带有if/else函数的mutate()

Question

我有一个示例数据帧

df <- data.frame(cust = sample(1:100, 1000, TRUE),
             channel = sample(c("WEB", "POS"), 1000, TRUE))

我正试图改变

get_channels <- function(data) {
    d <- data
    if(unique(d) %>% length() == 2){
        d <- "Both"
    } else {
        if(unique(d) %>% length() < 2 && unique(d) == "WEB") {
            d <- "Web"
        } else {
            d <- "POS"
            }
        }
    return(d)
}

这没有问题,在小型数据帧上,它根本不需要时间.

start.time <- Sys.time()

df %>%
    group_by(cust) %>%
    mutate(chan = get_channels(channel)) %>%
    group_by(cust) %>% 
    slice(1) %>%
    group_by(chan) %>%
    summarize(count = n()) %>%
    mutate(perc = count/sum(count))

end.time <- Sys.time()
time.taken <- end.time - start.time
time.taken

时差0.34602秒

但是,当数据帧变得相当大时,例如,大于> 1000000或更多cust,我的基本if/elsefx需要更长时间.

如何简化此功能以使其更快地运行？

Answer 1

你应该为此使用data.table.

setDT(df)
t1 = Sys.time()
df = df[ , .(channels = ifelse(uniqueN(channel) == 2, "both", as.character(channel[1]))), by = .(cust)]

> Sys.time() - t1
Time difference of 0.00500083 secs

> head(df)
   cust channels
1:   37     both
2:   45     both
3:   74     both
4:   20     both
5:    1     both
6:   68     both