# 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)

# 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.
#train <- fread("../input/train.csv", 
#              select = c("Semana", "Cliente_ID", "Producto_ID", "Demanda_uni_equil"))
#test <- fread("../input/test.csv")

#head(test,n=5)


x <- 0.1:1000 
y = log(x)
plot(y)