data.table Computing summary statistics The summary function
Example
# example data
DT = data.table(iris)
DT[, Bin := cut(Sepal.Length, c(4,6,8))]
summary is handy for browsing summary statistics. Besides direct usage like summary(DT), it can also be applied per-group conveniently with split:
lapply(split(DT, by=c("Species", "Bin"), drop=TRUE, keep.by=FALSE), summary)
# $`setosa.(4,6]`
# Sepal.Length Sepal.Width Petal.Length Petal.Width
# Min. :4.300 Min. :2.300 Min. :1.000 Min. :0.100
# 1st Qu.:4.800 1st Qu.:3.200 1st Qu.:1.400 1st Qu.:0.200
# Median :5.000 Median :3.400 Median :1.500 Median :0.200
# Mean :5.006 Mean :3.428 Mean :1.462 Mean :0.246
# 3rd Qu.:5.200 3rd Qu.:3.675 3rd Qu.:1.575 3rd Qu.:0.300
# Max. :5.800 Max. :4.400 Max. :1.900 Max. :0.600
#
# $`versicolor.(6,8]`
# Sepal.Length Sepal.Width Petal.Length Petal.Width
# Min. :6.10 Min. :2.20 Min. :4.000 Min. :1.20
# 1st Qu.:6.20 1st Qu.:2.80 1st Qu.:4.400 1st Qu.:1.30
# Median :6.40 Median :2.90 Median :4.600 Median :1.40
# Mean :6.45 Mean :2.89 Mean :4.585 Mean :1.42
# 3rd Qu.:6.70 3rd Qu.:3.10 3rd Qu.:4.700 3rd Qu.:1.50
# Max. :7.00 Max. :3.30 Max. :5.000 Max. :1.70
#
# [...results truncated...]
To include zero-count groups, set drop=FALSE in split.
