# 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.

train <- read_csv("../input/train.csv")
#cliente_table <- read_csv("../input/cliente_tabla.csv")
#producto_tabla <- read_csv("../input/producto_tabla.csv")
#test <- read_csv("../input/test.csv")
#town_state <- read_csv("../town_state.csv")

#str(train)
#str(cliente_table)

train$Semana <- as.factor(train$Semana)
train$Canal_ID <- as.factor(train$Canal_ID)

str(train)