Data Visualization with R

Complex Visualizations

While basic visualizations like bar charts and scatter plots are excellent for straightforward data representation, complex visualizations offer a more nuanced and in-depth look at your data. These advanced techniques allow you to explore multiple dimensions, relationships, and temporal changes in your dataset. They can include facets, interactive elements, and even animations to make your data come alive. In this section, we will explore some of these complex visualization methods using the mtcars dataset, aiming to provide you with the tools to create more insightful and interactive data stories

Faceted Bar Chart

Regular Faceted Bar Chart

library(ggplot2) 
ggplot(mtcars, aes(x=factor(cyl))) + 
   geom_bar() + 
   facet_wrap(~gear) + 
   xlab("Number of Cylinders") + 
   ylab("Frequency")

Customized Faceted Bar Chart

ggplot(mtcars, aes(x=factor(cyl))) + 
 geom_bar(fill="blue", color="black") + 
 facet_wrap(~gear) + 
 xlab("Number of Cylinders") + 
 ylab("Frequency") + 
 theme_minimal()

Interactive Scatter Plot with Plotly

Regular Interactive Scatter Plot

library(plotly) 
fig <- plot_ly(mtcars, x = ~hp, y = ~mpg, type = 'scatter', mode = 'markers') 
fig

Customized Interactive Scatter Plot

fig <- plot_ly(mtcars, x = ~hp, y = ~mpg, type = 'scatter', mode = 'markers') %>% 
 layout(title = "Customized Interactive Scatter Plot") 
fig

Heatmap

Regular Heatmap

library(heatmaply) 
heatmaply(cor(mtcars), 
              main = "Correlation Heatmap", 
              xlab = "Features", 
              ylab = "Features")

Customized Heatmap

heatmaply(cor(mtcars), 
              main = "Customized Correlation Heatmap", 
              xlab = "Features", 
              ylab = "Features", 
              colors = heat.colors(256))

3D Scatter Plot

Regular 3D Scatter Plot

library(scatterplot3d) 
scatterplot3d(mtcars$hp, mtcars$mpg, mtcars$wt, 
              main="3D Scatter Plot")

Customized 3D Scatter Plot

scatterplot3d(mtcars$hp, mtcars$mpg, mtcars$wt, 
               main="Customized 3D Scatter Plot", 
               color="blue", 
               pch=19, 
               type="h")

These examples showcase how you can create more complex visualizations using the mtcars dataset. These complex charts can provide deeper insights and are particularly useful when you have multi-dimensional data or when you want to create more interactive visual experiences.