# Load in our libraries
import pandas as pd
import numpy as np
import re
import sklearn
import xgboost as xgb
import seaborn as sns
import matplotlib.pyplot as plt
#%matplotlib inline
plt.show()

import plotly.offline as py
py.init_notebook_mode(connected=True)
import plotly.graph_objs as go
import plotly.tools as tls

# Going to use these 5 base models for the stacking
from sklearn.ensemble import RandomForestClassifier, AdaBoostClassifier, GradientBoostingClassifier, ExtraTreesClassifier
from sklearn.svm import SVC
from sklearn.cross_validation import KFold;

# Load in the train and test datasets
train = pd.read_csv('../input/train.csv')
test = pd.read_csv('../input/test.csv')

# Store our passenger ID for easy access
PassengerId = test['PassengerId']
train.head(3)