爬蟲實戰：爬蟲加資料分析，重慶電氣小哥一文帶你分析重慶所有旅游景點

寒假已經到了，玩是要玩的，作為一個地地道道的重慶電網小哥，今天想用python爬蟲+資料分析 的方式告訴你重慶哪些地方好玩，

先上一張最后景區地點分布結果圖

資料來源：去哪兒旅行

網址：去哪兒旅行-重慶

用request請求到json資料

第一部分：爬蟲

資料搜索：小試牛刀

import requests
keyword = "重慶"
page=1#列印第一頁

headers = {"User-Agent": "Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/69.0.3947.100 Safari/537.36"}
url = f'http://piao.qunar.com/ticket/list.json?keyword={keyword}&region=&from=mpl_search_suggest&page={page}'
res = requests.request("GET", url, headers=headers)

try:
    res_json = res.json()
    data = res_json['data']
    print(data)
except:
    pass

結果

json回傳的資料格式是字典型，我們需要從中找到我感興趣的關鍵詞
搜索結果
發現我們感興趣的是sightList

于是可以修改代碼為

import requests
keyword = "重慶"
page=1

headers = {"User-Agent": "Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/69.0.3947.100 Safari/537.36"}
url = f'http://piao.qunar.com/ticket/list.json?keyword={keyword}&region=&from=mpl_search_suggest&page={page}'
res = requests.request("GET", url, headers=headers)


res_json = res.json()
sightLists = res_json['data']['sightList']#sightList是感興趣的
for  sight in sightLists:
    print(sight)

再次提取資訊，修改代碼為

import requests
import pandas as pd
keyword = "重慶"
page=1#查看第一頁

headers = {"User-Agent": "Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/69.0.3947.100 Safari/537.36"}
url = f'http://piao.qunar.com/ticket/list.json?keyword={keyword}&region=&from=mpl_search_suggest&page={page}'
res = requests.request("GET", url, headers=headers)


res_json = res.json()
sightLists = res_json['data']['sightList']#sightList是感興趣的
for  sight in sightLists:
    name=(sight['sightName'] if 'sightName' in sight.keys() else None)#名稱
    districts=(sight['districts'] if 'districts' in sight.keys() else None)#地址
    star=(sight['star'] if 'star' in sight.keys() else None) #星級
    qunarPrice=(sight['qunarPrice'] if 'qunarPrice' in sight.keys() else None)#最低價格
    saleCount=(sight['saleCount'] if 'saleCount' in sight.keys() else None)#購買人數
    score=(sight['score'] if 'score' in sight.keys() else None )#評分
    point=(sight['point'] if 'point' in sight.keys() else None )#坐標位置
    intro=(sight['intro'] if 'intro' in sight.keys() else None)#介紹
    print('名稱：{0}，地址:{1},星級：{2}，價格:{3},saleCount:{4}，評分:{5},坐標:{6},介紹:{7}'.format(name,districts,star,qunarPrice,saleCount,score,point,intro))

我們需要將資料寫入表格，

import requests
import pandas as pd
import numpy as np
keyword = "重慶"
page=1#查看第一頁

headers = {"User-Agent": "Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/69.0.3947.100 Safari/537.36"}
url = f'http://piao.qunar.com/ticket/list.json?keyword={keyword}&region=&from=mpl_search_suggest&page={page}'
res = requests.request("GET", url, headers=headers)


res_json = res.json()
sightLists = res_json['data']['sightList']#sightList是感興趣的
for  sight in sightLists:
    name=(sight['sightName'] if 'sightName' in sight.keys() else None)#名稱
    districts=(sight['districts'] if 'districts' in sight.keys() else None)#地址
    star=(sight['star'] if 'star' in sight.keys() else None) #星級
    qunarPrice=(sight['qunarPrice'] if 'qunarPrice' in sight.keys() else None)#最低價格
    saleCount=(sight['saleCount'] if 'saleCount' in sight.keys() else None)#購買人數
    score=(sight['score'] if 'score' in sight.keys() else None )#評分
    point=(sight['point'] if 'point' in sight.keys() else None )#坐標位置
    intro=(sight['intro'] if 'intro' in sight.keys() else None)#介紹
    #print('名稱：{0}，地址:{1},星級：{2}，價格:{3},saleCount:{4}，評分:{5},坐標:{6},介紹:{7}'.format(name,districts,star,qunarPrice,saleCount,score,point,intro))

    shuju=np.array((name,districts,star,qunarPrice,saleCount,score,point,intro))
    shuju=shuju.reshape(-1,8)
    shuju=pd.DataFrame(shuju,columns=['名稱','地址','星級','最低價格','購買人數','評分','坐標位置','介紹'])
    #print(shuju)

    shuju.to_csv('重慶景點資料.csv', mode='a+', index=False,header=False)  # mode='a+'追加寫入

多頁爬取
前面以一頁資料為例，整理出啦大概代碼，現在需要爬取多頁

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# @Author: yudengwu 余登武
# @Date  : 2021/1/30
import requests
import pandas as pd
import numpy as np
import random
from time import sleep
def get_data(keyword, page):
    headers = {
        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/69.0.3947.100 Safari/537.36"}
    url = f'http://piao.qunar.com/ticket/list.json?keyword={keyword}&region=&from=mpl_search_suggest&page={page}'
    res = requests.request("GET", url, headers=headers)
    sleep(random.uniform(1, 2))
    try:
        res_json = res.json()
        sightLists = res_json['data']['sightList']  # sightList是感興趣的
        for sight in sightLists:
            name = (sight['sightName'] if 'sightName' in sight.keys() else None)  # 名稱
            districts = (sight['districts'] if 'districts' in sight.keys() else None)  # 地址
            star = (sight['star'] if 'star' in sight.keys() else None)  # 星級
            qunarPrice = (sight['qunarPrice'] if 'qunarPrice' in sight.keys() else None)  # 最低價格
            saleCount = (sight['saleCount'] if 'saleCount' in sight.keys() else None)  # 購買人數
            score = (sight['score'] if 'score' in sight.keys() else None)  # 評分
            point = (sight['point'] if 'point' in sight.keys() else None)  # 坐標位置
            intro = (sight['intro'] if 'intro' in sight.keys() else None)  # 介紹
            # print('名稱：{0}，地址:{1},星級：{2}，價格:{3},saleCount:{4}，評分:{5},坐標:{6},介紹:{7}'.format(name,districts,star,qunarPrice,saleCount,score,point,intro))

            shuju = np.array((name, districts, star, qunarPrice, saleCount, score, point, intro))
            shuju = shuju.reshape(-1, 8)
            shuju = pd.DataFrame(shuju, columns=['名稱', '地址', '星級', '最低價格', '購買人數', '評分', '坐標位置', '介紹'])
            # print(shuju)

            shuju.to_csv('重慶景點資料.csv', mode='a+', index=False, header=False)  # mode='a+'追加寫入
    except:
        pass


if __name__ == '__main__':
    keyword = "重慶"
    for page in range(1, 75):  # 控制頁數
        print(f"正在提取第{page}頁")
        sleep(random.uniform(1, 2))
        get_data(keyword, page)

第二部分：資料分析

前面我們爬取了資料，現在來分析下，

1.讀取資料

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
plt.rcParams['font.sans-serif'] = ['SimHei']  # 設定加載的字體名
plt.rcParams['axes.unicode_minus'] = False#

df=pd.read_csv('重慶景點資料.csv',header=None,names=list(['名稱', '地址', '星級', '最低價格', '購買人數', '評分', '坐標位置', '介紹']))
df = df.drop_duplicates()#洗掉重復資料，得到470行資料
print(df.head())

去除重復資料后，得到重慶有470處景點

2.景點價格分析
最高Top20

df_qunarPrice = df.pivot_table(index='名稱',values='最低價格')
df_qunarPrice.sort_values('最低價格',inplace=True,ascending=False)#降序
#print(df_qunarPrice[:20])#最高價格top20
df_qunarPrice[:20].plot(kind='barh')
plt.title('價格最高Top20')
plt.show()

最低Top20

df_qunarPrice = df.pivot_table(index='名稱',values='最低價格')
df_qunarPrice.sort_values('最低價格',inplace=True,ascending=True)
#print(df_qunarPrice[:20])#最高價格top20
df_qunarPrice[:20].plot(kind='barh')
plt.title('最低Top20')
plt.show()

3.景點評分分析
評分最高Top20

#評分TOP20景點
df_score = df.pivot_table(index='名稱',values='評分')
df_score.sort_values('評分',inplace=True,ascending=False)
df_score[:20].plot(kind='barh',color='red')#barh橫條形圖
plt.title('評分最高Top20')
plt.show()

df_score = df.pivot_table(index='名稱',values='評分')
df_score.sort_values('評分',inplace=True,ascending=True )
df_score[:20].plot(kind='barh',color='red')#barh橫條形圖
plt.title('評分最低Top20')
plt.show()

沒有評分（可能是網站還未收錄該地方評分吧…）

4.月銷售額分析
最高Top20

df_saleCount = df.pivot_table(index='名稱',values='購買人數')
df_saleCount.sort_values('購買人數',inplace=True,ascending=False)
df_saleCount[:20].plot(kind='barh',color='green')#barh橫條形圖
plt.title('月銷售額最高Top20')
plt.show()

最低Top20（可能未收錄該地方資料把，可能該地方免費吧）

5.景點等級分布

from pyecharts.charts import *
from pyecharts import options as opts
from pyecharts.globals import ThemeType

df_star = df["星級"].value_counts()
df_star = df_star.sort_values(ascending=False)
print(df_star)

查找有等級的景點名稱，即3星級及其以上

print(df[df["星級"]!='無'].sort_values("星級",ascending=False)['名稱'])

展示部分圖，太多啦

6.景點地址地圖繪圖
先保存文本地檔案

df["lon"] = df["坐標位置"].str.split(",",expand=True)[0]#經度
df["lat"] = df["坐標位置"].str.split(",",expand=True)[1]#緯度
df.to_csv("data重慶.csv")

繪制地圖

import pandas as pd

stations = pd.read_csv('data重慶.csv',delimiter=',')

from pyecharts.charts import Geo
from pyecharts import options
from pyecharts.globals import GeoType

g = Geo().add_schema(maptype="重慶")

# 給所有點附上標簽 'StationID'
for i in stations.index:
    s = stations.iloc[i]
    g.add_coordinate(s['名稱'],s['lon'],s['lat'])#地區名稱，經度，緯度

# 給每個點的值賦為 1
data_pair = [(stations.iloc[i]['名稱'],1) for i in stations.index]

# 畫圖
g.add('',data_pair, type_=GeoType.EFFECT_SCATTER, symbol_size=2)
g.set_series_opts(label_opts=options.LabelOpts(is_show=False))
g.set_global_opts(title_opts=options.TitleOpts(title="重慶景點分布圖by-yudengwu"))

# 保存結果到 html
result = g.render('stations.html')

作者：電氣-余登武，寫作屬實不易，如果你覺得很好，動個手點個贊再走，