library(dplyr); library(tibble)
这是我的示例数据。我要加入单个数据框（listOfDFs）的小型数据框（points）的列表。
listOfDfs有5个小数据框，总共7行，而points是一个有7行的数据框：
points <- structure(list(EVENT_ID_CNTY = c("LBY1243", "LBY3389", "LBY3393",
"LBY3506", "LBY3822"), year = c(2013, 2015, 2015, 2015, 2015),
COUNTRY = c("Libya", "Libya", "Libya", "Libya", "Libya")), .Names = c("EVENT_ID_CNTY",
"year", "COUNTRY"), row.names = c(NA, -5L), class = c("tbl_df",
"tbl", "data.frame"))
listOfDFs <- structure(list(`1` = structure(list(CELL_ID = c(165267, 164547
), gwno = c(620L, 620L), POP = c(751.0737, 754.5745), prio_country = c("Libya",
"Libya")), .Names = c("CELL_ID", "gwno", "POP", "prio_country"
), row.names = c(NA, -2L), class = c("tbl_df", "tbl", "data.frame"
)), `2` = structure(list(CELL_ID = 172475, gwno = 620L, POP = 11676,
prio_country = "Libya"), .Names = c("CELL_ID", "gwno", "POP",
"prio_country"), row.names = c(NA, -1L), class = c("tbl_df",
"tbl", "data.frame")), `3` = structure(list(CELL_ID = 172475,
gwno = 620L, POP = 11676, prio_country = "Libya"), .Names = c("CELL_ID",
"gwno", "POP", "prio_country"), row.names = c(NA, -1L), class = c("tbl_df",
"tbl", "data.frame")), `4` = structure(list(CELL_ID = 172475,
gwno = 620L, POP = 11676, prio_country = "Libya"), .Names = c("CELL_ID",
"gwno", "POP", "prio_country"), row.names = c(NA, -1L), class = c("tbl_df",
"tbl", "data.frame")), `5` = structure(list(CELL_ID = c(165267,
164547), gwno = c(620L, 620L), POP = c(751.0737, 754.5745), prio_country = c("Libya",
"Libya")), .Names = c("CELL_ID", "gwno", "POP", "prio_country"
), row.names = c(NA, -2L), class = c("tbl_df", "tbl", "data.frame"
))), .Names = c("1", "2", "3", "4", "5"))
这些数据如下所示：
points
#> # A tibble: 5 x 3
#> EVENT_ID_CNTY year COUNTRY
#> <chr> <dbl> <chr>
#> 1 LBY1243 2013. Libya # Corresponds to the two items in listOfDFs[[1]]
#> 2 LBY3389 2015. Libya # Corresponds to the one item in listOfDFs[[2]]
#> 3 LBY3393 2015. Libya
#> 4 LBY3506 2015. Libya
#> 5 LBY3822 2015. Libya
listOfDFs
#> $`1`
#> # A tibble: 2 x 4
#> CELL_ID gwno POP prio_country
#> <dbl> <int> <dbl> <chr>
#> 1 165267. 620 751. Libya
#> 2 164547. 620 755. Libya
#>
#> $`2`
#> # A tibble: 1 x 4
#> CELL_ID gwno POP prio_country
#> <dbl> <int> <dbl> <chr>
#> 1 172475. 620 11676. Libya
#>
#> $`3`
#> # A tibble: 1 x 4
#> CELL_ID gwno POP prio_country
#> <dbl> <int> <dbl> <chr>
#> 1 172475. 620 11676. Libya
#>
#> $`4`
#> # A tibble: 1 x 4
#> CELL_ID gwno POP prio_country
#> <dbl> <int> <dbl> <chr>
#> 1 172475. 620 11676. Libya
#>
#> $`5`
#> # A tibble: 2 x 4
#> CELL_ID gwno POP prio_country
#> <dbl> <int> <dbl> <chr>
#> 1 165267. 620 751. Libya
#> 2 164547. 620 755. Libya
我如何结合这两个，使它们遵循以下模式？我是否必须找到一种方法将它们绑定到数据框的行索引上，还是有一种更优雅的方法？：
#> EVENT_ID_CNTY year COUNTRY CELL_ID gwno POP prio_country
#> <chr> <dbl> <chr> <dbl> <int> <dbl> <chr>
#> LBY1243 2013. Libya 165267. 620 751. Libya
#> LBY1243 2013. Libya 164547. 620 755. Libya
#> LBY3389 2015. Libya 172475. 620 11676. Libya
#> LBY3393 2015. Libya 172475. 620 11676. Libya
#> LBY3506 2015. Libya 172475. 620 11676. Libya
#> LBY3822 2015. Libya 165267. 620 751. Libya
#> LBY3822 2015. Libya 164547. 620 755. Libya
.........
答案 0 :(得分：2)
library(tidyr)
points %>% mutate(mm=listOfDFs) %>% unnest
# A tibble: 7 x 7
EVENT_ID_CNTY year COUNTRY CELL_ID gwno POP prio_country
<chr> <dbl> <chr> <dbl> <int> <dbl> <chr>
1 LBY1243 2013 Libya 165267 620 751. Libya
2 LBY1243 2013 Libya 164547 620 755. Libya
3 LBY3389 2015 Libya 172475 620 11676 Libya
4 LBY3393 2015 Libya 172475 620 11676 Libya
5 LBY3506 2015 Libya 172475 620 11676 Libya
6 LBY3822 2015 Libya 165267 620 751. Libya
7 LBY3822 2015 Libya 164547 620 755. Libya
答案 1 :(得分：1)
根据示例，我们将{points}数据集的行与c@http://localhost:8101/build/polyfills.js:3:19752
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onInvokeTask@http://localhost:8101/build/vendor.js:5125:24
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的每个元素的行一起复制并将列绑定在一起
list或在链中使用
library(tidyverse)
bind_cols(points[rep(seq_len(nrow(points)),
map_dbl(listOfDFs, nrow)),], bind_rows(listOfDFs))
# A tibble: 7 x 7
#EVENT_ID_CNTY year COUNTRY CELL_ID gwno POP prio_country
# <chr> <dbl> <chr> <dbl> <int> <dbl> <chr>
#1 LBY1243 2013 Libya 165267 620 751. Libya
#2 LBY1243 2013 Libya 164547 620 755. Libya
#3 LBY3389 2015 Libya 172475 620 11676 Libya
#4 LBY3393 2015 Libya 172475 620 11676 Libya
#5 LBY3506 2015 Libya 172475 620 11676 Libya
#6 LBY3822 2015 Libya 165267 620 751. Libya
#7 LBY3822 2015 Libya 164547 620 755. Libya
或者用'EVENT_ID_CNTY'设置map_dbl(listOfDFs, nrow) %>%
rep(seq_len(nrow(points)), .) %>%
magrittr::extract(points, ., ) %>%
bind_cols(bind_rows(listOfDFs))
的名称以创建一个id列并与'points'连接起来
list答案 2 :(得分：1)
使用dplyr::bind_rows和dplyr::inner_join的选项可以是：
library(dplyr)
mutate(points, rn = as.character(row_number())) %>%
inner_join(bind_rows(listOfDFs, .id="Name"), by=c("rn" = "Name")) %>%
select(-rn)
# # A tibble: 7 x 7
# EVENT_ID_CNTY year COUNTRY CELL_ID gwno POP prio_country
# <chr> <dbl> <chr> <dbl> <int> <dbl> <chr>
# 1 LBY1243 2013 Libya 165267 620 751 Libya
# 2 LBY1243 2013 Libya 164547 620 755 Libya
# 3 LBY3389 2015 Libya 172475 620 11676 Libya
# 4 LBY3393 2015 Libya 172475 620 11676 Libya
# 5 LBY3506 2015 Libya 172475 620 11676 Libya
# 6 LBY3822 2015 Libya 165267 620 751 Libya
# 7 LBY3822 2015 Libya 164547 620 755 Libya