如何从特定列中值大于1的数据框中选择行？
这就是我的数据的样子：
> dput(head(tbl_comp[,-1]))
structure(list(Meve_mean = c(7774.44229552491, 43374.1166119026,
585562.72426545, 3866.54724117546, 320338.197537275, 918368.01990607
), Mmor_mean = c(39113.5325249635, 119476.157216344, 1296530.34384725,
23511.2980313616, 209092.538981888, 577355.581852083), Mtot_mean = c(23443.9874102442,
81425.1369141232, 941046.53405635, 13688.9226362685, 264715.368259581,
747861.800879077), tot_meanMe = c(258492586.999527, NA, NA, NA,
NA, NA), tot_meanMm = c(246665241.110832, NA, NA, NA, NA, NA),
tot_sdMe = c(35569170.0311164, NA, NA, NA, NA, NA), tot_sdMm = c(30522099.9189256,
NA, NA, NA, NA, NA), Wteve_mean = c(10752.4381084666, 53658.8435672746,
715547.921685567, 3422.17220367207, 335384.199178456, 1013708.18845339
), Wtmor_mean = c(29254.6414790837, 98804.8007431987, 1001344.20496027,
11541.8862121394, 217110.411645861, 571826.157099177), Wttot_mean = c(18681.9538387311,
73007.110928385, 838032.04308901, 6902.04963587237, 284695.433093058,
824330.175015869), tot_meanwte = c(278901499.672313, NA,
NA, NA, NA, NA), tot_meanwtm = c(235415566.775308, NA, NA,
NA, NA, NA), tot_sdwte = c(16743477.4011497, NA, NA, NA,
NA, NA), tot_sdwtm = c(3922418.43271348, NA, NA, NA, NA,
NA), diff_eve = c(0.72303994843767, 0.808331185101342, 0.818341730189196,
1.12985174650959, 0.955138012828161, 0.905949098928778),
diff_mor = c(1.33700262752933, 1.20921408998001, 1.29478988086689,
2.03704122525771, 0.963070068343606, 1.00966976533735), diff_tot = c(1.25490018938172,
1.11530419268331, 1.12292428650774, 1.98331269093204, 0.929819510568173,
0.907235745512628)), .Names = c("Meve_mean", "Mmor_mean",
"Mtot_mean", "tot_meanMe", "tot_meanMm", "tot_sdMe", "tot_sdMm",
"Wteve_mean", "Wtmor_mean", "Wttot_mean", "tot_meanwte", "tot_meanwtm",
"tot_sdwte", "tot_sdwtm", "diff_eve", "diff_mor", "diff_tot"), row.names = c(NA,
6L), class = "data.frame")
在这个数据中有三列我最感兴趣的是：
diff_eve diff_mor diff_tot
0.7230399 1.3370026 1.2549002
0.8083312 1.2092141 1.1153042
0.8183417 1.2947899 1.1229243
1.1298517 2.0370412 1.9833127
0.9551380 0.9630701 0.9298195
0.9059491 1.0096698 0.9072357
我想创建由每个列中的值选择的新数据框。应该有6个新的数据框架。 ＆＃34; diff_eve＆＃34;中的值低于1列应位于新数据帧中，同样适用于1 =下一个数据帧的值。当然我想保留数据中的所有列（tbl_comp）。
让我展示新数据框的示例。在diff_eve列中选择低于1的值：
>newdata.frame
diff_eve diff_mor diff_tot .. ....... ..... rest of the columns from tbl_comp.
0.7230399 1.3370026 1.2549002
0.8083312 1.2092141 1.1153042
0.8183417 1.2947899 1.1229243
0.9551380 0.9630701 0.9298195
0.9059491 1.0096698 0.9072357
我希望你们中的一些人能够理解我想要达到的目标。
答案 0 :(得分：3)
这是一个解决方案，按以下顺序为您提供六个数据帧：
diff_eve <1
diff_mor <1
diff_tot <1
diff_eve >1
diff_mor >1
diff_tot >1
代码：
cols <- c("diff_eve", "diff_mor", "diff_tot")
c(lapply(cols, function(x)subset(tbl_comp, eval(parse(text=x))<1)), lapply(cols, function(x)subset(tbl_comp, eval(parse(text=x))>1)))
给你
[[1]]
Meve_mean Mmor_mean Mtot_mean tot_meanMe tot_meanMm tot_sdMe tot_sdMm Wteve_mean Wtmor_mean Wttot_mean tot_meanwte tot_meanwtm tot_sdwte tot_sdwtm diff_eve diff_mor diff_tot
1 7774.442 39113.53 23443.99 258492587 246665241 35569170 30522100 10752.44 29254.64 18681.95 278901500 235415567 16743477 3922418 0.7230399 1.3370026 1.2549002
2 43374.117 119476.16 81425.14 NA NA NA NA 53658.84 98804.80 73007.11 NA NA NA NA 0.8083312 1.2092141 1.1153042
3 585562.724 1296530.34 941046.53 NA NA NA NA 715547.92 1001344.20 838032.04 NA NA NA NA 0.8183417 1.2947899 1.1229243
5 320338.198 209092.54 264715.37 NA NA NA NA 335384.20 217110.41 284695.43 NA NA NA NA 0.9551380 0.9630701 0.9298195
6 918368.020 577355.58 747861.80 NA NA NA NA 1013708.19 571826.16 824330.18 NA NA NA NA 0.9059491 1.0096698 0.9072357
[[2]]
Meve_mean Mmor_mean Mtot_mean tot_meanMe tot_meanMm tot_sdMe tot_sdMm Wteve_mean Wtmor_mean Wttot_mean tot_meanwte tot_meanwtm tot_sdwte tot_sdwtm diff_eve diff_mor diff_tot
5 320338.2 209092.5 264715.4 NA NA NA NA 335384.2 217110.4 284695.4 NA NA NA NA 0.955138 0.9630701 0.9298195
[[3]]
Meve_mean Mmor_mean Mtot_mean tot_meanMe tot_meanMm tot_sdMe tot_sdMm Wteve_mean Wtmor_mean Wttot_mean tot_meanwte tot_meanwtm tot_sdwte tot_sdwtm diff_eve diff_mor diff_tot
5 320338.2 209092.5 264715.4 NA NA NA NA 335384.2 217110.4 284695.4 NA NA NA NA 0.9551380 0.9630701 0.9298195
6 918368.0 577355.6 747861.8 NA NA NA NA 1013708.2 571826.2 824330.2 NA NA NA NA 0.9059491 1.0096698 0.9072357
[[4]]
Meve_mean Mmor_mean Mtot_mean tot_meanMe tot_meanMm tot_sdMe tot_sdMm Wteve_mean Wtmor_mean Wttot_mean tot_meanwte tot_meanwtm tot_sdwte tot_sdwtm diff_eve diff_mor diff_tot
4 3866.547 23511.3 13688.92 NA NA NA NA 3422.172 11541.89 6902.05 NA NA NA NA 1.129852 2.037041 1.983313
[[5]]
Meve_mean Mmor_mean Mtot_mean tot_meanMe tot_meanMm tot_sdMe tot_sdMm Wteve_mean Wtmor_mean Wttot_mean tot_meanwte tot_meanwtm tot_sdwte tot_sdwtm diff_eve diff_mor diff_tot
1 7774.442 39113.53 23443.99 258492587 246665241 35569170 30522100 10752.438 29254.64 18681.95 278901500 235415567 16743477 3922418 0.7230399 1.337003 1.2549002
2 43374.117 119476.16 81425.14 NA NA NA NA 53658.844 98804.80 73007.11 NA NA NA NA 0.8083312 1.209214 1.1153042
3 585562.724 1296530.34 941046.53 NA NA NA NA 715547.922 1001344.20 838032.04 NA NA NA NA 0.8183417 1.294790 1.1229243
4 3866.547 23511.30 13688.92 NA NA NA NA 3422.172 11541.89 6902.05 NA NA NA NA 1.1298517 2.037041 1.9833127
6 918368.020 577355.58 747861.80 NA NA NA NA 1013708.188 571826.16 824330.18 NA NA NA NA 0.9059491 1.009670 0.9072357
[[6]]
Meve_mean Mmor_mean Mtot_mean tot_meanMe tot_meanMm tot_sdMe tot_sdMm Wteve_mean Wtmor_mean Wttot_mean tot_meanwte tot_meanwtm tot_sdwte tot_sdwtm diff_eve diff_mor diff_tot
1 7774.442 39113.53 23443.99 258492587 246665241 35569170 30522100 10752.438 29254.64 18681.95 278901500 235415567 16743477 3922418 0.7230399 1.337003 1.254900
2 43374.117 119476.16 81425.14 NA NA NA NA 53658.844 98804.80 73007.11 NA NA NA NA 0.8083312 1.209214 1.115304
3 585562.724 1296530.34 941046.53 NA NA NA NA 715547.922 1001344.20 838032.04 NA NA NA NA 0.8183417 1.294790 1.122924
4 3866.547 23511.30 13688.92 NA NA NA NA 3422.172 11541.89 6902.05 NA NA NA NA 1.1298517 2.037041 1.983313
如果您希望数据框前面的选择标准列（如示例中所示），您可以使用：
c(lapply(cols, function(x)subset(tbl_comp[,c(cols, setdiff(colnames(tbl_comp), cols))], eval(parse(text=x))<1)), lapply(cols, function(x)subset(tbl_comp[,c(cols, setdiff(colnames(tbl_comp), cols))], eval(parse(text=x))>1)))
答案 1 :(得分：1)
我不知道我是否正确理解了您的问题，但这可能是一个解决方案：
diff_eve_below <- subset(tbl_comp, diff_eve < 1)
diff_eve_above <- subset(tbl_comp, diff_eve > 1)
diff_mor_below <- subset(tbl_comp, diff_mor < 1)
diff_mor_above <- subset(tbl_comp, diff_mor > 1)
diff_tot_below <- subset(tbl_comp, diff_tot < 1)
diff_tot_above <- subset(tbl_comp, diff_tot > 1)