6. Plotting with Base Function
Nao Mimoto - Dept. of Statistics : The University of Akron – Class Web Page
1. Base Function vs ggplot2
We look at simple plotting with base functions (without using any
packages). R has very good visualization package called ggplot2.
Tutorial for that is on another page.
2. Plotting
Orig <- read.csv("https://nmimoto.github.io/datasets/plants.csv")
# load the dataset directly from website.
dim(Orig) # n=32. Ther are 3 columns## [1] 32 3## [1] "Cost" "MWatts" "Date"## Cost MWatts Date
## 1 345.39 514 67.92
## 2 460.05 687 68.58
## 3 452.99 1065 67.33
## 4 443.22 1065 67.33
## 5 652.32 1065 68.00
## 6 642.23 1065 68.00
Note that MWatts is on x-axis.
2. Plotting options
Let’s load lynx.csv from my website.
Orig <- read.csv("https://nmimoto.github.io/datasets/lynx.csv")
# load the dataset directly from website.
head(Orig) # the data only has one column called "Lynx"## Lynx
## 1 269
## 2 321
## 3 585
## 4 871
## 5 1475
## 6 2821## [1] 114 1Plot types
plot(X) # scatter plot is the default for plot()
plot(X, type="p") # type="p" gives the same scatter plot
Zooming in/out
3. Draw lines to Plot
You can add horizontal and vertical lines to existing plot.
Orig <- read.csv("https://nmimoto.github.io/datasets/lynx.csv")
X = Orig$Lynx
plot(X, type="l")
M = mean(X)
abline(h=M, col="red") # h for horizontal
abline(v=30, col="blue") # v for vertical
You can also draw line with intercept and slope.
4. Overlaying Two Plots
Orig2 <- read.csv("https://nmimoto.github.io/datasets/wine.csv")
# load in wine.csv from webpage
head(Orig2) # has 1 column called "wine"## wine
## 1 464
## 2 675
## 3 703
## 4 887
## 5 1139
## 6 1077## [1] 142 1
Overlay two plots
Note that lines() uses type=“l” as default. You can change it by usint type= command if you need to.
Note that lines() use uses the plot that is already drawn by plot(). So which one to plot first does matter. You can specify the range of the plot in plot().
plot(X, type="l", xlim=c(0,200), ylim=c(0, 8000)) # plot X with more range
lines(Y, col="red") # overlay Y
5. Plotting in Panels
You can plot more than 1 plot on a same page. Here’s horizontal stack.
Vertical stack.
As 2 by 2 panel.
layout(matrix(1:4, 2, 2)) # set up layout as (2x2) matrix
plot(X, type="l")
plot(Y, type="l")
plot(X, type="l")
plot(Y, type="l")
Code Only
### 1. Plotting
Orig <- read.csv("https://nmimoto.github.io/datasets/plants.csv")
# load the dataset directly from website.
dim(Orig) # n=32. Ther are 3 columns
names(Orig) # look up the names of columns
head(Orig)
plot(Orig$Cost) # scatter plot of Cost column
plot(Orig$MWatts) # scatter plot of MWatts column
plot(Orig$MWatts, Orig$Cost) # MWatts vs Cost
### 2. Plotting options
# load **lynx.csv** from my website.
Orig <- read.csv("https://nmimoto.github.io/datasets/lynx.csv")
# load the dataset directly from website.
head(Orig) # the data only has one column called "Lynx"
dim(Orig) # n = 114
X = Orig$Lynx # Call "Lynx" column of "Orig" data as "X" for convenience.
# Plot types
plot(X) # scatter plot is the default for plot()
plot(X, type="p") # type="p" gives the same scatter plot
plot(X, type="l") # line plot
plot(X, type="o") # both
# Change line width
plot(X, type="l", lwd=2) # thick line
plot(X, type="l", lwd=4) # thicker line
# Change color
plot(X, type="l", lwd=2, col="red")
plot(X, type="l", lwd=2, col="green")
# Zooming in/out
plot(X, type="l", xlim=c(0,60), ylim=c(0,4000)) # Zooming In
plot(X, type="l", xlim=c(0,200), ylim=c(0,10000)) # Zooming Out
# Put title and Label
plot(X, type="l",
xlab="Year", ylab="Number of Lynx Caught",
main="Lynx.csv")
# How to look up more options
# Googling something like "R how to change line type" is the best bet.
# You can also look at R documentation by command:
?plot
### 3. Draw lines to Plot
# You can add horizontal and vertical lines to existing plot.
Orig <- read.csv("https://nmimoto.github.io/datasets/lynx.csv")
X = Orig$Lynx
plot(X, type="l")
M = mean(X)
abline(h=M, col="red") # h for horizontal
abline(v=30, col="blue") # v for vertical
# You can also draw line with intercept and slope.
plot(X, type="l")
abline(a=1000, b=5, col="red") # a=intercept. b=slope
### 4. Overlaying Two Plots
Orig2 <- read.csv("https://nmimoto.github.io/datasets/wine.csv")
# load in wine.csv from webpage
head(Orig2) # has 1 column called "wine"
dim(Orig2) # n = 142
Y = Orig2$wine # Call "wine" column as "Y" for convenience.
# Single plots
# Note X was defined as Orig$Lynx above.
plot(X, type="l")
plot(Y, type="l")
# Overlay two plots
plot(X, type="l") # plot X on its own
lines(Y, col="red") # overlay Y
plot(Y, type="l", col="red") # plot Y on its own
lines(X) # overlay X
# lines() uses xllim and yllim that is already there
plot(X, type="l", xlim=c(0,200), ylim=c(0, 8000)) # plot X with more range
lines(Y, col="red") # overlay Y
### 5. Plotting in Panels
# Here's horizontal stack.
layout(matrix(1:2, 1, 2)) # set up layout as (2x1) matrix
plot(X, type="l")
plot(Y, type="l")
layout(1) # back to 1 plot layout
# Vertical stack.
layout(matrix(1:2, 2, 1)) # set up layout as (2x1) matrix
plot(X, type="l")
plot(Y, type="l")
layout(1) # back to 1 plot layout
# As 2 by 2 panel.
layout(matrix(1:4, 2, 2)) # set up layout as (2x2) matrix
plot(X, type="l")
plot(Y, type="l")
plot(X, type="l")
plot(Y, type="l")
layout(1) # back to 1 plot layout