用dplyr在保留行的前提下添加物种年月观测最大值列

要实现保留原数据所有行和列，同时新增列填充每个Species-Year-Month组的观测次数，直接用dplyr的group_by + mutate组合即可，无需summarise：

library(dplyr)

# 示例数据
Sp <- data.frame(Species = c("A","A","A","A","A","A","A","A","A","A","A","B","B","B","B","B","C","C","C","C","C","C","C","C","C","C","C","C","C","C","C","C","C","C","C","C","C","C"),
                 Month= c("2","3","4","4","4","7","3","4","4","5","6","4","5","6","6","7","4","3","4","5","6","7","3","4","4","5","6","4","5","6","4","5","6","2","2","8","5","5"),
                 Year= c("2018","2005","2006","2006","2006","2006","2008","2008","2008","2008","2018","2009","2009","2009","2018","2009","2009","2009","2009","2009","2018","2005","2005","2005","2006","2006","2005","2006","2005","2005","2005","2009","2009","2009","2018","2018","2018","2018"))

# 新增分组观测次数列
Sp <- Sp %>%
  group_by(Species, Year, Month) %>%
  mutate(obs_max = n()) %>%
  ungroup()

关键逻辑说明 #

• group_by(Species, Year, Month)：按物种、年份、月份进行分组，确保后续计算仅针对同一组内的数据。
• mutate(obs_max = n())：n()函数在分组后会返回当前组的行数（即该组的观测次数），mutate会将这个值填充到该组的每一行，同时保留原数据的所有行和列。
• ungroup()：可选操作，取消数据框的分组状态，避免后续操作受分组影响。

比如查看物种A在2006年4月的记录，该组共3行，对应的obs_max列值均为3，符合需求。

内容的提问来源于stack exchange，提问作者RGR_288