pyecharts数据分析及展示

仅仅从网上爬下数据当然是不够用的，主要还得对数据进行分析与展示，大部分人都看重薪资，但是薪资数据有的是*k/月，有的是*万/月，还有*万/年等等，就要对数据进行清理

将所有单位统一化，全部换算成统一单位，然后分类薪资范围，在计算各个范围的数量，最后绘图展示

import pymysql
import numpy as np
from pyecharts import Bar
from pyecharts import Pie

class Mysqlhelper(object):
    config = {
        "host": "localhost",
        "user": "root",
        "password": "",
        "db": "test",
        "charset": "utf8"
    }

    def __init__(self):
        self.connection = None
        self.cursor = None

    # 从数据库中查询多行数据
    def getlist(self, sql, *args):
        try:
            self.connection = pymysql.connect(**Mysqlhelper.config)  # **接函数所有参数
            self.cursor = self.connection.cursor()
            self.cursor.execute(sql, args)
            return self.cursor.fetchall()
        except Exception as ex:
            print(ex, ex)
        finally:
            self.close()

    def close(self):
        if self.cursor:
            self.cursor.close()
        if self.connection:
            self.connection.close()

if __name__ == "__main__":
    count=0
    list = []
    list1 = []
    list2 = [5000,10000,15000,20000,25000,30000,35000,40000]
    salary0 = []
    salary1 = []
    salary2 = []
    salary3 = []
    salary4 = []
    salary5 = []
    salary6 = []
    salary7 = []
    city=[]
    helper = Mysqlhelper()
    rows = helper.getlist("select * from t_job")

    #print(rows)
    for n in rows:
        if n[4][-1]=='月':
            list.append(n[4])
        elif n[4][-1]=='年':
            pass
        elif n[4][-1]=='天':
            pass
        else:
            pass
    for sale in list:
        #print(sale)
        money = sale.split('/')
        #print(money[0])
        money1 = money[0].split('-')
        #print(money1)
        if money[0][-1] == '万':
            a = float(money1[0]) * 10000
            b = float(money1[1][:-1]) * 10000
            aveage = (a + b) / 2
            count+=1
            list1.append(aveage)
        elif money[0][-1]=='千':
            a = float(money1[0]) * 1000
            b = float(money1[1][:-1]) * 1000
            #print(a)
            #print(b)
            aveage = (a + b) / 2
            #print(aveage)
            count += 1
            list1.append(aveage)
    #print(count)
    #print(list1)
    for i in list1:
        print(i)
        if 0 < i <= 5000:
            salary0.append(i)
        elif 5000 < i <= 10000:
            salary1.append(i)
        elif 10000 < i <= 15000:
            salary2.append(i)
        elif 15000 < i <= 20000:
            salary3.append(i)
        elif 20000 < i <= 25000:
            salary4.append(i)
        elif 25000 < i <= 30000:
            salary5.append(i)
        elif 30000 < i <= 35000:
            salary6.append(i)
        elif 35000 < i <= 40000:
            salary7.append(i)
    print(min(list1))
    print(max(list1))
    a = len(salary0)
    b = len(salary1)
    c = len(salary2)
    d = len(salary3)
    e = len(salary4)
    f = len(salary5)
    g = len(salary6)
    h = len(salary7)
    list3=[a,b,c,d,e,f,g,h]
    print(list2)   #x轴
    print(a,b,c,d,e,f,g,h)
    print(list3)   #数量

    bar = Bar('Python平均工资')
    bar.add("月薪", list2,list3)
    # bar.show_config()
    bar.render('Python工资柱状图.html')

    pie = Pie()
    pie.add("", list2, list3, is_label_show=True)
    #pie.show_config()
    pie.render('Python工资饼状图.html')
    '''

    #print(rows)
    citycount=[]
    cityname=['北京','异地招聘','海淀区','朝阳区','丰台区','昌平区','东城区','延庆区',
              '房山区','通州区','顺义区','大兴区','怀柔区','西城区','平谷区','门头沟区']
    beijing=[]
    yidi=[]

    haidian=[]
    chaoyang=[]
    fengtai=[]
    changping=[]
    dongcheng=[]
    yanqing=[]
    fangshan=[]
    tongzhou=[]
    shunyi=[]
    daxing=[]
    huairou=[]
    xicheng=[]
    pinggu=[]
    mentougou=[]

    for n in rows:
        #print(n[3])
        area=n[3].split('-')
        print(area)
        if len(area)==1:
            print(area[0])
            city.append(area[0])
        else:
            print(area[1])
            city.append(area[1])
    print(city)
    print(len(city))
    for i in city:
        if i=='北京':
            beijing.append(i)
        elif i=='异地招聘':
            yidi.append(i)
        elif i=='海淀区':
            haidian.append(i)
        elif i == '朝阳区':
            chaoyang.append(i)
        elif i=='丰台区':
            fengtai.append(i)
        elif i=='昌平区':
            changping.append(i)
        elif i=='东城区':
            dongcheng.append(i)
        elif i=='延庆区':
            yanqing.append(i)
        elif i=='房山区':
            fangshan.append(i)
        elif i=='通州区':
            tongzhou.append(i)
        elif i=='顺义区':
            shunyi.append(i)
        elif i=='大兴区':
            daxing.append(i)
        elif i=='怀柔区':
            huairou.append(i)
        elif i=='西城区':
            xicheng.append(i)
        elif i=='平谷区':
            pinggu.append(i)
        elif i=='门头沟区':
            mentougou.append(i)

    #print(beijing)
    #print(len(beijing))

    a = len(beijing)
    b = len(yidi)
    c = len(haidian)
    d = len(chaoyang)
    e = len(fengtai)
    f = len(changping)
    g = len(dongcheng)
    h = len(yanqing)
    j = len(fangshan)
    k = len(tongzhou)
    l = len(shunyi)
    m = len(daxing)
    n = len(huairou)
    o = len(xicheng)
    p = len(pinggu)
    q = len(mentougou)
    citycount=[a,b,c,d,e,f,g,h,j,k,l,m,n,o,p,q]
    print(cityname)
    print(citycount)

    pie = Pie()
    pie.add("", cityname, citycount, is_label_show=True)
    # pie.show_config()
    pie.render('北京各区Python职位占比饼状图.html')

    bar = Bar('北京各区职位数量')
    bar.add("数量", cityname, citycount)
    # bar.show_config()
    bar.render('北京各区Python职位占比柱状图.html')

    '''

前面写的是数据库的操作函数，其实可以封装成一个py文件，以后使用直接调用即可。

结果。：

我也分析了boss直聘网站的一些数据，类似于经验要求和学历要求等等，也可以自己分析想要的数据。

import pymysql
import numpy as np
from pyecharts import Bar
from pyecharts import Pie
import jieba
from collections import Counter
from os import  path

class Mysqlhelper(object):
    config={
        "host":"localhost",
        "user":"root",
        "password":"",
        "db":"test",
        "charset":"utf8"
    }

    def __init__(self):
        self.connection=None
        self.cursor=None

    # 从数据库中查询多行数据
    def getlist(self, sql, *args):
        try:
            self.connection = pymysql.connect(**Mysqlhelper.config)  # **接函数所有参数
            self.cursor = self.connection.cursor()
            self.cursor.execute(sql, args)
            return self.cursor.fetchall()
        except Exception as ex:
            print(ex,ex)
        finally:
            self.close()

    def close(self):
        if self.cursor:
            self.cursor.close()
        if self.connection:
            self.connection.close()

if __name__=="__main__":
    sale=[]
    exp=[]
    edu=[]
    one = []
    three = []
    five = []
    onein = []
    noexp = []
    qita=[]
    benke=[]
    dazhuan=[]
    noedu=[]
    boshi=[]
    other=[]
    helper = Mysqlhelper()
    rows = helper.getlist("select * from boss_job")
    #print(rows)

    for data in rows:
        #print(data[2])
        #print(data[5])
        #print(data[6])
        sale.append(data[2])
        exp.append(data[5])
        edu.append(data[6])
        if data[5]=='1-3年':
            one.append(data[5])
        elif data[5]=='3-5年':
            three.append(data[5])
        elif data[5]=='5-10年':
            five.append(data[5])
        elif data[5]=='经验不限':
            noexp.append(data[5])
        elif data[5]=='1年以内':
            onein.append(data[5])
        else:
            qita.append(data[5])
            pass
        if data[6]=='本科':
            benke.append(data[6])
        elif data[6]=='大专':
            dazhuan.append(data[6])
        elif data[6]=='博士':
            boshi.append(data[6])
        elif data[6]=='学历不限':
            noedu.append(data[6])
        else:
            other.append(data[6])

    #     with open('./data/jingyan.txt', 'a', encoding='utf-8') as fp:
    #         fp.write(data[5])
    #         fp.write(',')
    #         fp.flush()
    #         fp.close()
    print(exp)
    print(edu)
    print(len(exp))
    print(len(edu))

    '''
    d = path.dirname(__file__)
    jingyan_text = open(path.join(d, "data//jingyan.txt"), encoding='utf-8').read()
    print(len(jingyan_text))

    jieba.load_userdict("data//jingyan_dict.txt")

    seg_list = jieba.cut_for_search(jingyan_text)
    print(u"[全模式]: ", "/ ".join(seg_list))
    '''
    # sanguo_words = [x for x in jieba.cut(jingyan_text)if x!=','and len(x) >=2]
    # c = Counter(sanguo_words).most_common(20)
    # print(c)
    # print(''.join(jieba.cut(jingyan_text)))

    print(one)
    print(three)
    print(five)
    print(noexp)
    print(onein)
    print(qita)
    a=len(one)
    b=len(three)
    c=len(five)
    d=len(noexp)
    e=len(onein)
    f=len(qita)
    expcount=[f,e,a,b,c,d]
    expfenlei=['应届生','1年以内','1-3年','3-5年','5-10年','经验不限']
    print(expcount)
    print(a+b+c+d+e+f)

    print(other)
    g=len(benke)
    h=len(dazhuan)
    j=len(boshi)
    k=len(noedu)
    m=len(other)
    educount=[h,g,k,j,m]
    edufenlei=['大专','本科','硕士','博士','学历不限']
    print(educount)

    '''
    bar = Bar('工作年限')
    bar.add("要求", expfenlei, expcount)
    # bar.show_config()
    bar.render('工作年限柱状图.html')

    pie = Pie()
    pie.add("工作", expfenlei, expcount, is_label_show=True)
    # pie.show_config()
    pie.render('工作年限饼状图.html')
    '''

    bar = Bar('学历要求')
    bar.add("学历", edufenlei, educount)
    # bar.show_config()
    bar.render('学历要求柱状图.html')

    pie = Pie()
    pie.add("学历", edufenlei, educount, is_label_show=True)
    # pie.show_config()
    pie.render('学历要求饼状图.html')

我使用的是最基本的数组方法，不知道有什么简单方法么，例如jieba分词模块，等等

可以看出本科生需求还是很大的。。。