python数据挖掘Hello World
生活随笔
收集整理的這篇文章主要介紹了
python数据挖掘Hello World
小編覺得挺不錯(cuò)的,現(xiàn)在分享給大家,幫大家做個(gè)參考.
2019獨(dú)角獸企業(yè)重金招聘Python工程師標(biāo)準(zhǔn)>>>
開發(fā)環(huán)境
pip install numpy pip install pylab pip install matplotlib pip install scipy pip install sklearn pip install pyparsing pip install six數(shù)據(jù)導(dǎo)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建一個(gè)二維散點(diǎn)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()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(zhuǎn)載于:https://my.oschina.net/readerror/blog/1576364
總結(jié)
以上是生活随笔為你收集整理的python数据挖掘Hello World的全部內(nèi)容,希望文章能夠幫你解決所遇到的問題。
- 上一篇: MVC基于角色权限控制--用户管理
- 下一篇: [RHEL] RHEL7.0 下 Pos