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POBinning a dataframe with equal frequency of samples
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2013-12-23T16:02:26.010
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I have binned my data using the cut function <pre><code>breaks<-seq(0, 250, by=5) data<-split(df2, cut(df2$val, breaks)) </code></pre> My split dataframe looks like <pre><code>... ... $`(15,20]` val ks_Result c 15 60 237 18 70 247 ... ... $`(20,25]` val ks_Result c 21 20 317 24 10 140 ... ... </code></pre> My bins looks like <pre><code>> table(data) data (0,5] (5,10] (10,15] (15,20] (20,25] (25,30] (30,35] 0 0 0 7 128 2748 2307 (35,40] (40,45] (45,50] (50,55] (55,60] (60,65] (65,70] 1404 11472 1064 536 7389 1008 1714 (70,75] (75,80] (80,85] (85,90] (90,95] (95,100] (100,105] 2047 700 329 1107 399 376 323 (105,110] (110,115] (115,120] (120,125] (125,130] (130,135] (135,140] 314 79 1008 77 474 158 381 (140,145] (145,150] (150,155] (155,160] (160,165] (165,170] (170,175] 89 660 15 1090 109 824 247 (175,180] (180,185] (185,190] (190,195] (195,200] (200,205] (205,210] 1226 139 531 174 1041 107 257 (210,215] (215,220] (220,225] (225,230] (230,235] (235,240] (240,245] 72 671 98 212 70 95 25 (245,250] 494 </code></pre> When I mean the bins, I get on an average of ~900 samples <pre><code>> mean(table(data)) [1] 915.9 </code></pre> I want to tell R to make irregular bins in such a way that each bin will contain on an average 900 samples (e.g. (0, 27] = 900, (27,28.5] = 900, and so on). I found something similar <a href="https://stackoverflow.com/questions/5731116/equal-frequency-discretization-in-r">here</a>, which deals with only one variable, not the whole dataframe. I also tried Hmisc package, unfortunately the bins don't contain equal frequency!! <pre><code>library(Hmisc) data<-split(df2, cut2(df2$val, g=30, oneval=TRUE)) data<-split(df2, cut2(df2$val, m=1000, oneval=TRUE)) </code></pre>
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<r><split><subset><cut>
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Binning a dataframe with equal frequency of samples
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 POBinning a dataframe with equal frequency of samples
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