Question

我正在尝试使用DPLYR检索和汇总数据。我写了下面的代码，它可以工作，但是我想将所有这些结合成一个语句。这可能吗？

创建数据集

set.seed(1)
dbo_games <- data.frame(
  name = sample(c("Team1","Team2","Team3","Team4","Team5","Team6","Team7","Team8","Team9","Team10")),
  total_games = sample(1:10)

)

set.seed(1)
dbo_wins <- data.frame(
  name = sample(c("Team1","Team2","Team3","Team4","Team5","Team6","Team7","Team8","Team9","Team10")),
  tota_wins = sample(c("yes", "no"), 10, replace = TRUE)
)

total_games <- con %>% tbl("dbo_games")
total_wins <- con %>% tbl("dbo_wins")

total<- total_games %>% filter(games > 12) %>%
  group_by(NAME) %>%
  summarise(total_games = n_distinct(game_id)) %>% collect()

wins <- total_wins %>% filter( win == 'Y') %>%
  group_by(NAME) %>%
  summarise(total_wins = n_distinct(game_id)) %>% collect()

perc_win <- total %>% left_join(wins) %>%
  mutate(pct_won = total_wins/total_games)

此代码有效，但我相信可能会有更简洁的代码编写方式来达到相同的结果。有什么想法吗？

Answer 1

如果您共享示例数据以及执行工作的原因，那么解决这个问题会更容易。

但是，您仍然可以按如下所示将它们链接在一起：

total_games %>%
  filter(games > 12) %>%
  group_by(NAME) %>%
  summarise(total_games = n_distinct(game_id)) %>%
  left_join(total_wins %>% filter( win == 'Y') %>%
              group_by(NAME) %>%
              summarise(total_wins = n_distinct(game_id))) %>%
  mutate(pct_won = total_wins/total_games)

使用DPLYR在R中组合多个操作

1 个答案: