Author: Sebastian Kranz, Ulm University
Fast modification of data.frames and data.tables by reference; modify is essentially just a wrapper for data.table syntax but can be used for other data containers like data frames. It is thought as an addition to dplyr functions. While the functionality can be replicated by mutate, modify can be much faster and more concise if only values for selected rows shall be modified (see benchmark example below).
To install from github, first install devtools from CRAN and then run
library(devtools)
install_github(repo = "modify", username = "skranz")
library(microbenchmark)
library(modify)
n = 10
df = data.frame(a= sample(1:3,n,replace=TRUE),
b= sample(1:100,n,replace=TRUE),
x=rnorm(n))
# Set x to 100 where a==2
modify(df,a==2, x=100)
df
# Set x to the mean value of b*100 in each group of a
modify(df,.by=c("a"),
x=mean(b)*100)
df
# Call with strings
com = "x=200"
s_modify(df,"a==2", com)
# Benckmark compared to directly using data.table or dplyr
n = 1e6
df = data.frame(a= sample(1:5,n,replace=TRUE),
b= sample(1:100,n,replace=TRUE),
x=rnorm(n))
dt = as.data.table(df)
tbl = as.tbl(df)
modify(tbl, a==2,x = x+100)
mutate(df, x=ifelse(a==2,x+100,x))
tbl
microbenchmark(times = 5L,
modify(tbl,a==2, x = x+100),
modify(df,a==2, x = x+100),
modify(dt,a==2, x = x+100),
dt[a==2,x:=x+100],
mutate.df = mutate(df, x=ifelse(a==2,x+100,x)),
mutate.tbl = mutate(tbl, x=ifelse(a==2,x+100,x))
)
# Unit: milliseconds
# expr min lq median uq max neval
# modify(tbl, a == 2, x = x + 100) 51.37875 52.75087 53.43773 56.89211 65.82984 5
# modify(df, a == 2, x = x + 100) 62.41217 73.70730 81.48766 95.45519 104.04200 5
# modify(dt, a == 2, x = x + 100) 55.61156 58.30331 62.36006 65.13786 82.47056 5
# dt[a == 2, `:=`(x, x + 100)] 61.03452 69.32567 69.56923 74.70600 81.87845 5
# mutate.df 766.40427 881.66008 887.30054 940.57168 964.20248 5
# mutate.tbl 769.94984 836.24982 881.46705 883.49444 1015.74663 5