I am trying to plot in base R with the regular plot() fcn. However, when passing a vector of which pch to use, it will not plot the pch, it will only plot the number '1' instead of the shape of the pch I am calling.
Generating some data (my real data has over 400 rows for both the loads and meta objects:
loads <- data.frame(PC1 = c(11.32, 13.18, 12.82, 24.70), PC2 = c(-23.05, -24.71, -20.28, 10.09))
row.names(loads) <- c("100_A", "100_B", "100_C", "100_Orig")
meta <- data.frame(pch = c(17, 17, 17, 16), color = c("red", "red", "blue", "blue"))
row.names(meta) <- row.names(loads)
To plot:
x <- loads[, 1] ; y <- loads[, 2]
pch <- meta$pch
col <- meta$color
plot(x, y,
col = col, pch = pch, cex = 2, lwd = 4,
xlab = paste("PC1"), ylab = paste("PC2"))
Now, this will graph the correct color (red and blue) in the order I have them in the vector; the real issue becomes the plotting the pch. Instead of a circle (pch = 16) or a triangle (pch = 17) it's plotting a red or blue number 1 instead! I have included a pic of what my data is actually doing.
Thinking that the pch vector I am passing cannot have quotes around it, I have removed the quotes with the following code:
pch <- meta$pch
pch <-as.vector(noquote(pch))
class(pch)
[1] "character"
However, this generates the same results (getting a number 1 plotted). Interestingly, when use this code, it works fine. It turns all my colors to blue, and I get nice blue circles.
plot(x, y,
col = "blue, pch = 16, cex = 2, lwd = 4,
xlab = paste("PC1"), ylab = paste("PC2"))
This tells me that the plot function isn't recognizing my long vector composed of pch 16 and 17's mixed in.
Alternatively, if I use the rep function to generate my pch vector, a test shows it works fine. But I have over 400 rows. I cannot manually type rep for each pch. I will be here for eternity typing that out.
Any suggestions on what to do?????
Try defining the col as character and the pch as numeric like this:
plot(x, y,
col = as.character(col), pch = as.numeric(pch), cex = 2, lwd = 4,
xlab = paste("PC1"), ylab = paste("PC2"))
Related
I am doing quarterly analysis, for which I want to plot a graph. To maintain continuity on x axis I have turned quarters into factors. But then when I am using plot function and trying to color it red, the col argument is not working.
An example:
quarterly_analysis <- data.frame(Quarter = as.factor(c(2020.1,2020.2,2020.3,2020.4,2021.1,2021.2,2021.3,2021.4)),
AvgDefault = as.numeric(c(0.24,0.27,0.17,0.35,0.32,0.42,0.38,0.40)))
plot(quarterly_analysis, col="red")
But I am getting the graph in black color as shown below:
Converting it to a factor is not ideal to plot unless you have multiple values for each factor - it tries to plot a box plot-style plot. For example, with 10 observations in the same factor, the col = "red" color shows up as the fill:
set.seed(123)
fact_example <- data.frame(factvar = as.factor(rep(LETTERS[1:3], 10)),
numvar = runif(30))
plot(fact_example$factvar, fact_example$numvar,
col = "red")
With only one observation for each factor, this is not ideal because it is just showing you the line that the box plot would make.
You could use border = "red:
plot(quarterly_analysis$Quarter,
quarterly_analysis$AvgDefault, border="red")
Or if you want more flexibility, you can plot it numerically and do a little tweaking for more control (i.e., can change the pch, or make it a line graph):
# make numeric x values to plot
x_vals <- as.numeric(substr(quarterly_analysis$Quarter,1,4)) + rep(seq(0, 1, length.out = 4))
par(mfrow=c(1,3))
plot(x_vals,
quarterly_analysis$AvgDefault, col="red",
pch = 7, main = "Square Symbol", axes = FALSE)
axis(1, at = x_vals,
labels = quarterly_analysis$Quarter)
axis(2)
plot(x_vals,
quarterly_analysis$AvgDefault, col="red",
type = "l", main = "Line graph", axes = FALSE)
axis(1, at = x_vals,
labels = quarterly_analysis$Quarter)
axis(2)
plot(x_vals,
quarterly_analysis$AvgDefault, col="red",
type = "b", pch = 7, main = "Both", axes = FALSE)
axis(1, at = x_vals,
labels = quarterly_analysis$Quarter)
axis(2)
Data
set.seed(123)
quarterly_analysis <- data.frame(Quarter = as.factor(paste0(2019:2022,
rep(c(".1", ".2", ".3", ".4"),
each = 4))),
AvgDefault = runif(16))
quarterly_analysis <- quarterly_analysis[order(quarterly_analysis$Quarter),]
QUESTION: I am building a triplot for the results of my distance-based RDA in R, library(vegan). I can get a triplot to build, but can't figure out how to make the colours of my sites different based on their location. Code below.
#running the db-RDA
spe.rda.signif=capscale(species~canopy+gmpatch+site+year+Condition(pair), data=env, dist="bray")
#extract % explained by first 2 axes
perc <- round(100*(summary(spe.rda.signif)$cont$importance[2, 1:2]), 2)
#extract scores (coordinates in RDA space)
sc_si <- scores(spe.rda.signif, display="sites", choices=c(1,2), scaling=1)
sc_sp <- scores(spe.rda.signif, display="species", choices=c(1,2), scaling=1)
sc_bp <- scores(spe.rda.signif, display="bp", choices=c(1, 2), scaling=1)
#These are my location or site names that I want to use to define the colours of my points
site_names <-env$site
site_names
#set up blank plot with scaling, axes, and labels
plot(spe.rda.signif,
scaling = 1,
type = "none",
frame = FALSE,
xlim = c(-1,1),
ylim = c(-1,1),
main = "Triplot db-RDA - scaling 1",
xlab = paste0("db-RDA1 (", perc[1], "%)"),
ylab = paste0("db-RDA2 (", perc[2], "%)")
)
#add points for site scores - these are the ones that I want to be two different colours based on the labels in the original data, i.e., env$site or site_names defined above. I have copied the current state of the graph
points(sc_si,
pch = 21, # set shape (here, circle with a fill colour)
col = "black", # outline colour
bg = "steelblue", # fill colour
cex = 1.2) # size
Current graph
I am able to add species names and arrows for environmental predictors, but am just stuck on how to change the colour of the site points to reflect their location (I have two locations defined in my original data). I can get them labelled with text, but that is messy.
Any help appreciated!
I have tried separating shape or colour of point by site_name, but no luck.
If you only have a few groups (in your case, two), you could make the group a factor (within the plot call). In R, factors are represented as an integer "behind the scenes" - you can represent up to 8 colors in base R using a simple integer:
set.seed(123)
df <- data.frame(xvals = runif(100),
yvals = runif(100),
group = sample(c("A", "B"), 100, replace = TRUE))
plot(df[1:2], pch = 21, bg = as.factor(df$group),
bty = "n", xlim = c(-1, 2), ylim = c(-1, 2))
legend("topright", unique(df$group), pch = 21,
pt.bg = unique(as.factor(df$group)), bty = "n")
If you have more than 8 groups, or if you would like to define your own colors, you can simply create a vector of colors the length of your groups and still use the same factor method, though with a few slight tweaks:
# data with 10 groups
set.seed(123)
df <- data.frame(xvals = runif(100),
yvals = runif(100),
group = sample(LETTERS[1:10], 100, replace = TRUE))
# 10 group colors
ccols <- c("red", "orange", "blue", "steelblue", "maroon",
"purple", "green", "lightgreen", "salmon", "yellow")
plot(df[1:2], pch = 21, bg = ccols[as.factor(df$group)],
bty = "n", xlim = c(-1, 2), ylim = c(-1, 2))
legend("topright", unique(df$group), pch = 21,
pt.bg = ccols[unique(as.factor(df$group))], bty = "n")
For pch just a slight tweak to wrap it in as.numeric:
pchh <- c(21, 22)
ccols <- c("slateblue", "maroon")
plot(df[1:2], pch = pchh[as.numeric(as.factor(df$group))], bg = ccols[as.factor(df$group)],
bty = "n", xlim = c(-1, 2), ylim = c(-1, 2))
legend("topright", unique(df$group),
pch = pchh[unique(as.numeric(as.factor(df$group)))],
pt.bg = ccols[unique(as.factor(df$group))], bty = "n")
I want to assign the means of x and y to a scatterplot in R without ggplot, just basic R. However, in the way I try (using abline), it does not illustrate the lines in the plot. I already had to do another task earlier, hence the slightly longer code.
I tried using abline for either x and y to assign a horizontal and a vertical dashed line to the plot. The result was that the plot inclusive the blue dot is illustrated, but the means don't show up.
plot(x, y, axes = TRUE, pch = 16, xlim = c(40,120)
points(46, 150, col = "blue", pch = 16), main = abline(v = mean(y), lty = 2, lwd = 4)
abline(h = mean(x), lty = 2, lwd = 4))
You have a few syntax errors in the supplied code, but ultimately I think your problem is that you are trying to plot a vertical line at the mean y value when it should be at the mean x value, and a horizontal line at the mean x value, when it should be at the mean y value:
set.seed(1)
x <- rnorm(10, 47, 5)
y <- rnorm(10, 150, 5)
plot(x, y, axes = T, pch = 16)
points(46, 150, col = "blue", pch = 16)
abline(v = mean(x), lty = 2, lwd = 4)
abline(h = mean(y), lty = 2, lwd = 4)
Created on 2022-10-30 with reprex v2.0.2
I have file from that wanted plot the smoothscatterplot using R. plot must have the dots, diagonal axis and a curve for that I have formula, I am creating smoothscatterplot but not able plot diagonal and curve any suggestion and help will be appreciated
https://drive.google.com/file/d/1KknqYcRBCGm8Xrj1XKh3mE7rb7LK9iny/view?usp=sharing
what I tried
diagonal axis
df$P0+df$P2 =1
curve
p2 = (√df$P0 − 1)^2
df=read.table("scale_out",sep='\t', header=TRUE)
df = data.frame(df)
smoothScatter(df$P0,df$P2, cex=10)
what I got
what I want
Thank you
The data doesn't seem to contain what you think it contains.
For example, if we just do a straight plot of P0 and P2, we get this:
plot(df$P0, df$P2, pch = 18, cex = 0.5)
The desired plot that you show in your question suggests that this should be a scatter plot of noisy data, but it isn't. If we plot all the numeric variables in your data frame against each other, we get this:
The only plot here that looks like a scatter plot of the correct shape is P0 versus B.prop.
Assuming that this is what you want, you can create the desired plot like this:
smoothScatter(df$P0, df$B.prop, cex = 2, xlab = "P0", ylab = "P2")
curve((sqrt(x) - 1)^2, 0, 1, lty = 2, lwd = 5, col = "red", add = TRUE)
lines(0:1, 1:0, lty = 2, lwd = 5, col = "deepskyblue4")
legend(0.35, 1, c("Coordination", "Independence"),
col = c("deepskyblue4", "red"), bg = "#FFFFFFAA",
lty = 2, lwd = 5, box.col = "#FFFFFF00")
I am using R for plotting. When my graph plots the legend appears where I want it to be but the colors are missing. mtcars 2 is a modified version of mtcars (one of the pre-loaded data sets) that adds a model and country of origin to the data set. mtcars.pca is what I named my redundance analysis (rda function under vegan), and mtcars.clust is titled for hierarchical clustering of the continuous factors of mtcars (hclust function of vegan) Below is the code I am using with mtcars2.
pca.fig = ordiplot(mtcars.pca, type = "none", las=1, xlim=c(-15,15), ylim = c(-20,10))
points(pca.fig, "sites", pch = 19, col = "green", select = mtcars2$origin =="domestic")
points(pca.fig, "sites", pch = 19, col = "blue", select = mtcars2$origin =="foreign")
ordiellipse(mtcars.pca, mtcars2$origin, conf = 0.95, label = FALSE)
ordicluster(mtcars.pca, mtcars.clust, col = "gray")
legend("bottomright", title="Car Origin", c("domestic", "foreign"), col = "origin")
You need to specify a vector of colours in legend and also a pch:
library("vegan")
data(dune, dune.env)
ord <- rda(dune)
plot(ord, type = "n")
cols <- c("red","blue","green")
points(ord, col = cols[dune.env$Use], pch = 19)
legend("bottomright", legend = levels(dune.env$Use), bty = "n",
col = cols, pch = 19)
If you don't add pch but just use col = cols legend() doesn't display any points. Because you used pch = 19 in your points() calls, use the same in the legend() call.
Also, note how to plot points of different colours in a single pass. I have some examples and explanation that go through the indexing trick I used in my code above to achieve this in a blog post of mine from a few years ago: http://www.fromthebottomoftheheap.net/2012/04/11/customising-vegans-ordination-plots/
I came to this question having the next problem in xts object:
I wanted to plot all time-series in xts object with legend. Moreover, there were around 20.
I used (wrong):
plot(returns_xts)
addLegend(...)
Correct version:
plot(returns_xts, legend.loc = "bottomright", col=1:20, lty = 1)
There is legend.loc parameter
col = 1:20 generates colors for you
Result: