Exploring Life Expectancy and Fertility Trends Across Region

Load packages

library(tidyverse)

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library(dslabs) # for the gapminder dataset
library(highcharter) # FOR INTERACTING

Registered S3 method overwritten by 'quantmod':
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  as.zoo.data.frame zoo 
Highcharts (www.highcharts.com) is a Highsoft software product which is
not free for commercial and Governmental use

Attaching package: 'highcharter'

The following object is masked from 'package:dslabs':

    stars

Load the gapminder dataset from the dslabs package library(dslabs)

data("gapminder")

Filter dataset to include only recent years for clarity

gapminder_recent <- gapminder %>% filter(year >= 1990)

Creating the heapmap 

gapminder %>%
  filter(year >= 1990) %>%
  ggplot(aes(x = year, y = region, fill = life_expectancy)) +
  geom_tile(color = "white") +  # Creates a heatmap with white gridlines between tiles
  scale_fill_viridis_c(option = "C") +  # Color scale for life expectancy
  labs(
    title = "Life Expectancy by Region Over Time (1990-Present)",  # Title
    x = "Year",                # X-axis label
    y = "Region"               # Y-axis label
  ) +
  theme_minimal(base_size = 15) +  # Minimal theme for readability
  theme(
    plot.title = element_text(hjust = 0.5, size = 18, face = "bold"),  # Centered, bold title
    axis.text.x = element_text(angle = 45, hjust = 1)  # Rotate x-axis labels
  )

Adds interactivity so users can hover over points to see more information

highchart() %>%
  hc_add_series(
    data = gapminder %>% filter(year >= 1990),
    type = "heatmap",
    hcaes(x = fertility, y = life_expectancy, group = region),
    marker = list(radius = 5, symbol = "circle")
  ) %>%
  hc_title(text = "Life Expectancy vs. Fertility Rate by Region") %>%
  hc_xAxis(title = list(text = "Fertility Rate (Children per Woman)")) %>%
  hc_yAxis(title = list(text = "Life Expectancy (Years)")) %>%
  hc_legend(enabled = TRUE)