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)
Update 2020-5-14
Working with a different but similar dataset from here, I found read_csv seems to work fine. I haven't tried it with the original data yet though.
Although the replies didn't help solve the problem because my question was not correct, Shan's reply fits the original question I posted the most, so I accepted his answer.
Update 2020-5-12
I think my original question is not correct. Like mentioned in the comment, the data was quoted. Although changing the separator made the 11582 row in R look the same as the 11583 row in excel, it doesn't mean it's "right". Maybe there is some incorrect line switch due to inappropriate encoding or something, and thus causing some of the columns to be displaced. If I open the data with notepad++, the instance at row 11583 in excel is at the 11596 row.
Original question
I am trying to read the listings.csv from this dataset in kaggle into R. I downloaded the file and wrote the coderead.csv('listing.csv'). The first column, the column id, is supposed to be numeric. However, it shows:
listing$id[1:10]
[1] 2015 2695 3176 3309 7071 9991 14325 16401 16644 17409
13129 Levels: Ole Berl穩n!,16736423,Nerea,Mitte,Parkviertel,52.55554132116211,13.340658248460871,Entire home/apt,36,6,3,2018-01-26,0.16,1,279\n17312576,Great 2 floor apartment near Friederich Str MITTE,116829651,Selin,Mitte,Alexanderplatz,52.52349354926847,13.391003496971203,Entire home/apt,170,3,31,2018-10-13,1.63,1,92\n17316675,80簡 m of charm in 3 rooms with office space,116862833,Jon,Neuk繹lln,Schillerpromenade,52.47499080234379,13.427509313575928...
I think it is because there are values with commas in the second column. For example, opening the file with MiCrosoft excel, I can see one of the value in the second column is Ole,Ole...:
How can I read a csv file into R correctly when some values contain commas?
Since you have access to the data in Excel, you can 'Save As' in Excel with a seperator other than comma (,). First go in to Control Panel –> Region and Language -> Additional settings, you can change the "List Seperator". Most common one other than comma is pipe symbol (|). In R, when you read_csv, specify the seperator as '|'.
You could try this?
lsitings <- read.csv("listings.csv", stringsAsFactors = FALSE)
listings$name <- gsub(",","", listings$name) - This will remove the comma in Col name
If you don't need the information in the second column, then you can always delete it (in Excel) before importing into R. The read.csv function, which calls scan, can also omit unwanted columns using the colClasses argument. However, the fread function from the data.table package does this much more simply with the drop argument:
library(data.table)
listings <- fread("listings.csv", drop=2)
If you do need the information in that column, then other methods are needed (see other solutions).
I've got a strange text file with a bunch of NUL characters in it (actually about 10 such files), and I'd like to programmatically replace them from within R. Here is a link to one of the files.
With the aid of this question I've finally figured out a better-than-ad-hoc way of going into each file and find-and-replacing the nuisance characters. It turns out that each pair of them should correspond to one space ([NUL][NUL]->) to maintain the intended line width of the file (which is crucial for reading these as fixed-width further down the road).
However, for robustness' sake, I prefer a more automable approach to the solution, ideally (for organization's sake) something I could add at the beginning of an R script I'm writing to clean up the files. This question looked promising but the accepted answer is insufficient - readLines throws an error whenever I try to use it on these files (unless I activate skipNul).
Is there any way to get the lines of this file into R so I could use gsub or whatever else to fix this issue without resorting to external programs?
You want to read the file as binary then you can substitute the NULs, e.g. to replace them by spaces:
r = readBin("00staff.dat", raw(), file.info("00staff.dat")$size)
r[r==as.raw(0)] = as.raw(0x20) ## replace with 0x20 = <space>
writeBin(r, "00staff.txt")
str(readLines("00staff.txt"))
# chr [1:155432] "000540952Anderson Shelley J FW1949 2000R000000000000119460007620 3 0007000704002097907KGKG1616"| __truncated__ ...
You could also substitute the NULs with a really rare character (such as "\01") and work on the string in place, e.g., let's say if you want to replace two NULs ("\00\00") with one space:
r = readBin("00staff.dat", raw(), file.info("00staff.dat")$size)
r[r==as.raw(0)] = as.raw(1)
a = gsub("\01\01", " ", rawToChar(r), fixed=TRUE)
s = strsplit(a, "\n", TRUE)[[1]]
str(s)
# chr [1:155432] "000540952Anderson Shelley J FW1949 2000R000000000000119460007620 3 0007000704002097907KGKG1616"| __truncated__
I'm trying to read in a .csv file from the IRS and it doesn't appear to be formatted in any weird way.
I'm using the read.table() function, which I have used several times in the past but it isn't working this time; instead, I get this error:
data_0910<-read.table("/Users/blahblahblah/countyinflow0910.csv",header=T,stringsAsFactors=FALSE,colClasses="character")
Error in read.table("/Users/blahblahblah/countyinflow0910.csv", :
more columns than column names
Why is it doing this?
For reference, the .csv files can be found at:
http://www.irs.gov/uac/SOI-Tax-Stats-County-to-County-Migration-Data-Files
(The ones I need are under the county to county migration .csv section - either inflow or outflow.)
It uses commas as separators. So you can either set sep="," or just use read.csv:
x <- read.csv(file="http://www.irs.gov/file_source/pub/irs-soi/countyinflow1011.csv")
dim(x)
## [1] 113593 9
The error is caused by spaces in some of the values, and unmatched quotes. There are no spaces in the header, so read.table thinks that there is one column. Then it thinks it sees multiple columns in some of the rows. For example, the first two lines (header and first row):
State_Code_Dest,County_Code_Dest,State_Code_Origin,County_Code_Origin,State_Abbrv,County_Name,Return_Num,Exmpt_Num,Aggr_AGI
00,000,96,000,US,Total Mig - US & For,6973489,12948316,303495582
And unmatched quotes, for example on line 1336 (row 1335) which will confuse read.table with the default quote argument (but not read.csv):
01,089,24,033,MD,Prince George's County,13,30,1040
you have have strange characters in your heading # % -- or ,
For the Germans:
you have to change your decimal commas into a Full stop in your csv-file (in Excel:File -> Options -> Advanced -> "Decimal seperator") , then the error is solved.
Depending on the data (e.g. tsv extension) it may use tab as separators, so you may try sep = '\t' with read.csv.
This error can get thrown if your data frame has sf geometry columns.
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).