如何根据多个条件对行求和 - R？

Question

我有一个包含地块 ID (plotID)、树种代码 (species) 和覆盖值 (cover) 的数据框。您可以看到其中一个地块内有多个树种记录。如果每个图中有重复的 "species" 行，我如何对 "cover" 字段求和？

例如，这里有一些示例数据：

# 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)

Answer 1

您可以通过多种方式做到这一点。使用 base-r，dplyr 和 data.table 将是最典型的。

这是dplyr的方式：

library(dplyr)

df_original %>% group_by(plotID, species) %>% summarize(cover = sum(cover))

#          plotID species     cover
#1 SUF200001035014    ABBA 26.893939
#2 SUF200001035014    BEPA  5.681818
#3 SUF200001035014   PIBA2  9.469697
#4 SUF200001035014    PIMA 16.287879
#5 SUF200001035014    PIRE  1.893939
#6 SUF200046012040   PIBA2 20.454546
#7 SUF200046012040    PIMA 27.651515
#8 SUF200046012040    PIRE 11.363636
#9 SUF200046012040   POTR5 31.439394

这将是 base-r 方式：

aggregate(df_original$cover, by=list(df_original$plotID, df_original$species), FUN=sum)

还有一个 data.table 方式 -

    library(data.table)
    DT <- as.data.table(df_original)
    DT[, lapply(.SD,sum), by = "plotID,species"]

Answer 2

轻松 aggregate

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)]

Answer 3

如上所述，ddply来自plyr包

    library(plyr)
    ddply(df_original, c("plotID","species"), summarise,cover2= sum(cover))


            plotID          species cover2
    1       SUF200001035014 ABBA    26.893939
    2       SUF200001035014 BEPA    5.681818
    3       SUF200001035014 PIBA2   9.469697
    4       SUF200001035014 PIMA    16.287879
    5       SUF200001035014 PIRE    1.893939
    6       SUF200046012040 PIBA2   20.454546
    7       SUF200046012040 PIMA    27.651515
    8       SUF200046012040 PIRE    11.363636
    9       SUF200046012040 POTR5   31.439394

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