爬虫的代码如下所示，大家可以把谷歌的主页换成百度，修改一下爬虫的命令，就可以自己试试看这段代码。注意要先定义你需要爬取的城市名称的列表cityname哦。
import time from selenium import webdriver #导入需要的模块，其中爬虫使用的是selenium import pandas as pd import numpy as np #导入元数据 city = pd.read_csv(r'D:whole_development_of_the_stack_studyRS_Algorithm_CoursePracticalmachine_learning 8_09_10_11SVM_01Cityclimate.csv') city #第一列是城市名，第二列是气候。
City Climate Adelaide Warm temperate Albany Mild temperate Albury Hot dry summer, cool winter Wodonga Hot dry summer, cool winter AliceSprings Hot dry summer, warm winter Amata Hot dry summer, cool winter Ballarat Cool temperate Bathurst Cool temperate Birdsville Hot dry summer, warm winter Borroloola High humidity summer, warm winter Bourke Hot dry summer, cool winter Brisbane Warm humid summer, mild winter BrokenHill Hot dry summer, cool winter Broome High humidity summer, warm winter Bunbury Warm temperate Burketown High humidity summer, warm winter Burra Mild temperate Cairns High humidity summer, warm winter Canberra Cool temperate Carnarvon Hot dry summer, warm winter Ceduna Warm temperate Charleville Hot dry summer, warm winter CooberPedy Hot dry summer, cool winter Cooktown High humidity summer, warm winter CoffsHarbour Warm humid summer, mild winter Dampier High humidity summer, warm winter Darwin High humidity summer, warm winter Derby High humidity summer, warm winter Devonport Cool temperate Dubbo Hot dry summer, cool winter Elliot Hot dry summer, warm winter Esperance Warm temperate Eucla Warm temperate Exmouth High humidity summer, warm winter GascoyneJunction Hot dry summer, warm winter Geraldton Warm temperate Goondiwindi Hot dry summer, warm winter Griffith Hot dry summer, cool winter HallsCreek Hot dry summer, warm winter Hobart Cool temperate Horsham Mild temperate Innamincka Hot dry summer, cool winter Ivanhoe Hot dry summer, cool winter Kalgoorlie–Boulder Hot dry summer, cool winter Katherine High humidity summer, warm winter Kingscote Mild temperate KingstonSE Mild temperate Kulgera Hot dry summer, warm winter LakesEntrance Mild temperate Launceston Cool temperate LeighCreek Warm temperate Longreach Hot dry summer, warm winter LordHoweIsland Warm temperate Mackay Warm humid summer, mild winter MargaretRiver Warm temperate Maryborough Warm humid summer, mild winter Melbourne Mild temperate MelbourneAirport Mild temperate Merredin Hot dry summer, cool winter Mildura Hot dry summer, cool winter MountGambier Mild temperate MountIsa Hot dry summer, warm winter Newcastle Warm temperate Newdegate Hot dry summer, cool winter Newman Hot dry summer, warm winter Nhulunbuy High humidity summer, warm winter Norseman Hot dry summer, cool winter Nullarbor Hot dry summer, cool winter Oenpelli High humidity summer, warm winter Oodnadatta Hot dry summer, cool winter Perth Warm temperate PerthAirport Warm temperate PortHedland High humidity summer, warm winter PortLincoln Warm temperate PortMacquarie Warm temperate Renmark Warm temperate Rockhampton Warm humid summer, mild winter Shepparton Hot dry summer, cool winter Southport Cool temperate Strahan Cool temperate Swansea Cool temperate Sydney Warm temperate SydneyAirport Warm temperate Tamworth Hot dry summer, cool winter Taroom Hot dry summer, warm winter Telfer Hot dry summer, warm winter TennantCreek Hot dry summer, warm winter Thargomindah Hot dry summer, warm winter Tibooburra Hot dry summer, cool winter TimberCreek High humidity summer, warm winter Townsville High humidity summer, warm winter Warburton Hot dry summer, cool winter Weipa High humidity summer, warm winter Whyalla Hot dry summer, cool winter Wiluna Hot dry summer, cool winter Wollongong Warm temperate Wyndham High humidity summer, warm winter Yalgoo Hot dry summer, cool winter Yulara Hot dry summer, warm winter Uluru Hot dry summer, warm winter
#提取城市名 cityname = city.iloc[:,0] cityname
#开始爬虫
df =pd.DataFrame(index = cityname.index) #创建新dataframe用于存储爬取的数据
driver = webdriver.Chrome() #调用谷歌浏览器
time0 = time.time() #计时开始
#循环开始
for num,city in enumerate(cityname): #在城市名称中进行遍历
#首先打开谷歌浏览器
driver.get('https://www.google.co.uk/webhp?hl=en&sa=X&ved=0ahUKEwimtcX24cTfAhUJE7wKHVkWB5AQPAgH')
#停留1秒让我们知道发生了什么
time.sleep(1)
#锁定谷歌的搜索框 ，因为谷歌搜索框的name="q"
search_box = driver.find_element_by_name('q')
#在输入框中输入“城市” 澳大利亚 经纬度
search_box.send_keys("%s Australia Latitude and longitude" % (city))
#enter,确认开始搜索
search_box.submit()
#爬取需要的经纬度
result = driver.find_element_by_xpath('//div[@]').text
#将爬取的结果用split进行分割
resultsplit = result.split(" ")
#向提前创建好的df中输入爬取的数据，第一列是城市名
df.loc[num,"City"] = city
#第二列是纬度
df.loc[num,"Latitude"] = resultsplit[0]
#第三列是经度
df.loc[num,'Longitude'] = resultsplit[2]
#第四列是纬度的方向
df.loc[num,"Latitudedir"] = resultsplit[1]
#第五列是经度的方向
df.loc[num,"Longitudedir"] = resultsplit[3]
#每次爬虫成功之后，就打印“城市”成功了
print("%i webcrawler successful for city %s" %(num, city))
time.sleep(1) #全部爬取完毕后，停留1秒钟
driver.quit() #关闭浏览器
print(time.time()-time0) #打印所需的时间
df #所有城市的经纬度
#保存 df.to_csv(r"D:whole_development_of_the_stack_studyRS_Algorithm_CoursePracticalmachine_learning 8_09_10_11SVM_01csvcityll.csv")
机器学习-Sklearn-11（支持向量机SVM-SVC真实数据案例：预测明天是否会下雨）中爬取数据模块内容https://blog.csdn.net/m0_37755995/article/details/123944354
