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    <p>Yes. Two methods. The easiest to understand at first is probably just to is <code>as.is=TRUE</code> to preserve them as character vectors and then use <code>gsub</code> to remove the commas and any currency symbols before converting to numeric. The second is a bit more difficult, but I think more kewl. Create an as-method for the format you are using. Then you can use <code>colClasses</code> to do it in one step.</p> <p>I see @EDi already did version #1 (using <code>stringsAsFactors</code> rather than <code>as.is</code>, so I will document strategy #2:</p> <pre><code> library(methods) setClass("num.with.commas") #[1] "num.with.commas" setAs("character", "num.with.commas", function(from) as.numeric(gsub(",", "", from))) require(RCurl) #Loading required package: RCurl #Loading required package: bitops myCsv &lt;- getURL("https://docs.google.com/spreadsheet/pub?hl=en_US&amp;hl=en_US&amp;key=0Agbdciapt4QZdE95UDFoNHlyNnl6aGlqbGF0cDIzTlE&amp;single=true&amp;gid=0&amp;range=A1%3AG4928&amp;output=csv", ssl.verifypeer=FALSE) &gt; fullmatrix &lt;- read.csv(textConnection(myCsv), colClasses=c(rep("num.with.commas",2), rep("numeric",4) )) str(fullmatrix) #-------------- 'data.frame': 4927 obs. of 7 variables: $ wave. : num 9999 9997 9995 9993 9992 ... $ wavelength : num 1000 1000 1000 1001 1001 ... $ d2o : num 85.2 87.7 86.3 87.6 85.6 ... $ di : num 54.3 55.8 54.9 55.6 54.9 ... $ ddw : num 48.2 49.7 49.4 50.2 49.6 ... $ ddw.old : num 53.3 55 53.9 54.8 53.7 ... $ d2o.ddw.mix: num 65.8 67.9 67.2 68.4 66.8 ... </code></pre> <p>as-methods are coercive. There are many such methods in base R, such as <code>as.list</code>, <code>as.numeric</code>, <code>as.character</code>. In each case they attempt to take input that is in one mode and make a sensible copy of that in a different mode. For instance, it makes sense to coerce a matrix to a dataframe because they both have two dimensions. It makes a bit less sense to coerce a dataframe to a matrix (but it does succeed with loss of all the attributes of the columns and coercion to a common mode.)</p> <p>In the present case I am taking a character string as input, removing any commas, and coercing the character values to numeric. Then I use <code>read.table</code>'s ( in this case by way of <code>read.csv</code>) 'colClasses' argument to dispatch to the as-method I registered with <code>setAs</code>. You may want to go to the <code>help(setAs)</code> page for more details. The S4 class system confuses a lot of people, me included. This is about the only area of success I have had with S4 methods. </p>
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    1. POGoogle Docs exports spreadsheet values with commas. read.csv() in R treats these as factors instead of numeric
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    1. COThanks! Agree very cool. It works for me, but don't fully understand...yet :)
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    2. COI will add some more explanatory text.
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