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- How to sum a variable by group 13 answers
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?
For example, here is some sample data:
# 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)
And here is the intended output:
# 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)
ExperimenteR
Easy with aggregate
aggregate(cover~species+plotID, data=df_original, FUN=sum)
Easier with data.table
as.data.table(df_original)[, sum(cover), by = .(plotID, species)]
You can do this in a number of ways. Using base-r, dplyr and data.table would be the most typical.
Here is dplyr 's way:
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
This would be the base-r way:
aggregate(df_original$cover, by=list(df_original$plotID, df_original$species), FUN=sum)
And a data.table way -
library(data.table)
DT <- as.data.table(df_original)
DT[, lapply(.SD,sum), by = "plotID,species"]
As mentioned above, ddply from the plyr package
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
来源：https://stackoverflow.com/questions/28923168/how-to-sum-rows-based-on-multiple-conditions-r