R - pipe("pbcopy") columns not lining up with pasting - r
As a follow-up to a question I wrote a few days ago, I finally figured out how to copy to the clipboard to paste into other applications (read: Excel).
However, when using the function to copy and paste, the variable column headers are not lining up correctly when pasting.
Data (taken from a Flowing Data example I happened to be looking at):
data <- read.csv("http://datasets.flowingdata.com/post-data.txt")
Copy function:
write.table(file = pipe("pbcopy"), data, sep = "\t")
When loaded in, the data looks like this:
id views comments category
1 5019 148896 28 Artistic Visualization
2 1416 81374 26 Visualization
3 1416 81374 26 Featured
4 3485 80819 37 Featured
5 3485 80819 37 Mapping
6 3485 80819 37 Data Sources
There is a row number without a column variable name (1, 2, 3, 4, ...)
Using the read.table(pipe("pbpaste")) function, it will load back into R fine.
However, when I paste it into Excel, or TextEdit, the column name for the second variable will be in the first variable column name slot, like this:
id views comments category
1 5019 148896 28 Artistic Visualization
2 1416 81374 26 Visualization
3 1416 81374 26 Featured
4 3485 80819 37 Featured
5 3485 80819 37 Mapping
6 3485 80819 37 Data Sources
Which leaves the trailing column without a column name.
Is there a way to ensure the data copied to the clipboard is aligned and labeled correctly?
The row numbers do not have a column name in an R data.frame. They were not in the original dataset but they are put into the output to the clipboard unless you suppress it. The default for that option is set to TRUE but you can override it. If you want such a column as a named column, you need to make it. Try this when sending to excel.
df$rownums <- rownames(df)
edf <- df[ c( length(df), 1:(length(df)-1))] # to get the rownums/rownames first
write.table(file = pipe("pbcopy"), edf, row.names=FALSE, sep = "\t")
You may just want to add the argument col.names=NA to your call to write.table(). It has the effect of adding an empty character string (a blank column name) to the header row for the first column.
write.table(file = pipe("pbcopy"), data, sep = "\t", col.names=NA)
To see the difference, compare these two function calls:
write.table(data[1:2,], sep="\t")
# "id" "views" "comments" "category"
# "1" 5019 148896 28 "Artistic Visualization"
# "2" 1416 81374 26 "Visualization"
write.table(data[1:2,], sep="\t", col.names=NA)
# "" "id" "views" "comments" "category"
# "1" 5019 148896 28 "Artistic Visualization"
# "2" 1416 81374 26 "Visualization"
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>titletool<-read.csv("TotalCSVData.csv",header=FALSE,sep=",") > class(titletool) [1] "data.frame" >titletool[1,1] [1] Experiment name : CONTROL DB AD_1 >t<-titletool[1,1] >t [1] Experiment name : CONTROL DB AD_1 >class(t) [1] "character" now i want to create an object (vector) with the name "Experiment name : CONTROL DB AD_1" , or even better if possible CONTROL DB AD_1 Thank you
Use assign: varname <- "Experiment name : CONTROL DB AD_1" assign(varname, 3.14158) get("Experiment name : CONTROL DB AD_1") [1] 3.14158 And you can use a regular expression and sub or gsub to remove some text from a string: cleanVarname <- sub("Experiment name : ", "", varname) assign(cleanVarname, 42) get("CONTROL DB AD_1") [1] 42 But let me warn you this is an unusual thing to do. Here be dragons.
If I understand correctly, you have a bunch of CSV files, each with multiple experiments in them, named in the pattern "Experiment ...". You now want to read each of these "experiments" into R in an efficient way. Here's a not-so-pretty (but not-so-ugly either) function that might get you started in the right direction. What the function basically does is read in the CSV, identify the line numbers where each new experiment starts, grabs the names of the experiments, then does a loop to fill in a list with the separate data frames. It doesn't really bother making "R-friendly" names though, and I've decided to leave the output in a list, because as Andrie pointed out, "R has great tools for working with lists." read.funkyfile = function(funkyfile, expression, ...) { temp = readLines(funkyfile) temp.loc = grep(expression, temp) temp.loc = c(temp.loc, length(temp)+1) temp.nam = gsub("[[:punct:]]", "", grep(expression, temp, value=TRUE)) temp.out = vector("list") for (i in 1:length(temp.nam)) { temp.out[[i]] = read.csv(textConnection( temp[seq(from = temp.loc[i]+1, to = temp.loc[i+1]-1)]), ...) names(temp.out)[i] = temp.nam[i] } temp.out } Here is an example CSV file. Copy and paste it into a text editor and save it as "funkyfile1.csv" in the current working directory. (Or, read it in from Dropbox: http://dl.dropbox.com/u/2556524/testing/funkyfile1.csv) "Experiment Name: Here Be",, 1,2,3 4,5,6 7,8,9 "Experiment Name: The Dragons",, 10,11,12 13,14,15 16,17,18 Here is a second CSV. Again, copy-paste and save it as "funkyfile2.csv" in your current working directory. (Or, read it in from Dropbox: http://dl.dropbox.com/u/2556524/testing/funkyfile2.csv) "Promises: I vow to",, "H1","H2","H3" 19,20,21 22,23,24 25,26,27 "Promises: Slay the dragon",, "H1","H2","H3" 28,29,30 31,32,33 34,35,36 Notice that funkyfile1 has no column names, while funkyfile2 does. That's what the ... argument in the function is for: to specify header=TRUE or header=FALSE. Also the "expression" identifying each new set of data is "Promises" in funkyfile2. Now, use the function: read.funkyfile("funkyfile1.csv", "Experiment", header=FALSE) # read.funkyfile("http://dl.dropbox.com/u/2556524/testing/funkyfile1.csv", # "Experiment", header=FALSE) # Uncomment to load remotely # $`Experiment Name Here Be` # V1 V2 V3 # 1 1 2 3 # 2 4 5 6 # 3 7 8 9 # # $`Experiment Name The Dragons` # V1 V2 V3 # 1 10 11 12 # 2 13 14 15 # 3 16 17 18 read.funkyfile("funkyfile2.csv", "Promises", header=TRUE) # read.funkyfile("http://dl.dropbox.com/u/2556524/testing/funkyfile2.csv", # "Experiment", header=TRUE) # Uncomment to load remotely # $`Promises I vow to` # H1 H2 H3 # 1 19 20 21 # 2 22 23 24 # 3 25 26 27 # # $`Promises Slay the dragon` # H1 H2 H3 # 1 28 29 30 # 2 31 32 33 # 3 34 35 36 Go get those dragons. Update If your data are all in the same format, you can use the lapply solution mentioned by Andrie along with this function. Just make a list of the CSVs that you want to load, as below. Note that the files all need to use the same "expression" and other arguments the way the function is currently written.... temp = list("http://dl.dropbox.com/u/2556524/testing/funkyfile1.csv", "http://dl.dropbox.com/u/2556524/testing/funkyfile3.csv") lapply(temp, read.funkyfile, "Experiment", header=FALSE)