Visualizing Categorical Data

Math Unit 8

In this unit, we are focusing on visualizing categorical data using pie charts and even better, bar graphs. I will be using ggplot and highcharter to visualize the data.

library(tidyverse)
library(highcharter)
library(ggplot2)

Create and view my data

#Problem 7-8
Mode_of_trans <- c("bus", "bike", "car", "walk")
Num_of_Students <- c(90, 30, 75, 45)
Survey_Data = tibble(Mode_of_trans, Num_of_Students)

#Now I'm going to calculate the proportion using dplyr verbs
Prop_survey_data <- Survey_Data %>% mutate(prop_of_students = (Num_of_Students/sum(Num_of_Students))*100)
Prop_survey_data

## # A tibble: 4 × 3
##   Mode_of_trans Num_of_Students prop_of_students
##           <chr>           <dbl>            <dbl>
## 1           bus              90            37.50
## 2          bike              30            12.50
## 3           car              75            31.25
## 4          walk              45            18.75

Now I’ll use highcharter to create a pie chart

highchart() %>% 
 hc_add_series(Prop_survey_data, "pie", hcaes(name = Mode_of_trans, y = prop_of_students), name = "% of Trans", dataLabels = list(enabled = TRUE, format = '{point.name}: {point.y}%')) %>% 
 hc_add_theme(hc_theme_ffx())

Highcharter to create a bar graph

# highchart() %>% 
#  hc_add_series(Prop_survey_data, "column", hcaes(x = Mode_of_trans, y = prop_of_students), name = "% of trans", dataLabels = list(enabled = TRUE, format = '{point.y}%')) %>% 
#  hc_add_theme(hc_theme_538())

hchart(Prop_survey_data, "column", hcaes(x = Mode_of_trans, y = prop_of_students), name = "%n of trans", dataLabels = list(enabled = TRUE, format = '{point.y}%')) %>% 
  hc_add_theme(hc_theme_538())

ggplot to create a bar graph

ggplot(Prop_survey_data, aes(x = Mode_of_trans, y = prop_of_students, fill = Mode_of_trans)) + geom_bar(stat = "identity")