在R语言中按日期将Precip_Tot列重复值转为NA（保留行）

原始数据结构 #

dput(prec)
structure(list(date = structure(c(19091, 19091, 19092, 19092, 
19093, 19093, 19094, 19094, 19095, 19095, 19096, 19096, 19097, 
19097, 19098, 19098, 19099, 19099, 19100, 19100, 19101, 19101, 
19102, 19102, 19103, 19103, 19104, 19104, 19105, 19105, 19106, 
19106, 19107, 19107, 19109, 19109, 19110, 19110, 19111, 19111, 
19112, 19112, 19113, 19113, 19114, 19114), class = "Date"), target = c("grass", 
"tree", "grass", "tree", "grass", "tree", "grass", "tree", "grass", 
"tree", "grass", "tree", "grass", "tree", "grass", "tree", "grass", 
"tree", "grass", "tree", "grass", "tree", "grass", "tree", "grass", 
"tree", "grass", "tree", "grass", "tree", "grass", "tree", "grass", 
"tree", "grass", "tree", "grass", "tree", "grass", "tree", "grass", 
"tree", "grass", "tree", "grass", "tree"), Precip_Tot = c(0, 
0, 0, 0, 0.0464, 0.0464, 0.0362, 0.0362, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.131, 0.131, 0, 0, 0, 0, 0, 
0, 0.016, 0.016, 0, 0, 0, 0, 0, 0, 0, 0, 0.4506, 0.4506)), row.names = c(NA, 
46L), class = "data.frame")

解决方案 #

方法1：使用dplyr（tidyverse）

按日期分组后，仅保留每组首行的Precip_Tot值，其余行转为NA：

library(dplyr)

prec <- prec %>%
  group_by(date) %>%
  mutate(Precip_Tot = if_else(row_number() == 1, Precip_Tot, NA_real_)) %>%
  ungroup()

方法2：使用Base R（无需额外包）

利用duplicated()标记重复日期行，直接将对应位置的Precip_Tot设为NA：

prec$Precip_Tot[duplicated(prec$date)] <- NA

效果说明 #

处理后，每个日期仅第一行保留原始Precip_Tot值，同日期的其他行该字段转为NA，所有原始行完整保留。例如日期19093对应的grass行保留0.0464，tree行的Precip_Tot变为NA。

内容的提问来源于stack exchange，提问作者Cláudio Siva