数据从txt文本导入python

机器学习实战 p21

源代码：

def file2matrix(filename):     fr = open(filename)     numberOfLines = len(fr.readlines())         #get the number of lines in the file     returnMat = zeros((numberOfLines,3))        #prepare matrix to return     classLabelVector = []                       #prepare labels return        fr = open(filename)     index = 0     for line in fr.readlines():         line = line.strip()         listFromLine = line.split('\t')         returnMat[index,:] = listFromLine[0:3]         classLabelVector.append(int(listFromLine[-1]))  此句报错         index += 1     return returnMat,classLabelVector

报错如下：

>>> mat,label = kNN.file2matrix('datingTestSet.txt') Traceback (most recent call last):   File "<stdin>", line 1, in <module>   File "kNN.py", line 50, in file2matrix     classLabelVector.append(int(listFromLine[-1])) ValueError: could not convert string to int: largeDoses

解决方法：

listFromLine[-1]的值形似如下格式，带有回车换行符

largeDoses\r\n

smallDoses\r\n

didntLike\r\n

didntLike\r\n

didntLike\r\n

要将字母字符串转换为int类型是不可能的。

作者定义largeDoses 为3，smallDoses 为2，didntLike为1

于是笔者增加了一个字典类型

d = {'didntLike': 1, 'smallDoses': 2, 'largeDoses': 3}

通过d[listFromLine[-1]]得到对应的label

更改后的代码如下：

rf.py

from numpy import * import operator from os import listdir def rf(filename):     fr = open(filename)     numberOfLines = len(fr.readlines())         #get the number of lines in the file     returnMat = zeros((numberOfLines,3))        #prepare matrix to return d = {'didntLike': 1, 'smallDoses': 2, 'largeDoses': 3}     classLabelVector = []     index = 0     fr = open(filename)     for line in fr.readlines():         listFromLine = line.split('\t')         returnMat[index,:] = listFromLine[0:3]         listFromLine[-1] = listFromLine[-1][0:-2]        #去除尾端的回车换行符         classLabelVector.append(d[listFromLine[-1]])   #取到字典中对应的label值         index += 1     return returnMat,classLabelVector

画图：

import rf mat,label = rf.rf('datingTestSet.txt') import matplotlib import matplotlib.pyplot as plt fig = plt.figure() >>> ax1 = fig.add_subplot(2, 2, 1) >>> ax1.scatter(mat[:,0],mat[:,1]) >>> ax2 = fig.add_subplot(2, 2, 2) >>> ax2.scatter(mat[:,1],mat[:,2]) from numpy import array #需要自己导入array，否则会报错 >>> ax3 = fig.add_subplot(2, 2, 3) >>> ax3.scatter(mat[:,0],mat[:,1],15.0*array(label),15.0*array(label)) ax4 = fig.add_subplot(2, 2, 4) ax4.scatter(mat[:,1],mat[:,2],15.0*array(label),15.0*array(label)) plt.show()