Data Science – Examine Data Spread using Histogram and Density Plot

This article represents code samples in R programming language which could be used to draw histogram and density plot. Note that these plots are very useful for examining the data spread. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos.
Code Sample – Draw Histogram and Density Plot

Histrogram and density plot are very useful for examining the spread of a data variable. Following R commands with ggplot package helps in drawing histogram and density plots. As I am explaining with ggplot package, I am using diamonds data which comes with ggplot package. Pay attention to some of the following:

  • Draw Histogram: Command “ggplot(data) + geom_histogram(aes(x=variableName))” is used to draw the histogram. One could also provide binwidth as an additional parameter to geom_histogram function
  • Draw Density Plot: Command “ggplot(data) + geom_density(aes(x=variableName))” is used to create the density plot.
# Histogram to evaluate the spread of carat data
ggplot(diamonds) + geom_histogram(aes(x=carat))

# Density plot to evaluate the spread of carat data
ggplot(data=diamonds) + geom_density(aes(x=carat))
Ajitesh Kumar

Ajitesh Kumar

Ajitesh has been recently working in the area of AI and machine learning. Currently, his research area includes Safe & Quality AI. In addition, he is also passionate about various different technologies including programming languages such as Java/JEE, Javascript and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data etc.

He has also authored the book, Building Web Apps with Spring 5 and Angular.
Ajitesh Kumar

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