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Visualize Multivariate Data – Box plot in R
In R, a box plot, also known as a box-and-whisker plot, is a useful tool for visualizing multivariate data, or data that has more than one variable. A box plot shows the distribution of the data by plotting the median, quartiles and outliers in a graph. It allows to visualize the shape of the distribution of the data, to compare multiple variables and identify any potential outliers.
To create a box plot in R, you can use the boxplot() function. This function takes the data and the variables to be plotted as arguments and returns a box plot of the data. You can also customize the appearance of the plot by adding additional arguments to the function, such as the colors of the boxes.
For example, if you have a dataframe called “data” with variables called “var1” and “var2”, you can create a box plot of the data by using the command boxplot(data[,c(“var1″,”var2”)])
You can also use the ggplot2 library in R to create a box plot. ggplot2 is a powerful data visualization package that provides a lot of customization options for creating box plots.
For example, if you have a dataframe called “data” with variables called “var1” and “var2”, you can create a box plot of the data by using the command ggplot(data, aes(x=var1,y=var2)) + geom_boxplot()
In summary, In R, a box plot, also known as a box-and-whisker plot, is a useful tool for visualizing multivariate data, or data that has more than one variable. A box plot shows the distribution of the data by plotting the median, quartiles and outliers in a graph. It allows to visualize the shape of the distribution of the data, to compare multiple variables and identify any potential outliers. To create a box plot in R, you can use the boxplot() function, which takes the data and the variables to be plotted as arguments and returns a box plot of the data. You can also customize the appearance of the plot by adding additional arguments to the function, such as the colors of the boxes. Alternatively, you can use the ggplot2 library in R to create a box plot, which is a powerful data visualization package that provides a lot of customization options for creating box plots.
In this Applied Machine Learning & Data Science Recipe (Jupyter Notebook), the reader will find the practical use of applied machine learning and data science in R programming: Visualize Multivariate Data – Box plot in R.
Visualize Multivariate Data – Box plot in R
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