "Other 4"), 
  c4 = c("url1.com","ur2.com","url3.com","url4.com","url5.com","url6.com")) 

df <- rbind(List_before, List_short_after, List_after)

df$list_id <- as.factor(df$list_id)
df$category <- as.factor(df$category)

ggplot(df, aes(y = number_trackers, x = list_id)) +
  geom_bar(aes(fill = list_id), stat = "identity", position = position_dodge()) +
  theme(axis.text.x = element_blank(),
        axis.ticks.x = element_blank()) +
  facet_grid(~category) +
  labs(y = "Number of Trackers", x = NULL)

plot boxplots from two datasets side by side

This type of problems generally has to do with reshaping the data. The format should be the long format and the data is in wide format. See this post on how to reshape the data from wide to long format.

But fore reshaping the data, create a new column telling from which data set is this data and bind the two data sets.

x <- '
ID  score1  score2
1   200     300
2   300     150
3   400     -100'

y <- '
ID  score1  score2
200     200     300
300     300     150
400     400     -100'

df1 <- read.table(textConnection(x), header = TRUE)
df2 <- read.table(textConnection(y), header = TRUE)

dfboth <- rbind(
  cbind(data = 1, df1),
  cbind(data = 2, df2)
)

suppressPackageStartupMessages({
  library(dplyr)
  library(tidyr)
  library(ggplot2)
})

bind_rows(
  df1 %>% mutate(data = "1"),
  df2 %>% mutate(data = "2")
) %>%
  pivot_longer(starts_with("score"), names_to = "score") %>%
  ggplot(aes(data, value, fill = score)) +
  geom_boxplot() +
  xlab("Data set")

^{Created on 2022-04-29 by the reprex package (v2.0.1)}

---

Related Topics