I have a .csv file with 175 rows and 6 columns. I want to append a 176th row. My code is as follows:
x <- data.frame('1', 'ab', 'username', '<some.sentence>', '2017-05-04T00:51:35Z', '24')
write.table(x, file = "Tweets.csv", append = T)
What I expect to see is:
Instead, my result is:
How should I change my code?
write.table(x, file = "Tweets.csv", sep = ",", append = TRUE, quote = FALSE,
col.names = FALSE, row.names = FALSE)
im trying to separate a unique column in multiple csv files. I've already done it for one single file with this code:
tempmax <- read.csv(file="path", header=TRUE, sep=";", fill = TRUE)
colnames(tempmax) = c("Fecha", "Hora", "Temperatura max")
rbind(tempmax)
write.csv(tempmax, "path", sep = ";", append = FALSE, row.names = FALSE, col.names = FALSE)
However, I haven't found the way to do it in multiple csv saved in a folder. I would like to do the same: read, modify and write the new one.
I used this to read the multiple files:
getwd <- ("path")
filenames <- list.files("path",
pattern = "*.csv", full.names = TRUE)
But i just cant find the way to edit what i want. (i'm pretty new using R)
I appreciate the help. Thanks!
If we have several files, we can use lapply. It is not clear about the transformation. So, the file is written back by selecting the first column
lapply(filenames, function(file){
tempmax <- read.csv(file= file, header=TRUE, sep=";", fill = TRUE)
colnames(tempmax) = c("Fecha", "Hora", "Temperatura max")
write.csv(tempmax[1], file, sep = ";", append = FALSE,
row.names = FALSE, col.names = FALSE)})
I have 400+ quite large csv files (~ million rows) having all a similar structure :
A long header of which I only need the 2nd and 3rd rows
A first time serie (always preceded by 'Target1')
A second time serie (always preceded by 'Target2')
Here is an example of data :
#multiple rows of header#
Target 1
Timestamp,X,Y,Z
1553972886851,0.017578,-0.003052,-0.971375
1553972886851,0.017883,-0.003662,-0.980408
1553972886851,0.016418,-0.003174,-0.977295
1553972886999,0.017151,-0.002808,-0.978088
1553972886999,0.016785,-0.003113,-0.977051
1553972886999,0.017883,-0.002197,-0.975830
1553972887096,0.017517,-0.003113,-0.976624
1553972887096,0.017883,-0.003113,-0.977966
1553972887096,0.017883,-0.002869,-0.978210
1553972887243,0.017151,-0.003113,-0.976135
1553972887243,0.018250,-0.003235,-0.975647
1553972887243,0.017273,-0.002991,-0.976257
1553972887340,0.018372,-0.003235,-0.977722
1553972887340,0.017761,-0.003235,-0.978027
Target 2
Timestamp,X,Y,Z
1553972886753,-0.411585,0.072409,-0.849848
1553972886753,-0.339177,-0.053354,-0.556402
1553972886753,-0.411585,-0.262957,-0.483994
1553972886855,-0.506860,-0.057165,-0.472561
1553972886855,-0.499238,-0.007622,-0.529726
1553972886855,-0.472561,-0.041921,-0.560213
1553972887002,-0.510671,-0.083841,-0.480183
1553972887002,-0.525915,-0.057165,-0.480183
1553972887002,-0.544969,-0.038110,-0.522104
1553972887098,-0.510671,-0.030488,-0.510671
1553972887098,-0.529726,-0.026677,-0.525915
1553972887098,-0.510671,-0.068598,-0.518293
I need to split each csv files in those 3 parts and name them accordingly.
I managed to do step 1) and step 3) but struggle for step 2).
Here is what I did for step 3) :
fileNames <- basename(list.files(path = ".", all.files = FALSE, full.names = FALSE, recursive = TRUE, ignore.case = FALSE, include.dirs = FALSE))
extension <- "txt"
fileNumbers <- seq(fileNames)
for (fileNumber in fileNumbers) {
newFileName <- paste("Target2-",
sub(paste("\\.", extension, sep = ""), "", fileNames[fileNumber]),
".", extension, sep = "")
# read old data:
Lines <- readLines(fileNames[fileNumber])
ix <- which(Lines == "Target2")
sample <- read.csv(fileNames[fileNumber],
header = TRUE,
sep = ",", skip= ix)
# write old data to new files:
write.table(sample,
newFileName,
append = FALSE,
quote = FALSE,
sep = ",",
row.names = FALSE,
col.names = TRUE)
}
I'm quite sure this is not the most straightforward approach and I can't get the data comprised between Target 1 and Target 2 using this approach. Also, this is super slow and I was wondering it there could be a more memory efficient approach ?
foo = function(filename) {
cat("\nprocessing", filename, "...")
x = readLines(con = filename)
idx = grepl("^Target", x)
x = split(x[!idx], cumsum(idx)[!idx])[-1]
invisible(lapply(seq_along(x), function(i) {
write.table(
x = x[[i]],
file = sub("\\.csv", paste0("_", i, ".csv"), filename),
append =FALSE,
row.names = FALSE,
quote = FALSE,
col.names = FALSE)
}))
}
files = list.files(path = "path/to/files", pattern = ".+\\.csv$")
lapply(files, foo)
I have some strings in one of the columns of my data frame that look like:
bem\\2015\black.rec
When I export the data frame into a text file using the next line:
write.table(data, file = "sample.txt", quote = FALSE, row.names = FALSE, sep = '\t')
Then in the text file the text looks like:
bem\2015BELblack.rec
Do you know an easy way to ignore all backslashes when writing the table into a text file so the backslashes are kept.
They way I have resolved this is converting backslashes into forwardslashes:
dataset <- read_delim(dataset.path, delim = '\t', col_names = TRUE, escape_backslash = FALSE)
dataset$columnN <- str_replace_all(dataset$Levfile, "\\\\", "//")
dataset$columnN <- str_replace_all(dataset$Levfile, "//", "/")
write.table(dataset, file = "sample.txt", quote = FALSE, row.names = FALSE, sep = '\t')
This exports the text imported as bem\\2015\black.rec with the required slashes: bem//2015/black.rec
I want to create a function that changes specific cells of a given CSV file(s) and saves them back into the exact same format.
I have tried to read the CSV file and write it back with the edited values, but the only way to do it without misinterpreting commas is to quote everything.
Is there a way to edit the files without putting quotes for every single value?
My guess is that there is some other way to read and write the CSV files than read.table
p.s. The csv files I want to edit are not in values seperated by columns, but have rather vague format(there may be unquoted, quoted (mostly because of a comma in a string) strings and integers in the same column/row)
Here is the code I use:
editcell = function(id,
newvalue,
row,
col,
dbpath = "C:/data/",
add = FALSE
)
{
#READ
temptable = read.table(file = file(paste0(dbpath, id, ".csv")),
header = F,
sep = ",",
dec = ".",
fill = TRUE,
quote = "",
comment.char = "",
colClasses = "character",
# nrows = 400,
stringsAsFactors = F
);
cat("There are",nrow(temptable),"rows and",
ncol(temptable),"columns.");
#EDIT
if(add == TRUE) { temptable[x,y] = paste0(temptable[x,y],newvalue)}
else {temptable[x,y] = newvalue};
#WRITE
write.table(temptable,
file=paste0(dbpath, id,".csv"),
append = F,
quote = T,
sep=",",
eol = "\n",
na = "NA",
dec = ".",
row.names=F,
col.names=F,
qmethod = "double",
fileEncoding = ""
)
}