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Import / Export - Understanding the Basics with CSV

POSTED IN: Data Analytics & Visualization Blog

We had a good "Study Group" session this Sunday - and spent much of the session covering the basics of syntax, and how to get our own data into R.  

The code can be found in the links below.  A few highlights of what we covered included

  1. READ.CSV - explored the different settings the function can receive - for example in:  LOG <- read.csv("PEAR - Log Example Microsoft.csv", skip=3, stringsAsFactors = FALSE) we saw how we can 'trim' the first three rows (junk header) and import the good data starting on Row 4
  2. TRIM TAIL - with ---  end2 <- dim(log)[1] //   end1 <- end2-4 // log <- log[-c(end1:end2),]   we saw how we can take the length of a variable log file, figure out how many rows were in it, and then 'trim' of the LAST rows of the file - in this case last four (end2-4) to delete last five rows
  3. WRITE - we saw how we can, once we finish our work - can export the file in the format we want with write.csv(log, file = "Pear_Log_Export.csv", row.names=FALSE) - in this case, row.names=FALSE ensures we don't end up with index numbers in the first column
  4. CSV formats - Dan noted that when he saved CSV local, it inserted extra 'white lines' between each row - we're not sure why (Unicode?) but will take a look this week to try to figure it out - and also find a way to remove the extra blank lines in CSV.  We did a quick experiment with remove white space / blanks, but no luck , so more homework

Sample files


R Newbies - CSV/LOG Cleanup Script


R Newbies - R Code Example - Excel tasks in R - Part 1


R Newbies - Reaching for Pivot Tables in R


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About the Author

Ryan Anderson

Ryan Anderson

Hi! I like to play with data, analytics and hack around with robots and gadgets in my garage. Lately I've been learning about machine learning.

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Created: July 25, 2014


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