Writing a csv file with fixed width in r - r

I read a file, change its content, and then I want to write the dataframe into a new file. The thing that bugs me is that the width of the columns isn't adjustable within Excel (it does not save changes).
I was wondering if it is possible to write the csv file with column width that fits the longest value.
dat <- read.csv("Input.csv")
# Do some processing
#Write the new file
write.csv(dat, "Output.csv", row.names=FALSE)
Edit 1:
dat <- read.csv("Input.csv")
createSheet(wb, "test")
writeWorksheet(wb, dat, "test")
colWidths <- sapply(1:ncol(dat), function(i) max(c(8, nchar(c(names(dat)[i], as.character(dat[, i]))))))
setColumnWidth(wb, "test", 1:ncol(dat), colWidths * 256)
saveWorkbook(wb)
what did I do wrong? It writes an empty file.

It doesn't matter what widths you write for your csv; Excel will always have its default column width when you open it.
Your options are:
Accept this behaviour.
Resave the file from Excel as something else (.xls or .xlsx)
Write the file from R using a package that directly exports Excel files. XLConnect will do this and even has a setColumnWidth function to set the column widths within R.
e.g.
dat <- data.frame(x = 1:24, `Long Column Name` = 25:48, `Wide Column` = paste(LETTERS, collapse = " "))
library("XLConnect")
wb <- loadWorkbook("Output.xlsx", create = TRUE)
createSheet(wb, "Output")
writeWorksheet(wb, dat, "Output")
colWidths <- sapply(1:ncol(dat), function(i) max(c(8, nchar(c(names(dat)[i], as.character(dat[, i])))))
setColumnWidth(wb, "Output", 1:ncol(dat), colWidths * 256)
saveWorkbook(wb)

You may need to close the .csv in Excel before you run write.csv in R because Excel locks the file.
It is also possible to pad the columns like this if that is what you want.

Related

Select specific data frames from global environment [duplicate]

I am surprised to find that there is no easy way to export multiple data.frame to multiple worksheets of an Excel file? I tried xlsx package, seems it can only write to one sheet (override old sheet); I also tried WriteXLS package, but it gives me error all the time...
My code structure is like this: by design, for each iteration, the output dataframe (tempTable) and the sheetName (sn) got updated and exported into one tab.
for (i in 2 : ncol(code)){
...
tempTable <- ...
sn <- ...
WriteXLS("tempTable", ExcelFileName = "C:/R_code/../file.xlsx",
SheetNames = sn);
}
I can export to several cvs files, but there has to be an easy way to do that in Excel, right?
You can write to multiple sheets with the xlsx package. You just need to use a different sheetName for each data frame and you need to add append=TRUE:
library(xlsx)
write.xlsx(dataframe1, file="filename.xlsx", sheetName="sheet1", row.names=FALSE)
write.xlsx(dataframe2, file="filename.xlsx", sheetName="sheet2", append=TRUE, row.names=FALSE)
Another option, one that gives you more control over formatting and where the data frame is placed, is to do everything within R/xlsx code and then save the workbook at the end. For example:
wb = createWorkbook()
sheet = createSheet(wb, "Sheet 1")
addDataFrame(dataframe1, sheet=sheet, startColumn=1, row.names=FALSE)
addDataFrame(dataframe2, sheet=sheet, startColumn=10, row.names=FALSE)
sheet = createSheet(wb, "Sheet 2")
addDataFrame(dataframe3, sheet=sheet, startColumn=1, row.names=FALSE)
saveWorkbook(wb, "My_File.xlsx")
In case you might find it useful, here are some interesting helper functions that make it easier to add formatting, metadata, and other features to spreadsheets using xlsx:
http://www.sthda.com/english/wiki/r2excel-read-write-and-format-easily-excel-files-using-r-software
You can also use the openxlsx library to export multiple datasets to multiple sheets in a single workbook.The advantage of openxlsx over xlsx is that openxlsx removes the dependencies on java libraries.
Write a list of data.frames to individual worksheets using list names as worksheet names.
require(openxlsx)
list_of_datasets <- list("Name of DataSheet1" = dataframe1, "Name of Datasheet2" = dataframe2)
write.xlsx(list_of_datasets, file = "writeXLSX2.xlsx")
There's a new library in town, from rOpenSci: writexl
Portable, light-weight data frame to xlsx exporter based on
libxlsxwriter. No Java or Excel required
I found it better and faster than the above suggestions (working with the dev version):
library(writexl)
sheets <- list("sheet1Name" = sheet1, "sheet2Name" = sheet2) #assume sheet1 and sheet2 are data frames
write_xlsx(sheets, "path/to/location")
Many good answers here, but some of them are a little dated. If you want to add further worksheets to a single file then this is the approach I find works for me. For clarity, here is the workflow for openxlsx version 4.0
# Create a blank workbook
OUT <- createWorkbook()
# Add some sheets to the workbook
addWorksheet(OUT, "Sheet 1 Name")
addWorksheet(OUT, "Sheet 2 Name")
# Write the data to the sheets
writeData(OUT, sheet = "Sheet 1 Name", x = dataframe1)
writeData(OUT, sheet = "Sheet 2 Name", x = dataframe2)
# Export the file
saveWorkbook(OUT, "My output file.xlsx")
EDIT
I've now trialled a few other answers, and I actually really like #Syed's. It doesn't exploit all the functionality of openxlsx but if you want a quick-and-easy export method then that's probably the most straightforward.
I'm not familiar with the package WriteXLS; I generally use XLConnect:
library(XLConnect)
##
newWB <- loadWorkbook(
filename="F:/TempDir/tempwb.xlsx",
create=TRUE)
##
for(i in 1:10){
wsName <- paste0("newsheet",i)
createSheet(
newWB,
name=wsName)
##
writeWorksheet(
newWB,
data=data.frame(
X=1:10,
Dataframe=paste0("DF ",i)),
sheet=wsName,
header=TRUE,
rownames=NULL)
}
saveWorkbook(newWB)
This can certainly be vectorized, as #joran noted above, but just for the sake of generating dynamic sheet names quickly, I used a for loop to demonstrate.
I used the create=TRUE argument in loadWorkbook since I was creating a new .xlsx file, but if your file already exists then you don't have to specify this, as the default value is FALSE.
Here are a few screenshots of the created workbook:
Incase data size is small, R has many packages and functions which can be utilized as per your requirement.
write.xlsx, write.xlsx2, XLconnect also do the work but these are sometimes slow as compare to openxlsx.
So, if you are dealing with the large data sets and came across java errors. I would suggest to have a look of "openxlsx" which is really awesome and reduce the time to 1/12th.
I've tested all and finally i was really impressed with the performance of openxlsx capabilities.
Here are the steps for writing multiple datasets into multiple sheets.
install.packages("openxlsx")
library("openxlsx")
start.time <- Sys.time()
# Creating large data frame
x <- as.data.frame(matrix(1:4000000,200000,20))
y <- as.data.frame(matrix(1:4000000,200000,20))
z <- as.data.frame(matrix(1:4000000,200000,20))
# Creating a workbook
wb <- createWorkbook("Example.xlsx")
Sys.setenv("R_ZIPCMD" = "C:/Rtools/bin/zip.exe") ## path to zip.exe
Sys.setenv("R_ZIPCMD" = "C:/Rtools/bin/zip.exe") has to be static as it takes reference of some utility from Rtools.
Note: Incase Rtools is not installed on your system, please install it first for smooth experience. here is the link for your reference: (choose appropriate version)
https://cran.r-project.org/bin/windows/Rtools/
check the options as per link below (need to select all the check box while installation)
https://cloud.githubusercontent.com/assets/7400673/12230758/99fb2202-b8a6-11e5-82e6-836159440831.png
# Adding a worksheets : parameters for addWorksheet are 1. Workbook Name 2. Sheet Name
addWorksheet(wb, "Sheet 1")
addWorksheet(wb, "Sheet 2")
addWorksheet(wb, "Sheet 3")
# Writing data in to respetive sheets: parameters for writeData are 1. Workbook Name 2. Sheet index/ sheet name 3. dataframe name
writeData(wb, 1, x)
# incase you would like to write sheet with filter available for ease of access you can pass the parameter withFilter = TRUE in writeData function.
writeData(wb, 2, x = y, withFilter = TRUE)
## Similarly writeDataTable is another way for representing your data with table formatting:
writeDataTable(wb, 3, z)
saveWorkbook(wb, file = "Example.xlsx", overwrite = TRUE)
end.time <- Sys.time()
time.taken <- end.time - start.time
time.taken
openxlsx package is really good for reading and writing huge data from/ in excel files and has lots of options for custom formatting within excel.
The interesting fact is that we dont have to bother about java heap memory here.
I had this exact problem and I solved it this way:
library(openxlsx) # loads library and doesn't require Java installed
your_df_list <- c("df1", "df2", ..., "dfn")
for(name in your_df_list){
write.xlsx(x = get(name),
file = "your_spreadsheet_name.xlsx",
sheetName = name)
}
That way you won't have to create a very long list manually if you have tons of dataframes to write to Excel.
I regularly use the packaged rio for exporting of all kinds. Using rio, you can input a list, naming each tab and specifying the dataset. rio compiles other in/out packages, and for export to Excel, uses openxlsx.
library(rio)
filename <- "C:/R_code/../file.xlsx"
export(list(sn1 = tempTable1, sn2 = tempTable2, sn3 = tempTable3), filename)
tidy way of taking one dataframe and writing sheets by groups:
library(tidyverse)
library(xlsx)
mtcars %>%
mutate(cyl1 = cyl) %>%
group_by(cyl1) %>%
nest() %>%
ungroup() %>%
mutate(rn = row_number(),
app = rn != 1,
q = pmap(list(rn,data,app),~write.xlsx(..2,"test1.xlsx",as.character(..1),append = ..3)))
For me, WriteXLS provides the functionality you are looking for. Since you did not specify which errors it returns, I show you an example:
Example
library(WriteXLS)
x <- list(sheet_a = data.frame(a=letters), sheet_b = data.frame(b = LETTERS))
WriteXLS(x, "test.xlsx", names(x))
Explanation
If x is:
a list of data frames, each one is written to a single sheet
a character vector (of R objects), each object is written to a single sheet
something else, then see also what the help states:
More on usage
?WriteXLS
shows:
`x`: A character vector or factor containing the names of one or
more R data frames; A character vector or factor containing
the name of a single list which contains one or more R data
frames; a single list object of one or more data frames; a
single data frame object.
Solution
For your example, you would need to collect all data.frames in a list during the loop, and use WriteXLS after the loop has finished.
Session info
R 3.2.4
WriteXLS 4.0.0
I do it in this way for openxlsx using following function
mywritexlsx<-function(fname="temp.xlsx",sheetname="Sheet1",data,
startCol = 1, startRow = 1, colNames = TRUE, rowNames = FALSE)
{
if(! file.exists(fname))
wb = createWorkbook()
else
wb <- loadWorkbook(file =fname)
sheet = addWorksheet(wb, sheetname)
writeData(wb,sheet,data,startCol = startCol, startRow = startRow,
colNames = colNames, rowNames = rowNames)
saveWorkbook(wb, fname,overwrite = TRUE)
}
I do this all the time, all I do is
WriteXLS::WriteXLS(
all.dataframes,
ExcelFileName = xl.filename,
AdjWidth = T,
AutoFilter = T,
FreezeRow = 1,
FreezeCol = 2,
BoldHeaderRow = T,
verbose = F,
na = '0'
)
and all those data frames come from here
all.dataframes <- vector()
for (obj.iter in all.objects) {
obj.name <- obj.iter
obj.iter <- get(obj.iter)
if (class(obj.iter) == 'data.frame') {
all.dataframes <- c(all.dataframes, obj.name)
}
obviously sapply routine would be better here
for a lapply-friendly version..
library(data.table)
library(xlsx)
path2txtlist <- your.list.of.txt.files
wb <- createWorkbook()
lapply(seq_along(path2txtlist), function (j) {
sheet <- createSheet(wb, paste("sheetname", j))
addDataFrame(fread(path2txtlist[j]), sheet=sheet, startColumn=1, row.names=FALSE)
})
saveWorkbook(wb, "My_File.xlsx")

How to use write.xlsx in R when the excel file exists or the sheet exists

I am trying to use openxlsx::write.xlsx to write results into Excel spreadsheet in R.
if the file exists and a new sheet is to be added, I can use append=T. Instead of using if to check the file, are there any ways to automatically check?
if the file and sheet both exist and this sheet is to be updated, how should I do to overwrite the results? Thanks.
Here is an openxlsx answer. In order to demonstrate, we need some data.
## Create a simple test file
library(openxlsx)
hs <- createStyle(textDecoration = "Bold")
l <- list("IRIS" = iris, "MTCARS" = mtcars)
write.xlsx(l, file = "TestFile.xlsx", borders = "columns", headerStyle = hs)
Question 1
You can check whether or not the file exists with
## Check existence of file
file.exists("TestFile.xlsx")
You can check if the tab (sheet) exists within the workbook
## Check available sheets
getSheetNames("TestFile.xlsx")
Steps for question 2:
1. Read the file into a Workbook object.
2. Pull the data from the sheet you want to modify into a data.frame.
3. Modify the data.frame to taste
4. Save the data back into the Workbook
5. Save the Workbook out to disk
In order to have a simple example to work with, let's create a simple test file.
## Load existing file
wb = loadWorkbook("TestFile.xlsx")
## Pull all data from sheet 1
Data = read.xlsx(wb, sheet=1)
## Change a single element for demonstration
## ** Beware!! ** Because of the header,
## the 2,2 position in the data
## is row 3 column 2 in the spreadsheet
Data[2,2] = 1492
## Put the data back into the workbook
writeData(wb, sheet=1, Data)
## Save to disk
saveWorkbook(wb, "TestFile.xlsx", overwrite = TRUE)
You can open up the spreadsheet and check that the change has been made.
If you want to completely change the sheet (as in your comment),
you can just delete the old sheet and replace it with a new one
using the same name.
removeWorksheet(wb, "IRIS")
addWorksheet(wb, "IRIS")
NewData = data.frame(X1=1:4, X2= LETTERS[1:4], X3=9:6)
writeData(wb, "IRIS", NewData)
saveWorkbook(wb, "TestFile.xlsx", overwrite = TRUE)
You can check if sheet exists before and if so remove it, if not append it to existing file this command also will create file if it does not exist.
library(xlsx)
path <- "testing.xlsx"
sheet_name = "new_sheet"
data <-
data.frame(
B = c(1, 2, 3, 4)
)
if(sheet_name %in% names(getSheets(loadWorkbook(path)))){
wb <- loadWorkbook(path)
removeSheet(wb, sheetName = sheet_name)
saveWorkbook(wb, path)
}
write.xlsx(data, path, sheetName = sheet_name, append = TRUE)

How do I get the file path of a file saved using write.xlsx or another function in R?

I am creating two dataframes and one graph on Rstudio. I wrote code to transfer them to an Excel file on different sheets, but each time I have to choose the file path using file.choose(). Is it possible to assign the file path to the variable when saving the file for the first time? If such a method exists, how can it be done?
I would also like to receive comments on how to more easily export my dataframes to an excel file. I shared my codes.
Thank you to everyone.
dataframe1 <- data.frame("A"=1, "B"=2)
dataframe2 <- data.frame("C"=3,"D"=4)
list_of_datasets <- list("Name of DataSheet1" = dataframe1, "Name of Datasheet2" = dataframe2, )
write.xlsx(list_of_datasets, file = "writeXLSX2.xlsx")
dflist <- list("Sonuçlar"=yazılacakdosya0, "Frame"=dtf, "Grafik"="")
edc <- write.xlsx(dflist, file.choose(new = T), colNames = TRUE,
borders = "surrounding",
firstRow = T,
headerStyle = hs)
require(ggplot2)
q1 <- qplot(hist(yazılacakdosya0$Puan))
print(q1)
insertPlot(wb=edc, sheet = "Grafik")
saveWorkbook(edc, file = file.choose(), overwrite = T)
Just save the file path before you call saveWorkbook
file = file.choose()
saveWorkbook(edc, file = file, overwrite = T)

Exporting two data frames into same file

I currently have two data-frames, One DF contains around ~100,000 rows, while the other only has ~1000. I can export either one of these using the write.table function shown below...
write.table(DF_1, file = paste("DF_one.csv" ),
row.names = F, col.names = T, sep = ",")
This is easily opened by excel and works well. The problem is I need to include the other data frame in the very same excel file, and I'm not sure how to do this or if it is even possible.
I am open to any ideas, and have provided some example data to work with below.
#Example data for data frame one, length =30
Dates<-c(Sys.Date()+1:30)
Data1<-c(1+1:30)
#Data Frame One
Df1<-data.frame(Dates,Data1)
#Example data for data rame two, length=10
Letters<-c(letters[1:10])
Data2<-c(1:10)
#Data Frame Two
Df2<-data.frame(Letters,Data2)
#Now, is there a way can we export both to the same file?
#Here is the export for just data frame one
write.table(Df1, file = paste("DFone.csv" ),
row.names = F, col.names = T, sep = ",")
Any ideas including:"stop being picky and just export 2 files and then merge in excel" are appreciated.
Research Done:
I like this approach but would prefer a horizontal format instead of vertical
(I should probably just not be picky)
How to merge multiple data frame into one table and export to Excel?
How to write multiple tables, dataframes, regression results etc - to one excel file?
Thanks for all the help!
I have no idea if this preserves the information structure that you want but you are really intent on getting them into the same table you could do the following.
Both <- data.frame(Df1,Df2)
write.table(Both, file = paste("DF_Both.csv" ),
row.names = F, col.names = T, sep = ",")
Because the first solution did not meet your requirements here is another one that saves data frames to multiple tabs of an excel spreadsheet.
install.packages("xlsx")
library(xlsx)
###Define the save.xlsx function
save.xlsx <- function (file, ...)
{
require(xlsx, quietly = TRUE)
objects <- list(...)
fargs <- as.list(match.call(expand.dots = TRUE))
objnames <- as.character(fargs)[-c(1, 2)]
nobjects <- length(objects)
for (i in 1:nobjects) {
if (i == 1)
write.xlsx(objects[[i]], file, sheetName = objnames[i])
else write.xlsx(objects[[i]], file, sheetName = objnames[i],
append = TRUE)
}
print(paste("Workbook", file, "has", nobjects, "worksheets."))
}
### Save the file to your working directory.
save.xlsx("WorkbookTitle.xlsx", Df1, Df2)
Full discolsure this was adapted from another question on stack overflow R dataframes to multi sheet Excel Work

read.xlsx cannot find Excel file

I want to read a bunch of excel files all located in the same directory and store them in different sheets in a consolidated Excel file.
I initially tried using XLConnect but kept getting the error GC overhead limit exceeded. I stumbled upon this question which says that it is a common problem with Java based Excel handling packages such as XLConnect and xlsx. I tried the memory management trick suggested there, but it did not work. One of the comments in one of the comments on the accepted answers suggested using openxls as it based on RCpp and hence avoid this particular problem.
My current code is as follows:
library(openxlsx)
mnth="January"
files <- list.files(path="./Original Files", pattern=mnth, full.names=T, recursive=FALSE) #pattern match as multiple files are from the same month
# Read them into a list and write to sheet
wb <- createWorkbook()
lapply(files, function(x){
print(x)
xlFile<-read.xlsx(xlsxFile = x, sheet = 1, startRow = 2, colNames = T) #Also tried
str(xlFile)
#Create a sheet in the new Excel file called Consolidated.xlsx with the month name
#Append current data in sheet
})
The problem I am getting is the error: Error in read.xlsx.default(xlsxFile = x, sheet = 1, startRow = 2, colNames = T) : openxlsx can not read .xls or .xlm files!
I have ensured that files variable contains all the files of interest (Ex: January 2015.xls, January 2016.xls, etc). I have also ensured that the path to the file is correct and the Excel files actually exists there.
I have left the writing to Excel as skeleton code as I need to solve the problem with reading the files first.
In case it helps, here is the code attempt with XLConnect
library(XLConnect)
setwd("D:/something/something")
mnth="January"
files <- list.files(path="./Original Files", pattern=mnth, full.names=T, recursive=FALSE)
# Read them into a list
df.list = lapply(files, readWorksheetFromFile, sheet=1, startRow=2)
#combine them into a single data frame and write to disk:
df = do.call(rbind, df.list)
rm(df.list)
outputFileName<-"Consolidated.xlsx"
# Load workbook (create if not existing)
wb <- loadWorkbook(outputFileName, create = TRUE)
createSheet(wb, name = mnth)
writeWorksheet(wb,df,sheet = mnth)
#write.xlsx2(df, outputFileName, sheetName = mnth, col.names = T, row.names = F, append = TRUE)
saveWorkbook(wb)
rm(df)
gc()

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