2019獨角獸企業重金招聘Python工程師標準>>>

開發環境

pip install numpy pip install pylab pip install matplotlib pip install scipy pip install sklearn pip install pyparsing pip install six

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數據導入和可視化

前4列包含著特征值，最后一列代表著樣本類型。CSV文件很容易被numpy類庫的genfromtxt方法解析：

import urllib2 url = 'http://aima.cs.berkeley.edu/data/iris.csv' u = urllib2.urlopen(url) localFile = open('iris.csv'', 'w') localFile.write(u.read()) localFile.close()from numpy import genfromtxt, zeros data = genfromtxt('iris.csv',delimiter=',',usecols=(0,1,2,3)) target = genfromtxt('iris.csv',delimiter=',',usecols=(4),dtype=str)print data.shape print target.shape

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建一個二維散點圖

from pylab import plot, show plot(data[target=='setosa',0],data[target=='setosa',2],'bo') plot(data[target=='versicolor',0],data[target=='versicolor',2],'ro') plot(data[target=='virginica',0],data[target=='virginica',2],'go') show()

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分特性繪制直方圖

from pylab import figure, subplot, hist, xlim, show xmin = min(data[:,0]) xmax = max(data[:,0]) figure()hist(data[target=='setosa',0],color='b',alpha=.7) xlim(xmin,xmax)hist(data[target=='versicolor',0],color='r',alpha=.7) xlim(xmin,xmax)hist(data[target=='virginica',0],color='g',alpha=.7) xlim(xmin,xmax)hist(data[:,0],color='y',alpha=.7) xlim(xmin,xmax) show()

轉載于:https://my.oschina.net/readerror/blog/1576364

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