Site icon R-bloggers

R-Change Number of Bins in Histogram

[This article was first published on R Archives » Data Science Tutorials, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

The post R-Change Number of Bins in Histogram appeared first on Data Science Tutorials

Unravel the Future: Dive Deep into the World of Data Science Today! Data Science Tutorials.

R-Change Number of Bins in Histogram, the default number of bins is determined by Sturges’ Rule.

However, you can override this rule by specifying a specific number of bins using the breaks argument in the hist function.

R-Change Number of Bins in Histogram

For example, to create a histogram with 7 bins, you can use the following code:

hist(data, breaks = seq(min(data), max(data), length.out = 7))

Note that the number of bins used in the histogram will be one less than the number specified in the length.out argument.

Add Footnote to ggplot2 » Data Science Tutorials

Here are some examples of how to use this syntax:

Example 1: Basic Histogram

The following code creates a basic histogram without specifying the number of bins:

data <- c(1, 2, 2, 3, 4, 4, 4, 5, 5, 6, 7, 10, 11, 13, 16, 16, 16)
hist(data, col = 'lightblue')

Using Sturges’ Rule, R defaults to using 8 bins in the histogram.

Example 2: Specifying the Number of Bins

The following code creates a histogram with exactly 6 bins:

data <- c(1, 2, 2, 3, 4, 4, 4, 5, 5, 6, 7, 10, 11, 13, 16, 16, 16)
hist(data, col = 'lightblue', breaks = seq(min(data), max(data), length.out = 7))

When choosing a specific number of bins for your histogram, it’s important to consider the potential impact on your data interpretation. Using too few bins can hide underlying patterns in the data:

data <- c(1, 2, 2, 3, 4, 4, 4, 5, 5, 6, 7, 10, 11, 13, 16, 16, 16)
hist(data, col = 'lightblue', breaks = seq(min(data), max(data), length.out = 4))

On the other hand, using too many bins can simply visualize noise in the data:

data <- c(1, 2, 2, 3, 4, 4, 4, 5, 5, 6, 7, 10, 11, 13, 16, 16, 16)
hist(data, col = 'lightblue', breaks = seq(min(data), max(data), length.out = 16))

In general, it’s recommended to use the default Sturges’ Rule for optimal results.

However, if you need to specify a specific number of bins for your histogram analysis.

The post R-Change Number of Bins in Histogram appeared first on Data Science Tutorials

Unlock Your Inner Data Genius: Explore, Learn, and Transform with Our Data Science Haven! Data Science Tutorials.

To leave a comment for the author, please follow the link and comment on their blog: R Archives » Data Science Tutorials.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
Exit mobile version