fread
library(data.table) Similar to read.table but faster and more convenient.
ans <- flights[origin == "JFK" & month == 6L]
column can be referred to as if they are variables
%>%
pheno1 = pheno1 %>% mutate(WHR=WC/HC, FFR=FEV/FVC, WHRadjBMI=resid(lm(WHR~BMI, na.action=na.exclude)), HTsq=HT^2, HTcube=HT^3) The meaning of %>% iris %>% head() is equivalent to head(iris). I think the benefit is to decrease variables when a lot of process.
mutate
library(dplyr) like above add new variables
![]zhttps://tva1.sinaimg.cn/large/00831rSTly1gdl3lm2ct8j312q0u0ttr.jpg)
