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【Python数据分析】从Web收集数据小实例

最近在看《鲜活的数据:数据可视化指南》,学习一些数据可视化与数据分析的技术,本例是该书第一章的一个例子衍伸而来。

实例内容:从www.wunderground.com收集美国纽约州布法罗市(水牛城)2014年3月份每天最高气温,并导入Excel或WPS表格,制做成折线图。

 

工具准备:安装好的Python2.7,Beautiful Soup库(将其python文件放入Python库文件路径中)

 

步骤1:撰写Python程序。代码如下:

# -*- coding: cp936 -*-
import urllib2
from BeautifulSoup import BeautifulSoup     

f = open('wunder-data.txt','w')     #open the file

m = 3                               #get weather data of March(3) 2014
for d in range(1,32):               #loop from 2014.3.1 to 2014.3.31

    timestamp = '2014' + str(m) + str(d)    
    print "Getting data for " + timestamp   #for we can see the process in shell
    url = "http://www.wunderground.com/history/airport/KBUF/2014/" + str(m) + "/" + str(d) + "/DailyHistory.html"
    page = urllib2.urlopen(url)     #get the web page

    soup = BeautifulSoup(page)      #use BeautifulSoup to parsing the web page

    dayTemp = soup.findAll(attrs = {"class":"nobr"})[4].span.string   #the data is showed in some HTML code where <class = "nobr">s are appeared 

    if len(str(m)) < 2:             #format it
        mStamp = '0' + str(m)
    else:
        mStamp = str(m)

    if len(str(d)) < 2:             #format it
        dStamp = '0' + str(d)
    else:
        dStamp = str(d)
            
    timestamp = '2014-' + mStamp + '-' + dStamp  #make data look like 2014-03-01,which is convinient for excel or WPS to deal with

    f.write(timestamp + ',' + dayTemp + '\n')   #write it to the file
f.close()                           #close the file

 

步骤2:运行程序,得到数据文件wunder-data.txt。

步骤3:将数据导入WPS或Excel中,我用的是WPS表格:数据->导入数据->.....(这里就不贴图了)

步骤4:图表制作。

结果:

posted @ 2014-04-04 13:10 whatbeg 阅读(...) 评论(...) 编辑 收藏