r - 基于另一个数据框在数据框中扩展行和添加列

Question

概览

team.df 中的每一行都包含一个 NBA team . list.of.all.stars 中的每个数据框包含基于 all star players 数量的多行与每支 NBA 球队相关联。

使用 apply()函数系列，我如何扩展 team.df 中的行以增加每个团队的所有明星球员的数量并组合 列表中的列.of.all.stars 到最终输出？

我也完全接受非apply() 方法，只是想举一个例子，我希望避免编写 for 循环。

下面是我想要的输出:

#   Team_Name Team_Location         Player Captain
# 1 Cavaliers Cleveland, OH   LeBron James    TRUE
# 2 Cavaliers Cleveland, OH     Kevin Love   FALSE
# 3  Warriors   Oakland, CA  Stephen Curry    TRUE
# 4  Warriors   Oakland, CA   Kevin Durant   FALSE
# 5  Warriors   Oakland, CA  Klay Thompson   FALSE
# 6  Warriors   Oakland, CA Draymond Green   FALSE

可重现的例子

# create data frame 
# about team information
team.df <-
  data.frame(
    Team_Name       = c( "Cavaliers", "Warriors" )
    , Team_Location = c( "Cleveland, OH", "Oakland, CA")
    , stringsAsFactors = FALSE
  )

# create list about
# all stars on each team
list.of.all.stars <-
  list( 
    data.frame(
      Player = c( "LeBron James", "Kevin Love" )
      , Captain = c( TRUE, FALSE )
      , stringsAsFactors = FALSE
    )
    , data.frame( 
      Player = c( "Stephen Curry", "Kevin Durant"
                  , "Klay Thompson", "Draymond Green"
      )
      , Captain = c( TRUE, FALSE, FALSE, FALSE )
      , stringsAsFactors = FALSE
    )
  )

非 apply() 族方法

# cbind each data frame within the list.of.all.stars
# to its corresponding row in team.df
team.and.all.stars.list.of.df <-
  list(
    cbind(
      df[ 1, ]
      , list.of.all.stars[[1]]
    )
    ,   cbind(
      df[ 2, ]
      , list.of.all.stars[[2]]
    )
  )
# Warning messages:
#   1: In data.frame(..., check.names = FALSE) :
#   row names were found from a short variable and have been discarded
# 2: In data.frame(..., check.names = FALSE) :
#   row names were found from a short variable and have been discarded

# collapse each list
# into data frame
final.df <-
  data.frame(
    do.call(
      what = "rbind"
      , args = team.and.all.stars.list.of.df
    )
    , stringsAsFactors = FALSE
  )
# view final output
final.df
# Team_Name Team_Location         Player Captain
# 1 Cavaliers Cleveland, OH   LeBron James    TRUE
# 2 Cavaliers Cleveland, OH     Kevin Love   FALSE
# 3  Warriors   Oakland, CA  Stephen Curry    TRUE
# 4  Warriors   Oakland, CA   Kevin Durant   FALSE
# 5  Warriors   Oakland, CA  Klay Thompson   FALSE
# 6  Warriors   Oakland, CA Draymond Green   FALSE

# end of script #

mapply() 尝试失败

# Hoping to Apply A Function
# using a data frame and
# a list of data frames
mapply.method <-
  mapply(
    FUN = function( x, y )
      cbind.data.frame(
        x
        , y
        , stringsAsFactors = FALSE
      )
    , team.df
    , list.of.all.stars
  )

# view results
mapply.method
#         Team_Name   Team_Location
# x       Character,2 Character,4  
# Player  Character,2 Character,4  
# Captain Logical,2   Logical,4 

# end of script #

Answer 1

关于 OP 在 Map/mapply 中使用“team.df”作为输入的方法 “team.df”是一个 data.frame，它是一个 列的列表。因此，基本输入是一列 vector。它循环遍历 vector 或列而不是整个数据集或行(基于所需的输出)。为了防止这种情况，如果我们用 list 包装，它是一个单独的单元，它循环到 'list.of.all.stars' 的每个 list 元素

do.call(rbind, Map(cbind, list(team.df), list.of.all.stars))

---

根据预期的输出，“team.df”的每一行都应具有“list.of.all.stars”的相应 list 元素。在这种情况下，按行拆分“team.df”并执行cbind

res <- do.call(rbind, Map(cbind,  split(team.df, seq_len(nrow(team.df))), list.of.all.stars))
row.names(res) <- NULL
res
#   Team_Name Team_Location         Player Captain
#1 Cavaliers Cleveland, OH   LeBron James    TRUE
#2 Cavaliers Cleveland, OH     Kevin Love   FALSE
#3  Warriors   Oakland, CA  Stephen Curry    TRUE
#4  Warriors   Oakland, CA   Kevin Durant   FALSE
#5  Warriors   Oakland, CA  Klay Thompson   FALSE
#6  Warriors   Oakland, CA Draymond Green   FALSE

---

我们也可以在 tidyverse 中做到这一点。在按“team.df”中的所有列分组后，嵌套 以创建“data”的基本列表(长度为 2)，将“data”分配给“list.of”。 mutate 中的 all.stars' 和 unnest list

library(tidyverse)
team.df %>% 
      group_by_all() %>%
      nest %>% 
      mutate(data = list.of.all.stars) %>% 
      unnest
# A tibble: 6 x 4
#  Team_Name Team_Location Player         Captain
#  <chr>     <chr>         <chr>          <lgl>  
# 1 Cavaliers Cleveland, OH LeBron James   T      
# 2 Cavaliers Cleveland, OH Kevin Love     F      
# 3 Warriors  Oakland, CA   Stephen Curry  T      
# 4 Warriors  Oakland, CA   Kevin Durant   F      
# 5 Warriors  Oakland, CA   Klay Thompson  F      
# 6 Warriors  Oakland, CA   Draymond Green F