# This R environment comes with all of CRAN preinstalled, as well as many other helpful packages
# The environment is defined by the kaggle/rstats docker image: https://github.com/kaggle/docker-rstats
# For example, here's several helpful packages to load in 

library(ggplot2) # Data visualization
library(readr) # CSV file I/O, e.g. the read_csv function

# Input data files are available in the "../input/" directory.
# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directory

system("ls ../input")

# Any results you write to the current directory are saved as output.
a<- rep(1:4, 2)
a
b<- rep(1:4, each = 2) 
b
c<- rep(1:4, c(2,2,2,2))
c
d<- rep(1:4, c(2,1,2,1))
d
e<- rep(1:4, each = 2, len = 4)    # first 4 only.
e
f<- rep(1:4, each = 2, len = 10)   # 8 integers plus two recycled 1's.
f
g<- rep(1:4, each = 2, 3)  # length 24, 3 complete replications
g
df.dd<- c(a,b,c,d,e,f,g)