# 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.library(data.table)
library(data.table)
train=fread("../input/train.csv")
train.book=train[is_booking==1,]
write.table(train.book,'train_book.csv',sep=',',row.names=F)

#test <- fread("../input/test.csv")
#summary(test)