如何将数据帧变量名移动到第一行,并将新变量名添加到列表中的多个数据帧? 库(purrr) 图书馆(tibble) 图书馆(dplyr)
数据帧的起始列表如何将数据帧变量名移动到第一行,并将新变量名添加到列表中的多个数据帧? 库(purrr) 图书馆(tibble) 图书馆(dplyr),r,purrr,tibble,R,Purrr,Tibble,数据帧的起始列表 lst <- list(df1 = data.frame(X.1 = as.character(1:2), heading = letters[1:2]), df2 = data.frame(X.32 = as.character(3:4), another.topic = paste("Line ", 1:2))) lst #
lst <- list(df1 = data.frame(X.1 = as.character(1:2),
heading = letters[1:2]),
df2 = data.frame(X.32 = as.character(3:4),
another.topic = paste("Line ", 1:2)))
lst
#> $df1
#> X.1 heading
#> 1 1 a
#> 2 2 b
#>
#> $df2
#> X.32 another.topic
#> 1 3 Line 1
#> 2 4 Line 2
add_row
需要“名称-值对,传递到tibble()。只能为中已存在的列定义值。数据列和未设置列将获得NA值。”
这就是我认为我在这方面取得的成就:
df_nms <-
map(lst, names) %>%
map(set_names)
#> $df1
#> X.1 heading
#> "X.1" "heading"
#>
#> $df2
#> X.32 another.topic
#> "X.32" "another.topic"
最好用一个指针来解决最后一个步骤。这里有一种方法,使用
数据中的map
、rbindlist
。table
和一些基本R函数:
library(purrr)
library(dplyr)
library(data.table)
map(lst, ~ as.data.frame(unname(rbind(colnames(.x),as.matrix(.x))))) %>%
rbindlist(idcol = "id")
# id V1 V2
#1: df1 X.1 heading
#2: df1 1 a
#3: df1 2 b
#4: df2 X.32 another.topic
#5: df2 3 Line 1
#6: df2 4 Line 2
或者,如果我们使用colnames%,我们可以使用map\u df
`colnames不太清楚如何通过purr
map函数实现这一点,但这里有一个替代方案
library(dplyr)
bind_rows(lapply(lst, function(i){d1 <- as.data.frame(matrix(names(i), ncol = ncol(i)));
rbind(d1, setNames(i, names(d1)))}), .id = 'id')
# id V1 V2
#1 df1 X.1 heading
#2 df1 1 a
#3 df1 2 b
#4 df2 X.32 another.topic
#5 df2 3 Line 1
#6 df2 4 Line 2
库(dplyr)
bind_rows(lappy(lst,函数(i){d1在lst
中创建data.frames时,我稍微更改了示例数据,将stringsAsFactors
设置为FALSE
#sample data
lst <- list(df1 = data.frame(X.1 = as.character(1:2),
heading = letters[1:2],
stringsAsFactors = FALSE), # !! <--
df2 = data.frame(X.32 = as.character(3:4),
another.topic = paste("Line ", 1:2),
stringsAsFactors = FALSE) # !! <--
)
DT <- data.table::rbindlist( lapply( lst, function(x) rbind( names(x), x ) ),
use.names = FALSE, idcol = "id" )
setnames(DT, names( lst[[1]] ), c("h1", "h2") )
# id h1 h2
# 1: df1 X.1 heading
# 2: df1 1 a
# 3: df1 2 b
# 4: df2 X.32 another.topic
# 5: df2 3 Line 1
# 6: df2 4 Line 2
下面是一个使用data.table::rbindlist()
的解决方案
#示例数据
非常感谢你的建议。次要的一点,我认为在备选方案的末尾有一个多余的括号。很抱歉。修正了。
map_df(lst, ~ as.data.frame(rbind(colnames(.x),as.matrix(.x))) %>%
`colnames<-`(.,paste0("h",seq(1,dim(.)[2]))), .id = "id")
# id h1 h2
#1 df1 X.1 heading
#2 df1 1 a
#3 df1 2 b
#4 df2 X.32 another.topic
#5 df2 3 Line 1
#6 df2 4 Line 2
library(dplyr)
bind_rows(lapply(lst, function(i){d1 <- as.data.frame(matrix(names(i), ncol = ncol(i)));
rbind(d1, setNames(i, names(d1)))}), .id = 'id')
# id V1 V2
#1 df1 X.1 heading
#2 df1 1 a
#3 df1 2 b
#4 df2 X.32 another.topic
#5 df2 3 Line 1
#6 df2 4 Line 2
#sample data
lst <- list(df1 = data.frame(X.1 = as.character(1:2),
heading = letters[1:2],
stringsAsFactors = FALSE), # !! <--
df2 = data.frame(X.32 = as.character(3:4),
another.topic = paste("Line ", 1:2),
stringsAsFactors = FALSE) # !! <--
)
DT <- data.table::rbindlist( lapply( lst, function(x) rbind( names(x), x ) ),
use.names = FALSE, idcol = "id" )
setnames(DT, names( lst[[1]] ), c("h1", "h2") )
# id h1 h2
# 1: df1 X.1 heading
# 2: df1 1 a
# 3: df1 2 b
# 4: df2 X.32 another.topic
# 5: df2 3 Line 1
# 6: df2 4 Line 2