Plots

Plots

There is a large number of different types of plots for visualizing data.

Basic plots

The following plots are frequently used:

  • The bar plot shows the extent of values according to the height of bars. If the data are normally distributed, they can be display variation by including error bars.
  • The box plot indicates variation by showing the most frequently observed measurements in terms of the first, second, and third quartile.
  • The histogram consists of bars that indicate the frequency of measurements and is ideal for showing the distribution of a variable.
  • The line plot connects individual measurements using lines. It is most suited for time-series data.
  • The scatter plot shows the value of two variables as points and is ideal for identifying correlated variables.

Further plots

The following plots are less frequently used than the basic plots. Nevertheless, these plots may be very useful for specific applications.

  • The beeswarm plot is an alternative to the box plot that draws individual data points in a well-defined manner.
  • The Q-Q plot can be used to compare whether two samples have similar distributions.
  • The radar plot shows the values of several properties in a circular layout.
  • The violin plot is an alternative to the box plot that shows a density estimate.
  • The geospatial plot is concerned with drawing the locations of entities on a map.

Posts about plots

The following posts exemplify the use of plots in R.

Radar plots

Radar plots

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Radar plots are exceptional for visualizing the properties of individual objects. Here, I demonstrate how to draw radar plots in R by plotting the properties of whiskeys from several distilleries.

Bar Plots and Error Bars

Bar Plots and Error Bars

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Bar plots are frequently used due to their simplicity. However, they also do not convey a lot of information. Here, I discuss how error bars can be used to visualize variance and under which circumstances bar charts should not be used.