For a very large table, I would like to automatically have a barplot for each column, which is then also saved as a png.
The title can simply be the column title and the description of the columns correspond to the column variables. So no individual edit of the barplots is necessary
I have already created barplots by hand and experimented with the "lapply" command without success.
Here the barplot code
png(file="a_x.png", width=600, height=400)
barplot(table(Example$a_x), main = "a_x")
dev.off()
You can do a simple for loop and paste0 for the file name:
Data
df <- data.frame(a_x = sample(c("Yes","No"), 100, prob = c(0.10,0.90), replace = TRUE),
b_x = sample(c("Yes","No"), 100, prob = c(0.10,0.90), replace = TRUE),
c_x = sample(c("Yes","No"), 100, prob = c(0.10,0.90), replace = TRUE))
Code
for(i in colnames(df)){
png(file = paste0(i,".png"), width = 600, height = 400)
barplot(table(df[i]), main = i)
dev.off()
}
Related
I have generated several Utilisation Distributions (UD) with AdehabitatHR and stored them as Geotiffs. I am now using the same UDs with the Lattice package to generate some maps and saving them to a high-res tiff image with LZW compression. Problem is that I have literally hundreds of maps to make, save and name. Is there a way automatically do this once i have loaded all the necessary files from a directory? Each one of my UDs has the following structure of the filename "UD_resolution_species_area_year_season. tif" and in the final name I give to my map I would like to keep the same structure (or entire filename) but add the prefix "blablabla_" e.g. "blablabla_UD_resolution_species_area_year_season.tiff". The image also include a main name, a capital letter, which should also change.
At the moment I am using the following:
rlist = list.files(getwd(), pattern = "tif$", full.names = FALSE)
for (i in rlist) {
assign(unlist(strsplit(i, "[.]"))[1], raster(i))
}
shplist = list.files(getwd(), pattern = "shp$", full.names = FALSE)
for (i in shplist) {
assign(unlist(strsplit(i, "[.]"))[1], readOGR(i))
}
UD <- 'UD_resolution_species_area_year_season'
ext <- extent(UD) + 0.3 # set the extent for the plot
aa <-
quantile(UD,
probs = c(0.25, 0.75),
type = 8,
names = TRUE)
my.at <- c(aa[1], aa[2])
my.at <- round(my.at, 3)
maxval <- maxValue(UD)
tiff(
"C:/myworkingdirectory/maps/blablabla_UD_resolution_species_area_year_season.tiff",
res = 600,
compression = "lzw",
width = 15,
height = 15,
units = "cm"
)
levelplot(
UD,
xlab = "",
ylab = "",
xlim = c(ext[1], ext[2]),
ylim = c(ext[3], ext[4]),
margin = FALSE,
contour = FALSE,
col.regions = viridis(1000),
colorkey = list(at = seq(0, maxval)),
main = "A",
maxpixels = 2e5
) + latticeExtra::layer(sp.polygons(Land, fill = "grey50", col = NA)) + contourplot(
`UD`,
at = my.at[1],
labels = FALSE,
margin = FALSE,
lty = 2,
col = "orange",
pretty = TRUE
) + contourplot(
UD,
at = my.at[2],
labels = FALSE,
margin = FALSE,
lty = 2,
col = "red",
pretty = TRUE,
)
dev.off()
It is a common beginners mistake to use assign. Do not use it, it creates the type of trouble you are now facing. In stead, you can make lists and/or use a loop.
Also what you are asking is basic R stuff, but you are complicating the question with adding lots of irrelevant detail about setting the extent, and levelplot. It is better to learn about doing these basic things by removing the clutter and focus on a simple case first. That is also how you should write questions for this forum.
In essence you have a bunch of files you want to process. Below I show how you can loop over a vector of the names and then loop and do what you need to do in that loop.
library(raster)
rastfiles <- list.files(pattern = "tif$", full.names=TRUE)
outputfiles <- file.path("output/path", paste0("prefix_", basename(rastfiles)))
for (i in 1:length(rastfiles))
r <- raster(rastfiles[i])
png(outputfiles[i])
plot(r)
dev.off()
}
You can also first read all the files into a list
rastfiles <- list.files(pattern = "tif$", full.names=TRUE)
rlist <- lapply(rastfiles, raster)
names(rlist) <- gsub(".tif$", "", basename(rastfiles))
rastfiles <- list.files(pattern = "shp$", full.names=TRUE)
slist <- lapply(shpfiles, readOGR)
names(slist) <- gsub(".shp$", "", basename(shpfiles))
And perhaps create a vector of output filenames
outputtif <- file.path("output/dir", basename(rastfiles))
And then loop over the items in the list, or the output filenames
I am using following function to generate stars(), one the visualization technique for multivariate data.
library(randomNames)
set.seed(3)
Name = randomNames(50, which.names = 'first')
height = sample(160:180, 50, replace = TRUE)
weight = sample(45:85, 50, replace = TRUE)
tumour_size = runif(50, 0,1)
df = data.frame(Name, height, weight, tumour_size, rnorm(50, 10,3))
stars(df,labels = Name)
But, I get the output like this:
How to align the names exactly below the stars?
Use option flip.labels=FALSE.
stars(df, labels = Name, flip.labels = FALSE)
Result
I want to skip a empty panel using lattice package in R.
set.seed(1)
df1 <- data.frame("treatment" = c(rep("A",16),rep("B",16),rep("C",16)),
"disease_type" = c(rep("1",8),rep("2",8)),
"days_after_application" = rep(c(rep("10-24",4),rep("24-48",4)),6),
"severity" = rnorm(48, mean = 80, sd = 5))
df1[(df1$disease_type == "2" & df1$days_after_application == "24-48"),"severity"] <- NA
library(lattice)
figure1 <- bwplot(treatment~severity|days_after_application+disease_type,
data = df1,layout = c(2,2),
strip = strip.custom(strip.names = TRUE))
jpeg("figure1.jpeg")
print(figure1)
dev.off()
Here is what I get
My question is how I can remove/skip empty panel in the top right WITHOUT changing layout?
I have tried following code. However, it doesn't work.
figure2 <- bwplot(treatment~severity|days_after_application+disease_type,
data = df1,layout = c(2,2),
strip = strip.custom(strip.names = TRUE),
skip = c(FALSE,FALSE,FALSE,TRUE))
jpeg("figure2.jpeg")
print(figure2)
dev.off()
Here is what I got
I also tried following codes. But it is not what I want since I do want 2 levels strips.
df1[(df1$disease_type == "2" & df1$days_after_application == "24-48"),] <- NA
bwplot(treatment~severity|interaction(days_after_application,disease_type),
data = df1,layout = c(2,2),
strip = strip.custom(strip.names = TRUE))
Thank you!
Get help from a Professor in Temple University.
Here is his solution:
figure4 <- bwplot(treatment~severity|days_after_application+disease_type,
data = df1,layout = c(2,2),
strip = strip.custom(strip.names = TRUE),
skip = c(FALSE,FALSE,FALSE,TRUE),
scales=list(alternating=FALSE), ## keep x-scale on bottom
between=list(x=1, y=1)) ## space between panels
pdf("figure4%03d.pdf",onefile = FALSE) ## force two pages in file.
print(figure4)
dev.off()
I often create large plots in RStudio which I save to PDF but would also like to partly show in the PDF knitr report.
Is there a way to create the full object then cut a piece (ideally top left corner) and include that second picture in the PDF report?
as example, a pheatmap code that produces a plot with 56 cols and 100's of rows. I would like to show only the left-top-most 10col and 10 rows but if I sample the input data, I obviously get another plot due to the clustering being done on different data. Also, I would love a solution applicable to any plot types (not only pheatmap).
drows <- "euclidean"
dcols <- "euclidean"
clustmet <- "complete"
col.pal <- c("lightgrey","blue")
main.title <- paste("Variant (freq>", minfreq, "%) in all samples", sep="")
hm.parameters.maj <- list(hm.maj.data,
color = col.pal,
fontsize = 10,
cellwidth = 14,
cellheight = 14,
scale = "none",
treeheight_row = 200,
kmeans_k = NA,
show_rownames = T,
show_colnames = T,
main = main.title,
clustering_method = clustmet,
cluster_rows = TRUE,
cluster_cols = FALSE,
clustering_distance_rows = drows,
clustering_distance_cols = dcols,
legend=FALSE)
# To draw the heatmap on screen (comment-out if you run the script from terminal)
do.call("pheatmap", hm.parameters.maj)
# To draw to file (you may want to adapt the info(header(vcf))sizes)
outfile <- paste("major-variants_heatmap_(freq>", minfreq, ")_", drows, ".pdf", sep="")
do.call("pheatmap", c(hm.parameters.maj, filename=outfile, width=24, height=35))
Thanks in advance
Stephane
I am trying to create the simplest of scatter charts using dimple and rCharts. I am curious if there is something I mis-understand about the 'scatter' type. When I run this code, the y-axis values are off by factors of ten or larger--almost as if the scatter chart is acting as a stacked bar chart instead of a simple scatter plot. The sample data below mimics my data exactly.
testdat1 <- data.frame(Recommend = sample(60:90, 200, replace = T), Quiet = sample(20:60, 200, replace = T),
Owner = as.factor(rep(c(1,2), 100)))
summary(testdat1) # no values exceed 90
dtest <- dPlot(Recommend ~ Quiet, groups = 'Owner', data = testdat1, type = 'scatter')
dtest # plotted y-values reach upwards of 450
Any thoughts?
See comment but answer might be accomplished through this block of code:
require(rCharts)
testdat1 <- data.frame(Recommend = sample(60:90, 200, replace = T), Quiet = sample(20:60, 200, replace = T),
Owner = as.factor(rep(c(1,2), 100)))
summary(testdat1) # no values exceed 90
dtest <- dPlot(Recommend ~ Quiet, groups = 'Owner', data = testdat1, type = 'bubble')
#will aggregate as avg by default
dtest$xAxis(type="addMeasureAxis")
dtest
#add x,y, and grouping so now only will aggregate where x,y,and group is exact same
#if still a problem, could a unique id and group on that
dtest$params$groups <- c('Recommend','Quiet','Owner')
dtest # plotted y-values reach upwards of 450