# 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 

suppressMessages(library(ggplot2)) # Data visualization
suppressMessages(library(readr)) # CSV file I/O, e.g. the read_csv function
suppressMessages(library(data.table))
suppressMessages(library(Rmisc))
suppressMessages(library(plotly))
suppressMessages(library(yaml))
suppressMessages(library(caret))
suppressMessages(library(stringr))
suppressMessages(library(data.table))
suppressMessages(library(rpart))
suppressMessages(library(partykit))
suppressMessages(library(rpart.plot))
suppressMessages(library(corrplot))
suppressMessages(library(glmnet))
suppressMessages(library(doParallel))
# 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

data <- fread("../input/events.csv")
dim(data)
length(unique(data$display_id))
# Any results you write to the current directory are saved as output.