# 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")
library(needs)
# Any results you write to the current directory are saved as output.

train <- read_csv("../input/train.csv")
sample <- train[1:250000,]

plot(sample$row_id,sample$time)

sample$time <- log(sample$time)

str(sample)

Place1 <- subset(train, place_id = 1)

plot(Place1$x,Place1$y)