Draw ggplot2 Plot with Mean & Standard Deviation by Category in R (Example Code)

data(iris)                    # Loading example data frame
head(iris)
#   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
# 1          5.1         3.5          1.4         0.2  setosa
# 2          4.9         3.0          1.4         0.2  setosa
# 3          4.7         3.2          1.3         0.2  setosa
# 4          4.6         3.1          1.5         0.2  setosa
# 5          5.0         3.6          1.4         0.2  setosa
# 6          5.4         3.9          1.7         0.4  setosa

data(iris) # Loading example data frame head(iris) # Sepal.Length Sepal.Width Petal.Length Petal.Width Species # 1 5.1 3.5 1.4 0.2 setosa # 2 4.9 3.0 1.4 0.2 setosa # 3 4.7 3.2 1.3 0.2 setosa # 4 4.6 3.1 1.5 0.2 setosa # 5 5.0 3.6 1.4 0.2 setosa # 6 5.4 3.9 1.7 0.4 setosa

install.packages("dplyr")     # Install dplyr package
library("dplyr")              # Load dplyr

install.packages("dplyr") # Install dplyr package library("dplyr") # Load dplyr

iris_group <- iris %>%        # Calculate means & standard deviations
  group_by(Species) %>%
  summarise_at(vars(Sepal.Length),
               list(mn = mean,
                    sd = sd))
iris_group
                   # # A tibble: 3 × 3
#   Species       mn    sd
#   <fct>      <dbl> <dbl>
# 1 setosa      5.01 0.352
# 2 versicolor  5.94 0.516
# 3 virginica   6.59 0.636

iris_group <- iris %>% # Calculate means & standard deviations group_by(Species) %>% summarise_at(vars(Sepal.Length), list(mn = mean, sd = sd)) iris_group # # A tibble: 3 × 3 # Species mn sd # <fct> <dbl> <dbl> # 1 setosa 5.01 0.352 # 2 versicolor 5.94 0.516 # 3 virginica 6.59 0.636

install.packages("ggplot2")   # Install ggplot2 package
library("ggplot2")            # Load ggplot2 package

install.packages("ggplot2") # Install ggplot2 package library("ggplot2") # Load ggplot2 package

ggplot(iris_group,            # Plot means & standard deviations for each category
       aes(x = Species, y = mn)) +
  geom_point() + 
  geom_errorbar(aes(ymin = mn - sd,
                    ymax = mn + sd))

ggplot(iris_group, # Plot means & standard deviations for each category aes(x = Species, y = mn)) + geom_point() + geom_errorbar(aes(ymin = mn - sd, ymax = mn + sd))