Hello
Apologies if this is a simple question, I have searched the help and have not managed to work out a solution. Does anybody know an efficient method for reading many text files of the same format into one table/dataframe? I have around 90 files that contain continuous data over 3 months but that are split into individual days data and I need the whole 3 months in one file for analysis. Each days file contains a large amount of data (approx 30MB each) and so I need a memory efficient method to merge all of the files into the one dataframe object. From what I have read I will probably want to avoid using for loops etc? All files are in the same directory, none have a header row, and each contain around 180,000 rows and the same 25 columns/variables. Any suggested packages/routines would be very useful. Thanks Jennifer ----------------------------------------- *******************************************************************If you are not the intended recipient, please notify our Help Desk at Email postmas...@nats.co.uk immediately. You should not copy or use this email or attachment(s) for any purpose nor disclose their contents to any other person. NATS computer systems may be monitored and communications carried on them recorded, to secure the effective operation of the system and for other lawful purposes. Please note that neither NATS nor the sender accepts any responsibility for viruses or any losses caused as a result of viruses and it is your responsibility to scan or otherwise check this email and any attachments. NATS means NATS (En Route) plc (company number: 4129273), NATS (Services) Ltd (company number 4129270), NATSNAV Ltd (company number: 4164590) or NATS Ltd (company number 3155567) or NATS Holdings Ltd (company number 4138218). All companies are registered in England and their registered office is at 5th Floor, Brettenham House South, Lancaster Place, London, WC2E 7EN. ********************************************************************** [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.