import pandas as pd
import numpy as np
from sklearn.tree import DecisionTreeClassifier

data = pd.read_csv('titanic.csv', index_col = 'PassengerId')

data = data.dropna()
data['Sex'] = np.where(data['Sex'] == 'male', 1, 0)

features = data[['Pclass', 'Fare', 'Age', 'Sex']]
target = data['Survived']

clf = DecisionTreeClassifier(random_state = 241)
clf.fit(features, target)

clf.feature_importances_
Out: array([ 0.01793336,  0.29549222,  0.40310552,  0.2834689 ])