# 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.

require(data.table)
require(bit64)

dir()
train_df = fread('../input/train.csv')
block_1 = train_df[train_df$x <= 1 &
                         train_df$y <= 1 &
                         train_df$x >= 0 &
                         train_df$y >= 0,]
head(block_1)