#Boxplot in r code

#Boxplot in r code

There is a lot of ggplot2 code to digest here. Let’s use this information to generate a legend, and make the code reusable by creating a standalone function that we used in earlier code ( ggplot_box_legend). Let’s check that the output matches boxplot.stats: # Using base R:īase_R_output <- boxplot.stats(sample_df$values) Outlier values are considered any values over 1.5 times the interquartile range over the 75th percentile or any values under 1.5 times the interquartile range under the 25th percentile.The lower whisker is the minimum value of the data that is within 1.5 times the interquartile range under the 25th percentile.The upper whisker is the maximum value of the data that is within 1.5 times the interquartile range over the 75th percentile.Interquartile range is the difference between the 75th and 25th percentiles.Quartiles (25, 50, 75 percentiles), 50% is the median.Ggplot_output <- ggplot2_boxplot(sample_df$values)

'75th percentile' = as.numeric(quartiles), '50th percentile (median)' = as.numeric(quartiles), '25th percentile' = as.numeric(quartiles), TimeOfDay = case_when(hourOfDay 6 ~ 'daytime', Mutate(hourOfDay = as.numeric(format(dateTime, '%H')), We’ll use the package dataRetrieval to get the data (see this tutorial for more information on dataRetrieval), and plot a simple boxplot by month using ggplot2: library(dataRetrieval) Here we’ll use chloride data (parameter code “00940”) measured at a USGS station on the Fox River in Green Bay, WI (station ID “04085139”). Features in this blog post take advantage of enhancements to ggplot2 in version 3.0.0 or later.įirst, let’s get some data that might be typically plotted in a USGS report using a boxplot. Some additional goals here are to create boxplots that come close to USGS style. Therefore, this blog post breaks down the calculations into (hopefully!) easy-to-follow chunks of code for you to make your own box plot legend if necessary. The help file for this function is very informative, but it’s often non-R users asking what exactly the plot means. The base R function to calculate the box plot limits is boxplot.stats. A question that comes up is what exactly do the box plots represent? The ggplot2 box plots follow standard Tukey representations, and there are many references of this online and in standard statistical text books. Boxplots are often used to show data distributions, and ggplot2 is often used to visualize data.