r - 关于规则集的逻辑问题：在数据框中选择行值达到最大值和最小值的行
问题描述
我有以下带有 lan lon坐标、cloud_point_distance_to_ziel以及到点f0..f2的相对距离的数据框
lon lat cloud_point_distance_to_ziel f0_distance_to_point f1_distance_to_point f2_distance_to_point
24 11.7 48 32356 6524 20802 35162
89 11.7 48 32356 6649 21219 34585
132 11.7 48 33660 6503 20698 35311
192 11.7 48 32356 6766 21589 34044
...
我希望能够在以下条件下有效地选择一行：
选择cloud_point_distance_to_ziel值达到最小值 而f0..f2值达到最大值的行。最大值和最小值在行内不必是绝对值，但应根据后续规则达到它们的 min/mx 值。
例子：
a has values (3,4,5,6,1,2,4,5,8,9,4)
b has values (2,5,6,3,2,9,7,4,2,4,3)
c has values (2,1,4,6,3,6,8,9,2,1,2)
possible min values of (a)->1,2,3,4
possible max values of (b)->9,7,6,5
possible max values of (c)->9,8,6,4
selected row with a,b,c values 2,9,6
结果应该选择一行
我尝试了以下方法，但我不相信结果。也许使用四分位数可以解决问题？
f0_mean<-mean(data$f0_distance_to_point)
f1_mean<-mean(data$f1_distance_to_point)
f2_mean<-mean(data$f2_distance_to_point)
point_result<-data[(which.min(data$cloud_point_distance_to_ziel)
& (data$f0_distance_to_point > f0_mean)
& (data$f1_distance_to_point > f1_mean)
& (data$f2_distance_to_point > f2_mean)),]
其他方法：
data<-data[data$f0_distance_to_point>quantile(data$f0_distance_to_point,0.85),]
data<-data[data$f1_distance_to_point>quantile(data$f1_distance_to_point,0.85),]
data<-data[data$f2_distance_to_point>quantile(data$f2_distance_to_point,0.85),]
point_result <- data[which.min(data$cloud_point_distance_to_ziel),]
数据代码：
data <-
structure(
list(
lon = c(
11.7397709792062,
11.7448661049966,
11.7384976841411,
11.7492009896508,
11.798531500208,
11.7562989433643,
11.7817986819213,
11.7457818355317,
11.7565528127003,
11.775019447482,
11.7990427748903,
11.768883801117,
11.7820267269428,
11.7526821785921,
11.7729644807609,
11.7656290403773,
11.7689881451332,
11.7856195303942,
11.7784078217926,
11.7614946153811,
11.7513483568678,
11.773126221415,
11.7836991580849,
11.7650082634726,
11.7480285610035,
11.7598040660488,
11.7673422104715,
11.7549204850733,
11.7725605176412,
11.7671241745901,
11.7668667395602,
11.7900370162996,
11.785291372675,
11.7462798005881,
11.7854305475734,
11.7472521033403,
11.7706277569342,
11.7582629707936,
11.7812623910872,
11.7618026552496
),
lat = c(
48.0406345358279,
48.0366692132014,
48.0416864931132,
48.0326126303325,
48.01404507432,
48.0250544655736,
48.0127446150512,
48.0310952221558,
48.0191463660624,
48.0141901000025,
48.0173447367971,
48.0125637323678,
48.0259059854022,
48.0300255676393,
48.0149681602546,
48.0205116689316,
48.0132250539091,
48.0155813575988,
48.0163665355201,
48.0221114178826,
48.0277707588402,
48.0251052314425,
48.0143854199087,
48.0128206848559,
48.0294561032443,
48.0274566855892,
48.0222287044966,
48.0308697960588,
48.0263675936893,
48.0222650935833,
48.023463537079,
48.0192912029751,
48.0207717565613,
48.0301403042609,
48.0201970547079,
48.0282788741312,
48.019573189748,
48.0260046046014,
48.0251574108575,
48.023237280448
),
cloud_point_distance_to_ziel = list(
32355.8059191835,
32355.8059191835,
33659.7804661781,
32355.8059191835,
32355.8059191835,
31960.7024820624,
33659.7804661781,
32355.8059191835,
31960.7024820624,
33659.7804661781,
32355.8059191835,
33659.7804661781,
32355.8059191835,
32355.8059191835,
31960.7024820624,
32355.8059191835,
31960.7024820624,
32355.8059191835,
33659.7804661781,
32355.8059191835,
33659.7804661781,
31960.7024820624,
32355.8059191835,
33659.7804661781,
31960.7024820624,
32355.8059191835,
31960.7024820624,
33659.7804661781,
31960.7024820624,
32355.8059191835,
32355.8059191835,
31960.7024820624,
33659.7804661781,
32355.8059191835,
33659.7804661781,
31960.7024820624,
32355.8059191835,
33659.7804661781,
31960.7024820624,
31960.7024820624
),
f0_distance_to_point = c(
6523.56087201753,
6649.28217687594,
6503.46768539322,
6765.95829619417,
6442.12791798449,
6671.40625006645,
6230.34780000719,
6468.47038347654,
6252.13607978831,
6432.22943583159,
6810.39601414163,
6325.85372739144,
7691.27105446194,
6881.83516439466,
6538.07646927175,
6878.62834481693,
6396.4585747719,
6539.5519957707,
6647.70571839638,
6745.04532140725,
6629.26187444153,
7630.64388285189,
6408.02619767719,
6367.71629639824,
6565.05469806704,
7044.18856439527,
7094.89054298961,
7062.73262801013,
7682.87937043481,
7084.41530641291,
7150.67826425775,
6960.02910152723,
7116.38557806022,
6466.92695660631,
7052.50291443861,
6469.64693739617,
7070.06497164368,
6850.02543111819,
7610.26353022488,
6842.4247208008
),
f1_distance_to_point = c(
20801.5164909635,
21218.7363557505,
20697.9752625597,
21588.685952041,
25527.6407705382,
22226.5828888995,
24333.8450858125,
21357.567838855,
22355.9495480481,
23808.1236364208,
25500.5889158094,
23397.5147560411,
24104.3477362433,
21881.511455553,
23641.4840149903,
22993.0892224942,
23390.0677717411,
24552.7137121619,
24009.6860310581,
22660.185764715,
21817.7744631735,
23462.2419669878,
24437.1899218789,
23109.7140789518,
21547.2569810623,
22444.8013577727,
23086.8031247124,
22034.3678067779,
23400.505352285,
23070.1548188659,
23030.0084246067,
24804.4448056518,
24429.6367079515,
21408.2062843106,
24450.1656200026,
21508.3844081874,
23377.0720196865,
22354.8622851421,
24059.8022609345,
22662.3554001251
),
f2_distance_to_point = c(
35161.890114791,
34585.1875379748,
35310.6054979667,
34043.6744250552,
29954.8203279982,
33090.0886089445,
30765.5644251227,
34120.3101266009,
32643.0111946674,
31247.8830306243,
30183.3149564129,
31471.1319336641,
31753.0551465962,
33658.9659164565,
31419.4770485574,
32236.5066464529,
31513.466445502,
30769.3037095555,
31222.7894718709,
32584.1630048325,
33565.6468925473,
32170.4412766329,
30783.9567801719,
31708.0000202251,
33874.5024543128,
33075.0473409777,
32269.6466231121,
33598.8050527318,
32297.1668032941,
32284.3666525881,
32388.1365599397,
30814.0868557006,
31182.6177367083,
34022.1959836496,
31131.0603020996,
33831.1039551706,
31890.5101319178,
33051.7003546685,
31736.1029439456,
32650.4643103276
)
),
row.names = c(
24L,
89L,
132L,
192L,
403L,
413L,
418L,
420L,
422L,
430L,
432L,
436L,
447L,
453L,
458L,
465L,
470L,
474L,
477L,
482L,
483L,
505L,
515L,
525L,
538L,
542L,
544L,
561L,
574L,
575L,
578L,
586L,
597L,
602L,
618L,
630L,
634L,
638L,
642L,
645L
),
class = "data.frame"
)
解决方案
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