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boxplot (by = 'Account_Type' ,grid = 'True' ,column =, color = 'red' ) # Display the box plots based on parameter usedĭf.
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# Print the first 8 rows of the loaded data run_line_magic ( 'matplotlib', 'inline' ) # Import get_ipython for format the output inline # Import matplotlib to setup the figure size of box plot If you have not installed the pandas and seaborn libraries before, then you should run the following command from the terminal to install these libraries: In this tutorial, I will use spyder3 to execute the code. You can use any Python interpreter for executing the code. If you are a new Python user, then you will first have to set up the environment to show the output of the box plot.
#BOX AND WHISKER PLOT PYTHON HOW TO#
This tutorial will show you how to create box plots based on a given data set using the pandas and seaborn libraries of Python. A box plot summarizes this data in the 25 th, 50 th, and 75 th percentiles. These values include the median, maximum, minimum, upper-quartile, and lower-quartile statistical values. Three types of quartiles are used in the box plot to plot the data. Box plots can be very useful when we want to know how the data is distributed and spread. This function helps users to understand the data summary properly. A box plot is used to summarize data sets by using the box and whisker plot method.