如何在R中遍历比赛ID列表并将结果合并至DataFrame？

问题原因 #

你当前的代码每次循环都会用新比赛的结果覆盖output变量，循环结束后仅保留最后一场的数据，没有累积所有比赛的结果。

解决方案一：循环累积 + 最终合并 #

先初始化空列表存储每场比赛的数据，循环时将单场结果追加到列表，最后统一合并。同时建议添加game_id字段，方便区分不同比赛的数据：

library(rvest)
library(dplyr)
library(purrr)
library(tidyr)

game_ids <- list(401559239,401559240)
url_ = "https://www.espn.com/nhl/boxscore/_/gameId"

# 初始化空列表存储每场比赛结果
all_results <- list()

for (game_id in game_ids) {
  url2 = paste(url_, game_id, sep = '/')
  
  boxscore <- read_html(url2) %>% 
    html_elements("div.Boxscore div.Wrapper") %>% 
    set_names(html_elements(., ".BoxscoreItem__TeamName") %>% html_text()) %>% 
    map(\(team_section) html_elements(team_section, "table")) %>% 
    map(\(team_tables) list(
      tbl_1 = html_table(team_tables[1:2]) %>% 
        bind_cols(.name_repair = "minimal") %>% 
        set_names(.[1,]) %>% 
        rename(player = Skaters) %>% 
        mutate(position = if_else(G == "G", player, NA), .before = 1) %>% 
        fill(position, .direction = "down") %>% 
        filter(G != "G"),
      tbl_2 = html_table(team_tables[3:4]) %>% 
        bind_cols(.name_repair = "minimal") %>% 
        set_names(.[1,]) %>% 
        filter(SA != "SA")
    ))
  
  # 提取当前比赛的skater数据，添加game_id字段
  current_output <- boxscore %>% 
    map("tbl_1") %>% 
    list_rbind(names_to = "team") %>%
    mutate(game_id = game_id, .before = 1)  # 添加比赛ID
  
  # 将当前结果追加到列表
  all_results[[length(all_results) + 1]] <- current_output
}

# 合并所有比赛数据为一个DataFrame
final_df <- list_rbind(all_results)

解决方案二：用purrr::map_dfr简化代码 #

利用tidyverse的map_dfr函数，直接对game_ids列表映射处理逻辑，自动将结果合并为DataFrame，代码更简洁：

library(rvest)
library(dplyr)
library(purrr)
library(tidyr)

game_ids <- list(401559239,401559240)
url_ = "https://www.espn.com/nhl/boxscore/_/gameId"

# 定义处理单场比赛的函数
process_game <- function(game_id) {
  url2 = paste(url_, game_id, sep = '/')
  
  boxscore <- read_html(url2) %>% 
    html_elements("div.Boxscore div.Wrapper") %>% 
    set_names(html_elements(., ".BoxscoreItem__TeamName") %>% html_text()) %>% 
    map(\(team_section) html_elements(team_section, "table")) %>% 
    map(\(team_tables) list(
      tbl_1 = html_table(team_tables[1:2]) %>% 
        bind_cols(.name_repair = "minimal") %>% 
        set_names(.[1,]) %>% 
        rename(player = Skaters) %>% 
        mutate(position = if_else(G == "G", player, NA), .before = 1) %>% 
        fill(position, .direction = "down") %>% 
        filter(G != "G"),
      tbl_2 = html_table(team_tables[3:4]) %>% 
        bind_cols(.name_repair = "minimal") %>% 
        set_names(.[1,]) %>% 
        filter(SA != "SA")
    ))
  
  boxscore %>% 
    map("tbl_1") %>% 
    list_rbind(names_to = "team") %>%
    mutate(game_id = game_id, .before = 1)
}

# 处理所有比赛并合并
final_df <- map_dfr(game_ids, process_game)

关键说明 #

• 添加game_id字段是核心：能明确每条数据所属的比赛，避免数据混淆。
• 两种方法本质都是累积多场数据后合并，map_dfr更符合tidyverse的函数式编程风格，代码更紧凑。

内容的提问来源于stack exchange，提问作者Michael