Project Part 2

Interactive and static plots for the age of students in school

1. Packages I will use to read in and plot the data

library(tidyverse)
library(echarts4r)
library(ggplot2)

2. Read the data in from part 1

countries_age  <- read_csv(here::here("countries_age.csv"))

Interactive Graph

• Start with the data
• Group_by country so there will be a “river” for each region
• Use mutate to round Age so only 2 digits will be displayed when you hover over it.
• Use mutate to change Year so it will be displayed as end of year instead of beginning of year
• Use e_charts to create an e_charts object with Year on the x axis
• Use e_river to build “rivers” that contain Age by countries. The depth of each river represents the age for each region.
• Use e_tooltip to add a tooltip that will display based on the axis values
• Use e_title to add a title, subtitle, and link to subtitle
• Use e_theme to change the theme to roma

countries_age   %>%
  group_by(Country)  %>%
  mutate(Age = round(Age, 2),
         Year = paste(Year, "12", "31", sep="-"))  %>%
  e_charts(x = Year)   %>% 
  e_river(serie = Age, legend=FALSE)  %>% 
  e_tooltip(trigger = "axis")  %>% 
  e_title(text = "Years in school by countries",
          subtext = "(Age in Years). Source: Our World in Data",
          sublink = "https://ourworldindata.org/grapher/expected-years-of-schooling?tab=chart",
          left = "center")  %>% 
  e_theme("roma")

---

Static Graph

• Start with the data
• Use ggplot to create a new ggplot object. Use aes to indicate that Year will be mapped to the x axis; Age will be mapped to the y axis; Country will be the fill variable
• geom_bin2d will display Age
• scale_fill_discrete_divergingx is a function in the colorspace package. It sets the color palette to roma and selects a maximum of 12 colors for the different regions
• theme_classic sets the theme
• theme(legend.position = “bottom”) puts the legend at the bottom of the plot
• labs sets the y axis label, fill = NULL indicates that the fill variable will not have the labelled Country

countries_age   %>% 
  ggplot(aes(x = Year, y = Age, 
             fill = Country)) +
  geom_bin2d ()+
  colorspace::scale_fill_discrete_divergingx(palette = "roma", nmax =11) +
  theme_classic() +
  theme(legend.position = "bottom") +
  labs( y = "Age in Years",
       fill = NULL)

This graph shows a small increase for the age of students in school since 2000.

ggsave(filename = here::here("_posts/2022-05-16-project-part-2/preview.png"))