我有一个数据框，类似于下面的数据框，创造性地称为“统计”
在 psuedo-R 代码中我想这样做:
justMeans<-stats[rowname(stats)=="CD.Mean*",]
其中 * 是通配符。
我也尝试过使用以下内容
justMeans<-stats[substr(names(stats),1,7)=="CD.Mean"),]
...这不仅不起作用，我意识到我缺乏对正在发生的事情的基本理解。但我已经尝试了好几个小时了!请帮助! ;o)
鲍勃
<小时/>>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 20 100.0201235
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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最佳答案
stats[grepl("CD.Mean*", rownames(stats)), ]
关于R——如何根据 grep 行名称进行子集化，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/8959378/