The faceplate glass labels at the base of the columns makes it possible to interpret the results even when printed in gray-scale or by a colourblind individual. The plot shows the means, the standard deviation and the compact letter display for each treatment. In the ggplot() function we specify the data set that holds the variables we will be mapping to aesthetics, the visual properties of the graph.The data set must be a ame object. This bar plot is suitable for any presentation and also for written reports. All graphics begin with specifying the ggplot() function (Note: not ggplot2, the name of the package). # coloured barplot ggplot(data_summary, aes( x = factor(Temp), y = mean, fill = Glass, colour = Glass)) + geom_bar( stat = "identity", position = "dodge", alpha = 0.5) + geom_errorbar( aes( ymin=mean -sd, ymax=mean +sd), position = position_dodge( 0.9), width = 0.25, show.legend = FALSE) + labs( x= "Temperature (˚C)", y= "Light Output") + theme_bw() + theme( = element_blank(), = element_blank()) + theme( legend.position = c( 0.1, 0.75)) + geom_text( aes( label=Tukey), position = position_dodge( 0.90), size = 3, vjust= - 0.8, hjust= - 0.5, colour = "gray25") + ylim( 0, 1500) + geom_text( aes( label=Glass, y = 100), position = position_dodge( 0.90), show.legend = FALSE) + scale_fill_brewer( palette = "Dark2") + scale_color_brewer( palette = "Dark2") You can download the csv file with the summarised data or you can follow the Two-Way ANOVA in R – Step-by-Step Tutorial to build it. To build the barplots, we are going to use the summarised data, with the mean, the standard deviation and the letters indicating significant differences by Tukey’s test (compact letter display). The data 1 presents the results of an experiment conducted to study the influence of the operating temperature (100˚C, 125˚C and 150˚C) and three faceplate glass types (A, B and C) in the light output of an oscilloscope tube. ![]() In this tutorial we are going to see how to build a high-quality barplot for two explanatory variables. Cleaning unwanted information in the legend.
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