R ggplot: Combine a barplot and a line chart from a long dataset-CodePudding

I have a wide dataset that records the blood glucose values from 10 subjects.

library(dplyr) 

df_wide = data.frame(
  ID = seq(1, 10),
  gender = sample(0:1, 10, replace = T),
  glucose_0 = sample(100:125, 10, replace = T),
  glucose_60 = sample(180:200, 10, replace = T),
  glucose_120 = sample(130:160, 10, replace = T),
  glucose_180 = sample(100:125, 10, replace = T)
)

I then transformed it into a long dataset using gather:

df_long = df_wide %>% 
  gather("glucose_0", "glucose_60", "glucose_120", "glucose_180", key = Time, value = glucose) %>% 
  arrange(ID)

To show how the glucose values changed from 0 min to 180 min, I then made the following line chart:

df_long %>% 
  ggplot(aes(x = Time, y = glucose, group = ID))   
  geom_line(aes(linetype = as.factor(gender)))  
  geom_point()  
  theme_classic()  
  scale_x_discrete(limits = c("glucose_0", "glucose_60", "glucose_120", "glucose_180"),
                   labels = c("0", "60", "120", "180"))  
  theme(legend.position = "bottom")  
  labs(
    x = "Time",
    y = "Glucose",
    fill = "Gender"
  )

Finally, to show the glucose at each time point, I also made a barplot:

df_long %>% 
  ggplot(aes(x = Time, y = glucose, fill = as.factor(gender)))   
  geom_bar(stat = 'identity', position = position_dodge())  
  theme_classic()  
  scale_x_discrete(limits = c("glucose_0", "glucose_60", "glucose_120", "glucose_180"))

My question is: How to combine the line chart and the barplot into one figure that looks like this?

CodePudding user response：

In order to plot the mean glucose levels as both bar and line

df_long %>%
  group_by(gender, Time) %>% 
  mutate(glucose = mean(glucose)) %>% 
  ggplot(aes(x = Time, y = glucose, fill = as.factor(gender)))   
  geom_bar(stat = 'identity', position = position_dodge())  
  geom_line(aes(linetype=as.factor(gender), group=ID))  
  theme_classic()  
  scale_x_discrete(limits = c("glucose_0", "glucose_60", "glucose_120", "glucose_180"))

CodePudding user response：

Are you looking for such a solution?

library(tidyverse)

df_wide %>% 
  pivot_longer(
    starts_with("glucose")
  ) %>% 
  mutate(gender = fct_inorder(factor(gender))) %>% 
  arrange(ID) %>% 
  ggplot(aes(x = name, y = value))   
  geom_col(aes(fill = gender, group=gender), width = 0.5, position = position_dodge()) 
  stat_summary(aes(group = gender), fun = mean, geom = 'line', size=1, alpha=0.9)  
  stat_summary(aes(group = gender), fun = mean, geom = 'point', size=2, alpha=0.9)  
  theme_classic()  
  scale_x_discrete(limits = c("glucose_0", "glucose_60", "glucose_120", "glucose_180"),
                   labels = c("0", "60", "120", "180"))  
  theme(legend.position = "bottom")  
  labs(
    x = "Time",
    y = "Glucose",
    fill = "Gender"
  )