Coursera_ML/Week1_task6.py at master · andrew-kulikov/Coursera_ML · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
# -*- coding: utf-8 -*-
"""
Created on Tue Jul  4 14:50:40 2017

@author: User-PC
"""

import pandas
import numpy as np

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

f = open('test6.txt', 'w')

def ExtractName(full_name):
    first_name = ''
    if full_name.find('(') != -1:
        name_splitted = full_name.split('(')
        name_splitted1 = name_splitted[1].split(' ')
        first_name = name_splitted1[0]
    else :
        name_splitted = full_name.split(' ')
        first_name = name_splitted[2]
    return first_name

def ClearName(name):
    if ')' in name:
        name = name.replace(')', '')
    if '.' in name:
         name = name.replace('.', '')
    if '"' in name:
         name = name.replace('"', '')
    return name

def FindMax(names, amounts):
    max_c = 0
    max_ind = 0
    for i in range(len(names)):
        if amounts[i] > max_c:
            max_c = amounts[i]
            max_ind = i
    return names[max_ind]

name_arr = np.array(data['Name'])
name_arr1 = []
sex_arr1 = np.array(data['Sex'])
j = 0
for i in range(len(name_arr)):
    if sex_arr1[i] == 'female':
        name_arr1.append(ClearName(ExtractName(name_arr[i])))
name_counts = []
for x in name_arr1:
    n = 0
    for y in name_arr1:
        if x == y:
            n += 1
    name_counts.append(n)

print(FindMax(name_arr1, name_counts))
f.write(str(FindMax(name_arr1, name_counts)))
f.close()