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POWeighted means for all columns in R data.frame
 

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  1. POWeighted means for all columns in R data.frame
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    <p>I have a 32x43 data.frame called "allg2", and I recreated a small portion of it here as 5x5 for simplicity:</p> <pre><code>gneiss mylonite syenite sedimentary Catg 0 3 4 0 -105.7 2 90 1 0 -99.7 15 51 0 0 -95.25 6 0 0 0 -90.5 0 3 9 0 -85.45 </code></pre> <p>As requested, a sample calculation: The 'gneiss' column would be wm=(0/21*-105.7)+(2/21*-99.7)+(15/21*-95.25)+(6/21*-90.5)+(0/21*-85.45) </p> <p>I would like a weighted mean for each column (with the values of interest in Catg, and each column as the weights for that column), but each solution to this that I can find relies on coding in all of the column names. Is it possible to do this without such a list? Note: I just realized that I have been flipping the weights and values to weigh the entire time. My attempts:</p> <pre><code>wm=allg2[,lapply(.SD,weighted.mean,w=Catg),by=list(allg2[1,])] Error: unused argument (by = list(allg2[1, ])) </code></pre> <p>I found this idea from <a href="https://stackoverflow.com/questions/14145859/weighted-means-by-group-and-column">this thread</a>, and tried to adapt it to my situation. Is it not selecting the column names because they're not a true row? I don't really know what this is doing, and I tried temoving the by= part, which gives the error</p> <pre><code> Error in lapply(.SD, weighted.mean, w = Catg) : object '.SD' not found </code></pre> <p>Another attempt was based on <a href="https://stackoverflow.com/questions/9864631/weighted-mean-by-row">this thread</a>. "Catg" is in the 43rd column, so I tried organizing the line as such:</p> <pre><code>wm=apply(allg2, 2, function(x) weighted.mean(x[,43], x[,1:42])) Error in x[, 43] : incorrect number of dimensions </code></pre> <p>I really don't understand this error, because my column of weights should be in [,43].</p> <p>I have also tried: </p> <pre><code>mallg=data.matrix(allg2) wm=colWeightedMeans(mallg,allg2$Catg) Error in colWeightedMeans.matrix(mallg, allg2$Catg) : Argument 'w' has negative weights. </code></pre> <p>I'm really at a loss here. Am I making some small error or am I going about this the completely wrong way?</p>
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    1. COYou've edited the question, it's too confusing. Could you please do a weighted mean by hand so that we can understand your problem?
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    2. COGladly, sorry for any confusion. The 'gneiss' column would be wm=(0/21*-105.7)+(2/21*-99.7)+(15/21*-95.25)+(6/21*-90.5)+(0/21*-85.45)
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    3. COYou should realize that dataframes are NOT the same as `data.table` objects. You are using `data.table` code on dataframes in your first erroneous attempt, and that's just not the way to succeed.
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