R中的雙向列聯表

Question

我有一個數據框，我想從兩列中輸出一個雙向列聯表。他們都有價值「太少」，「關於正確」或「太多」。

我打字

df %>% 
    filter(!is.na(col1)) %>% 
    group_by(col1) %>% 
    summarise(count = n()) 

分別爲二者的和得到的東西是這樣的：

col1  count 
<fctr>  <int> 
Too Little 19259   
About Right 9539    
Too Much 2816  

我想實現的是：

 Too Little About Right Too Much Total 
col1 19259  9539   2816  31614 
col2 20619  9374   2262  32255 
Total 39878  18913   5078  63869 

我一直試圖使用表功能

addmargins(table(df$col1, df$col2)) 

但結果不是我想要

   Too Little About Right Too Much Sum 
    Too Little  13770  4424  740 18934 
    About Right  4901  3706  700 9307 
    Too Much   1250   800  679 2729 
    Sum    19921  8930  2119 30970 

Answer 1

我給tabulate一試，這是table基礎（見?tabulate）是什麼。例如，給定

set.seed(123) 
vals <- LETTERS[1:3] 
df <- as.data.frame(replicate(3, sample(vals, 5, T))) 
df <- data.frame(lapply(df, "levels<-", vals)) 

那麼你可以做

m <- t(sapply(df, tabulate, nbins = length(vals))) 
colnames(m) <- vals 
addmargins(m) 
#  A B C Sum 
# V1 1 1 3 5 
# V2 1 3 1 5 
# V3 1 2 2 5 
# Sum 3 6 6 15 

或（通過@thelatemail）剛剛

addmargins(t(sapply(df, table))) 
#  A B C Sum 
# V1 1 1 3 5 
# V2 1 3 1 5 
# V3 1 2 2 5 
# Sum 3 6 6 15 

Answer 2

我們可以在一個循環，然後rbind使用表：

# Using dummy data from @lukeA's answer 

addmargins(do.call(rbind, lapply(df1, table))) 
#  A B C Sum 
# V1 1 1 3 5 
# V2 1 3 1 5 
# V3 1 2 2 5 
# Sum 3 6 6 15 

---

標杆

# bigger data 
set.seed(123) 
vals <- LETTERS[1:20] 
df1 <- as.data.frame(replicate(20, sample(vals, 100000, T))) 
df1 <- data.frame(lapply(df1, "levels<-", vals)) 


microbenchmark::microbenchmark(
    lukeA = { 
    m1 <- t(sapply(df1, tabulate, nbins = length(vals))) 
    colnames(m1) <- vals 
    m1 <- addmargins(m1) 
    }, 
    # as vals only used for luke's solution, keep it in. 
    lukeA_1 = { 
    vals <- LETTERS[1:20] 
    m2 <- t(sapply(df1, tabulate, nbins = length(vals))) 
    colnames(m2) <- vals 
    m2 <- addmargins(m2) 
    }, 
    thelatemail = {m3 <- addmargins(t(sapply(df1, table)))}, 
    zx8754 = {m4 <- addmargins(do.call(rbind, lapply(df1, table)))} 
) 
# Unit: milliseconds 
#  expr  min  lq  mean median  uq  max neval 
#  lukeA 2.349969 2.371922 2.518447 2.473839 2.558653 3.363738 100 
#  lukeA_1 2.351680 2.377196 2.523473 2.473839 2.542831 3.459242 100 
# thelatemail 38.316506 42.054136 43.785777 42.674912 44.234193 90.287809 100 
#  zx8754 38.695101 41.979728 44.933602 42.762006 44.244314 110.834292 100