I am using the fread function in R for reading files to data.tables objects.
However, when reading the file I'd like to skip lines that start with #, is that possible?
I could not find any mention to that in the documentation.
fread can read from a piped command that filters out such lines, like this:
fread("grep -v '^#' filename")
Not currently, but it's on the list to do.
Are the # lines at the top forming a header which is more than 30 lines long?
If so, that's come up before and the solution is :
fread("filename", autostart=60)
where 60 is chosen to be inside the block of data to be read.
From ?fread :
Once the separator is found on line autostart, the number of columns
is determined. Then the file is searched backwards from autostart
until a row is found that doesn't have that number of columns. Thus,
the first data row is found and any human readable banners are
automatically skipped. This feature can be particularly useful for
loading a set of files which may not all have consistently sized
banners. Setting skip>0 overrides this feature by setting
autostart=skip+1 and turning off the search upwards step.
The default autostart=30 might just need bumping up a bit in your case.
Or maybe skip=n or skip="string" helps :
If -1 (default) use the procedure described below starting on line autostart to find the first data row. skip>=0 means ignore autostart and take line skip+1 as the first data row (or column names according to header="auto"|TRUE|FALSE as usual). skip="string" searches for "string" in the file (e.g. a substring of the column names row) and starts on that line (inspired by read.xls in package gdata).
Related
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 some kind of logfile I'd like to read and analyse. Unfortunately the files are saved in a pretty "ugly" way (with lots of special characters in between), so I'm not able to read in just the lines with each one being an entry. The only way to separate the different entries is using regular expressions, since the beginning of each entry follows a specified pattern.
My first approach was to identify the pattern in the character vector (I use read_file from the readr-package) and use the corresponding positions to split the vector with strsplit. Unfortunately the positions seem not always to match, since the result doesn't always correspond to the entries (I'd guess that there's a problem with the special characters).
A typical line of the file looks as follows:
16/10/2017, 21:51 - George: This is a typical entry here
The corresponding regular expressions looks as follows:
([[:digit:]]{2})/([[:digit:]]{2})/([[:digit:]]{4}), ([[:digit:]]{2}):([[:digit:]]{2}) - ([[:alpha:]]+):
The first thing I want is a data.frame with each line corresponding to a specific entry (in a next step I'd split the pattern into its different parts).
What I tried so far was the following:
regex.log = "([[:digit:]]{2})/([[:digit:]]{2})/([[:digit:]]{4}), ([[:digit:]]{2}):([[:digit:]]{2}) - ([[:alpha:]]+):"
log.regex = gregexpr(regex.log, file.log)[[1]]
log.splitted = substring(file.log, log.regex, log.regex[2:355]-1)
As can be seen this logfile has 355 entries. The first ones are separated correctly. How can I separate the character vector using a regular expression without loosing the information of the regular expression/pattern?
Use capturing and non-capturing groups to identify the parts you want to keep, and be sure to use anchors:
file.log = "16/10/2017, 21:51 - George: This is a typical entry here"
regex.log = "^((?:[[:digit:]]{2})\\/(?:[[:digit:]]{2})\\/(?:[[:digit:]]{4}), (?:[[:digit:]]{2}):(?:[[:digit:]]{2}) - (?:[[:alpha:]]+)): (.*)$"
gsub(regex.log,"\\1",file.log)
>> "16/10/2017, 21:51 - George"
gsub(regex.log,"\\2",file.log)
>> "This is a typical entry here"
I've been using asd=readcsv(filename) to read a csv file in Julia.
The first row of the csv file contains strings which describe the column contents; the rest of the data is a mix of integers and floats. readcsv reads the numbers just fine, but only reads the first 4+1/2 string entries.
After that, it renders "". If I ask the REPL to display asd[1,:], it tells me it is 1x65 Array{Any,2}.
The fifth column in the first row of the csv file (this seems to be the entry it chokes on) is APP #1 bias voltage [V]; but asd[1,5] is just APP . So it looks to me as though readcsv has choked on the "#" character.
I tried using "quotes=false" keyword in readcsv, but it didn't help.
I used to use xlsread in Matlab and it worked fine.
Has anybody out there seen this sort of thing before?
The comment character in Julia is #, and this applies when reading files from delimited text files.
But luckily, the readcsv() and readdlm() functions have an optional argument to help in these situations.
You should try readcsv(filename; comment_char = '/').
Of course, the example above assumes that you don't have any / characters in your first line. If you do, then you'll have to change that / above to something else.
I am using the following code to read a file with the data.table library:
fread(myfile, header=FALSE, sep=",", skip=100, colClasses=c("character","numeric","NULL","numeric"))
but I get the following error:
The supplied 'sep' was not found on line 80. To read the file as a single character column set sep='\n'.
It says it did not find sep on line 80, however I set skip=100 so it should not pay attention to the first 100 lines.
UPDATE:
I tried with skip=101 and it worked but it skips the first line where the data starts
I am using version 1.9.2 of the data.table package and R version 3.02 64 bit on windows 7
We don't know the version number you're using, but I can make a guess in this case.
Try setting autostart=101.
Note the first paragraph of Details in ?fread :
Once the separator is found on line autostart, the number of columns is determined. Then the file is searched backwards from autostart until a row is found that doesn't have that number of columns. Thus, the first data row is found and any human readable banners are automatically skipped. This feature can be particularly useful for loading a set of files which may not all have consistently sized banners. Setting skip>0 overrides this feature by setting autostart=skip+1 and turning off the search upwards step.
the skip argument has :
If -1 (default) use the procedure described below starting on line autostart to find the first data row. skip>=0 means ignore autostart and take line skip+1 as the first data row (or column names according to header="auto"|TRUE|FALSE as usual). skip="string" searches for "string" in the file (e.g. a substring of the column names row) and starts on that line (inspired by read.xls in package gdata).
and the autostart argument has :
Any line number within the region of machine readable delimited text, by default 30. If the file is shorter or this line is empty (e.g. short files with trailing blank lines) then the last non empty line (with a non empty line above that) is used. This line and the lines above it are used to auto detect sep, sep2 and the number of fields. It's extremely unlikely that autostart should ever need to be changed, we hope.
In your case perhaps the human readable header is much larger than 30 rows, which is why I guess setting autostart=101 might work. No need to use skip.
One motivation is for convenience when a file contains multiple tables. By setting autostart to any row inside the table that you want to pluck out of the file, it'll find the first data row and header row for you automatically, and then read just that table. You don't have to worry about getting the exact line number at the start of data like you do with skip. fread can only read one table currently. It could feasibly return a list of tables from a single file, but that's getting a bit complicated and nobody has asked for that.
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.