class.py

# -*- coding: utf-8 -*-
"""
Created on Thu Nov 10 21:27:59 2016

@author: ben
"""

import csv

import numpy
import matplotlib.pyplot as plt

def age_or_mean(age):
    if age == '':
        age = 28.5
    else:
        age = float(age)
    return age        
    
def predict(datapoint):
    #we want to return the prediction about this datapoint

    age = datapoint['Age']
    sex = datapoint['Sex']
    pclass = int(datapoint['Pclass'])
    age = age_or_mean(age)
        
    if age <= 15:
        if pclass < 3:
            return True
        else:
            return False
    else:
        if sex == 'female':
            return True
        else:
            if pclass == 1:
                return True
            else:
                return False
    

myfile = open('/Users/Ben/Desktop/train.csv').readlines()

myreader = csv.DictReader(myfile)

actuals = []
predictions = []

ages = []
classes = []
colors = []
for x in myreader:
#    print x['Name']
#    print x['Age']
#    print x['Sex']
    age = age_or_mean(x['Age'])
    sex = x['Sex']
    pred = predict(x)
    predictions.append(pred)
#    print pred
    ages.append(age)
    classes.append(int(x['Pclass']))
#    if sex == 'male':
#        sexes.append(1)
#    else:
#        sexes.append(0)
    if x['Survived'] == '1':
        actuals.append(True)
        colors.append('g')
    else:
       
        actuals.append(False)
        colors.append('r')
#    print '-------'

corrects = 0
for index in range(len(actuals)):
    if actuals[index] == predictions[index]:
        corrects += 1
print "You got " + str(corrects/float(len(actuals))) + " percent correct"

plt.scatter(ages, sexes, color=colors)
plt.show()
#
#print numpy.mean(yesses), numpy.std(yesses)
#plt.hist(yesses, bins=2)
#plt.show()
#
#print '\n'
#print numpy.mean(nos), numpy.std(nos)
#plt.hist(nos, bins=2)
#plt.show()