Challenge 5

Introduction to Visualization

library(tidyverse)
library(ggplot2)

knitr::opts_chunk$set(echo = TRUE, warning=FALSE, message=FALSE)

Read in data

# reading the ceral dataset 
cereal <- read_csv("_data/cereal.csv")
head(cereal,4)

# A tibble: 4 × 4
  Cereal              Sodium Sugar Type 
  <chr>                <dbl> <dbl> <chr>
1 Frosted Mini Wheats      0    11 A    
2 Raisin Bran            340    18 A    
3 All Bran                70     5 A    
4 Apple Jacks            140    14 C    

Briefly describe the data

This data set contains four columns:

• Cereal <chr>: Cereal Name
• Sodium <dbl>: Amount of sodium per serving of the cereal
• Sugar <dbl>: Amount of sugar per serving of cereal
• Type <chr>: Cereal Type (Child or Adult)

Tidy Data (as needed)

Just making a few changes to the dataset.

cereal <- cereal %>%
  mutate(Type = recode(Type, "A" = "Adult", "C" = "Child"))

# Display first 5 rows of the modified data
head(cereal, 5)

# A tibble: 5 × 4
  Cereal              Sodium Sugar Type 
  <chr>                <dbl> <dbl> <chr>
1 Frosted Mini Wheats      0    11 Adult
2 Raisin Bran            340    18 Adult
3 All Bran                70     5 Adult
4 Apple Jacks            140    14 Child
5 Captain Crunch         200    12 Child

Univariate Visualizations

# Create a histogram for the distribution of Sodium based on Type
sodium_plot <- ggplot(cereal, aes(Sodium)) +
  geom_histogram(binwidth = 100) +
  facet_grid(vars(Type)) +
  labs(title = "Distribution of Sodium based on Type")

# Display the Sodium histogram
print(sodium_plot)

# Create a histogram for the distribution of Sugar based on Type
sugar_plot <- ggplot(cereal, aes(Sugar)) +
  geom_histogram(binwidth = 5) +
  facet_grid(vars(Type)) +
  labs(title = "Distribution of Sugar based on Type")

# Display the Sugar histogram
print(sugar_plot)

Because we are dealing with univariate, continuous data, I chose histograms. I wanted to compare things by type, so I used a facet grid.

Bivariate Visualization(s)

# Create a boxplot for the amount of Sugar in Cereal by Type
sugar_by_type_plot <- ggplot(cereal, aes(Type, Sugar)) +
  geom_boxplot() +
  labs(title = "Amount of Sugar in Cereal by Type")

# Display the boxplot
print(sugar_by_type_plot)

We can see that, on average, children’s cereal contains more sugar than adult cereal. Because the data is so sparse, I went with a box plot.