# 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")

data = read_csv('../input/sample_submission.csv')

superSecretRecipe = function(x){
  pred = sample(1:5, 5)
  data[x,2] <<- paste0(pred[1],' ',pred[2],' ',pred[3],' ',pred[4],' ',pred[5])
}

unused = sapply(1:nrow(data), superSecretRecipe)

write.csv(data, file = 'submission.csv', quote = F, row.names = F)

# Any results you write to the current directory are saved as output.