An online community for showcasing R & Python tutorials. It operates as a networking platform for data scientists to promote their talent and get hired. Our mission is to empower data scientists by bridging the gap between talent and opportunity.
Visualizing Data

# How to make Histogram with R

• Published on August 10, 2015 at 8:10 pm
• Updated on October 30, 2017 at 3:35 pm

Histogram are frequently used in data analyses for visualizing the data. Through histogram, we can identify the distribution and frequency of the data. Histogram divide the continues variable into groups (x-axis) and gives the frequency (y-axis) in each group. The function that histogram use is hist(). Below I will show a set of examples by using a iris dataset which comes with R.

Basic histogram:

hist(iris$Petal.Length)  Here is the basic histogram: Adding color and labels in histograms: hist(iris$Petal.Length, col="blue", xlab="Petal Length", main="Colored histogram")


Histogram with labels:

hist(iris$Petal.Length, breaks=30, col="gray", xlab="Petal Length", main="Colored histogram")  Histogram with more bars: In statistics, the histogram is used to evaluate the distribution of the data. In order to show the distribution of the data we first will show density (or probably) instead of frequency, by using function freq=FALSE. Secondly, we will use the function curve() to show normal distribution line. Here the example: # add a normal distribution line in histogram hist(iris$Petal.Length, freq=FALSE, col="gray", xlab="Petal Length", main="Colored histogram")
curve(dnorm(x, mean=mean(iris$Petal.Length), sd=sd(iris$Petal.Length)), add=TRUE, col="red") #line