Graph plotting workshop I.
1. Import data (03_xy.csv) into R
2. Create histograms of both x and y – combine them into a single two-panel plot, save in pdf or svg
format, delete the histogram title
3 Adjust margins of the plots to improve the fill of the graphical layout and fix the ranges of y-axes to
the same values.
4. Create scatterplot of y ~ x
5. Change the point symbols to filled circles, change the colors of the points to illustrate the type
variable Have a look at http://dr-k-lo.blogspot.cz/2013/11/in-in-r-underused-in-operator.html to see
how %in% operator works.
Graph plotting workshop II.
6. Add color-key legend to the plot
7. Adjust point size
8. Change the orientation of y-axis values, adjust size of the axis titles and axis values
9. log-scale y- and both axes
10. Add text "Colorful points" somewhere inside the plot region and onto the plot margins
11. Add text r2
= value of squared correlation coefficient somewhere into the plot region
12. Create boxplot of y ~ type
13. Create barplot of mean y classified by type, add error bars indicating standard errors
14. Create dotchart of mean y classified by type, add error bars indicating standard errors
15. Generate new data frame by:
big.data<-data.frame(y=rlnorm(30000, 4, 0.5)+sample(c(1,50, 8, 100,
9, -11, 20, 40, -20), 30000, replace=T), fact=c(rep("a", 12000),
rep("b", 18000)))
16. Create a boxplot of y ~ fact
17. Create a beanplot of y ~ fact
Homework (to be completed after the second graph plotting workshop): Create a graphically nice
plot with nice axis labels and minimum two panels – embed in into a word document with the code
used to generate the figure pastet below. Convert the word file to pdf named surname.pdf and upload to
Homework Vaults in IS. You can use your own real data or generate some imaginary data for this task.