R语言distinct搭配summarise报错：找不到age对象

数据示例 #

ACCOUNT = c("M205109", "M205109", "M201212", "M205668", "M207954", "M208966", "M203465", "M207622", "M201869", "M201869")
age = c(20, 20, 18, 29, 21, 19, 19, 23, 22, 22)
data <- data.frame(ACCOUNT, age)

报错原因 #

distinct(ACCOUNT)执行后，数据框仅保留ACCOUNT列，后续summarise调用age时自然找不到该列。你的需求是基于唯一账户做年龄统计，必须保留age列的同时完成账户去重。

解决方案 #

方案1：指定distinct保留需要的列 #

如果同一账户的age值完全一致，直接在distinct中指定要保留的列，启用.keep_all参数保留其他列：

library(tidyverse)

age_summary_all <- data %>%
  distinct(ACCOUNT, age, .keep_all = TRUE) %>%
  summarise(
    min = min(age, na.rm = TRUE),
    q1 = quantile(age, 0.25, na.rm = TRUE),
    median = median(age, na.rm = TRUE),
    mean = mean(age, na.rm = TRUE),
    q3 = quantile(age, 0.75, na.rm = TRUE),
    max = max(age, na.rm = TRUE)
  )

方案2：分组后取唯一账户的年龄 #

如果存在同一账户对应不同age值的情况（示例中未体现），先按ACCOUNT分组，取每组的一个age值（比如第一条记录的age），再做统计：

age_summary_all <- data %>%
  group_by(ACCOUNT) %>%
  slice_head(n = 1) %>% # 取每组第一条记录的age
  ungroup() %>%
  summarise(
    min = min(age, na.rm = TRUE),
    q1 = quantile(age, 0.25, na.rm = TRUE),
    median = median(age, na.rm = TRUE),
    mean = mean(age, na.rm = TRUE),
    q3 = quantile(age, 0.75, na.rm = TRUE),
    max = max(age, na.rm = TRUE)
  )

也可以在分组时直接确定每个账户的唯一age值（比如取最小/最大值，假设同一账户age一致）：

age_summary_all <- data %>%
  group_by(ACCOUNT) %>%
  summarise(age = first(age)) %>% # 用min(age)/max(age)结果一致
  ungroup() %>%
  summarise(
    min = min(age, na.rm = TRUE),
    q1 = quantile(age, 0.25, na.rm = TRUE),
    median = median(age, na.rm = TRUE),
    mean = mean(age, na.rm = TRUE),
    q3 = quantile(age, 0.75, na.rm = TRUE),
    max = max(age, na.rm = TRUE)
  )

结果验证 #

执行上述任意方案后，统计的样本量会是8（对应8个唯一账户），所有统计指标均可正常计算。

内容的提问来源于stack exchange，提问作者Pendragon