R语言tidyverse场景下如何对dbl类型temp列实现向下取整

对双精度浮点型的temp列做向下取整后再分组，直接使用R内置的floor()函数即可实现，根据是否需要保留原始temp值，有两种常用写法：

• 写法1（最小代码改动）：在分组环节直接对temp值取整，不修改原数据集的列，最终输出的列名与原有逻辑完全一致：

library(tidyverse)
library(nycflights13)

dep_delay_by_temp <- flights %>%
  inner_join(weather, by = c(
    "origin" = "origin",
    "year" = "year",
    "month" = "month",
    "day" = "day",
    "hour" = "hour"
  )) %>%
  group_by(temp = floor(temp)) %>%
  summarise(avg_delay = mean(dep_delay, na.rm = TRUE))

• 写法2（直接修改temp列）：如果不需要保留原始的浮点型temp值，可以在分组前用mutate把temp列的值替换为向下取整的结果：

dep_delay_by_temp <- flights %>%
  inner_join(weather, by = c(
    "origin" = "origin",
    "year" = "year",
    "month" = "month",
    "day" = "day",
    "hour" = "hour"
  )) %>%
  mutate(temp = floor(temp)) %>%
  group_by(temp) %>%
  summarise(avg_delay = mean(dep_delay, na.rm = TRUE))

补充说明：floor()的计算逻辑为返回不大于输入值的最大整数，完全匹配向下取整的需求。如果原数据的temp列存在缺失值，分组逻辑与原有代码完全一致，会自动将缺失值归为单独的NA组，不会改变原有平均延误的计算规则。

内容的提问来源于stack exchange，提问作者Destry3