我有一个数据框，其中包含样地 ID (plotID)、树种代码 (species) 和覆盖值 (cover)。您可以看到其中一张图中有多个树种记录。如果每个图中存在重复的“物种”行，如何对“覆盖”字段求和？
例如，这里是一些示例数据:
# Sample Data
plotID = c( "SUF200001035014", "SUF200001035014", "SUF200001035014", "SUF200001035014", "SUF200001035014", "SUF200046012040",
"SUF200046012040", "SUF200046012040", "SUF200046012040", "SUF200046012040", "SUF200046012040", "SUF200046012040")
species = c("ABBA", "BEPA", "PIBA2", "PIMA", "PIRE", "PIBA2", "PIBA2", "PIMA", "PIMA", "PIRE", "POTR5", "POTR5")
cover = c(26.893939, 5.681818, 9.469697, 16.287879, 1.893939, 16.287879, 4.166667, 10.984848, 16.666667, 11.363636, 18.181818,
13.257576)
df_original = data.frame(plotID, species, cover)
这是预期的输出:
# Intended Output
plotID2 = c( "SUF200001035014", "SUF200001035014", "SUF200001035014", "SUF200001035014", "SUF200001035014", "SUF200046012040",
"SUF200046012040", "SUF200046012040", "SUF200046012040")
species2 = c("ABBA", "BEPA", "PIBA2", "PIMA", "PIRE", "PIBA2", "PIMA", "PIRE", "POTR5")
cover2 = c(26.893939, 5.681818, 9.469697, 16.287879, 1.893939, 20.454546, 18.651515, 11.363636, 31.439394)
df_intended_output = data.frame(plotID2, species2, cover2)
最佳答案
轻松使用聚合
aggregate(cover~species+plotID, data=df_original, FUN=sum)
使用data.table更容易
as.data.table(df_original)[, sum(cover), by = .(plotID, species)]
关于r - 如何根据多个条件对行求和 - R？，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/28923168/