R 如何根据列的数据提取列名称列表？
我对R很陌生，希望我能说清楚R 如何根据列的数据提取列名称列表？,r,R,我对R很陌生，希望我能说清楚 music <- read.table(text = " AVIS1 AVIS2 AVIS3 AVIS4 AVIS5 1 2 1 2 3 2 2 2 5 2 3 2 3 3 2 5 5 1 4 1 2 5 5 5 5 1 5 1 3 1 6 4 1 4 5 4", header = TRUE) # your data scores <- seq(1, by = -0.5,
music <- read.table(text = "
AVIS1 AVIS2 AVIS3 AVIS4 AVIS5
1 2 1 2 3 2
2 2 5 2 3 2
3 3 2 5 5 1
4 1 2 5 5 5
5 1 5 1 3 1
6 4 1 4 5 4", header = TRUE) # your data
scores <- seq(1, by = -0.5, length.out = 6) # vector of scores
library(tidyr)
library(dplyr)
music2 <- music %>%
gather(AVIS, Value) %>% # here you tidy the data
mutate(score = scores[Value]) %>% # match score to value
group_by(AVIS) %>% # group AVIS levels
summarise(score.mean = mean(score)) %>% # find mean scores for AVIS levels
arrange(desc(score.mean))
list <- list(AVIS = music2$AVIS) # here is the list
> list$AVIS
[1] "AVIS1" "AVIS5" "AVIS2" "AVIS3" "AVIS4"
music <- read.table(text = "
AVIS1 AVIS2 AVIS3 AVIS4 AVIS5
1 2 1 2 3 2
2 2 5 2 3 2
3 3 2 5 5 1
4 1 2 5 5 5
5 1 5 1 3 1
6 4 1 4 5 4", header = TRUE) # your data
scores <- seq(1, by = -0.5, length.out = 6) # vector of scores
library(tidyr)
library(dplyr)
music2 <- music %>%
gather(AVIS, Value) %>% # here you tidy the data
mutate(score = scores[Value]) %>% # match score to value
group_by(AVIS) %>% # group AVIS levels
summarise(score.mean = mean(score)) %>% # find mean scores for AVIS levels
arrange(desc(score.mean))
list <- list(AVIS = music2$AVIS) # here is the list
> list$AVIS
[1] "AVIS1" "AVIS5" "AVIS2" "AVIS3" "AVIS4"
head（musico[，69:73]）music <- read.table(text = "
AVIS1 AVIS2 AVIS3 AVIS4 AVIS5
1 2 1 2 3 2
2 2 5 2 3 2
3 3 2 5 5 1
4 1 2 5 5 5
5 1 5 1 3 1
6 4 1 4 5 4", header = TRUE) # your data
scores <- seq(1, by = -0.5, length.out = 6) # vector of scores
library(tidyr)
library(dplyr)
music2 <- music %>%
gather(AVIS, Value) %>% # here you tidy the data
mutate(score = scores[Value]) %>% # match score to value
group_by(AVIS) %>% # group AVIS levels
summarise(score.mean = mean(score)) %>% # find mean scores for AVIS levels
arrange(desc(score.mean))
list <- list(AVIS = music2$AVIS) # here is the list
> list$AVIS
[1] "AVIS1" "AVIS5" "AVIS2" "AVIS3" "AVIS4"
1232
2 2 5 2 3 2
3 3 2 5 1
4 1 2 5 5
515131
641454
music <- read.table(text = "
AVIS1 AVIS2 AVIS3 AVIS4 AVIS5
1 2 1 2 3 2
2 2 5 2 3 2
3 3 2 5 5 1
4 1 2 5 5 5
5 1 5 1 3 1
6 4 1 4 5 4", header = TRUE) # your data
scores <- seq(1, by = -0.5, length.out = 6) # vector of scores
library(tidyr)
library(dplyr)
music2 <- music %>%
gather(AVIS, Value) %>% # here you tidy the data
mutate(score = scores[Value]) %>% # match score to value
group_by(AVIS) %>% # group AVIS levels
summarise(score.mean = mean(score)) %>% # find mean scores for AVIS levels
arrange(desc(score.mean))
list <- list(AVIS = music2$AVIS) # here is the list
> list$AVIS
[1] "AVIS1" "AVIS5" "AVIS2" "AVIS3" "AVIS4"
musico$score1<-0
musico$score1[musico$AVIS1==1]<-1
musico$score1[musico$AVIS1==2]<-0.5
music <- read.table(text = "
AVIS1 AVIS2 AVIS3 AVIS4 AVIS5
1 2 1 2 3 2
2 2 5 2 3 2
3 3 2 5 5 1
4 1 2 5 5 5
5 1 5 1 3 1
6 4 1 4 5 4", header = TRUE) # your data
scores <- seq(1, by = -0.5, length.out = 6) # vector of scores
library(tidyr)
library(dplyr)
music2 <- music %>%
gather(AVIS, Value) %>% # here you tidy the data
mutate(score = scores[Value]) %>% # match score to value
group_by(AVIS) %>% # group AVIS levels
summarise(score.mean = mean(score)) %>% # find mean scores for AVIS levels
arrange(desc(score.mean))
list <- list(AVIS = music2$AVIS) # here is the list
> list$AVIS
[1] "AVIS1" "AVIS5" "AVIS2" "AVIS3" "AVIS4"
musico$score1这里有一种使用base的方法，尽管您想要什么还不清楚。score1
与AVIS1
有什么关系？我想您可能丢失了musico
中的一些数据
music <- read.table(text = "
AVIS1 AVIS2 AVIS3 AVIS4 AVIS5
1 2 1 2 3 2
2 2 5 2 3 2
3 3 2 5 5 1
4 1 2 5 5 5
5 1 5 1 3 1
6 4 1 4 5 4", header = TRUE) # your data
scores <- seq(1, by = -0.5, length.out = 6) # vector of scores
library(tidyr)
library(dplyr)
music2 <- music %>%
gather(AVIS, Value) %>% # here you tidy the data
mutate(score = scores[Value]) %>% # match score to value
group_by(AVIS) %>% # group AVIS levels
summarise(score.mean = mean(score)) %>% # find mean scores for AVIS levels
arrange(desc(score.mean))
list <- list(AVIS = music2$AVIS) # here is the list
> list$AVIS
[1] "AVIS1" "AVIS5" "AVIS2" "AVIS3" "AVIS4"
根据提供的示例，这里是一个基本的R解决方案vapply
循环遍历data.frame并生成每列的平均值。然后，堆栈
和顺序
只是为了使输出成为一个看起来不错的数据帧
music <- read.table(text = "
AVIS1 AVIS2 AVIS3 AVIS4 AVIS5
1 2 1 2 3 2
2 2 5 2 3 2
3 3 2 5 5 1
4 1 2 5 5 5
5 1 5 1 3 1
6 4 1 4 5 4", header = TRUE) # your data
scores <- seq(1, by = -0.5, length.out = 6) # vector of scores
library(tidyr)
library(dplyr)
music2 <- music %>%
gather(AVIS, Value) %>% # here you tidy the data
mutate(score = scores[Value]) %>% # match score to value
group_by(AVIS) %>% # group AVIS levels
summarise(score.mean = mean(score)) %>% # find mean scores for AVIS levels
arrange(desc(score.mean))
list <- list(AVIS = music2$AVIS) # here is the list
> list$AVIS
[1] "AVIS1" "AVIS5" "AVIS2" "AVIS3" "AVIS4"
music首先引入一个scores
向量用作查找，我就是这样做的。我假设分数下降了0.5，并且所需分数的数量取决于列中的最大级别数（即AVIS1
中的6）
music <- read.table(text = "
AVIS1 AVIS2 AVIS3 AVIS4 AVIS5
1 2 1 2 3 2
2 2 5 2 3 2
3 3 2 5 5 1
4 1 2 5 5 5
5 1 5 1 3 1
6 4 1 4 5 4", header = TRUE) # your data
scores <- seq(1, by = -0.5, length.out = 6) # vector of scores
library(tidyr)
library(dplyr)
music2 <- music %>%
gather(AVIS, Value) %>% # here you tidy the data
mutate(score = scores[Value]) %>% # match score to value
group_by(AVIS) %>% # group AVIS levels
summarise(score.mean = mean(score)) %>% # find mean scores for AVIS levels
arrange(desc(score.mean))
list <- list(AVIS = music2$AVIS) # here is the list
> list$AVIS
[1] "AVIS1" "AVIS5" "AVIS2" "AVIS3" "AVIS4"
然后，使用tidyr
可以组织数据集，这样就必须创建包含相应级别的变量（即AVIS
和值
）。然后使用dplyr
中的mutate
函数添加分数变量，其中score
向量中的分数位置与value
变量中的值匹配。从这里，您可以找到与AVIS
级别对应的平均分数，相应地排列它们并将它们放入列表中
music <- read.table(text = "
AVIS1 AVIS2 AVIS3 AVIS4 AVIS5
1 2 1 2 3 2
2 2 5 2 3 2
3 3 2 5 5 1
4 1 2 5 5 5
5 1 5 1 3 1
6 4 1 4 5 4", header = TRUE) # your data
scores <- seq(1, by = -0.5, length.out = 6) # vector of scores
library(tidyr)
library(dplyr)
music2 <- music %>%
gather(AVIS, Value) %>% # here you tidy the data
mutate(score = scores[Value]) %>% # match score to value
group_by(AVIS) %>% # group AVIS levels
summarise(score.mean = mean(score)) %>% # find mean scores for AVIS levels
arrange(desc(score.mean))
list <- list(AVIS = music2$AVIS) # here is the list
> list$AVIS
[1] "AVIS1" "AVIS5" "AVIS2" "AVIS3" "AVIS4"
music%#将分数与值匹配
按（AVIS）分组%>%#分组AVIS水平
总结（分数.平均值=平均值（分数））%>%#查找AVIS水平的平均值
排列（描述（分数平均值））
列表$AVIS
[1] “AVIS1”“AVIS5”“AVIS2”“AVIS3”“AVIS4”
非常感谢，堆栈指令正是我想要的！谢谢，我不知道收集说明，非常有用。我最终使用科尔提出的解决方案，因为对我来说似乎更容易。是的，没问题。也许您应该只运行music2%gather（AVIS，Value）
来查看gather（）
如何操作数据集。这是一个非常简洁的函数。