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import requests # 網(wǎng)絡(luò)請(qǐng)求

import re

import time

import random

# post的網(wǎng)址

url = 'https://www.lagou.com/jobs/positionAjax.json?needAddtionalResult=false&isSchoolJob=0'

# 反爬措施

header = {'Host': 'www.lagou.com',

'User-Agent':'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/63.0.3239.84 Safari/537.36',

'Accept': 'application/json, text/javascript, */*; q=0.01',

'Accept-Language': 'zh-CN,en-US;q=0.7,en;q=0.3',

'Accept-Encoding': 'gzip, deflate, br',

'Referer': 'https://www.lagou.com/jobs/list_Python?labelWords=&fromSearch=true&suginput=',

'Content-Type': 'application/x-www-form-urlencoded; charset=UTF-8',

'X-Requested-With': 'XMLHttpRequest',

'X-Anit-Forge-Token': 'None',

'X-Anit-Forge-Code': '0',

'Content-Length': '26',

'Cookie': 'user_trace_token=20171103191801-9206e24f-9ca2-40ab-95a3-23947c0b972a; _ga=GA1.2.545192972.1509707889; LGUID=20171103191805-a9838dac-c088-11e7-9704-5254005c3644; JSESSIONID=ABAAABAACDBABJB2EE720304E451B2CEFA1723CE83F19CC; _gat=1; LGSID=20171228225143-9edb51dd-ebde-11e7-b670-525400f775ce; PRE_UTM=; PRE_HOST=www.baidu.com; PRE_SITE=https%3A%2F%2Fwww.baidu.com%2Flink%3Furl%3DKkJPgBHAnny1nUKaLpx2oDfUXv9ItIF3kBAWM2-fDNu%26ck%3D3065.1.126.376.140.374.139.129%26shh%3Dwww.baidu.com%26sht%3Dmonline_3_dg%26wd%3D%26eqid%3Db0ec59d100013c7f000000055a4504f6; PRE_LAND=https%3A%2F%2Fwww.lagou.com%2F; LGRID=20171228225224-b6cc7abd-ebde-11e7-9f67-5254005c3644; index_location_city=%E5%85%A8%E5%9B%BD; TG-TRACK-CODE=index_search; SEARCH_ID=3ec21cea985a4a5fa2ab279d868560c8',

'Connection': 'keep-alive',

'Pragma': 'no-cache',

'Cache-Control': 'no-cache'}

for n in range(30):

   # 要提交的數(shù)據(jù)

   form = {'first':'false',

           'kd':'Python',

           'pn':str(n)}

   time.sleep(random.randint(2,5))

   # 提交數(shù)據(jù)

   html = requests.post(url,data=form,headers = header)

   # 提取數(shù)據(jù)

   data = re.findall('{'companyId':.*?,'positionName':'(.*?)','workYear':'(.*?)','education':'(.*?)','jobNature':'(.*?)','financeStage':'(.*?)','companyLogo':'.*?','industryField':'.*?','city':'(.*?)','salary':'(.*?)','positionId':.*?,'positionAdvantage':'(.*?)','companyShortName':'(.*?)','district'',html.text)

   # 轉(zhuǎn)換成數(shù)據(jù)框

   data = pd.DataFrame(data)

   # 保存在本地

   data.to_csv(r'D:\Windows 7 Documents\Desktop\My\LaGouDataMatlab.csv',header = False, index = False, mode = 'a+')

import pandas as pd # 數(shù)據(jù)框操作

import numpy as np

import matplotlib.pyplot as plt # 繪圖

import jieba # 分詞

from wordcloud import WordCloud # 詞云可視化

import matplotlib as mpl  # 配置字體

from pyecharts import Geo # 地理圖

mpl.rcParams['font.sans-serif'] = ['Microsoft YaHei']

# 配置繪圖風(fēng)格

plt.rcParams['axes.labelsize'] = 16.  

plt.rcParams['xtick.labelsize'] = 14.

plt.rcParams['ytick.labelsize'] = 14.

plt.rcParams['legend.fontsize'] = 12.

plt.rcParams['figure.figsize'] = [15., 15.]

# 導(dǎo)入數(shù)據(jù)

data = pd.read_csv('D:\\Windows 7 Documents\\Desktop\\My\\LaGouDataPython.csv',encoding='gbk')  # 導(dǎo)入數(shù)據(jù)

data.head()

data.tail()

data['學(xué)歷要求'].value_counts().plot(kind='barh',rot=0)

plt.show()

data['工作經(jīng)驗(yàn)'].value_counts().plot(kind='bar',rot=0,color='b')

plt.show()

final = ''  

stopwords = ['PYTHON','python','Python','工程師','（','）','/'] # 停止詞

for n in range(data.shape[0]):

   seg_list = list(jieba.cut(data['崗位職稱(chēng)'][n]))

   for seg in seg_list:  

       if seg not in stopwords:  

               final = final + seg + ' '

# final 得到的詞匯

data['工作地點(diǎn)'].value_counts().plot(kind='pie',autopct='%1.2f%%',explode = np.linspace(0,1.5,25))

plt.show()

# 提取數(shù)據(jù)框

data2 = list(map(lambda x:(data['工作地點(diǎn)'][x],eval(re.split('k|K',data['工資'][x])[0])*1000),range(len(data))))

# 提取價(jià)格信息

data3 = pd.DataFrame(data2)

# 轉(zhuǎn)化成Geo需要的格式

data4 = list(map(lambda x:(data3.groupby(0).mean()[1].index[x],data3.groupby(0).mean()[1].values[x]),range(len(data3.groupby(0)))))

# 地理位置展示

geo = Geo('全國(guó)Python工資布局', '制作人:挖掘機(jī)小王子', title_color='#fff', title_pos='left', width=1200, height=600,

background_color='#404a59')

attr, value = geo.cast(data4)

geo.add('', attr, value, type='heatmap', is_visualmap=True, visual_range=[0, 300], visual_text_color='#fff')

# 中國(guó)地圖Python工資，此分布是最低薪資

geo