library('ggplot2') # visualization
library('ggthemes') # visualization
library('scales') # visualization
library('dplyr') # data manipulation
library('mice') # imputation
library('randomForest') # classification algorithm

train <- read.csv('../input/train.csv', stringsAsFactors = F)
test  <- read.csv('../input/test.csv', stringsAsFactors = F)

full  <- bind_rows(train, test) # bind training & test data

# check data
str(full)