R-Change Number of Bins in Histogram
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.
