similar to: write.xlsx error message

? Thu, 14 Mar 2024 14:12:12 +0000 Subia Thomas OI-US-LIV5 <Thomas.Subia at draexlmaier.com> ?????: > Using write.xlsx to extract data from an Excel file, I get this error > message. > > > Error in .jcall("RJavaTools", "Ljava/lang/Object;", "invokeMethod", > cl, : java.lang.OutOfMemoryError: GC overhead limit exceeded There seems to be a

Colleagues, Using write.xlsx to extract data from an Excel file, I get this error message. Error in .jcall("RJavaTools", "Ljava/lang/Object;", "invokeMethod", cl, : java.lang.OutOfMemoryError: GC overhead limit exceeded I was thinking that this might be a RAM issue but with 16 GB RAM, I wasn't expecting this error message. Any guidance would be

I am trying to read an xlsx spreadsheet (1506 rows, 501columns) all populated but getting the following error: Please advise as to how to get around this issue. > res <- read.xlsx("c:\\BSE_v2.xlsx",1) Error in .jcall("RJavaTools", "Ljava/lang/Object;", "invokeMethod", cl, : java.lang.OutOfMemoryError: Java heap space Here is the session info:

Dear list, I'm running windows xp with R 2.12.0. I'm trying to load a excel spreadsheet into R using the xlsx package. I posted my code below with the error I get. > res <- read.xlsx("Copy of test_excel_input_data.xlsx", 6) Error in .jcall("RJavaTools", "Ljava/lang/Object;", "invokeMethod", cl, : java.lang.IllegalStateException: Cannot get

Hi, I am facing trouble when trying to read large xlsx file into R. please find the code and error below. The file I was trying to read has 36,500 rows X 188 col, ~ 37 MB size. > options( java.parameters = "-Xmx4g" ) > library(xlsx) Loading required package: xlsxjars Loading required package: rJava > cftc =

?s 05:17 de 12/08/2023, Thomas Subia via R-help escreveu: > Colleagues, > > Here is my reproducible code for a graph using geom_smooth > set.seed(55) > scatter_data <- tibble(x_var = runif(100, min = 0, max = 25) > ?????????????????????? ,y_var = log2(x_var) + rnorm(100)) > > library(ggplot2) > library(cowplot) > > ggplot(scatter_data,aes(x=x_var,y=y_var))+

Colleagues, Here is my reproducible code for a graph using geom_smooth set.seed(55) scatter_data <- tibble(x_var = runif(100, min = 0, max = 25) ?????????????????????? ,y_var = log2(x_var) + rnorm(100)) library(ggplot2) library(cowplot) ggplot(scatter_data,aes(x=x_var,y=y_var))+ ? geom_point()+ ? geom_smooth(se=TRUE,fill="blue",color="black",linetype="dashed")+

As you apparently haven't received any responses yet, I'll try to suggest something useful. However, I have absolutely zero experience with plotly, so this is just from general principles and reading the plot_ly Help file, which says for the "..." arguments: "Arguments (i.e., attributes) passed along to the trace type. See schema() for a list of acceptable attributes for a

G'day Thomas, On Sat, 12 Aug 2023 04:17:42 +0000 (UTC) Thomas Subia via R-help <r-help at r-project.org> wrote: > Here is my reproducible code for a graph using geom_smooth The call "library(tidyverse)" was missing. :) > I'd like to add a black boundary around the shaded area. I suspect > this can be done with geom_ribbon but I cannot figure this out. Some >

plotly is _not_ associated with posit. I think you are unlikely to find expertise with plotly in their forums. You might find help at stackoverflow.com. On July 21, 2023 1:40:49 PM PDT, Bert Gunter <bgunter.4567 at gmail.com> wrote: >As you apparently haven't received any responses yet, I'll try to >suggest something useful. However, I have absolutely zero experience >with

Colleagues Here is my reproducible code plot_ly( ? domain = list(x = c(0, 1), y = c(0, 1)), ? value = 2874, ? title = list(text = "Generic"), ? type = "indicator", ? mode = "gauge+number+delta", ? delta = list(reference = 4800), ? gauge = list( ??? axis =list(range = list(NULL, 5000)), ??? steps = list( ??? list(range = c(0, 4800), color = "white"), ???

Colleagues, Many of my colleagues come to me for a recommendation for statistical software. Since I am an R user, that's my typical answer. Some colleagues of mine refuse to use it because of its steep learning curve and lack of a GUI. They wanted a statistical software that's free and that had a GUI. I recently learned about JASP. See https://jasp-stats.org/ for more details This may be

What do you mean "Rounded"? What do you expect, what do you get instead? ? > On Jul 22, 2023, at 10:40, Thomas Subia via R-help <r-help at r-project.org> wrote: > > Colleagues, > Thanks for the update. > My colleagues at work have run this script but the resulting graph output for value is rounded. How can one turn this annoying feature off? > I've

ChatGPT-4: ------ Query: ---------------------------------- Thank you. The `value` in the code example is 2874. The plot shows a large number at the center and a smaller value computed as a delta relative to the `reference` of 4800. But the large value is given as 2870, and the smaller value is given as -1930 i.e. both values are rounded. Can I control the precision of these two numbers?

Thanks for writing this great piece of code. x = rnorm(100) boxplot(x) # you shouldn't see any outliers here although sometimes yow will # lets add some outliers intentionally x = c(21, 20, 25, x) # now 10, 15 and 20 are outliers myboxplot <- boxplot(x) # now you should see your three outliers myboxplot$out # it will print the values of the outliers How does one amend

Colleagues, Here is my reproducible code. library(plotly) t <- list( ? family = "Arial", ? size = 12, ? color = "black", ? face="bold") t3 <- list( ? family = "Arial", ? size = 12, ? color = "black", ? face="bold") t5 <- list( ? family = "Arial", ? size = 12, ? color = "black", ? face="bold")

Dear Rxperts, Through Windows OS, I created shortcuts (paste as shortcut) to excel spreadsheets ( with "xlsx" as the file extension). I wasn't able to read the shortcuts through R and using "read" functions of "xlsx" package. exf <- "a1.xlsx.lnk" > read.xlsx(exf,1) Error in .jcall("RJavaTools", "Ljava/lang/Object;",

Default level = 0.95. Does this mean +/- 0.025 from estimate? [[alternative HTML version deleted]]

Hey everyone, Thanks for all the input. It's happening again. This time for the packages "DBI", "parallelly", "segmented", "survival", "V8". So, RStudio shows updates for those and updating them via RStudio leads to this output: ``` > install.packages(c("DBI", "parallelly", "segmented", "survival",

I?ve got an Excel workbook with about 30 worksheets. Each worksheet has 10000 rows of data over 30 columns. I?d like to read the data from each worksheet into a dataframe or matrix in R for processing. Normally, I use read.csv when interacting with Excel but I?d rather manipulate a multisheet workbook directly than set about splitting the original workbook and saving down each part as a csv.