saveWorkbook() function in XLConnect saves the workbook and the changes and updated calculations are visible in the excel file but not on R (because it has a formula not accepted by the apache poi)
However, to view the cell I save the file to disk and call it using another function. But when I call the same file again the calculated fields still show the old values. I don't want to save the excel file every time I make a change in the workbook.
Would you know a workaround to be able to call the new values without manually saving excel?
Code -
options(java.parameters = "-Xmx1024m")
library(rJava)
library(XLConnect)
wb = loadWorkbook(file.choose(), create = TRUE)
readWorksheet(wb,16, region = 'D25:D26')
writeWorksheet(wb,-.45,sheet = 16,startRow = 25,startCol = 4)
setForceFormulaRecalculation(wb,sheet = 16, TRUE)
saveWorkbook(wb)
detach("package:XLConnect", unload=TRUE)
detach("package:XLConnectJars", unload=TRUE)
library(xlsx)
y = read.xlsx(file.choose(), sheetIndex = 16)
So the Excel file on the system shows the changes corresponding to the new -.45 value but when I read the file again, the calculated values are the old values and not the new ones. This gets fixed if I save the file manually.
I believe the command you are using is correct but maybe some small modifications would make this work.
I think you could try placing the needed calculations in a different sheet in excel and treat the data you inserted as a dependency for those calculations in the new sheet.
Then read it in as a fresh workbook and call the new sheet. I think that will you the output you need.
setForceFormulaRecalculation(wb, sheet = "*", TRUE)
I would use this command to force all sheets to recalculate instead.
Hope that helps!
I am using "openxlsx" package to read and write excel files. I have a fixed file with a sheet called "Data" which is used by formulas in other sheets. I want to update this Data sheet without touching the other.
I am trying the following code:
write.xlsx(x = Rev_4, file = "Revenue.xlsx", sheetName="Data")
But this erases the excel file and creates a new one with just the new data in the "Data" sheet while all else gets deleted. Any Advice?
Try this:
wb <- loadWorkbook("Revenue.xlsx")
writeData(wb, sheet = "Data", Rev_4, colNames = F)
saveWorkbook(wb,"Revenue.xlsx",overwrite = T)
You need to load the complete workbook, then modify its data and then save it to disk. With writeData you can also specify the starting row and column. And you could also modify other sections before saving to disk.
I've found this package. It depends on openxlsx and helps to insert many sheets on a xlsx file. Maybe it makes easier:
Package documentation
library(xlsx2dfs)
# However, be careful, the function xlsx2dfs assumes
# that all sheets contain simple tables. If that is not the case,
# use the accepted answer!
dfs <- xlsx2dfs("Revenue.xlsx") # all sheets of file as list of dfs
dfs["Data"] <- Rev_4 # replace df of sheet "Data" by updated df Rev_4
dfs2xlsx(dfs, "Revenue.xlsx") # this overwrites the existing file! cave!
I was trying to read an excel spreadsheet into R data frame. However, some of the columns have formulas or are linked to other external spreadsheets. Whenever I read the spreadsheet into R, there are always many cells becomes NA. Is there a good way to fix this problem so that I can get the original value of those cells?
The R script I used to do the import is like the following:
options(java.parameters = "-Xmx8g")
library(XLConnect)
# Step 1 import the "raw" tab
path_cost = "..."
wb = loadWorkbook(...)
raw = readWorksheet(wb, sheet = '...', header = TRUE, useCachedValues = FALSE)
UPDATE: read_excel from the readxl package looks like a better solution. It's very fast (0.14 sec in the 1400 x 6 file I mentioned in the comments) and it evaluates formulas before import. It doesn't use java, so no need to set any java options.
# sheet can be a string (name of sheet) or integer (position of sheet)
raw = read_excel(file, sheet=sheet)
For more information and examples, see the short vignette.
ORIGINAL ANSWER: Try read.xlsx from the xlsx package. The help file implies that by default it evaluates formulas before importing (see the keepFormulas parameter). I checked this on a small test file and it worked for me. Formula results were imported correctly, including formulas that depend on other sheets in the same workbook and formulas that depend on other workbooks in the same directory.
One caveat: If an externally linked sheet has changed since the last time you updated the links on the file you're reading into R, then any values read into R that depend on external links will be the old values, not the latest ones.
The code in your case would be:
library(xlsx)
options(java.parameters = "-Xmx8g") # xlsx also uses java
# Replace file and sheetName with appropriate values for your file
# keepFormulas=FALSE and header=TRUE are the defaults. I added them only for illustration.
raw = read.xlsx(file, sheetName=sheetName, header=TRUE, keepFormulas=FALSE)
How can i append my R outputs in a single sheet of xlsx file? I am currently working on web crawling wherein i need to scrap the user reviews from website and save it in my deskstop in xlsx format. I need to every time change the website url(as user reviews are in different pages) in my code and save the output in one sheet of xlsx file.
Can you please help me with the code of appending outputs in a single sheet of xlsx file? Below is the code which i am using: Every time i need to change the website url and run the same below code and save the corresponding output in a single sheet of mydata.xlsx
library("rvest")
htmlpage <- html("http://www.glassdoor.com/GD/Reviews/Symphony-Teleca-Reviews-E28614_P2.htm?sort.sortType=RD&sort.ascending=false&filter.employmentStatus=REGULAR&filter.employmentStatus=PART_TIME&filter.employmentStatus=UNKNOWN")
proshtml <- html_nodes(htmlpage, ".pros")
pros <- html_text(proshtml)
pros
data=data.frame(pros)
library(xlsx)
write.xlsx(data, "D:/mydata.xlsx", append=TRUE)
A trivial, but super-slow way:
If you only need to add (a few) row(s) to an existing Excel file, and it only has one sheet to which you want to append, you can just do a simple read => overwrite step:
SHEET.NAME <- '...' # fill in with yours
existing.data <- read.xlsx(file, sheetName = SHEET.NAME)
new.data <- rbind(existing.data, data)
write.xlsx(new.data, file, sheetName = SHEET.NAME, row.names = F, append = F)
Note:
It's quite slow in general, will work only for small scale
read.xlsx is a slow function. Try read.xlsx2 to make it much faster (see the difference in the docs)
If your R process is run once and keeps working for a long time, obviously don't do it this way (reading and overwriting a file is ridiculous in that case)
look at package xlsx.
?write.xlsx will show you what you want. append=TRUE is the key.
========= EDIT TO CORRECT =========
As #Jakub pointed out, append=TRUE adds another worksheet to the file.
========= EDIT TO ADD: ANOTHER METHOD ==========
Another method is to save the data to a .csv file, which could easily open from excel. In this case, the append=T works as expected (adding to the existing sheet):
write.table(df,"D:/MyFile.csv",append=T,sep=",")
I am writing code to export database from R into Excel, I have been trying others code including:
write.table(ALBERTA1, "D:/ALBERTA1.txt", sep="\t")
write.csv(ALBERTA1,":\ALBERTA1.csv")
your_filename_in_R = read.csv("ALBERTA1.csv")
your_filename_in_R = read.csv("ALBERTA1.csv")
write.csv(df, file = "ALBERTA1.csv")
your_filename_in_R = read.csv("ALBERTA1.csv")
write.csv(ALBERTA1, "ALBERTA1.csv")
write.table(ALBERTA1, 'clipboard', sep='\t')
write.table(ALBERTA1,"ALBERTA1.txt")
write.table(as.matrix(ALBERTA2),"ALBERTA2.txt")
write.table(as.matrix(vecm.pred$fcst$Alberta_Females[,1]), "vecm.pred$fcst$Alberta_Females[,1].txt")
write.table(as.matrix(foo),"foo.txt")
write.xlsx(ALBERTA2, "/ALBERTA2.xlsx")
write.table(ALBERTA1, "D:/ALBERTA1.txt", sep="\t").
Other users of this forum advised me this:
write.csv2(ALBERTA1, "ALBERTA1.csv")
write.table(kt, "D:/kt.txt", sep="\t", row.names=FALSE)
You can see on the pictures the outcome I have got from the code above. But this numbers can't be used to make any further operations such as addition with other matrices.
Has someone experienced this kind of problems?
Another option is the openxlsx-package. It doesn't depend on java and can read, edit and write Excel-files. From the description from the package:
openxlsx simplifies the the process of writing and styling Excel xlsx files from R and removes the dependency on Java
Example usage:
library(openxlsx)
# read data from an Excel file or Workbook object into a data.frame
df <- read.xlsx('name-of-your-excel-file.xlsx')
# for writing a data.frame or list of data.frames to an xlsx file
write.xlsx(df, 'name-of-your-excel-file.xlsx')
Besides these two basic functions, the openxlsx-package has a host of other functions for manipulating Excel-files.
For example, with the writeDataTable-function you can create formatted tables in an Excel-file.
Recently used xlsx package, works well.
library(xlsx)
write.xlsx(x, file, sheetName="Sheet1")
where x is a data.frame
writexl, without Java requirement:
# install.packages("writexl")
library(writexl)
tempfile <- write_xlsx(iris)
The WriteXLS function from the WriteXLS package can write data to Excel.
Alternatively, write.xlsx from the xlsx package will also work.
One could also use the readODS package. Granted it doesn't produce an .xlsx, but Excel can read Open Document Spreadsheet (ODS) / LibreOffice files too.
require(readODS)
tmp = file.path(tempdir(), 'iris.ods')
write_ods(iris, tmp)
If I might offer an alternative, you could also save your dataframe in a regular csv file, and then use the "get data" function within Excel to import the dataframe. This worked like a charm for me, and you need not bother with any excel packages in R.
Here is a way to write data from a dataframe into an excel file by different IDs and into different tabs (sheets) by another ID associated to the first level id. Imagine you have a dataframe that has email_address as one column for a number of different users, but each email has a number of 'sub-ids' that have all the data.
data <- tibble(id = c(1,2,3,4,5,6,7,8,9), email_address = c(rep('aaa#aaa.com',3), rep('bbb#bbb.com', 3), rep('ccc#ccc.com', 3)))
So ids 1,2,3 would be associated with aaa#aaa.com. The following code splits the data by email and then puts 1,2,3 into different tabs. The important thing is to set append = True when writing the .xlsx file.
temp_dir <- tempdir()
for(i in unique(data$email_address)){
data %>%
filter(email_address == i) %>%
arrange(id) -> subset_data
for(j in unique(subset_data$id)){
write.xlsx(subset_data %>% filter(id == j),
file = str_c(temp_dir,"/your_filename_", str_extract(i, pattern = "\\b[A-Za-z0-
9._%+-]+"),'_', Sys.Date(), '.xlsx'),
sheetName = as.character(j),
append = TRUE)}
}
The regex gets the name from the email address and puts it into the file-name.
Hope somebody finds this useful. I'm sure there's more elegant ways of doing this but it works.
Btw, here is a way to then send these individual files to the various email addresses in the data.frame. Code goes into second loop [j]
send.mail(from = "sender#sender.com",
to = i,
subject = paste("Your report for", str_extract(i, pattern = "\\b[A-Za-z0-9._%+-]+"), 'on', Sys.Date()),
body = "Your email body",
authenticate = TRUE,
smtp = list(host.name = "XXX", port = XXX,
user.name = Sys.getenv("XXX"), passwd = Sys.getenv("XXX")),
attach.files = str_c(temp_dir, "/your_filename_", str_extract(i, pattern = "\\b[A-Za-z0-9._%+-]+"),'_', Sys.Date(), '.xlsx'))
I have been trying out the different packages including the function:
install.packages ("prettyR")
library (prettyR)
delimit.table (Corrvar,"Name the csv.csv") ## Corrvar is a name of an object from an output I had on scaled variables to run a regression.
However I tried this same code for an output from another analysis (occupancy models model selection output) and it did not work. And after many attempts and exploration I:
copied the output from R (Ctrl+c)
in Excel sheet I pasted it (Ctrl+V)
Select the first column where the data is
In the "Data" vignette, click on "Text to column"
Select Delimited option, click next
Tick space box in "Separator", click next
Click Finalize (End)
Your output now should be in a form you can manipulate easy in excel. So perhaps not the fanciest option but it does the trick if you just want to explore your data in another way.
PS. If the labels in excel are not the exact one it is because Im translating the lables from my spanish excel.