import numpy as np
import pandas as pd
import xgboost
from sklearn import model_selection
from sklearn.metrics import accuracy_score 

#Print you can execute arbitrary python code
train = pd.read_csv("../input/train.csv")
test = pd.read_csv("../input/test.csv")

#print(train.head())
#print(train.info())
#print(train.Survived)
#print(train.head())
#
#print("\n\nSummary statistics of training data")
#print(train.describe())

#Any files you save will be available in the output tab below
#train.to_csv('copy_of_the_training_data.csv', index=False)