R数据处理：如何去除重复观测并保留两份观测的有效信息

核心逻辑是先定位重复出现的物种，再修改对应字段，最后过滤无效行即可，操作步骤如下：

1. 依赖安装（首次运行执行） #

如果还没安装数据处理包，先执行安装代码：

install.packages("dplyr")

2. 加载包和数据 #

library(dplyr)

# 此处示例数据可替换为你自己的数据集
df <- structure(list(species = structure(c(1L, 2L, 3L, 4L, 2L, 3L), .Label = c("Aa achalensis", 
"Aa argyrolepis", "Aa aurantiaca", "Aa calceata"), class = "factor"), 
    establishment = structure(c(1L, 1L, 1L, 1L, 2L, 2L), .Label = c("farm", 
    "field"), class = "factor"), region = structure(c(1L, 1L, 
    1L, 1L, 1L, 1L), .Label = "ABT", class = "factor"), leaf.area = c(0.348046463, 
    0.265755867, 0.382584479, 0.336147631, NA, NA), ses = c(-0.3906, 
    -0.6257, -0.2987, -0.423, NA, NA)), row.names = c(NA, 6L), class = "data.frame")

3. 核心处理代码 #

df_result <- df %>%
  # 标记出现次数大于1的重复物种
  group_by(species) %>%
  mutate(is_duplicated_species = n() > 1) %>%
  ungroup() %>%
  # 将重复物种的establishment字段从farm修改为field
  mutate(establishment = as.character(establishment),
         establishment = ifelse(is_duplicated_species & establishment == "farm", "field", establishment),
         establishment = as.factor(establishment)) %>%
  # 删除最后两列全为NA的field行
  filter(!(establishment == "field" & is.na(leaf.area) & is.na(ses))) %>%
  # 移除辅助标记列
  select(-is_duplicated_species)

处理结果示例 #

最终得到的df_result结构如下，完全符合需求：

基础R版本（无需安装额外包） #

如果不想用dplyr，也可以用原生R语法实现：

# 标记重复物种
dup_species <- names(which(table(df$species) > 1))
# 修改establishment字段
df$establishment <- as.character(df$establishment)
df$establishment[df$species %in% dup_species & df$establishment == "farm"] <- "field"
df$establishment <- as.factor(df$establishment)
# 过滤无效行
df_result <- df[!(df$establishment == "field" & is.na(df$leaf.area) & is.na(df$ses)), ]

内容的提问来源于stack exchange，提问作者Jose