冬天来了，用Python看看哪里的人最喜欢吃火锅

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数据来源于百度地图。开发者工具就不说了，直接上代码：

"""
    爬取百度地图全国火锅店并可视化
"""
import pprint

import openpyxl as op
import requests

# 热门城市
wb_hotCity = op.Workbook() # 工作簿
ws_hotCity = wb_hotCity.create_sheet(index=0)
ws_hotCity.cell(row=1, column=1, value='城市')
ws_hotCity.cell(row=1, column=2, value='数量')

# 省份
wb_province = op.Workbook() # 工作簿
ws_province = wb_province.create_sheet(index=0) #工作表
ws_province.cell(row=1, column=1, value='省份')
ws_province.cell(row=1, column=2, value='数量')

# 省份下的市数量
wb_province_cities = op.Workbook()
ws_province_cities = wb_province_cities.create_sheet(index=0)
ws_province_cities.cell(row=1, column=1, value='城市')
ws_province_cities.cell(row=1, column=2, value='数量')

def get_json():
    url = 'https://xx.baixx.com/?newmap=1&reqflag=pcmap&biz=1&from=webmap&da_par=direct&pcevaname=pc4.1&qt=s&c=1&wd=火锅店&da_src=shareurl&on_gel=1&l=4&gr=1&b=(6818483.628395475,-1378890.6182441516;19500319.04895588,5539245.839424342)&pn=0&device_ratio=2&auth=G0dY4cVy9WzEHUcbN2egDb@CE3v8H2ESuxLBNRzEzNBtDcnVDpneC@BvYgP1PcGCgYvjPuVtvYgPMGvgWv@uVtvYgPPxRYuVtvYgP@vYZcvWPCuVtvYgP@ZPcPPuVtvYgPhPPyheuVtvhgMuxVVty1uVtCGYuVt1GgvPUDZYOYIZuVt1cv3uVtGccZcuVtPWv3Guxt58Jv7ucvY1SGpuxLt@jUfJxvYlcvIKMNQTXZbegHcEWe1GD8zv7u@ZPuVtc3CuVteuVtegvcguxLBNRzEzNBtquTTGdFrZZWuV&seckey=Ml81XZ+wbx7jyS5hXlEdUOZNM5KJW3eWH1zi1SkgdUw=,2ccphtdcku0z52vCIEYIggYcdu8QHAJF1lQ+5wl2NMlaWIlTiCrONly/LJX4jdosle2Jf9LuHi8DHeLXtZRfnXu5J/0ctPoquwFQq6tZMA4TzSUjV2KQkSKzylzZf30ZOmZRhyug2Upr+mVaZqFcTu6hRc8/N3XYrjIVwQLMken5x8Iaqv13CW13nUMjW9LO&tn=B_NORMAL_MAP&nn=0&u_loc=13182436,2819866&ie=utf-8&t=1637824275666&newfrom=zhuzhan_webmap'
    headers = {
        'Cookie':cooikes,
        'Referer':'https://map.baidu.com/search/xxxx/@13000533.070537817,2742247.240299427,4.95z?querytype=s&c=1&wd=%E7%81%AB%E9%94%85%E5%BA%97&da_src=shareurl&on_gel=1&l=4&gr=1&b=(6818483.628395475,-1378890.6182441516;19500319.04895588,5539245.839424342)&pn=0&device_ratio=2',
        'User-Agent':'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/96.0.4664.45 Safari/537.36',
    }
    response = requests.get(url=url, headers=headers)
    return response.json()

# 热门城市
def get_hotCities(json_data):
    # 获取热门城市数量
    hotCities = json_data['content']
    for item in hotCities:
        cityName = item['name']
        num = item['num']
        ws_hotCity.append([cityName, num])

def get_province(json_data):
    # 获取其他省市的总数量
    moreProvince = json_data['more_city']
    for item in moreProvince:
        province = item['province'] # 省份
        num = item['num'] # 数量
        ws_province.append([province, num]) # 各省总数

def get_cities(json_data):
    # 获取省下面市的数量
    provinceCities = json_data['more_city']
    print(type(provinceCities)) # list
    for item in provinceCities:
        # print(item['city'])
        for needitem in item['city']:
            city = needitem['name']
            num = needitem['num']
            print(city, num)
            ws_province_cities.append([city, num]) # 各省下城市总数量
json_data = get_json()
# pprint.pprint(json_data)
if __name__ == "__main__":
    get_hotCities(json_data)
    get_province(json_data)
    get_cities(json_data)
    wb_hotCity.save('热门城市火锅店数量.xlsx')
    wb_province.save('各省总火锅店数量.xlsx')
    wb_province_cities.save('各省城市火锅店数量.xlsx')
    wb_hotCity.close()
    wb_province.close()
    wb_province_cities.close()

保存结果，三张图：

 

虽然数据来源于百度地图，为了学习，用python也做个地图：

"""
    首先是全国火锅店分布数量
"""
import pandas as pd
from pyecharts.charts import Map
from pyecharts.globals import ThemeType
import pyecharts.options as opts

data = pd.read_excel('各省总火锅店数量.xlsx') #用熊猫读取数据
# 提取出省份和数量
provinceList = data['省份'].tolist() # 将省份名称作为列表
num = data['数量'].tolist() # 将数量也做成列表
print(provinceList)

provinces = []
# 修正省份参数，因为pyecharts只支持前面有标识的字，内蒙古自治区要处理成内蒙古，广西壮族自治区要处理成广西
for i in provinceList:
    if '省' and '市' in i:
        provinces.append(i[:-1])
    elif '内蒙古' in i: # 处理内蒙古自治区为内蒙古
        neimenggu = i[0:3]
        provinces.append(neimenggu)
    elif '自治区' in i: # 处理类似广西壮族自治区和宁夏回族自治区之类的字符广西和宁夏
        provinces.append(i[0:2])
    else:
        provinces.append(i[:-1]) # 处理黑龙江省成黑龙江
# print(len(provinceList)) # 比较长度是否相等
# print(len(provinces)) # 比较长度是否相等

# 开始绘图
map = (
    Map(init_opts=opts.InitOpts(width='1280px',height='960px', theme=ThemeType.VINTAGE))
    .add('数量', [list(z) for z in zip(provinces, num)], 'china') # 中国地图
    .set_global_opts(
        title_opts=opts.TitleOpts(title='全国火锅店分布数量',),
        legend_opts=opts.LegendOpts(pos_left='10%', pos_top='10%')
    )
).render('全国火锅店分布数量.html')

运行截图：

 

 数据发现，全国火锅店数量最多的不是四川，而是山东，做下山东地图可视化：

"""
做一下全国火锅店数量最多的省的可视化
"""
import pandas as pd
from pyecharts.charts import Map
import pyecharts.options as opts
from pyecharts.globals import ThemeType

# 读取数据
data = pd.read_excel('各省城市火锅店数量.xlsx')
cities = data['城市'].tolist()
counts = data['数量'].tolist()
# 数据发现山东最多，做下山东的图
city = []
count = []
flag = 0
for i in range(0, len(cities)):
    if cities[i] == '青岛市':
        flag = 1
    if flag:
        city.append(cities[i])
        count.append(int(counts[i]))
    if cities[i] == '日照市':
        city.append(cities[i]) # 提取日照
        count.append(int(counts[i])) # 将日照的数量提取
        break

print(city, count) #打印符合预期

c = (
    Map(init_opts=opts.InitOpts(width='1280px', height='960px', theme=ThemeType.VINTAGE))
        .add("山东火锅分布", [list(z) for z in zip(city, count)], "山东")
        .set_global_opts(
            title_opts=opts.TitleOpts(title="山东火锅店数量分布"),
            visualmap_opts=opts.VisualMapOpts(),
            legend_opts=opts.LegendOpts(pos_left='5%', pos_top='10%'),
    )
).render("山东火锅店数量分布.html")

截图：

 收工。