Is it possible to get the number of rows in a CSV file without opening it?

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I have a CSV file of size ~1 GB, and as my laptop is of basic configuration, I'm not able to open the file in Excel or R. But out of curiosity, I would like to get the number of rows in the file. How am I to do it, if at all I can do it?

For Linux/Unix:

wc -l filename

For Windows:

find /c /v "A String that is extremely unlikely to occur" filename

Is it possible to get the number of rows in a CSV file without opening it?, For Linux/Unix: wc -l filename. For Windows: find /c /v "A String that is extremely unlikely to occur" filename. You can always read the file as you normally would, then parse the entire row set, counting each iteration. Other people have suggested to just read CR LF, but this is WRONG, since a true CSV parser will perhaps include CR LF embedded in a field value. You can't just count lines, you have to be smarter than the CSV file you're trying to read.

Option 1:

Through a file connection, count.fields() counts the number of fields per line of the file based on some sep value (that we don't care about here). So if we take the length of that result, theoretically we should end up with the number of lines (and rows) in the file.

length(count.fields(filename))

If you have a header row, you can skip it with skip = 1

length(count.fields(filename, skip = 1))

There are other arguments that you can adjust for your specific needs, like skipping blank lines.

args(count.fields)
# function (file, sep = "", quote = "\"'", skip = 0, blank.lines.skip = TRUE, 
#     comment.char = "#") 
# NULL

See help(count.fields) for more.

It's not too bad as far as speed goes. I tested it on one of my baseball files that contains 99846 rows.

nrow(data.table::fread("Batting.csv"))
# [1] 99846

system.time({ l <- length(count.fields("Batting.csv", skip = 1)) })
#   user  system elapsed 
#  0.528   0.000   0.503 

l
# [1] 99846
file.info("Batting.csv")$size
# [1] 6153740

(The more efficient) Option 2: Another idea is to use data.table::fread() to read the first column only, then take the number of rows. This would be very fast.

system.time(nrow(fread("Batting.csv", select = 1L)))
#   user  system elapsed 
#  0.063   0.000   0.063 

Maximum number of rows of CSV data in excel sheet, How do you count the number of rows without opening an Excel file? Your code is pretty much exactly what I need - I have a lengthy excel file and I want to know how many rows it has without actually opening it. The problem is, when I try to use your macro with an excel file instead of .csv file, it always just returns 1.

Estimate number of lines based on size of first 1000 lines

size1000  <- sum(nchar(readLines(con = "dgrp2.tgeno", n = 1000)))

sizetotal <- file.size("dgrp2.tgeno")
1000 *  sizetotal / size1000

This is usually good enough for most purposes - and is a lot faster for huge files.

How to count the number of lines in a CSV file in Python, How do I count the number of rows in a csv file in Python? Through a file connection, count.fields() counts the number of fields per line of the file based on some sep value (that we don't care about here). So if we take the length of that result, theoretically we should end up with the number of lines (and rows) in the file.

Here is something I used:

testcon <- file("xyzfile.csv",open="r")
readsizeof <- 20000
nooflines <- 0
( while((linesread <- length(readLines(testcon,readsizeof))) > 0 ) 
nooflines <- nooflines+linesread )
close(testcon)
nooflines

Check out this post for more: https://www.r-bloggers.com/easy-way-of-determining-number-of-linesrecords-in-a-given-large-file-using-r/

What is the maximum size CSV file you can upload?, up vote 6 down vote. First you have to open the file with open input_file At the last, you can take the number of row with the instruction 'len' Simply opening th CSV file in AA and looping through it you can easily have an IF statement to filter a particular value and act accordingly. If you are dealing with larger datasets you can either use the method above with the database command or you can create a dll which will read the csv file into a datatable

Row count in a csv file, Hi Friends, I have 394 excel sheet or CSV files in one folder in data is in same format in give us the coun of number of used rows in a worksheet without opening the file: Can you make it to count from column number 419. You would have to open the file reading in each line to get the count: var lines = File.ReadAllLines(filename); var count = lines.Length; share | improve this answer | follow | | | |

how-to-count-the-number-of-rows-without-opening-an-excel-file, Now let's have a look at that file… SET ROWCOUNT ON. Looks like someone (​me) has exported data from SQL Server without adding SET  Simply Open the csv file in Notepad++. It shows the total row count in a jiffy. :) Or in cmd prompt , Provide file path and key in the command find \c \v "some meaningless string" Filename.csv

Count rows within CSV files using PowerShell, Create a CSV reader by calling the function csv.reader(csvfile) with csvfile as the result of the previous step. Get a list representation of the CSV file by calling list  I think it might be noteworthy that the row names ARE NOT a column in the table. This is a common misunderstanding for new users, which I admit happened to me. In R the row names do not impact data handling, I.E. you do not need to skip the first

Comments
  • Maybe just wc -l yourfile.csv from a command line prompt, or something?
  • If the file size is 1 GB you should be able to import it. Of course, you shouldn't do this with read.table and friends. Use fread from package data.table.
  • so you're saying that nrow(read.csv("file.csv", header= T/F)) crashes R? And yes, fread certainly prefered
  • @Alex Don't use read.csv with a 1 GB file. It's slow.
  • If all methods crash, you can use csv splitter to break the big file into chunks.. Not elegant, but might work
  • Regarding the "Windows" solution, note that: (1) this is run from cmd.exe; (2) filename includes the full path to the file (& turn the slashes around); (3) if there's a header, that 'row' is counted, ie, a file with a header + 10 rows will result in returning 11. (None of this detracts from the quality of the answer.)
  • #option 2 is better. data.table for the win.