python学习

“人生苦短，我用python”

这几日折腾搭建了python平台，主要安装了numpy，scipy，matplotlib，scikit-learn这几个包。

先来一个小程序练练手。

 

from numpy import *

import sklearn

import random

from sklearn import linear_model



# load dataset

infile = "C:\\Users\\Administrator\\Desktop\\1.txt"

fr = open(infile)

lines = fr.readlines()

numberOfLines = len(lines)

src = []

result = []

for line in lines:

    listFromLine = line.strip().split('\t')

    # map all elements to float

    floatLine = map(float, listFromLine)

    src.append(floatLine)

    

src = array(src)

row, col = src.shape

for loop in range(0, 10):

    

    # shuffle the sample

    random.shuffle(src)

    

    trainFeature = src[0 : row / 2, 0 : -1]

    trainLabel = src[0 : row / 2, -1]

    testFeature = src[row / 2 : row, 0 : -1]

    testLabel = src[row / 2 : row, -1]

    testNumber = len(testLabel)

    

    # train

    clf = linear_model.LogisticRegression()

    clf.fit(trainFeature, trainLabel)

    

    # test

    Y = clf.predict(testFeature)



    # predict answer

    right = 0

    for i in range(0, testNumber):

        if Y[i] == testLabel[i]:

            right = right + 1

    result.append(float(right) / float(testNumber) * 100)

    

print sum(result) / len(result)

 

　　

 

整理的一些python学习资料

一.python入门

1.Python教程，廖雪峰

2.Python初学者，GithHub上的PythonShare

3.学习Python的11个资源

4.Python正则表达式指南

二.爬虫

1.Python爬虫教程大全

2.零基础自学用Python3开发网络爬虫（一）（2,3,4）

三.机器学习

1.scilit-learn主页