使用pivot_longer和pivot_wider每年获取一行/代码/名称。然后您可以轻松地使用lag在连续年份之间进行比较。

library(tidyverse)

df <- structure(list(code = c("M0000273", "M0000357", "M0000545"), 
                     name = c("industry", "agriculture", "service"), 
                     `2019_actual` = c(16.78, 9.26, 49.38), 
                     `2019_pred` = c(17.78, 10.26, NA), 
                     `2020_actual` = c(35.74, NA, 49.38), 
                     `2020_pred` = c(36.74, 66.56, 25.36), 
                     `2021_actual` = c(30.74, 83.42, 63.26), 
                     `2021_pred` = c(31.74, 84.42, 35.23)), 
                class = "data.frame", row.names = c(NA, -3L)) %>% 
    as_tibble()

df %>% 
    pivot_longer(cols = c(-code, -name), names_to = c("year", "type"), names_sep = "_") %>% 
    pivot_wider(names_from = "type", values_from = "value") %>% 
    mutate(year = as.integer(year)) %>% 
    group_by(code, name) %>% 
    arrange(year) %>% 
    mutate(act_direction = case_when(actual > lag(actual) ~ "increase",
                                     actual < lag(actual) ~ "decrease",
                                     actual == lag(actual) ~ "unchanged"),
           pred_direction = case_when(pred > lag(actual) ~ "increase",
                                   pred < lag(actual) ~ "decrease",
                                   pred == lag(actual) ~ "unchanged"))