R:在基于多列的数据帧中使用排序函数
我是一名心脏病专家,喜欢用R编码——我对数据帧的排序有一个真正的问题,我怀疑解决方案真的很简单 我有一个数据框架,包含多个研究的总结值。大多数研究只有一个摘要值(df$summary)。然而,正如您所见,研究A有三个汇总值(df$no.of.estimate)。见下文R:在基于多列的数据帧中使用排序函数,r,R,我是一名心脏病专家,喜欢用R编码——我对数据帧的排序有一个真正的问题,我怀疑解决方案真的很简单 我有一个数据框架,包含多个研究的总结值。大多数研究只有一个摘要值(df$summary)。然而,正如您所见,研究A有三个汇总值(df$no.of.estimate)。见下文 study <- c("E", "A", "F", "A", "B", "A", "C", "D") no.of.estimate <- c(1, 2, 1, 3, 1, 1, 1, 1) summary <-
study <- c("E", "A", "F", "A", "B", "A", "C", "D")
no.of.estimate <- c(1, 2, 1, 3, 1, 1, 1, 1)
summary <- c(1, 2, 3, 5, 6 ,7 ,8 ,9)
df <- data.frame(study, no.of.estimate, summary)
你可以试试
library(dplyr)
df %>%
mutate(study=factor(study, levels=unique(study))) %>%
arrange(study,no.of.estimate)
# study no.of.estimate summary
#1 E 1 1
#2 A 1 7
#3 A 2 2
#4 A 3 5
#5 F 1 3
#6 B 1 6
#7 C 1 8
#8 D 1 9
或基本R
方法
df$study <- factor(df$study, levels=unique(df$study))
df[with(df, order(study, no.of.estimate)), ]
df$study这是我的数据表
在保持列不变并创建新索引的同时尝试(尽管先看我的注释)。它的主要优点是,您可以通过引用更新数据集,而不是创建新的副本
library(data.table)
setorder(setDT(df)[, indx := .GRP, study], indx, no.of.estimate)[]
# study no.of.estimate summary indx
# 1: E 1 1 1
# 2: A 1 7 2
# 3: A 2 2 2
# 4: A 3 5 2
# 5: F 1 3 3
# 6: B 1 6 4
# 7: C 1 8 5
# 8: D 1 9 6
您一定注意到,通过使用cbind
,您创建了一个矩阵,其中列作为字符类。使用data.frame(研究,估计数…
您不想按sudy
和no.of.estimate
对整个数据集进行排序,而只是在no.of.estimate
有多个值的情况下?你似乎把这件事复杂化了一点。看起来你可以用(df,order(study,no.of.estimate)),]来做df,
,不过先看看@akruns comment。
df <- structure(list(study = structure(c(5L, 1L, 6L, 1L, 2L, 1L, 3L,
4L), .Label = c("A", "B", "C", "D", "E", "F"), class = "factor"),
no.of.estimate = c(1, 2, 1, 3, 1, 1, 1, 1), summary = c(1,
2, 3, 5, 6, 7, 8, 9)), .Names = c("study", "no.of.estimate",
"summary"), row.names = c(NA, -8L), class = "data.frame")
df1 <- structure(list(study = structure(c(5L, 1L, 1L, 1L, 6L, 2L, 3L,
4L), .Label = c("A", "B", "C", "D", "E", "F"), class = "factor"),
no.of.estimate = c(1, 1, 2, 3, 1, 1, 1, 1), summary = c(1,
7, 2, 5, 3, 6, 8, 9)), .Names = c("study", "no.of.estimate",
"summary"), row.names = c(NA, -8L), class = "data.frame")
library(data.table)
setorder(setDT(df)[, indx := .GRP, study], indx, no.of.estimate)[]
# study no.of.estimate summary indx
# 1: E 1 1 1
# 2: A 1 7 2
# 3: A 2 2 2
# 4: A 3 5 2
# 5: F 1 3 3
# 6: B 1 6 4
# 7: C 1 8 5
# 8: D 1 9 6