Unlock Visual Insights with R Strip Charts: A Step-by-Step Guide

Unleash the Power of Visual Data Analysis with Strip Charts in R

Getting Started with Strip Charts

Imagine having the ability to visualize dozens of time series at once, all on a single strip. That’s exactly what strip charts offer – a powerful tool for data analysis. But before we dive into the world of strip charts, let’s first load the dataset we’ll be working with. In this tutorial, we’ll be using the built-in airquality dataset to create our strip chart.

First Glance at the Dataset

Take a look at the first six rows of the airquality dataset:

[Output]

This dataset is just the starting point for our visual data analysis journey.

Creating a Strip Chart in R

Now that we have our dataset, it’s time to create a strip chart using the stripchart() function in R. Here’s an example:

[Output]

In this example, we’ve used the stripchart() function along with the $ operator to create a strip chart of the Ozone reading from the airquality dataset. But that’s not all – we can also pass additional parameters to customize the look of our plot.

Customizing Your Strip Chart

Want to add a title, labels, and change the color of your strip chart? No problem! Here’s how:

[Output]

In this example, we’ve added a title, labels for the x-axis and y-axis, and changed the color of the strip to orange. We achieved this by using the following parameters:

• main adds the title “Mean ozone in parts per billion at Roosevelt Island”
• xlab adds the label “Parts Per Billion” for the x-axis
• ylab adds the label “Ozone” for the y-axis
• col = "Orange" changes the color of the strip to orange

Jitter Plots: A Variant of Strip Plots

When dealing with large clusters of data points, jitter plots come to the rescue. This variant of strip plots provides a better view of overlapping data points. To create a jitter plot, simply pass method = "jitter" inside the stripchart() function:

[Output]

In this example, we’ve used the method parameter to create a jitter plot, ensuring that coincident points are plotted without overlapping.

Multiple Strip Charts in One Go

What if you want to draw multiple strip charts in a single plot? Easy! Just pass a list of numeric vectors to the stripchart() function:

[Output]

In this example, we’ve passed a list named list1 with two vectors – Ozone and Solar Radiation from the airquality dataset – inside stripchart() to create multiple strips. We’ve also provided two colors to represent the two different strip charts: orange for Ozone readings and brown for Solar.R readings.