[英]Subset a dataframe based on identifying max and min values in a column (in R)
對於示例數據框:
df1 <- structure(list(id = 1:21, region = structure(c(1L, 1L, 1L, 1L,
2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L,
4L), .Label = c("a", "b", "c", "d"), class = "factor"), weight = c(0.35,
0.65, 0.99, 1.5, 3.2, 2.1, 1.3, 3.2, 1.3, 2, 0.6, 0.6, 0.6, 0.45,
1, 1.2, 1.4, 2, 1.3, 1, 2), condition = c(0L, 1L, 0L, 1L, 0L,
0L, 0L, 1L, 0L, 1L, 0L, 1L, 0L, 1L, 0L, 1L, 1L, 1L, 1L, 0L, 0L
)), .Names = c("id", "region", "weight", "condition"), class = "data.frame", row.names = c(NA,
-21L))
我希望按區域排除結果變量中沒有最大1或最小1的區域。 例如,我通常會這樣做:
summary <- setDT(df)[,.(.result = weighted.mean((condition==1),
w = weight)*100), by = region]
這會給我:總結
region .result
1: a 61.60458
2: b 39.69466
3: c 50.56180
4: d 61.03896
因此,我將從數據幀df中划分區域c和d。
是否可以一步執行此操作而不必手動查看摘要數據框?
我的理解是,您希望排除所有不是最高值和最低值的值。 它不能作為一個單一的班輪完成,但是如果添加以下內容,那么您應該得到想要的:
incl <- summary[c(which.min(.result), which.max(.result)),region]
newdf <- df1[region %in% incl,]
newdf
id region weight condition
1: 5 b 3.20 0
2: 6 b 2.10 0
3: 7 b 1.30 0
4: 8 b 3.20 1
5: 9 b 1.30 0
6: 10 b 2.00 1
7: 1 a 0.35 0
8: 2 a 0.65 1
9: 3 a 0.99 0
10: 4 a 1.50 1
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