R에서 EPS 이미지 생성

EPS 이미지로 저장하는 방법을 다루겠다.

postscript(file="plot.eps", onefile=FALSE, horizontal=FALSE)

dev.off()

If you are using ggplot2 to generate a figure, then a ggsave(file="name.eps") will also work

Theme 설정 방법

테마로 한번 설정해 놓으면 변경된 내용을 쉽게 유지 할 수 있다.

변경 할 수 있는 요소들:

axis.title.x // 축 이름을 의미함.

axis.text.x //축 눈끔을 의미함.

plot.title // 도표의 제목을 의미함.

Pie chart

How to show percentage in this chart?

use annotate()

usage:

annotate("text", x="?", y="?", label="name")

참고자료

ggpie: pie graphs in ggplot2

R: Pie chart with percentage as labels using ggplot2

Base

1. “Artist’s palette” model
2. Start with blank canvas and build up from there
3. Start with plot function (or similar)
4. Use annotation functions to add/modify (text, lines, points, axis)

Pros:

Convenient, mirrors how we think of building plots and analyzing data

Cons:

1. Can’t go back once plot has started (i.e. to adjust margins);
2. need to plan in advance
3. Difficult to “translate” to others once a new plot has been created (no graphical “language”). Plot is just a series of R commands

Lattice

Plots are created with a single function call (xyplot, bwplot, etc.)

Pros:

1. Most useful for conditioning types of plots: Looking at how y changes with x across levels of z
2. Thinks like margins/spacing set automatically because entire plot is specified at once
3. Good for putting many many plots on a screen

Cons:

1. Sometimes awkward to specify an entire plot in a single function call
2. Annotation in plot is not intuitive
3. Use of panel functions and subscripts difficult ot wield and requires intense preparation
4. Cannot “add” to the plot once it’s created

ggplot2

Pros:

1. Split the difference between base and lattice
2. Automatically deals with spacings, text, titles but also allows you to annotate by “adding”
3. Superficial similarity to lattice but generally easier/more intuitive to use
4. Default mode makes many choices for you (but you can customize!)

ggplot2 vs lattice.pdf

ggplot2_part1.pptx