What types of data plots can be created in R?

Being data visualization one of the strong sides of the R programming languages, we can create all types of data plots in R:

• Common types of data plots:
  • Bar plot—shows the numerical values of categorical data.
  • Line plot—shows a progression of a variable, usually over time.
  • Scatter plot—shows the relationships between two variables.
  • Area plot—based on a line plot, with the area below the line colored or filled with a pattern.
  • Pie chart—shows the proportion of each category of categorical data as a part of the whole.
  • Box plot—shows a set of descriptive statistics of the data.
• Advanced types of data plots:
  • Violin plot—shows both a set of descriptive statistics of the data and the distribution shape for that data.
  • Heatmap—shows the magnitude of each numeric data point within the dataset.
  • Treemap—shows the numerical values of categorical data, often as a part of the whole.
  • Dendrogram—shows an inner hierarchy and clustering of the data.
  • Bubble plot—shows the relationships between three variables.
  • Hexbin plot—shows the relationships of two numerical variables in a relatively large dataset.
  • Word cloud—shows the frequency of words in an input text.
  • Choropleth map—shows aggregate thematic statistics of geodata.
  • Circular packing chart—shows an inner hierarchy of the data and the values of the data points
  • etc.

The skill track Data Visualization with R will help you broaden your horizons in the field of R graphics. If you prefer to learn data visualization in R in a broader context, explore a thorough and beginner-friendly career track Data Scientist with R.