I want to install the package impactr from github. Following the guideline stated by the package developer (https://rdrr.io/github/kamclean/impactr/f/vignettes/vignette_2_extract.Rmd), I repeatedly get the following error.
devtools::install_github("kamclean/impactr")
my_dois <- c("10.1111/j.1365-2486.2008.01617.x","10.1007/s10533-011-9655-2")
out_doi <- impactr::extract_doi(doi = my_dois, get_impact = TRUE)
Error: 'extract_doi' is not an exported object from 'namespace:impactr'
What is the problem? Any help is highly appreciated!
Related
I'm trying to run Data Exploration in my R Studio, version 1.3.959 on my windows10.I wrote following test code
if (!require(devtools)) install.packages("devtools")
devtools::install_github("boxuancui/DataExplorer", ref = "develop")
library(DataExplorer)
diabetes_data <- read.csv("https://raw.githubusercontent.com/jbrownlee/Datasets/master/pima-indians-diabetes.csv", header = FALSE)
names(diabetes_data) <- c("number_of_times_pregnant", "plasma_glucose_conc", "diastolic_bp", "triceps_skinfold_thickness", "two_hr_serum_insulin", "bmi", "diabetes_pedigree_function", "age", "label")
# create report
create_report(diabetes_data)
But I'm getting error message
Error: 'set_envvar' is not an exported object from 'namespace:xfun'
Can you please help me to resolve the issue?
I just had this problem and updating my packages solved the issue, especially the package xfun from which set_envvar is originated.
I am trying to do GO term enrichment analysis in R. I followed this tutorial. When I get to this step...
catdb <- makeCATdb(myfile="data/GO/GOannotationsBiomart_mod.txt", lib=NULL, org="", colno=c(1,2,3), idconv=NULL)
...I get this error:
Error in makeCATdb(myfile = "GOannotationsBiomark_mod.txt", lib = "NULL", :
could not find function "makeCATdb"
I tried installing systemPipeRdata and got the same error. Please, how do I install this function? Thanks!
I figured it out! systemPipeR was not properly installed in RStudio. For best results, please follow the instructions from the Bioconductor website.
if (!requireNamespace("BiocManager", quietly=TRUE))
install.packages("BiocManager")
BiocManager::install("systemPipeR")
Usually I'm using the openxlsx package and the write.xlsx function when exporting R data frames into .xlsx-files. Since yesterday - probably after I was using the package XLConnect - something got messed up and the write.xlsx function doesn't work anymore. This is the error I get:
Error in zipr(zipfile = tmpFile, include_directories = FALSE, files = list.files(path = tmpDir, :
unused argument (include_directories = FALSE)
Unfortunately, I don't understand what this error means. Thanks for any helpful advice.
Edit: The function works when I use an older openxlsx version (4.1.0).
I was getting the same error.
I think the problem is with dependencies of openxlsx. There is a "zipR" package that might be picked up when you install openxlsx, while the actual dependency is zip package:
https://cran.r-project.org/web/packages/zip/index.html
https://cran.r-project.org/web/packages/zipR/zipR.pdf
I installed "zip" along with openxlsx and I don't get the error anymore.
I do not really understand the error message here. My computer does not allow me to save files to "c:/". So, if remove "c:/" part, it works fine, to save the file to the current working directory.
library(openxlsx)
df <- data.frame('x' = c(1,2,3),
'y' = c(3,2,1))
openxlsx::write.xlsx(df, "test.xlsx")
You would also try another package: writexl
writexl::write_xlsx(df, "text5.xlsx")`
This works on my machine.
I'm quite new to R and I got an assignment that includes a sourcecode.
Part of the source code includes the following line:
library(preprocessCore)
Then I have in my source code a definition of the following function:
quantile.normalize.raw.gtex <- function(edata.mat)
{
norm_edata = normalize.quantiles(as.matrix(edata.mat))
rownames(norm_edata) = rownames(edata.mat)
colnames(norm_edata) = colnames(edata.mat)
return(norm_edata)
}
Finally, I have an object being initialized to the output of this function, after sending a predefined parameter:
tissue.edata.qn = quantile.normalize.raw.gtex(tissue.edata)
From what I understand, the library function is supposed to include the function normalize.quantiles, which is called in the function that is defined in my source code.
However, when I run the line library(preprocessCore) I get the following error:
Error in library(preprocessCore) :
there is no package called ‘preprocessCore’
I also tried to run the rest of the code and got the error:
Error in normalize.quantiles(as.matrix(edata.mat)) :
could not find function "normalize.quantiles"
I looked for the preprocessCore online and eventually I tried to write install.packages("preprocessCore"), but I got a warning message that this package is only available in version 3.6.0 of R, even though I checked and this is the version that I have.
If somebody has any idea what the problem is, I will appreciate your help.
Thanks in advance
The preprocessCore package is available in Bioconductor. So, to install it, you need the following lines:
source("http://bioconductor.org/biocLite.R")
biocLite("preprocessCore")
After that, you can load the package using library(preprocessCore)
Hope it helps.
I tried to use get_rollit_source from the RcppRoll package as follows:
library(RcppRoll)
get_rollit_source(roll_max,edit=TRUE,RStudio=TRUE)
I get an error:
Error in get("outFile", envir = environment(fun)) :
object 'outFile' not found
I tried
outFile="C:/myDir/Test.cpp"
get_rollit_source(roll_max,edit=TRUE,RStudio=FALSE,outFile=outFile)
I get an error:
Error in get_rollit_source(roll_max, edit = TRUE, RStudio = FALSE, outFile = outFile) :
File does not exist!
How can fix this issue?
I noticed that the RcppRoll folder in the R library doesn't contain any src directory. Should I download it?
get_rollit_source only works for 'custom' functions. For things baked into the package, you could just download + read the source code (you can download the source tarball here, or go to the GitHub repo).
Anyway, something like the following should work:
rolling_sqsum <- rollit(final_trans = "x * x")
get_rollit_source(rolling_sqsum)
(I wrote this package quite a while back when I was still learning R / Rcpp so there are definitely some rough edges...)