# 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
library(data.table)
#library(xgboost)
library(rpart)
#library(sqldf) # to write sql commands

# 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.
#rm(list=ls())
click_train <- fread("../input/clicks_train.csv")
click_train <- click_train[(1:10000000),]

events <- fread("../input/events.csv")
events <- events[-(303066),]