R语言如何填充DataFrame的Logger列，替换为前一个带下划线的标识值

核心思路 #

先识别出所有带下划线的分组标识，将其余位置的Logger值设为缺失值，再向下填充缺失值即可匹配需求，无需使用padr包。

解法1：tidyverse实现（最简洁） #

library(tidyverse)

# 原始数据
df <- data.frame("Logger" = c("119_1", "1","2","3","119_2","5","6","7","119_3","7","8","9"),
                 "Temp"  =c (4.5, 5.7, 3.8, 8.9, 8.6, 10.5, 11.0, 7.8, 5.6, 7.8, 9.9, 17.3),
                 "RH"    = c(6.5, 2.7, 11.8, 4.9, 3.6, 12.5, 115.0, 3.8, 9.6, 1.8, 3.9,5.3))

# 处理数据
df_result <- df %>%
  # 不含下划线的Logger替换为缺失值
  mutate(Logger = ifelse(grepl("_", Logger), Logger, NA_character_)) %>%
  # 向下填充缺失值
  fill(Logger, .direction = "down")

运行后得到的df_result和你需求的df_desired完全一致。

解法2：基础R实现（无需额外安装包） #

# 原始数据
df <- data.frame("Logger" = c("119_1", "1","2","3","119_2","5","6","7","119_3","7","8","9"),
                 "Temp"  =c (4.5, 5.7, 3.8, 8.9, 8.6, 10.5, 11.0, 7.8, 5.6, 7.8, 9.9, 17.3),
                 "RH"    = c(6.5, 2.7, 11.8, 4.9, 3.6, 12.5, 115.0, 3.8, 9.6, 1.8, 3.9,5.3))

# 生成分组标识，每遇到一个带下划线的Logger就新增一个分组
group_id <- cumsum(grepl("_", df$Logger))
# 每个分组统一取第一个Logger值替换整组
df$Logger <- ave(df$Logger, group_id, FUN = function(x) x[1])

运行后会直接修改原始df的Logger列为目标值。

内容的提问来源于stack exchange，提问作者Effigy