R Dataframe from a Text file with 2 Byts Separator - r
if you can help with converting a big text:
sample of the text :
X1"II"ID_Sitze.x"II"Produktionsdatum.x"II"Herstellernummer.x"II"Werksnummer.x"II"Fehlerhaft.x"II"Fehlerhaft_Datum.x"II"Fehlerhaft_Fahrleistung.x"II"ID_Sitze.y"II"Produktionsdatum.y"II"Herstellernummer.y"II"Werksnummer.y"II"Fehlerhaft.y"II"Fehlerhaft_Datum.y"II"Fehlerhaft_Fahrleistung.y""1"II1II"K2LE1-109-1091-2"II2008-11-12II"109"II1091II1II2010-10-18II37080IINAIINAIINAIINAIINAIINAIINA"2"II2II"K2LE1-109-1091-1"II2008-11-12II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"3"II3II"K2LE1-109-1091-12"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"4"II4II"K2LE1-109-1091-5"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"5"II5II"K2LE1-109-1091-40"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"6"II6II"K2LE1-109-1091-15"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"7"II7II"K2LE1-109-1091-31"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"8"II8II"K2LE1-109-1091-6"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"9"II9II"K2LE1-109-1091-8"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"10"II10II"K2LE1-109-1091-25"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"11"II11II"K2LE1-109-1091-24"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"12"II12II"K2LE1-109-1091-36"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"13"II13II"K2LE1-109-1091-33"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"14"II14II"K2LE1-109-1091-42"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"15"II15II"K2LE1-109-1091-14"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"16"II16II"K2LE1-109-1091-21"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"17"II17II"K2LE1-109-1091-43"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"18"II18II"K2LE1-109-1091-44"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"19"II19II"K2LE1-109-1091-19"II2008-11-13II"109"II1091II1II2010-10-19II37
with separator "II" to a Dataframe.
i have used :
df_BSt7<-readLines("Komponente_K2LE1.txt")
df_BST7<-str_replace_all(df_BSt7,"II",",")
df_BST7<-read.table(df_BST7,sep = ",")
head(df_BST7)
but I am always getting an Error
could not allocate memory (206 Mb) in C function 'R_AllocStringBuffer'
and when i call head() I am getting
'"X1","ID_Sitze.x","Produktionsdatum.x","Herstellernummer.x","Werksnummer.x","Fehlerhaft.x","Fehlerhaft_Datum.x","Fehlerhaft_Fahrleistung.x","ID_Sitze.y","Produktionsdatum.y","Herstellernummer.y","Werksnummer.y","Fehlerhaft.y","Fehlerhaft_Datum.y","Fehlerhaft_Fahrleistung.y""1",1,"K2LE1-109-1091-2",2008-11-12,"109",1091,1,2010-10-18,37080,NA,NA,NA,NA,NA,NA,NA"2",2,"K2LE1-109-1091-1",2008-11-12,"109",1091,0,NA,0,NA,NA,NA,NA,NA,NA,NA"3",3,"K2LE1-109-1091-12",2008-11-13,"109",1091,0,NA,0,NA,NA,NA,NA,NA,NA,NA"4",4,"K2LE1-109-1091-5",2008-11-13,"109",1091,0,NA,0,NA,NA,NA,NA,NA,NA,NA"5",5,"K2LE1-109-1091-40",2008-11-13,"109",1091,0,NA,0,NA,NA,NA,NA,NA,NA,NA"6",6,"K2LE1-109-1091-15",2008-11-13,"109",1091,0,NA,0,NA,NA,NA,NA,NA,NA,NA"7",7,"K2LE1-109-1091-31",2008-11-13,"109",1091,0,NA,0,NA,NA,NA,NA,NA,NA,NA"8",8,"K2LE1-109-1091-6",2008-11-13,"109",1091,0,NA,0,NA,NA,NA,NA,NA,NA,NA"9",9,"K2LE1-109-1091-8",2008-11-13,"109",1091,0,NA,0,NA,NA,NA,NA,NA,NA,NA"10",10,"K2LE1-109-109 [... abgeschnitten]
So, there are several possible problems, some might be specific to your examples.
Clean example data
First, let's take a look at your example data. In what you provide, there are no newlines, everything is on a single line. Is that the case in the original "Komponente_K2LE1.txt" file? If yes, we might need some more work to find where to add newlines (see below).
The first column name, X1, only has a quote on the right. It can't work without the quote on the left: "X1"IIID_Sitze.
The saved dataframe has 16 columns, I expect because there is a row number at the beginning of each row which is not in the header. So we can add an additional column header to have 16 of them:
"row_nb"II"X1"II"ID_Sitze.x"II"Produktionsdatum.x"II"Herstellernummer.x"II"Werksnummer.x"II"Fehlerhaft.x"II"Fehlerhaft_Datum.x"II"
Then we have a small problem with line 19 which is truncated, I assume it comes from your copy/paste and that's not a problem with the full file. So let's forget about it for now. So I have this text:
raw_lines <- '"row_nb"II"X1"II"ID_Sitze.x"II"Produktionsdatum.x"II"Herstellernummer.x"II"Werksnummer.x"II"Fehlerhaft.x"II"Fehlerhaft_Datum.x"II"Fehlerhaft_Fahrleistung.x"II"ID_Sitze.y"II"Produktionsdatum.y"II"Herstellernummer.y"II"Werksnummer.y"II"Fehlerhaft.y"II"Fehlerhaft_Datum.y"II"Fehlerhaft_Fahrleistung.y"
"1"II1II"K2LE1-109-1091-2"II2008-11-12II"109"II1091II1II2010-10-18II37080IINAIINAIINAIINAIINAIINAIINA
"2"II2II"K2LE1-109-1091-1"II2008-11-12II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"3"II3II"K2LE1-109-1091-12"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"4"II4II"K2LE1-109-1091-5"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"5"II5II"K2LE1-109-1091-40"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"6"II6II"K2LE1-109-1091-15"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"7"II7II"K2LE1-109-1091-31"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"8"II8II"K2LE1-109-1091-6"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"9"II9II"K2LE1-109-1091-8"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"10"II10II"K2LE1-109-1091-25"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"11"II11II"K2LE1-109-1091-24"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"12"II12II"K2LE1-109-1091-36"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"13"II13II"K2LE1-109-1091-33"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"14"II14II"K2LE1-109-1091-42"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"15"II15II"K2LE1-109-1091-14"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"16"II16II"K2LE1-109-1091-21"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"17"II17II"K2LE1-109-1091-43"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"18"II18II"K2LE1-109-1091-44"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA'
Now you are replacing "II" with "," and reading it with read.table(), which is perfectly correct, except that read.table() would assume you're giving a file name and throw an error as it can't open that connection (that file). To make it work you need this:
df_BST7<-str_replace_all(raw_lines,'II',",")
df_BST7 <- read.table(text = df_BST7,sep = ",")
So now that does run on my computer.
Side note, since you're already using the tidyverse, you could as well use that equivalent code instead:
df_BST7 <- str_replace_all(raw_lines,'II',",")
df_BST7 <- read_csv(df_BST7)
which could help with something later
The error message
Now the error message you get suggests it's a memory problem. I see 2 possibilities: the table is so big it can't fit in your computer's memory, or indeed your whole input table is on a single line, so that makes a very long line, which won't fit in memory.
Whole table too big
I don't think it's the problem here, but just in case, check how big the file on the disk is, and how much memory is free on your computer, and whether you could free up enough memory by just closing a few programs. Possibly you could save your modified text to disk and delete it from R's memory with rm(df_BSt7), then load it directly from disk into df_BST7. Since the raw text fits in memory, that should work. If memory is a challenge, you can replace read_csv() with read_csv_chunked() and process one chunk at a time.
All on one line
I think this is the most likely. Again, there are two possibilities.
Missing carriage return
Actually line breaks can be described in 2 ways, Unix-like systems (MacOS and GNU/Linux) use the symbol newline (\n), whereas Windows uses a pair of carriage return and newline (\r\n). I'm not sure how this could create problems inside R, but if your file was generated on a Unix-like system and you're trying to read it on Windows that's an explanation. Then the goal would become to replace \n with \r\n.
No line breaks at all
If there is absolutely no line break, neither \r nor \n, then we need to guess where they are. On a Unix system you could try awk or sed, but there are ways to do it in R. The following code should work, except the last column will need some cleaning up afterwards:
raw_lines2 <- str_remove_all(raw_lines2, "\r")
all_fields <- raw_lines2 %>%
str_split("II") %>%
unlist()
nb_lines <- (length(all_fields) - 1)/15
reconstruct_lines <- map_chr(0:(nb_lines-1), ~ paste(all_fields[(2+15*.):(16+15*.)], collapse = ",")) %>%
paste(collapse = "\n")
cat(reconstruct_lines)
Related
Loading CSV with fread stops because of to large string
This is the command I'm using :
dallData <- fread("data.csv", showProgress = TRUE, colClasses = c(rep("NULL", 2), "character", rep("NULL", 37)))
but I get this error when trying to load it: R character strings are limited to 2^31-1 bytes|
Anyway to skip those values ?
Here's a strategy that may work or at least narrow down the possible sources of error. It assumes you have enough working memory to hold the data and that your separators are really commas. If you actually have tabs as separators then you will need to modify accordingly. The plan is to read using readLines which will basically ignore the quotes that are probably mismatched. Then figure out which line or lines are at fault using count.fields, table, and which.
input <- readLines("data.csv") # ignores quotes
counts.def <- count.fields(textConnection(input),
sep=",") # defaults quotes are both ' and "
table(counts.def) # might show a variety of line counts.
# Second try with just double-quotes
counts.dbl <- count.fields(textConnection(input),
sep=",", quote="\"") # just dbl-quotes
table(counts.dbl) # if all the same, then all you do is change the quotes argument
Depending on the results you may need to edit cerain lines which can be identified using which(counts.def < 40) assuming most of them are 40 as your input efforts suggest is the expected number of fields per line.
(If the tag for [ram] means you are limited and getting warnings or using virtual memory which slows things down horribly, then you should restart your OS, and only load R before trying again. R needs contiguous block of memory and Windoze isn't very good at memory management.)
Here's a small test case to work with:
input <- readLines(textConnection(
"v1,v2,v3,v4,v5,v6
text, text, text, text, text, text
text, text, O'Malley, text,text,text
junk,junk, more junk, \"text\", tex\"t, nothing
3,4,5,6,7,8")
readline is considering every record in the spreadsheet as a new line [R]
I am trying to create a function that will calculate the frequency count of keywords using TM package. The function works fine if the text pasted from readline is on free form text without a new line. The problem is, when I paste a bunch of text copied from a spreadsheet, readline considers it as a new line.
keyword <- function() {
x <- readline(as.character('Input text here: '))
x <- Corpus(VectorSource(x))
...
tdm <- TermDocumentMatrix(x)
...
tdm
}
Here's the full code: https://github.com/CSCDataAnalytics/PM-Analysis/blob/master/Keyword.R
How can I prevent this from happening or at least consider a bunch of text of every row from the spreadsheet as one vector only?
If I'm understanding you correctly, the problem is when the user pastes the text from another application: the newline is causing R to stop accepting the subsequent lines.
One technique (fragile as it may be) is to look for a specific line, such as an empty line "" or a period ".". It's a little fragile because now you need (1) assurance that the data will "never" include that as a whole line, and (2) it is easily appended by the user.
Try:
endofinput <- ""
totalstr <- ""
while(! endofinput == (x <- readline('prompt (empty string when done): ')))
totalstr <- paste(totalstr, x)
In this case, the empty string is the catch, and when the while loop is done, totalstr contains all input separated by a space (this can be changed in the paste function).
NB: one problem with this technique is that it is "growing" the vector totalstr, which will eventually cause performance penalties (depending on the size of the input data): every loop iteration, more memory is allocated and the entire string is copied plus the new line of text. There are more verbose ways to side-step this problem (e.g., pre-allocate a vector larger than your anticipated input data), but if you aren't anticipated 1000s of lines then you may be able to accept this naive programming for simplicity.
Another option would be to have the user save the data to a text file and use file.choose() and readLines() to get your data.
Try collapsing the data into a single string after using readline
x <- paste(readline(as.character('Input text here: ')), collapse=' ')
un-quote an R string?
TL;DR
I have a snippet of text
str <- '"foo\\dar embedded \\\"quote\\\""'
# cat(str, '\n') # gives
# "foo\dar embedded \"quote\""
# i.e. as if the above had been written to a CSV with quoting turned on.
I want to end up with the string:
str <- 'foo\\dar embedded "quote"'
# cat(str, '\n') # gives
# foo\dar embedded "quote"
essentially removing one "layer" of quoting. How may I do this?
(Initial attempt -- eval(parse(text=str)), which works unless you have something like \\dar, where you get the error "\d is an unrecognized escape in character string ...").
Gory details (optional)
The reason my strings are quoted once-too-many times is I kludged some data processing -- I wrote str (well, a dataframe in my case) to a table with quoting enabled, but forgot that many of the columns in my dataframe had embedded newlines with embedded quotes (i.e. forgot to escape/remove them).
It turns out that when I read.table a file with multiple columns in the same row that have embedded newlines and embedded quotes (or something like that), the function fails (fair enough).
I had since closed my R session so my only access to my data was through my munged CSV. So I wrote some spaghetti code to simply readLines my CSV and split everything up to reconstruct my dataframe again. However, since all my character columns were quoted in the CSV, I have a few columns in my restored dataframe that are still quoted that I want to unquote.
Messy, I know. I'll remember to save an original version of the data next time (save, saveRDS).
For those interested, the header row and three rows of my CSV are shown below (all the characters are ASCII)
"quote";"id";"date";"author";"context"
"< mwk> I tried to fix the bug I mentioned, but I accidentally ascended the character I started for testing... hoped she'd die soon and I could get to coding, but alas I was wrong";"< mwk> I tried to fix the bug I mentioned, but I accidentally ascended the character I started for testing... hoped she'd die soon and I could get to coding, but alas I was wrong";"February 28, 2013";"nhqdb";"nhqdb"
"< intx14> \"A gush of water hits the air elemental on the central core!\"
< intx14> What is this, a weather forecast?";"< intx14> \"A gush of water hits the air elemental on the central core!\"
< intx14> What is this, a weather forecast?";"February 28, 2013";"nhqdb";"nhqdb"
"< bcode> n - a spherical amulet. You are lucky! Full moon tonight.
< bcode> That must be a sign - I'll put it on! What could possibly go wrong...
< oracle\devnull> DIED : bcode2 (Wiz-Elf-Mal-Cha) 0 points, killed by strangulation on pcs1.nethack.devnull.net";"< bcode> n - a spherical amulet. You are lucky! Full moon tonight.
< bcode> That must be a sign - I'll put it on! What could possibly go wrong...
< oracle\devnull> DIED : bcode2 (Wiz-Elf-Mal-Cha) 0 points, killed by strangulation on pcs1.nethack.devnull.net";"February 28, 2013";"nhqdb";"nhqdb"
The first two columns of each row are the same, being the quote (the first row has no embedded newlines in the quote; the second and third do). Separator is ';'.
> read.table('test.csv', sep=';', header=T)
Error in scan(file, what, nmax, sep, dec, quote, skip, nlines, na.strings, :
line 1 did not have 5 elements
# same for with ,allowEscape=T
Use regular expressions:
str <- gsub('^"|"$', '', gsub('\\\"', '"', str, fixed = TRUE))
[EDIT 3: the OP has posted three separate versions of this - two of them irreproducible, interspersed with complaining. Due to this timewasting behavior and several people downvoting, I'm leaving the original answer to version 2 of the question.]
EDIT 1: My solution to the second version of the OP's question was this:
txt <- read.csv('escaped.csv', header=T, allowEscapes=T, sep=';')
EDIT 2: We now get a third version. Finally some reproducible code after 36 minutes asking and waiting. Due to the behavior of the OP and other posters I'm not inclined to waste more time on this. I'm going to complain about both of your behavior on MSO. Downvote yourselves silly.
ORIGINAL:
gsub is the ugly way.
Use read.csv(..., allowEscapes=TRUE, quote=..., encoding=...) arguments. See the manpage, section on Encoding
If you want actual code, you need to give us a full line or two of your CSV file.
See also SO: "How to detect the right encoding for read.csv?"
Quoting the relevant part of your question:
The reason my strings are quoted once-too-many times is I kludged some
data processing -- I wrote str (well, a dataframe in my case) to a
table with quoting enabled, but forgot that many of the columns in my
dataframe had embedded newlines within quotes (i.e. forgot to
escape/remove them).
It turns out that when I read.table a file with multiple columns in
the same row that have embedded newlines within quotes, the function
fails (fair enough).
Read lines by number from a large file
I have a file with 15 million lines (will not fit in memory). I also have a small vector of line numbers - the lines that I want to extract. How can I read-out the lines in one pass? I was hoping for a C function that does it on one pass.
The trick is to use connection AND open it before read.table:
con<-file('filename')
open(con)
read.table(con,skip=5,nrow=1) #6-th line
read.table(con,skip=20,nrow=1) #27-th line
...
close(con)
You may also try scan, it is faster and gives more control.
If it's a binary file Some discussion is here: Reading in only part of a Stata .DTA file in R If it's a CSV or other text file If they are contiguous and at the top of the file, just use the ,nrows argument to read.csv or any of the read.table family. If not, you can combine the ,nrows and the ,skip arguments to repeatedly call read.csv (reading in a new row or group of contiguous rows with each call) and then rbind the results together.
If your file has fixed line lengths then you can use 'seek' to jump to any character position. So just jump to N * line_length for each N you want, and read one line. However, from the R docs: Use of seek on Windows is discouraged. We have found so many errors in the Windows implementation of file positioning that users are advised to use it only at their own risk, and asked not to waste the R developers' time with bug reports on Windows' deficiencies. You can also use 'seek' from the standard C library in C, but I don't know if the above warning also applies!
Before I was able to get an R solution/answer, I've done it in Ruby:
#!/usr/bin/env ruby
NUM_SEQS = 14024829
linenumbers = (1..10).collect{(rand * NUM_SEQS).to_i}
File.open("./data/uniprot_2011_02.tab") do |f|
while line = f.gets
print line if linenumbers.include? f.lineno
end
end
runs fast (as fast as my storage can read the file).
I compile a solution based on the discussions here. scan(filename,what=list(NULL),sep='\n',blank.lines.skip = F) This will only show you number of lines but will read in nothing. If you really want to skip the blank lines, you could just set the last argument to TRUE.
R - read.table imports half of the dataset - no errors nor warnings
I have a csv file with ~200 columns and ~170K rows. The data has been extensively groomed and I know that it is well-formed. When read.table completes, I see that approximately half of the rows have been imported. There are no warnings nor errors. I set options( warn = 2 ). I'm using 64-bit latest version and I increased the memory limit to 10gig. Scratching my head here...no idea how to proceed debugging this. Edit When I said half the file, I don't mean the first half. The last observation read is towards the end of the file....so its seemingly random.
You may have a comment character (#) in the file (try setting the option comment.char = "" in read.table). Also, check that the quote option is set correctly.
I've had this problem before how I approached it was to read in a set number of lines at a time and then combine after the fact. df1 <- read.csv(..., nrows=85000) df2 <- read.csv(..., skip=84999, nrows=85000) colnames(df1) <- colnames(df2) df <- rbind(df1,df2) rm(df1,df2)
I had a similar problem when reading in a large txt file which had a "|" separator. Scattered about the txt file were some text blocks that contained a quote (") which caused the read.xxx function to stop at the prior record without throwing an error. Note that the text blocks mentioned were not encased in double quotes; rather, they just contained one double quote character here and there (") which tripped it up.
I did a global search and replace on the txt file, replacing the double quote (") with a single quote ('), solving the problem (all rows were then read in without aborting).