如何根据多个条件对行求和 - R? [英] How to sum rows based on multiple conditions - R?

问题描述

我有一个数据框，其中包含地块 ID (plotID)、树种代码 (species) 和覆盖值 (cover).您可以看到其中一个地块中有多个树种记录.如果每个地块中有重复的物种"行，我如何对封面"字段求和?

I have a dataframe that contains a plot ID (plotID), tree species code (species), and a cover value (cover). You can see there are multiple records of tree species within one of the plots. How can I sum the "cover" field if there are duplicate "species" rows within each plot?

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)

推荐答案

轻松使用聚合

aggregate(cover~species+plotID, data=df_original, FUN=sum) 

使用 data.table

as.data.table(df_original)[, sum(cover), by = .(plotID, species)]

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