MATLAB can be used to plot our data for visualizing and intuitively understanding it. Observe in the output that we have obtained a scatter plot of red color, as passed by us in the input argument. Observe in the code that we have passed pre-defined color code for red as an argument (Please refer to the table at the end of the article for pre-defined color codes) Here we discuss the Parameters under boxplot() function, how to create random data, changing the colour and graph analysis along with the Advantages and Disadvantages.For this example, we will scatter plot of red color Boxplot gives insights on the potential of the data and optimizations that can be done to increase sales.Ä«oxplot is an interesting way to test the data which gives insights on the impact and potential of the data. Boxplots are often used in data science and even by sales teams to group and compare data. We need consistent data and proper labels. The usability of the boxplot is easy and convenient. We can also vary the scales according to data.Ä«oxplots can be used to compare various data variables or sets. Box plot supports multiple variables as well as various optimizations. The data grouping is made easy with the help of boxplots. Comparing data with correct scales should be consistent.Scales are important changing scales can give data a different view.If there are discrepancies in the data then the box plot cannot be accurate.Helps to identify outliers in the data.Displays range and data distribution on the axis.Summarizing large amounts of data is easy with boxplot labels.Advantages & Disadvantages of Box PlotÄ«elow are the different Advantages and Disadvantages of the Box Plot: Advantages As medians of stat1 to stat4 donât match in the above plot. Notch parameter is used to make the plot more understandable. We can add labels using the xlab,ylab parameters in the boxplot() function.Ä«oxplot(data,las=2,xlab="statistics",ylab="random numbers",col=c("red","blue","green","yellow"))Ä«y using the main parameter, we can add heading to the plot.Ä«oxplot(data,las=2,xlab="statistics",ylab="random numbers",main="Random relation",notch=TRUE,col=c("red","blue","green","yellow")) Using the same above code, We can add multiple colours to the plot.Ä«oxplot(data,las=2,col=c("red","blue","green","yellow") We can add the parameter col = color in the boxplot() function. Let us see how to change the colour in the plot. In all of the above examples, We have seen the plot in black and white. The above plot has text alignment horizontal on the x-axis. Starting with the minimum value from the bottom and then the third quartile, mean, first quartile and minimum value. To understand the data let us look at the stat1 values. We have given the input in the data frame and we see the above plot. We can change the text alignment on the x-axis by using another parameter called las=2. We have 1-7 numbers on y-axis and stat1 to stat4 on the x-axis. STAT 1Ä«elow is the boxplot graph with 40 values. We add more values to the data and see how the plot changes.Äata
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