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yes I would want to reproduce this kind of graph in R. Apologies for not making this clearer in my question. In this case, I would prefer to plot letters with scores in Group1 only colored in red (the ...

Whats the goal here? Do you want to reproduce this kind of graph? Or highlight some points where x and y differ (by how much?) On the exemple graph, the color scale seems to be based on a calculated ...

Here is another approach that can be considered : #' @export `%||%` <- function(x, y) { if (is.null(x) || length(x) == 0) y else x } #' @export encode_graph_path <- function(path) { path &...

Thanks for the reply! What I really wonder is why is my map "cropped"? I'm supposed to have my raster from 20°S to 60°S, and yet it's limited to 30°S westside of the map. Is it the result of ...

Combining the two methods described in the other solutions (\uxxxx and intToUtf8()) is sometimes necessary or useful with regex, as shown below: I had this grepl() code: last_char <- "l" ;...

Skip creating the legend using render_scalebar(). Instead, we can save the snapshot to a file, create the legend using {ggplot2} and then overlay it on top of the final image; render_snapshot("...

You can bypass the whole manual calculation with the package "qol" like this: library(qol) example <- tibble(Student.ID = c("#001","#002","#003","#004&...

Changing from one projection to another will by definition change some combination of areas/form/distances/directions: https://www.axismaps.com/guide/map-projections I think it's the case that equal ...

Here is another solution. First count the positives in Student.Attended == "Yes". Then, filter those and compute the percentage of entryby19 == "Yes". Finally, join the two results ...

I'm not quite sure I understand if this is the logic you want -- it's showing the number of distinct student IDs by Type (regardless of Attended), and the share of the Attended who had entryby19. ...

As Limey's answer shows, this is to do with the data format used by Survfit. One approach to getting a facet like plot is to create separate plots for each surg and put them together using patchwork. ...

It seems the issue here is not the facetting, but rather the output data produced by survfit2. Consider survfit2(Surv(time, status) ~ sex + surg, data = df_colon) %>% broom::tidy() (Note that I've ...

I don't know exactly what your expected result is, but perhaps this will help you. As I suggest in my first comment, dplyr's group_xxxx family of functions may well be the way to go. In this case, ...

It's a bit hacky, but you could insert spaces using <span></span> = " " <span style='color:transparent;'>xxxxxxxx</span> = " " (8 spaces) and after ...

You can't all projections introduce a distortion in area or shape.

I do not have svn installed, but the R equivalent for Python's % is sprintf(); use it in system(): > filename <- 'a.txt' > ret <- system(sprintf('file %s', filename), intern=TRUE) > ret ...

I implemented the BERT model in R using the R package torch without dependence on Python. The code is available here : https://github.com/ManuHamel/rbert. Here is an example of how the package can be ...

You could patch UpSetR to do this, since this issue was not solved since 2017. library(UpSetR) X <- data.frame( name = 1:100000, food = rep(1, 100000), drink = c(rep(1, 50000), (rep(0, 50000)...

We can modify the grobs manually, after creating the plot. library(UpSetR) p <- upset(df, sets = c('food', 'drink', 'house'), main.bar.color = "blue", show.numbers =...

This is really a data modeling question, not a specific programming question. You should be asking at https://stats.stackexchange.com/ instead.

Maybe this help encoding = "UTF-16"

and it has been answered several times on SO.

To follow up on my original comment and to answer your question above, here is a tidyverse solution using the pivoting algorithm I described earlier. Note that I use d rather than data to avoid ...

Here is a dplyr option: library(dplyr) DF %>% filter(nchar(V1) == max(nchar(V1)))

This is more of a "how can I do it?" question than of an advice one, but here it goes. Instead of changing the data, create a labels vector with the plotmath expressions and add ...

Here's a minimal reproducible example. Since the operative thing here is the text wrapping in the legend title, I expect we can use simpler code and just keep that part. I expect it will work the same ...

@jared_mamrot, yes, that works perfectly! Thank you so much! See below: data <- structure(list(V1 = c(20, 2, 7, 20, 48, 12), V2 = c(1, 48, 23, 56, 28, 11), V3 = c(54, 20, 4, 51, 55, 30), V4 = c(...

Based off of @Limey's answer, I have written 2 sets of code, but neither one provides the satisfactory end result. Set 1 data <- structure(list(V1 = c(20, 2, 7, 20, 48, 12), V2 = c(1, 48, 23, 56, ...

Something like as.data.table(t(apply(t(data), 2, sort))) seems more straightforward; does that work with your actual data Irucka?

The error you are making is in how you are naming the 1st and 2nd arguments, df$AU and df2$UF1. The dollar sign has a special meaning in R, it's an extractor operator. The right way is mae1 <- ...

@Limey, thank you for the suggestion. I'll try that method as well.

After I posted the question, I came up with the following solution: data <- structure(list(V1 = c(20, 2, 7, 20, 48, 12), V2 = c(1, 48, 23, 56, 28, 11), V3 = c(54, 20, 4, 51, 55, 30), V4 = c(5, 28, ...

Pivot into long format Sort Recalculate the ID column Pivot into wide format This will work regardless of the number of rows and number of columns

For the parallel version, foreach + doParallel is the most straightforward drop-in: library(foreach) library(doParallel) cl <- makeCluster(parallel::detectCores() - 1) registerDoParallel(cl) ...

Here is another approach that can be considered. I created a R package rcamembert which is an R based implementation of the Camembert model available on Hugging face using the R package torch. There ...

Use the following pre-script with only recvWindow in the params for the v3 endpoint: const CryptoJS = require('crypto-js'); const timestamp = pm.environment.get("timestamp") const secret = ...

I created a new Rcpp binding for tesseract. The code is available here with the installaction code : https://github.com/ManuHamel/rtesseract. You can use this code to convert a scanned pdf to a ...

Here is another approach that can be considered for entites recognition. You can consider using the R package rmitie which is a Rcpp binding to the mitie library. library(rmitie) > paths <- ...

I created a R binding to the mitie library. The code is here available here : https://github.com/ManuHamel/rmitie. Here is an example of how you can use the library to perform entities recognition : ...

Construct the entire mutate as a string and parse and evaluate it. Note that this still works even if the formula has commas in it because it does not muck with them. For example, consider the ...

within(diamonds, eval(str2expression(sub(",", ";", my_formula2)))) # A tibble: 53,940 × 12 carat cut color clarity depth table price x y z total2 total <...

I've found solution that is static rather than dynamic. It will render the documentation exactly as you wish. But whenever you update the function signatures, you must remember to also update the @...

I created a new Rcpp binding to libpostal : https://github.com/ManuHamel/rlibpostal. There is a code to install libpostal using R which is presented below : run_cmd <- function(cmd, args = ...

If you are open to another package you can do it like this with 'qol': library(qol) diamonds |> if.(color %in% c('E','I'), kpi_a = "A", kpi_b = 1.1) |> else_if.(color %in% c('J'...

I created a new Rcpp binding for tesseract. The code is available here with the installaction code : https://github.com/ManuHamel/rtesseract. You can use this code to convert a scanned pdf to a ...

This is a very old question, but I came across it while researching a similar problem, and wanted to add an answer with some more details that might be helpful to anyone else who Googles across this. ...

I have been able to update a Sharepoint list with the following code : library(AzureGraph) library(jsonlite) `%||%` <- function(x, y) { if (is.null(x) || length(x) == 0) y else x } safe_name <...

Here is another approach that can be used : library(AzureGraph) library(jsonlite) `%||%` <- function(x, y) { if (is.null(x) || length(x) == 0) y else x } safe_name <- function(x) { x <- ...

Wrap a join solution up in a utility function Generalise for the case where NA is a kpi value to be assigned (so we can't rely on is.na or dplyr::coalesce for the default) Retain memory efficiency ...

It’s a bit more nuanced than that. In both cases, your input is being interpreted by mutate() as a single, unnamed argument. In the first example, this still works because mutate() falls back to its ...