計算R中滿足兩個條件的數據集的平均值

Question

我想在 R 中找到按年份和 book_Id 分組的數據集的平均值。

我嘗試使用 Tapply 但我只能在該函數中放置一個索引條件。

在 SQL 中它看起來像

Select year, book_id, avg(users_read)
From
Where year = 2018 
Group by year, book_id

So my final table would like 

year  | book_id | avg(users_read)
2018.   1.         12
2018.   2.         8
2018.   3.         13

Answer 1

R 中 SQL 代碼的翻譯將是 -

res <- aggregate(users_read~year + book_id, subset(df, year == 2018), mean)

或者在dplyr -

library(dplyr)

res <- df %>%
  filter( year == 2018) %>%
  group_by(book_id) %>%
  summarise(users_read = mean(users_read))

Answer 2

感謝sqldf包，您也可以在 R 中使用您的 SQL 語句：

sqldf::sqldf("
Select year, book_id, avg(users_read)
From df1
Where year = 2018 
Group by year, book_id
")

 year book_id avg(users_read) 1 2018 1 10.4 2 2018 2 15.5 3 2018 3 9.0

可重現的數據

set.seed(123)
n <- 20
df1 <- data.frame(year = sample(2018:2019, n, TRUE),
                  book_id = sample(3, n, TRUE),
                  users_read = sample(c(1:(n-1), NA), n))

請注意，列users_read包含一個NA值。

 df1

 year book_id users_read 1 2018 1 9 2 2018 1 NA 3 2018 1 10 4 2019 1 7 5 2018 3 5 6 2019 2 11 7 2019 3 6 8 2019 2 19 9 2018 1 2 10 2018 2 16 11 2019 3 8 12 2019 2 12 13 2019 1 1 14 2018 3 18 15 2019 3 3 16 2018 1 17 17 2019 3 13 18 2018 2 15 19 2018 1 14 20 2018 3 4