如何基于年份复制行数据，扩展州政策数据集（优先dplyr方案）

现有一份州政策数据集，仅记录政策发生变化的年份，示例数据如下：

df_have <- data.frame(state = c("AL", "AL", "AL", "AK", "AK", "AZ"),
                 year= c(2015, 2017, 2020, 2015, 2019, 2015),
                 policy= c(1, 2, 3, 1, 2, 1))

需要将数据集扩展至所有中间年份，复制上一年的政策值直到新政策出现，最终目标数据集如下：

df_want <- data.frame(state = c("AL", "AL", "AL", "AL", "AL", "AL", "AK", "AK", "AK", "AK", "AK", "AK", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ"),
                 year= c(2015, 2016, 2017, 2018, 2019, 2020, 2015, 2016, 2017, 2018, 2019, 2020, 2015, 2016, 2017, 2018, 2019, 2020),
                 policy= c(1, 1, 2, 2, 2, 3, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1))

结合dplyr和tidyr的函数可以快速实现需求，代码如下：

library(dplyr)
library(tidyr)

df_result <- df_have %>%
  group_by(state) %>%
  complete(year = full_seq(year, 1)) %>%
  fill(policy, .direction = "down") %>%
  ungroup()

代码说明 #

• group_by(state)：按州分组，保证每个州的年份补全逻辑独立执行
• complete(year = full_seq(year, 1))：生成该州记录年份的连续序列，补全中间缺失的年份，此时新增年份的policy值为NA
• fill(policy, .direction = "down")：将上一个非NA的政策值向下填充，实现"复制上一年政策直到新变化"的效果
• ungroup()：取消分组，回归普通数据框格式

内容的提问来源于stack exchange，提问作者Eric