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R Strip Chart 

A strip chart in R is a type of chart that displays individual data points along a single strip.

It is a simplified way to visualize distribution of dataset.

Stripchart in R helps to customize the appearance of plot by using the parameters like color, shape and size of data points for better understanding purposes.

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What is a strip chart in R?

A stripchart in R is a chart consisting of a plot which is used to display one-dimensional data. We use stripchart() function to create a strip chart. This stripchart() function consists of numeric values as a main argument and additional parameters are also used to adjust the appearance of the plot which includes color,shape,and label which define the appearance of the plot.

We use stripchart to analyse the difference in the distribution of data between groups which help to identify patterns or outliers in our data.

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1. Creating strip chart by using DataSet 

For creating a stripchart of a dataset, we need to load the dataset.

In this R programming tutorial, we will use the built- in dataset i.e.  air quality  to create a strip chart of air quality which will define the Daily air quality measurements in New York, May to September 1973.”-R documentation

Let’s see the first six rows of the dataset which can be used for plotting.

Example1-

Code-  

# using head() to load the first six rows of air quality DataSet
head(airquality)

Output-

2. Creating Strip chart of built-in Dataset air quality

In this Example we will create a stripchart of Ozone readings of the built in data set air quality.

Example 2- Creating Strip Chart for Ozone readings of air quality dataset

Let’s create a stripchart for Ozone readings

Code–

# creating strip chart of Ozone readings in air quality datase
stripchart(airquality$Ozone)

Output–

Explanation- 

In the above graph, we observed that till 50 most of the data is clustered. In this plot we can see multiple data points are overlapping each other like a stack of points.

In this we use x and Y provided to label the axes. We can also use methods which shows the data points plotting like stack or jitter etc

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3. Creating Strip Chart of dataset Air Quality Ozone using Jitter Method

In this Example, we will create a stripchart using a jitter method to avoid overlapping of data points.

Code- 

# creating strip chart using jitter method
stripchart(airquality$Ozone,
main=”Mean ozone in parts per billion at Roosevelt Island”,
xlab=”Parts Per Billion”,
ylab=”Ozone”,
method=”jitter”,
col=”orange”,
pch=1
)

Output-

Explanation- 

Here we use the jitter method in the stripchart() function which avoids overlapping of data points. This method is mostly used to clearly visualize the data points.

4. Creating Strip Charts by using Multiple data

In this Example, we will create a stripchart for multiple data from the Air quality dataset. Let’s generate the code  

Code- 

# creating strip chart for multiple data
list_new <- list(x=airquality$Ozone,y=airquality$Solar)
stripchart(list_new,method=’jitter’,
col=c(‘orange’, ‘magenta’),
vertical = TRUE)

Output –

Explanation-

In this code, we have used a dataset Air quality which consists of different variables as shown in example 1. In this code we had defined a list  “list_new” which consisted of two variables Ozone and Solar from the Air Quality Dataset. And then by using stripchart() function we created a vertical stripcharts. We also used the parameter color which specified two strip charts.

5. Creating Strip Chart by a Formula

Code- 

stripchart(Temp~Month,data=airquality,
main=”Different strip chart for each day”,
xlab=”Day”,
ylab=”Temperature”,
col=”brown3″,
group.names=c(“Tue”,”Wed”,”Thurs”, “Fri”, “Sat”),
vertical=TRUE,
pch=16
)

Output-

Conclusion

• With the help of Strip charts, we can easily visualize the datasets and their readings through data points.
• To visualize the data points in different ways, we can create Strip charts by using different methods like Jitter, Overplot, Stack.
• While creating Strip chart, we can easily change their styles, colors, labels and titles.va
• Creating a strip charts with multiple data can help us to derive valuable insights from the given data as it makes it easier to identify the data points.

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