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    <p>if you have a dataframe where some columns are numeric and some are other (character or factor) and you only want to do the correlations for the numeric columns, you could do the following:</p> <pre><code>set.seed(10) x = as.data.frame(matrix(rnorm(100), ncol = 10)) x$L1 = letters[1:10] x$L2 = letters[11:20] cor(x) Error in cor(x) : 'x' must be numeric </code></pre> <p>but</p> <pre><code>cor(x[sapply(x, is.numeric)]) V1 V2 V3 V4 V5 V6 V7 V1 1.00000000 0.3025766 -0.22473884 -0.72468776 0.18890578 0.14466161 0.05325308 V2 0.30257657 1.0000000 -0.27871430 -0.29075170 0.16095258 0.10538468 -0.15008158 V3 -0.22473884 -0.2787143 1.00000000 -0.22644156 0.07276013 -0.35725182 -0.05859479 V4 -0.72468776 -0.2907517 -0.22644156 1.00000000 -0.19305921 0.16948333 -0.01025698 V5 0.18890578 0.1609526 0.07276013 -0.19305921 1.00000000 0.07339531 -0.31837954 V6 0.14466161 0.1053847 -0.35725182 0.16948333 0.07339531 1.00000000 0.02514081 V7 0.05325308 -0.1500816 -0.05859479 -0.01025698 -0.31837954 0.02514081 1.00000000 V8 0.44705527 0.1698571 0.39970105 -0.42461411 0.63951574 0.23065830 -0.28967977 V9 0.21006372 -0.4418132 -0.18623823 -0.25272860 0.15921890 0.36182579 -0.18437981 V10 0.02326108 0.4618036 -0.25205899 -0.05117037 0.02408278 0.47630138 -0.38592733 V8 V9 V10 V1 0.447055266 0.210063724 0.02326108 V2 0.169857120 -0.441813231 0.46180357 V3 0.399701054 -0.186238233 -0.25205899 V4 -0.424614107 -0.252728595 -0.05117037 V5 0.639515737 0.159218895 0.02408278 V6 0.230658298 0.361825786 0.47630138 V7 -0.289679766 -0.184379813 -0.38592733 V8 1.000000000 0.001023392 0.11436143 V9 0.001023392 1.000000000 0.15301699 V10 0.114361431 0.153016985 1.00000000 </code></pre>
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    1. POCalculate correlation - cor() - for only a subset of columns
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    1. USGreg
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    1. POCalculate correlation - cor() - for only a subset of columns
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    1. COif you really only want to do the correlation on columns 1, 3, and 10, you could always do `cor(x[c(1, 3, 10)])`
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      1. USGreg
    2. COSorry, this is for numeric, not non-numeric data. I'll leave it just in case.
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      1. USGreg
    3. COglad you left it, Greg. You already helped someone – it already helped me to se sapply in another creative way :)
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      1. USMatt Bannert
 

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