# twoord.plot

##### Plot with two ordinates

Two sets of values are displayed on the same plot with different ordinate scales on the left and right.

- Keywords
- misc

##### Usage

```
twoord.plot(lx,ly,rx,ry,data=NULL,main="",xlim=NULL,lylim=NULL,rylim=NULL,
mar=c(5,4,4,4),lcol=1,rcol=2,xlab="",lytickpos=NA,ylab="",ylab.at=NA,
rytickpos=NA,rylab="",rylab.at=NA,lpch=1,rpch=2,
type="b",xtickpos=NULL,xticklab=NULL,halfwidth=0.4,axislab.cex=1,
do.first=NULL,...)
```

##### Arguments

- lx,ly,rx,ry
y and optional x values for the plot

- data
an optional data frame from which to obtain the above values

- main
Title for the plot

- xlim
optional x limits as in

`plot`- lylim,rylim
optional y limits for the left and right axes respectively

- mar
optional margin adjustment, defaults to

`c(5,4,4,4)`- lcol,rcol
colors to distinguish the two sets of values

- xlab
X axis label as in

`plot`- lytickpos
Optional positions for the left axis tick labels.

- ylab
Left Y axis label as in

`plot`- ylab.at
Optional position for the left Y axis label

- rytickpos
Optional positions for the right axis tick labels.

- rylab
Right Y axis label

- rylab.at
Optional position for the right Y axis label

- lpch,rpch
plot symbols to distinguish the two sets of values

- type
as in

`plot`- xtickpos
Optional positions for x-axis tick labels.

- xticklab
Optional labels for x-axis. Useful for things like dates.

- halfwidth
Half the width of the bars in user units. The bars are centered on successive integers if no

`x`values are supplied.- axislab.cex
Character expansion for the axis labels and tick labels.

- do.first
Optional command(s) that will be executed immediately after the blank plot is displayed.

- ...
additional arguments passed to

`plot`and`points`.

##### Details

`twoord.plot` automates the process of displaying two sets of
values that have different ranges on the same plot. It is principally
useful in illustrating some relationship between the values across the
observations. It is assumed that the `lx` and `rx` values
are at least adjacent, and probably overlapping.

It is best to pass all the arguments `lx, ly, rx, ry`, but the
function will attempt to substitute sensible x values if one or two
are missing.

If at least one of the `type` arguments is "bar", bars will be plotted
instead of points or lines. It is best to plot the bars first (i.e. relative
to the left axis) if the other type is points or lines, as the bars will
usually obscure at least some of the points or lines. Using NA for the color
of the bars will partially correct this. If both types are to be bars,
remember to pass somewhat different x values or the bars will be overplotted.

Note that more values can be added to the plot using `points` or
`lines`, but remember that these will be plotted relative to the left
ordinate.

The `do.first` argument is useful for adding a background color or grid
to the plot as shown in the first two examples.

##### Value

nil

##### Note

There are many objections to the use of plots with two different ordinate scales, and some of them are even sensible and supported by controlled observation. Many of the objections rest on assertions that the spatial arrangement of the values plotted will override all other evidence. Here are two:

The viewer will assume that the vertical position of the data points indicates a quantitative relationship.

To some extent. It is probably not a good idea to have the spatial relationship of the points opposed to their numerical relationship. That is to say, if one set of values is in the range of 0-10 and the other 20-100, it is best to arrange the plot so that the latter values are not plotted below the former. See the second example, which illustrates a method for separating the two series and offsetting the axes.

The viewer will assume that an intersection of lines indicates an intersection of values.

If the visual elements representing values can be arranged to avoid intersections, so much the better. Many people have no trouble distinguishing which visual elements are linked to which axis as long as they are both coded similarly, usually with colors and/or symbols. In the special case where there is an underlying relationship between the two such as the probability of that value occurring under some conditions, it may help to mark the point(s) where this occurs.

It may be useful to consider `gap.plot` or separate plots as an
alternative.

##### See Also

##### Examples

```
# NOT RUN {
xval1 <- seq.Date(as.Date("2017-01-02"),
as.Date("2017-01-10"), by="day")
xval2 <- seq.Date(as.Date("2017-01-01"),
as.Date("2017-01-15"), by="day")
going_up<-seq(3,7,by=0.5)+rnorm(9)
going_down<-rev(60:74)+rnorm(15)
twoord.plot(2:10,going_up,1:15,going_down,xlab="Sequence",
ylab="Ascending values",rylab="Descending values",lcol=4,
main="Plot with two ordinates - points and lines",
do.first="plot_bg();grid(col=\"white\",lty=1)")
axis.Date(1,xval2)
# now separate the lines
twoord.plot(2:10,going_up,1:15,going_down,xlab="Sequence",
lylim=range(going_up)+c(-1,10),rylim=range(going_down)+c(-10,2),
ylab="Ascending values",ylab.at=5,rylab="Descending values",
rylab.at=65,lcol=4,main="Plot with two ordinates - separated lines",
lytickpos=3:7,rytickpos=seq(55,75,by=5),
do.first="plot_bg();grid(col=\"white\",lty=1)")
twoord.plot(2:10,going_up,1:15,going_down,xlab="Sequence",
lylim=range(going_up)+c(-1,10),rylim=range(going_down)+c(-10,2),
type=c("bar","l"),ylab="Ascending values",ylab.at=5,
rylab="Descending values",rylab.at=65,
main="Bars on left axis, lines on right axis",
lytickpos=3:7,rytickpos=seq(55,75,by=5),
lcol=3,rcol=4,do.first="plot_bg()")
twoord.plot(2:10,going_up,1:15,going_down,xlab="Sequence",
lylim=c(-3,8),rylim=c(50,100),type=c("l","bar"),
ylab="Ascending values",rylab="Descending values",
lytickpos=3:7,rytickpos=seq(55,75,by=5),ylab.at=5,rylab.at=65,
main="Lines on left axis, bars on right axis",
lcol=3,rcol=4,do.first="plot_bg(\"yellow\")")
# histogram with density curve superimposed
xhist<-hist(rnorm(100),plot=FALSE)
xdens<-dnorm(seq(-3,3,by=0.05))
twoord.plot(xhist$mids,xhist$counts,seq(-3,3,by=0.05),
xdens,type=c("bar","l"),lcol=4,rcol=2,ylab="Counts",
rylab="Density",main="Histogram and density curve",
halfwidth=0.2,lylim=c(0,max(xhist$counts)+1),rylim=c(0,0.45),lwd=2)
# }
```

*Documentation reproduced from package plotrix, version 3.7-4, License: GPL (>= 2)*