1. ggplot2
Wu Shaohuan

2. Packages we need
install.packages(“ggplot2”)
install.pacakges(“grid”)

3. Functions of R (for data scientists)
Data analysis
Plotting
the results of data analysis

4. Two plotting systems in R
The base plotting system
Pre-installed (no need to install extra packages)
Plotting function & parameters structure
Different plotting functions may have different parameters
ggplot2
A grammaticalized plotting system
Different plots have the similar grammar structure
Names of the parameters are relatively more user-friendly
Anyone who can use both plotting systems?

5. An example to show the difference of two plotting systems
Scatter plot

6. Summary 1 (difference between base and ggplot2 plotting systems)
Function & parameter based vs. grammaticalized
Names of the parameters in ggplot2 are more user-friendly

7. Summary 2 (3 key elements for ggplot2)
Data- a data frame with the variables to be plotted.
Geometry-the kind of plot, scatter or histogram, or…?
Aesthetic-the x and y coordinates of the plot.
ggplot(Data, aes(x=A,y=B)) + geom_point()
underscore

8. Key elements for ggplot2
Data
Geometry
Aesthetic
underscore
ggplot(Data, aes(x=A,y=B)) + geom_point()

9. Data Usually a data frame Vectors
A data frame containing the variables
Vectors
One vector
Two vectors with the same length

10. Aesthetic x and y coordinates (names in a data frame)
Colour, size, shape
A variable
ggplot(data, aes(x=x,y=y)) + geom_point()

11. Geometry name description geom_point Scatterplot geom_bar Bar plot
geom_histogram
Histogram
geom_density
Prabablity distribution plot
geom_boxplot
Box and whiskers plot
geom_text
Textual annotations in a plot
geom_errorbar
Error bars

12. A practice of the choice of geom_ functions
1, Plot the correlation between carat and price
2, Plot the average price of diamonds with each kind of cut/color/clarity, and then add error bars
3, Plot the distributions of carat/price
4, Plot the rough price distributions of each kind of cut
5, test if the prices between “fair” and “good” diamonds are significantly different
6, Write the P value in plot 4

13. Take-home message Data Aesthetic Geometry Usually a data frame
Can be vectors
Aesthetic
Mapping data to coordinate system(x, y)
Distinguish between different groups of data(color, size, shape)
Geometry
Choose the right geometry

14. Add-on1, faceting (subgrouping and plot)
facet_grid

15. Add-on2, multiple plotting on one page
pushViewport(viewport(layout = grid.layout(2, 2)))
vplayout <- function(x, y) viewport(layout.pos.row = x, layout.pos.col = y)
p1<-
p2<-
p3<-
p4<-
print(p1, vp=vplayout(1,1))
print(p2, vp=vplayout(1,2))
print(p3, vp=vplayout(2,1))
print(p4, vp=vplayout(2,2)) p1 p2 p3 p4

16. Getting help
ggplot2 is well documented at
Google
Try to post your problems to the community (stack overflow, mailing lists, etc.).

17. Polite questions To check whether the question has been asked.
Most people ignore repeated questions
To give a brief and comprehensive description of your problem.
Including a small sample of your data
A precise description of your problem
To tell what you have tried or what you think about the problem.

18. Happy plotting with ggplot2!