Formatting a line graph in R-CodePudding

My code is a little different from the codes that people usually use when addressing this problem. I am trying to make some formatting adjustments to my code, including adding points to my line graph, and changing the color of the lines and error bars. Thanks in advance!

Reproducible sample:

set.seed(42)
n <- 100

    dat <- data.frame(Participant=1:n, 
                      Environment=rep(LETTERS[1:2], n/2),
                      Condition=rep(LETTERS[25:26], n/2),
                      Gate= sample(1:5, n, replace=TRUE),
                      Block = sample(1:2, n, replace=TRUE),
                      Sound=rep(LETTERS[3:4], n/2),
                      Correct=sample(0:1, n, replace=TRUE)
    )

Code:

dat %>% 
  group_by(Condition, Gate = fct_inorder(Gate), Sound) %>% #these relevant columns
  summarize(Accuracy = mean(Correct), #Defining y axis title 
            sd = sd(Correct)/sqrt(length(Correct))) %>%     #and SD
  ggplot(aes(x = Gate, y = Accuracy, color = Sound, group = Sound))   
  geom_line()   
  geom_errorbar(aes(ymin = Accuracy - sd, ymax = Accuracy   sd,))   
  scale_y_continuous(labels = scales::percent)  
  facet_wrap(~Condition)   
  theme_minimal()

CodePudding user response：

Sounds straightforward; does this solve your problem?

library(tidyverse)

set.seed(42)
n <- 100

dat <- data.frame(Participant = 1:n, 
                  Environment = rep(LETTERS[1:2], n/2),
                  Condition = rep(LETTERS[25:26], n/2),
                  Gate = sample(1:5, n, replace = TRUE),
                  Block = sample(1:2, n, replace = TRUE),
                  Sound = rep(LETTERS[3:4], n/2),
                  Correct = sample(0:1, n, replace = TRUE)
)

dat %>%
  mutate(Gate = factor(Gate),
         Sound = factor(Sound)) %>%
  group_by(Condition, Gate, Sound) %>% 
  summarize(Accuracy = mean(Correct),
            sd = sd(Correct)/sqrt(length(Correct))) %>%
  ggplot(aes(x = Gate, y = Accuracy, color = Sound, group = Sound))   
  geom_line()   
  geom_errorbar(aes(ymin = Accuracy - sd, ymax = Accuracy   sd,))   
  scale_y_continuous(labels = scales::percent)  
  facet_wrap(~Condition)   
  theme_minimal()
#> `summarise()` has grouped output by 'Condition', 'Gate'. You can override using the `.groups` argument.

# Change colour of lines
dat %>%
  mutate(Gate = factor(Gate),
         Sound = factor(Sound)) %>%
  group_by(Condition, Gate, Sound) %>% 
  summarize(Accuracy = mean(Correct),
            sd = sd(Correct)/sqrt(length(Correct))) %>%
  ggplot(aes(x = Gate, y = Accuracy, color = Sound, group = Sound))   
  geom_line()   
  geom_errorbar(aes(ymin = Accuracy - sd, ymax = Accuracy   sd,))   
  scale_y_continuous(labels = scales::percent)  
  facet_wrap(~Condition)   
  theme_minimal()  
  scale_color_brewer(palette = "Set1")
#> `summarise()` has grouped output by 'Condition', 'Gate'. You can override using the `.groups` argument.

# Add points
dat %>%
  mutate(Gate = factor(Gate),
         Sound = factor(Sound)) %>%
  group_by(Condition, Gate, Sound) %>% 
  summarize(Accuracy = mean(Correct),
            sd = sd(Correct)/sqrt(length(Correct))) %>%
  ggplot(aes(x = Gate, y = Accuracy, color = Sound, group = Sound))   
  geom_line()  
  geom_errorbar(aes(ymin = Accuracy - sd, ymax = Accuracy   sd))  
  geom_point()  
  scale_y_continuous(labels = scales::percent)  
  facet_wrap(~Condition)   
  theme_minimal()  
  scale_color_brewer(palette = "Set1")
#> `summarise()` has grouped output by 'Condition', 'Gate'. You can override using the `.groups` argument.

# different coloured lines, larger points
dat %>%
  mutate(Gate = factor(Gate),
         Sound = factor(Sound)) %>%
  group_by(Condition, Gate, Sound) %>% 
  summarize(Accuracy = mean(Correct),
            sd = sd(Correct)/sqrt(length(Correct))) %>%
  ggplot(aes(x = Gate, y = Accuracy, color = Sound, group = Sound))   
  geom_line()  
  geom_errorbar(aes(ymin = Accuracy - sd, ymax = Accuracy   sd), color = "grey75")   
  geom_point(size = 3)  
  scale_y_continuous(labels = scales::percent)  
  facet_wrap(~Condition)   
  theme_minimal()  
  scale_color_brewer(palette = "Set1")
#> `summarise()` has grouped output by 'Condition', 'Gate'. You can override using the `.groups` argument.

^{Created on 2022-02-09 by the reprex package (v2.0.1)}

I highly recommend the books ggplot2: Elegant Graphics for Data Analysis and the R Graphics Cookbook for further information/examples (both free to read online)