This refers to my previous question.
how to plot multiple polygon plots in R?
How can i add lines (not segments) to existing plot(with polygon) which has diamond at its each terminal.
You can use lines for this:
#random plot
plot(1:10, xlim=c(0, 10), ylim=c(0,10))
#then plot line with x1,x2 and y1,y2 co-ordinates
#below x1=0 x2=5 y1=2 and y2=8
lines(c(0, 5), c(2, 8), type='l')
Make sure you add xlim and ylim in plot in order for lines to pick up the correct scale.
Related
I've two datas to compare in a scatter plot.
data1 <-c(0.341, 0.655, 0.934, 1.741)
data2 <-c(1.8, 2, 2.4, 2.6)
With the code below I am getting this:
plot(data1, data2, main="Minute Max.", asp=1,
xlab="Historical Values ", ylab="Disaggregated Values", pch=19)
I have three wishes:
1) Adding a 45 degree line
2) Having same coordinate length. For the example above, you can see the max. value is 2.6 in total. So I want my scatter diagram as square. Both x and y coordinates lengths' must be 2.6.
3) I know how to export the plot manually. But which code should I use to export the plot?
1) Use abline to draw a straight line. This is called after your plot.
plot(data)
abline(0,1)
abline() also takes additional arguments, like col="red".
2) This can be done using xlim and ylim. For more information on how you can edit the plot, use ?plot() inside R to see the revelant helpfile.
plot(data, xlim=c(0,2.6),ylim=(0,2.6)
3) If you want it saved as e.g. a pdf, you can do the following.
pdf("myfile.pdf")
plot(data,....)
dev.off()
Also works with jpeg, e.g.
jpeg("myplot.jpg")
plot(data)
dev.off()
I would like to represent two-dimensional data as bars, placed over the x-axis values, but barplot() does not allow to control x-axis placement, and plot() does not draw bars:
x <- c(1, 2, 3, 5)
y <- 1:4
plot(x, y, type = "h")
barplot(y)
Click for an image illustrating the plot() and barplot() examples.
I understand that I can plot a histogram –
hist(rep(x, y), breaks = seq(min(x) - 0.5, max(x) + 0.5, 1))
Click for an image illustrating the hist() example.
– but the recreation of the original (non-frequency) data and the calculation of the breaks is not always as straightforward as in this example, so:
Is there a way to force plot() to draw bars?
Or is there a way to force barplot() to place the bars at specific values on the x-axis?
Basically, what I would like is something like:
barplot(y, at = x)
I would prefer to use base R and avoid ggplot.
While I agree with #Dave2e that a barplot may not be the best way to represent your data, you can get something like what you are describing by starting with a blank plot and drawing the relevant rectangles. I am using your y values (1:4) and the x values that you mentioned in your comment. I am not sure what you want on the x-axis, but I show labels for the x-values that you give. In order to look like a barplot, I suppress the tick marks on the x-axis.
plot(NULL, xlim=c(0,11), ylim=c(0,4.5), bty="n",
xaxt="n", xaxs="i", yaxs="i", xlab="", ylab="")
rect(x-0.5, 0, x+0.5, y, col="gray")
axis(side=1, at=x, col.ticks=NA)
I would like to plot two graphs in the same plotting region with horizontal grid lines. Each side of the grid lines should give the value for one graph or the other. There should be no y-axis.
The grid() function allows me to simply set the number of bins using the ny= argument. How do I get the corresponding labels to the grid lines? Usually, I would use axis(..., lwd=0) to get the labels. However, the function requires label positions with at=c() and does not feature a ny= argument. Is there a way to automatically set the locations from the number of bins?
Based on Miff's hint below, this should solve the problem.
plot(1:10, axes=FALSE, ylim=c(0,10), ylab="")
par(yaxp=c(0, 10, 5))
axis(2, lwd=0, col.axis="gray")
par(new=TRUE)
plot(60:50, axes=FALSE, ylim=c(50,60), ylab="")
par(yaxp=c(50, 60, 5))
axis(4, lwd=0, col.axis="gray")
grid(NA, NULL)
grid() gets its locations for gridlines from axTicks(), which in turn uses numbers from par("yaxp"). If you modify this parameter (rather than explicitly passing it to grid), the result will then apply to both the grid drawn and the axis. For example:
plot(1:10, axes=FALSE)
axis(2) #Default 4 sections between ticks
par(yaxp=c(par("yaxp")[1:2], 7)) #Lets have seven instead
axis(4)
grid() #Grid now matches with right rather than left
Obviously similar works for the x axis.
Purpose
Create scatter plot with third dimension and multiple colors.
First:
- 3rd dimension with another scale in contrast to y-axis
- create two colors (this is done using col, see code)
Sketch simulating the purpose:
Code
Two "containers" of points plotted in this way:
plot(1:3, c(3,3,3))
points(1:3, c(2,2,2), col="blue")
Another nice plotting is done by:
#install.packages("hexbin")
library(hexbin)
x <- 1:1000#rnorm(1000)
y <- 1500:501#rnorm(1000)
bin<-hexbin(x, y, xbins=50)
plot(bin, main="Hexagonal Binning")
But I do not know how to use hexbin (I do not understand the functionality). There are needed two colors which I do not know how to generate.
Questions
How to create the 3rd axis with other scaling than the y-axis?
Can I use ´hexbin´ to get the result?
For some reason, using points() does not work, but using plot() does work:
#Set margin on right side to be a bit larger
par(mar = c(5,4.5,4,5))
#Plot first set of data
plot(1:3, rep(3,3), ylim=c(-5,5), xlab="X-Axis", ylab="Y-Axis 1")
#Plot second set of data on different axis.
par(new=T)
plot(1:3, rep(5,3), ylim=c(-10,10), col="blue", xlab="", ylab="", axes=FALSE)
#Add numbers and labels to the second y-axis
mtext("Y-Axis 2",side=4,line=3)
axis(4, ylim=c(-10,10))
I am facing a probably pretty easy-to-solve issue: adding a log- curve to a scatter plot.
I have already created the corresponding model and now only need to add the respective curve/line.
The current model is as follows:
### DATA
SpStats_urbanform <- c (0.3702534,0.457769,0.3069843,0.3468263,0.420108,0.2548158,0.347664,0.4318018,0.3745645,0.3724192,0.4685135,0.2505839,0.1830535,0.3409849,0.1883303,0.4789871,0.3979671)
co2 <- c (6.263937,7.729964,8.39634,8.12979,6.397212,64.755192,7.330138,7.729964,11.058834,7.463414,7.196863,93.377393,27.854284,9.081405,73.483949,12.850917,12.74407)
### Plot initial plot
plot (log10 (1) ~ log10 (1), col = "white", xlab = "PUSHc values",
ylab = "Corrected GHG emissions [t/cap]", xlim =c(0,xaxes),
ylim =c(0,yaxes), axes =F)
axis(1, at=seq(0.05, xaxes, by=0.05), cex.axis=1.1)
axis(2, at=seq(0, yaxes, by=1), cex.axis=1.1 )
### FIT
fit_co2_urbanform <- lm (log10(co2) ~ log10(SpStats_urbanform))
### Add data points (used points() instead of simple plot() bc. of other code parts)
points (co2_cap~SpStats_urbanform, axes = F, cex =1.3)
Now, I've already all the fit_parameters and are still not able to construct the respective fit-curve for co2_cap (y-axis)~ SpStats_urbanform (x-axis)
Can anyone help me finalizing this little piece of code ?
First, if you want to plot in a log-log space, you have to specify it with argument log="xy":
plot (co2~SpStats_urbanform, log="xy")
Then if you want to add your regression line, then use abline:
abline(fit_co2_urbanform)
Edit: If you don't want to plot in a log-log scale then you'll have to translate your equation log10(y)=a*log10(x)+b into y=10^(a*log10(x)+b) and plot it with curve:
f <- coefficients(fit_co2_urbanform)
curve(10^(f[1]+f[2]*log10(x)),ylim=c(0,100))
points(SpStats_urbanform,co2)