Introduction

Exploring Population Growth Using Interactive Visualization

This presentation demonstrates how interactive plots can help us understand global population trends.

Created on: July 13, 2026

Dataset

We will visualize population data for selected countries.

library(plotly)
## Loading required package: ggplot2
## 
## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
## 
##     last_plot
## The following object is masked from 'package:stats':
## 
##     filter
## The following object is masked from 'package:graphics':
## 
##     layout
countries <- c("India", "USA", "China", "Japan", "Brazil")

population <- c(1438000000, 
                340000000,
                1410000000,
                123000000,
                216000000)

data <- data.frame(
  Country = countries,
  Population = population
)

data

Interactive Plotly Visualization

Population Comparison

plot <- plot_ly(
  data,
  x = ~Country,
  y = ~Population,
  type = "bar",
  text = ~paste(Country, "Population:", Population),
  hoverinfo = "text"
)

plot
## Warning: `arrange_()` was deprecated in dplyr 0.7.0.
## Please use `arrange()` instead.
## See vignette('programming') for more help
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was generated.

Conclusion

Interactive visualizations allow users to:

Plotly makes data storytelling more engaging.