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
Related
R Beginners here
I have a folder contains 150 csv files, each file name is "student1" "student2"....
Each files has 2 columns with Courses and Score
I want to run a for loop for this and store all of the data into a new dataframe.
so far I have :
data_1 = dir(path_cwd.full.names = TRUE, pattern = "csv$")
for(i in data_1)
{
b = read.csv(i,sep = ", " header = TRUE)
}
Please help me and explain it to me!
Much thanks
You can use lapply here. It is basically the same as for loop but you will more control over the operation. Here we will use lapply to get each file and then using do.call we will bind all data frames into one dataframe. The point is that you should make sure all csv files have the same number of columns and their names and order of columns are matched. Else, you may need to do more steps in between.
data_1 = dir(path_cwd.full.names = TRUE, pattern = "csv$"
final_df <- lapply(data_1, function(i){
b = read.csv(i,sep = ", " header = TRUE)
}) %>% do.call(what = rbind)
I am trying to add the name of each file in a list of .csv as the last column with all values also equal to the name. I am getting it, but the result show the files like transposed or something. I don´t know how to fix it, I have tried data.frame, unlist, but nothing.
This is the code:
workbooks <- list.files(pattern="*.csv", full.names= T)
read_workbooks <- lapply(workbooks, read.csv)
for (i in 1:length(workbooks)){
name_of_file[i] <- str_replace_all(str_sub(workbooks[i], 3,
end = unlist(gregexpr("-current",workbooks[i]))-1),"_"," ")
temp_workbook <- cbind(read_workbooks[i],"Filer Name" = name_of_file[i])
write.csv(temp_workbook, file = paste(name_of_file[i],".csv",sep = ""),
row.names = F)
}
You can do this in the same lapply call with the help of an anonymous function.
workbooks <- list.files(pattern="*.csv", full.names= TRUE)
lapply(workbooks, function(x) {
write.csv(transform(read.csv(x), file_name = basename(x)),sprintf('new_%s.csv',
tools::file_path_sans_ext(basename(x))), row.names = FALSE)
})
Read each csv in workbooks, add a new column name in each file which is the name of the file and write the new csv.
Within R, I am trying to print a series of dataframes into an Excel file using openxlsx. Specifically in this case, I'm using list.files, read.xlsx and write.xlsx.
I'm still unable to write multiple tabs into one Excel file.
Please see my code below, I've tried to approach this problem using a for loop as well as a manual solution to test the feasibility but have had no luck
This is what my code currently looks like. For the length of the file list, pipe each file into a read function which then writes the results.
lapply(
1:length(file.list),
function(x) {
write.xlsx(
read.xlsx(file.list[i]),
file = file_name,
sheetName = file.list[i],
col.names = TRUE,
row.names = FALSE,
append = TRUE)
}
)
A manual solution below also doesn't seem to have any luck for me either
df1 <- read.xlsx(file.list[1])
write.xlsx(df1, file = file_name, sheetName = file.list[1], col.names = TRUE, row.names = FALSE, append = FALSE)
df2 <- read.xlsx(file.list[2])
write.xlsx(df2, file = file_name, sheetName = file.list[2], col.names = TRUE, row.names = FALSE, append = TRUE)
No error messages so far. The final file does see data being written into it, however, it seems only the last file has the results print. I'm thinking that it's almost a cycle of overwrites,
Maybe you could try this:
wb <- createWorkbook(title = "Your_Workbook_Name")
lapply(1:length(file.list), function(y) lapply(1:length(file.list), function(x) writeData(wb,file.list[i],y,col.names = TRUE, row.names = FALSE, append = TRUE)))
Since I don't have a way to replicate this, perhaps you can understand the main idea behind this.
A double loop, in which your traverse all the files you want to write, before writing it you create a sheet with the name of the index, and then you can write in the newly created sheet, the data you want. I hope it's understandable (My knowledge about lapply and sapply is not the best, but the idea still stands)
You can simply use a named list of dataframes in write.xlsx. Something like this should work:
library(openxlsx)
df.list <- lapply(file.list, read.xlsx)
named.df.lst <- setNames(df.list, file.list)
write.xlsx( named.df.lst, file = file_name )
I'm quite new at R and a bit stuck on what I feel is likely a common operation to do. I have a number of files (57 with ~1.5 billion rows cumulatively by 6 columns) that I need to perform basic functions on. I'm able to read these files in and perform the calculations I need no problem but I'm tripping up in the final output. I envision the function working on 1 file at a time, outputting the worked file and moving onto the next.
After calculations I would like to output 57 new .txt files named after the file the input data first came from. So far I'm able to perform the calculations on smaller test datasets and spit out 1 appended .txt file but this isn't what I want as a final output.
#list filenames
files <- list.files(path=, pattern="*.txt", full.names=TRUE, recursive=FALSE)
#begin looping process
loop_output = lapply(files,
function(x) {
#Load 'x' file in
DF<- read.table(x, header = FALSE, sep= "\t")
#Call calculated height average a name
R_ref= 1647.038203
#Add column names to .las data
colnames(DF) <- c("X","Y","Z","I","A","FC")
#Calculate return
DF$R_calc <- (R_ref - DF$Z)/cos(DF$A*pi/180)
#Calculate intensity
DF$Ir_calc <- DF$I * (DF$R_calc^2/R_ref^2)
#Output new .txt with calcuated columns
write.table(DF, file=, row.names = FALSE, col.names = FALSE, append = TRUE,fileEncoding = "UTF-8")
})
My latest code endeavors have been to mess around with the intial lapply/sapply function as so:
#begin looping process
loop_output = sapply(names(files),
function(x) {
As well as the output line:
#Output new .csv with calcuated columns
write.table(DF, file=paste0(names(DF), "txt", sep="."),
row.names = FALSE, col.names = FALSE, append = TRUE,fileEncoding = "UTF-8")
From what I've been reading the file naming function during write.table output may be one of the keys I don't have fully aligned yet with the rest of the script. I've been viewing a lot of other asked questions that I felt were applicable:
Using lapply to apply a function over list of data frames and saving output to files with different names
Write list of data.frames to separate CSV files with lapply
to no luck. I deeply appreciate any insights or paths towards the right direction on inputting x number of files, performing the same function on each, then outputting the same x number of files. Thank you.
The reason the output is directed to the same file is probably that file = paste0(names(DF), "txt", sep=".") returns the same value for every iteration. That is, DF must have the same column names in every iteration, therefore names(DF) will be the same, and paste0(names(DF), "txt", sep=".") will be the same. Along with the append = TRUE option the result is that all output is written to the same file.
Inside the anonymous function, x is the name of the input file. Instead of using names(DF) as a basis for the output file name you could do some transformation of this character string.
example.
Given
x <- "/foo/raw_data.csv"
Inside the function you could do something like this
infile <- x
outfile <- file.path(dirname(infile), gsub('raw', 'clean', basename(infile)))
outfile
[1] "/foo/clean_data.csv"
Then use the new name for output, with append = FALSE (unless you need it to be true)
write.table(DF, file = outfile, row.names = FALSE, col.names = FALSE, append = FALSE, fileEncoding = "UTF-8")
Using your code, this is the general idea:
require(purrr)
#list filenames
files <- list.files(path=, pattern="*.txt", full.names=TRUE, recursive=FALSE)
#Call calculated height average a name
R_ref= 1647.038203
dfTransform <- function(file){
colnames(file) <- c("X","Y","Z","I","A","FC")
#Calculate return
file$R_calc <- (R_ref - file$Z)/cos(file$A*pi/180)
#Calculate intensity
file$Ir_calc <- file$I * (file$R_calc^2/R_ref^2)
return(file)
}
output <- files %>% map(read.table,header = FALSE, sep= "\t") %>%
map(dfTransform) %>%
map(write.table, file=paste0(names(DF), "txt", sep="."),
row.names = FALSE, col.names = FALSE, append = TRUE,fileEncoding = "UTF-8")
I am looping through some data, and appending it to csv file. What I want is to have column names on the top of the file once, and then as it loops to not repeat column names in the middle of file.
If I do col.names=T, it repeats including column names for each new loop. If I have col.names=F, there are no column names at all.
How do I do this most efficiently? I feel that this is such a common case that there must be a way to do it, without writing code especially to handle it.
write.table(dd, "data.csv", append=TRUE, col.names=T)
See ?file.exists.
write.table(dd, "data.csv", append=TRUE, col.names=!file.exists("data.csv"))
Thus column names are written only when you are not appending to a file that already exists.
You may or may not also see a problem with the row names being identical, as write.table does not allow identical row names when appending. You could give this a try. In the first write to file, try write.table with row.names = FALSE only. Then, starting from the second write to file, use both col.names = FALSE and row.names = FALSE
Here's the first write to file
> d1 <- data.frame(A = 1:5, B = 1:5) ## example data
> write.table(d1, "file.txt", row.names = FALSE)
We can check it with read.table("file.txt", header = TRUE). Then we can append the same data frame to that file with
> write.table(d1, "file.txt", row.names = FALSE,
col.names = FALSE, append = TRUE)
And again we can check it with read.table("file.txt", header = TRUE)
So, if you have a list of data frames, say dlst, your code chunk that appends the data frames together might look something like
> dlst <- rep(list(d1), 3) ## list of example data
> write.table(dlst[1], "file.txt", row.names = FALSE)
> invisible(lapply(dlst[-1], write.table, "file.txt", row.names = FALSE,
col.names = FALSE, append = TRUE))
But as #MrFlick suggests, it would be much better to append the data frames in R, and then send them to file once. This would eliminate many possible errors/problems that could occur while writing to file. If the data is in a list, that could be done with
> dc <- do.call(rbind, dlst)
> write.table(dc, "file.txt")
Try changing the column names of the data frame using names() command in R and replace with the same names as existing and then try the dbWriteTable command keeping row.names = False. The issue will get solved.
e.g.
if your data frame df1 has columns as obs, name, age then
names(df1) <- c('obs','name','age')
and then try
dbWriteTable(conn, 'table_name', df1, append = T, row.names = F)