的R - 如何基於grepping行名稱

Question

我有一個看起來像一個創造性以下稱「統計」

在僞-R代碼，我想這樣做一個數據幀子集：

justMeans<-stats[rowname(stats)=="CD.Mean*",] 

*是通配符。

我用下面還有

justMeans<-stats[substr(names(stats),1,7)=="CD.Mean"),] 

嘗試......這不僅不工作，我知道我缺少什麼事情的基本理解我。但我已經嘗試了好幾個小時！請幫助！ ; O）

鮑勃

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>stats 

      icntr  iexpt angle overlap  stat0 
CD.Mean  1 1R50_50  0  0 100.0074705 
CD.Max   1 1R50_50  0  0 102.265565 
CD.Min   1 1R50_50  0  0 97.540612 
CD.Sigma  1 1R50_50  0  0 1.44676377 
CD.Mean1  2 1R50_50 30  0 99.9647655 
CD.Max1  2 1R50_50 30  0 102.1616205 
CD.Min1  2 1R50_50 30  0 97.6584145 
CD.Sigma1  2 1R50_50 30  0 1.43740901 
CD.Mean2  3 1R50_50 45  0 99.966388 
CD.Max2  3 1R50_50 45  0 106.46566 
CD.Min2  3 1R50_50 45  0 94.2393295 
CD.Sigma2  3 1R50_50 45  0 3.59254625 
CD.Mean3  4 1R50_40  0  10 100.012901 
CD.Max3  4 1R50_40  0  10 101.82303 
CD.Min3  4 1R50_40  0  10 98.1111155 
CD.Sigma3  4 1R50_40  0  10 1.109652465 
CD.Mean4  5 1R50_40 30  10 99.999638 
CD.Max4  5 1R50_40 30  10 101.840065 
CD.Min4  5 1R50_40 30  10 98.0084015 
CD.Sigma4  5 1R50_40 30  10 1.170049515 
CD.Mean5  6 1R50_40 45  10 99.9709865 
CD.Max5  6 1R50_40 45  10 102.388835 
CD.Min5  6 1R50_40 45  10  97.63445 
CD.Sigma5  6 1R50_40 45  10 1.340972695 
CD.Mean6  7 1R50_30  0  20 100.0440445 
CD.Max6  7 1R50_30  0  20 101.311025 
CD.Min6  7 1R50_30  0  20 98.697445 
CD.Sigma6  7 1R50_30  0  20 0.785208705 
CD.Mean7  8 1R50_30 30  20 100.02
CD.Max7  8 1R50_30 30  20 101.538165 
CD.Min7  8 1R50_30 30  20 98.417954 
CD.Sigma7  8 1R50_30 30  20 0.94661223 
CD.Mean8  9 1R50_30 45  20 100.0167915 
CD.Max8  9 1R50_30 45  20 101.5269425 
CD.Min8  9 1R50_30 45  20 98.4979645 
CD.Sigma8  9 1R50_30 45  20 0.940915119 
CD.Mean9  10 1R100_75  0  25 100.0645345 
CD.Max9  10 1R100_75  0  25 104.51514 
CD.Min9  10 1R100_75  0  25 95.8851895 
CD.Sigma9  10 1R100_75  0  25 2.6710193 
CD.Mean10  11 1R100_75 30  25 100.0337035 
CD.Max10  11 1R100_75 30  25  104.5674 
CD.Min10  11 1R100_75 30  25 93.5928325 
CD.Sigma10 11 1R100_75 30  25 3.5593778 
CD.Mean11  12 1R100_75 45  25 100.1049655 
CD.Max11  12 1R100_75 45  25 118.187185 
CD.Min11  12 1R100_75 45  25 83.948139 
CD.Sigma11 12 1R100_75 45  25 11.668272 
CD.Mean12  13 1R100_100  0  0 100.0499555 
CD.Max12  13 1R100_100  0  0 101.648892 
CD.Min12  13 1R100_100  0  0 98.417499 
CD.Sigma12 13 1R100_100  0  0 1.0151079265 
CD.Mean13  14 1R100_100 30  0 100.1393825 
CD.Max13  14 1R100_100 30  0 123.641395 
CD.Min13  14 1R100_100 30  0 80.930049 
CD.Sigma13 14 1R100_100 30  0 14.127094 
CD.Mean14  15 1R100_140  0  60 100.079064 
CD.Max14  15 1R100_140  0  60 100.753091 
CD.Min14  15 1R100_140  0  60 99.389116 
CD.Sigma14 15 1R100_140  0  60 0.423668595 
CD.Mean15  16 1R100_140 30  60 100.0650495 
CD.Max15  16 1R100_140 30  60 101.310065 
CD.Min15  16 1R100_140 30  60 98.7794605 
CD.Sigma15 16 1R100_140 30  60 0.76266793 
CD.Mean16  17 1R100_150  0  50 100.0795465 
CD.Max16  17 1R100_150  0  50 100.868755 
CD.Min16  17 1R100_150  0  50 99.2802315 
CD.Sigma16 17 1R100_150  0  50 0.5030329375 
CD.Mean17  18 1R100_150 30  50 100.060051 
CD.Max17  18 1R100_150 30  50 101.919065 
CD.Min17  18 1R100_150 30  50 98.4232085 
CD.Sigma17 18 1R100_150 30  50 0.99587342 
CD.Mean18  19 1R100_150 45  50 100.0583935 
CD.Max18  19 1R100_150 45  50 103.077655 
CD.Min18  19 1R100_150 45  50 95.523467 
CD.Sigma18 19 1R100_150 45  50 2.1692677 
CD.Mean19  20 1R100_160  0  40 100.0773445 
CD.Max19  20 1R100_160  0  40 101.637125 
CD.Min19  20 1R100_160  0  40  98.18457 
CD.Sigma19 20 1R100_160  0  40 0.948741865 
CD.Mean20  21 1R100_160 30  40 100.0551155 
CD.Max20  21 1R100_160 30  40 101.796255 
CD.Min20  21 1R100_160 30  40 98.4833945 
CD.Sigma20 21 1R100_160 30  40 0.985182275 
CD.Mean21  22 1R100_160 45  40 99.982039 
CD.Max21  22 1R100_160 45  40 107.18366 
CD.Min21  22 1R100_160 45  40 90.728452 
CD.Sigma21 22 1R100_160 45  40 5.4489308 
CD.Mean22  23 1R100_200  0  0 100.0499555 
CD.Max22  23 1R100_200  0  0 101.648892 
CD.Min22  23 1R100_200  0  0 98.417499 
CD.Sigma22 23 1R100_200  0  0 1.0151079265 
. 
. 
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Answer 1

下面是一個例子：

> head(d) 
     icntr iexpt angle overlap  stat0 
CD.Mean  1 1R50_50  0  0 100.007470 
CD.Max  1 1R50_50  0  0 102.265565 
CD.Min  1 1R50_50  0  0 97.540612 
CD.Sigma  1 1R50_50  0  0 1.446764 
CD.Mean1  2 1R50_50 30  0 99.964765 
CD.Max1  2 1R50_50 30  0 102.161620 

> d[grep("^CD\\.Mean.*", rownames(d)), ] 
      icntr  iexpt angle overlap  stat0 
CD.Mean  1 1R50_50  0  0 100.00747 
CD.Mean1  2 1R50_50 30  0 99.96477 
CD.Mean2  3 1R50_50 45  0 99.96639 
CD.Mean3  4 1R50_40  0  10 100.01290 
CD.Mean4  5 1R50_40 30  10 99.99964 
CD.Mean5  6 1R50_40 45  10 99.97099 
CD.Mean6  7 1R50_30  0  20 100.04404 
CD.Mean7  8 1R50_30 30  20 100.02012 
CD.Mean8  9 1R50_30 45  20 100.01679 
CD.Mean9  10 1R100_75  0  25 100.06453 
CD.Mean10 11 1R100_75 30  25 100.03370 
CD.Mean11 12 1R100_75 45  25 100.10497 
CD.Mean12 13 1R100_100  0  0 100.04996 
CD.Mean13 14 1R100_100 30  0 100.13938 
CD.Mean14 15 1R100_140  0  60 100.07906 
CD.Mean15 16 1R100_140 30  60 100.06505 
CD.Mean16 17 1R100_150  0  50 100.07955 
CD.Mean17 18 1R100_150 30  50 100.06005 
CD.Mean18 19 1R100_150 45  50 100.05839 
CD.Mean19 20 1R100_160  0  40 100.07734 
CD.Mean20 21 1R100_160 30  40 100.05512 
CD.Mean21 22 1R100_160 45  40 99.98204 
CD.Mean22 23 1R100_200  0  0 100.04996 

substr是字符串的子集，而grep是，grep是...有哪些呢grep代表什麼？

Answer 2

stats[grepl("CD.Mean*", rownames(stats)), ] 

Answer 3

就快：names(stats)給列名的數據幀，而不是該行的名稱。你想要的是

justMeans<-stats[substr(row.names(stats),1,7)=="CD.Mean"),]