比方说,我想用两种不同的货币来比较每个国家的苹果和橙子的价格。美国和BTC
美国~各国的水果 BTC~各国的水果。
library(tidyverse)
prices <- tibble(
country = c(rep("USA", 6), rep("Spain", 6), rep("Korea", 6)),
fruit = rep(c("apples", "apples", "apples", "oranges", "oranges", "oranges"), 3),
price_USA = rnorm(18),
price_BTC = rnorm(18)
)
prices %>%
group_by(country) %>%
summarise(
pval_USA = t.test(price_USA ~ fruit)$p.value
pval_BTC = t.test(price_BTC ~ fruit)$p.value
)
现在假设有很多列,我想使用 summarise_all
而不是给每一列命名。是否有办法在每组中进行t检验(country
)和每一列(price_USA
, price_BTC
),使用 dplyr::summarise_all
函数?到目前为止,我试过的方法都给我出错。
prices %>%
group_by(country) %>%
summarise_at(
c("price_USA", "price_BTC"),
function(x) {t.test(x ~ .$fruit)$p.value}
)
> Error in model.frame.default(formula = x ~ .$fruit) :
variable lengths differ (found for '.$fruit')
您可以通过以下方式实现 将您的数据从宽幅调整为长幅。. 这是一个使用dplyr的解决方案。
library(tidyverse)
prices <- tibble(
country = c(rep("USA", 6), rep("Spain", 6), rep("Korea", 6)),
fruit = rep(c("apples", "apples", "apples", "oranges", "oranges", "oranges"), 3),
price_USA = rnorm(18),
price_BTC = rnorm(18)
)
prices %>%
pivot_longer(cols = starts_with("price"), names_to = "name",
values_to = "price", names_prefix = "price_") %>%
group_by(country, name) %>%
summarise(pval = t.test(price ~ fruit)$p.value)
#> # A tibble: 6 x 3
#> # Groups: country [3]
#> country name pval
#> <chr> <chr> <dbl>
#> 1 Korea BTC 0.458
#> 2 Korea USA 0.721
#> 3 Spain BTC 0.732
#> 4 Spain USA 0.526
#> 5 USA BTC 0.916
#> 6 USA USA 0.679