The best way is to download the data file and save it into a local folder
Then you can read it as much as you like
November 26, 2019
The best way is to download the data file and save it into a local folder
Then you can read it as much as you like
The commands in this page produce the plots of the following page
plot(survey$height_cm, main="1") plot(survey$height_cm, main="2", col="red") plot(survey$height_cm, main="3", cex=2) plot(survey$height_cm, main="4", cex=0.5) plot(survey$height_cm, main="5", pch=16) plot(survey$height_cm, main="6", pch=".")
The commands in this page produce the plots of the following page
plot(survey$height_cm, main="1", type = "l") plot(survey$height_cm, main="2", type = "o") plot(survey$height_cm, main="3", type = "b") plot(survey$height_cm, main="4", type = "p") plot(survey$height_cm, main="5", xlim=c(1,20)) plot(survey$height_cm, main="6", xlim=c(30,51))
plot(survey$height_cm, ylim=c(0,200)) points(survey$weight_kg, pch=2)
plot(survey$height_cm, type="l", ylim=c(0,200)) lines(survey$weight_kg, col="red")
plot(survey$height_cm, col=survey$Gender) legend("topleft", legend=c("Female", "Male"), fill=c(1,2))
plot(survey$height_cm) abline(h=mean(survey$height_cm), col="red", lwd=5)
This command adds a straight line in a specific position
abline(h=1)
adds a horizontal line in 1abline(v=2)
adds a vertical line in 2abline(a=3, b=4)
adds an \(y=a +b\cdot x\) line
a
is the intercept when \(x=0\)b
is the slopeplot(survey$height_cm) abline(v=20, col="blue") abline(a=160, b=0.5)
plot(survey$height_cm, survey$weight_kg)
plot(survey$height_cm, survey$hand_span_cm)
Instead of
plot(survey$height_cm, survey$weight_kg)
we can write
plot(survey$weight_kg ~ survey$height_cm)
or even
plot(weight_kg ~ height_cm, data = survey)
plot(height_cm ~ hand_span_cm, data = survey) plot(height_cm ~ hand_span_cm, data = survey, subset = Gender=="Female") plot(height_cm ~ hand_span_cm, data = survey, subset = Gender=="Male")
It is easier to specify the data.frame and which values to plot
plot(height_cm ~ weight_kg, data=survey)
survey$handness <- as.factor(survey$handness) plot(Gender ~ handness, data=survey)
plot(Gender ~ weight_kg, data=survey)
plot(weight_kg ~ Gender, data=survey)
Plotting a numeric value depending on a factor results in a boxplot
It is a graphical version of summary()
.
plot(weight_kg ~ Gender, data=survey, boxwex=0.3, notch=TRUE, col="grey")
plot(survey)
plot()
can be used with one or two vectors, or with a formulaplot(y ~ x)
looks like plot(x, y)
plot(y~x, data=dframe)
is better than plot(dframe$x, dframe$y)
The figure type depends on the data type of the vector
points()
or lines()
barplot()
boxplot()
pairs()
plot()
command defines the ranges, labels and titlepoints()
, lines()
text()
segment()
, arrows()
,rect()
, polygon()
xspline()
legend()
Learn more on the help page of each command
Colors can be specified in several ways: