getting_started_python.py

# -*- coding: utf-8 -*-
"""
Created on Tue May 19 13:29:23 2015

@author: Thomas
"""

import csv
import numpy as np

csv_file_object = csv.reader(open('train.csv', 'rb'))
header = csv_file_object.next()

# Import data in 'data' as numpy array
data = []
for row in csv_file_object:
    data.append(row)
data = np.array(data)

# Find number of passengers and survivors
number_passengers = np.size(data[0::,1].astype(np.float))
number_survived = np.sum(data[0::,1].astype(np.float))
proportion_survivors = number_survived / number_passengers

# Get only women and only men data
women_only_stats = data[0::,4] ==  'female'
men_only_stats = data[0::,4] != 'female'

# Find out survival percentage men/women
women_onboard = data[women_only_stats,1].astype(np.float)     
men_onboard = data[men_only_stats,1].astype(np.float)

proportion_women_survived = np.sum(women_onboard) / np.size(women_onboard)  
proportion_men_survived = np.sum(men_onboard) / np.size(men_onboard) 

test_file = open('test.csv', 'rb')
test_file_object = csv.reader(test_file)
header = test_file_object.next()

prediction_file = open("genderbasedmodel.csv", "wb")
prediction_file_object = csv.writer(prediction_file)

prediction_file_object.writerow(["PassengerId", "Survived"])
for row in test_file_object:       # For each row in test.csv
    if row[3] == 'female':         # is it a female, if yes then                                       
        prediction_file_object.writerow([row[0],'1'])    # predict 1
    else:                              # or else if male,       
        prediction_file_object.writerow([row[0],'0'])    # predict 0
test_file.close()
prediction_file.close()