临近五一，游玩地点想好了吗，Python帮你查找旅游景点的详细数据

前言

好不容易没有了疫情，三年整整三年，都要把我憋死了，想到去年暑假的时候，准备去厦门，攻略做好了，厦门疫情来了，想着转去济南也是这样，去三亚，结果收到好几万人都被留在三亚了…

搞的我又在家里躺了一个月，后面耐不住寂寞，找个班开始上班了

在这里插入图片描述

不过，这次我要抓住五一，好好玩一玩，但是也就几天假…天气还不咋地

这次我就用Python来好好做一个旅游攻略

知识点

requests 
parsel  
csv

第三方库：

requests 
parsel

模块安装:

按住键盘 win + r, 输入cmd回车
打开命令行窗口, 在里面输入 pip install 模块名

开发环境：

python 3.8

+python安装包安装教程视频
+pycharm 社区版专业版及激活码文末名片获取

代码实现步骤：

向目标网站发送网络请求
获取数据网页源代码
筛选我们需要的数据所有的详情页链接
向每一个详情页链接发送网络请求
获取数据网页源代码
提取数据
[出发日期天数人均费用人物玩法地点浏览量…]
保存数据
多页爬取
做一个可视化分析旅游景点推荐

导入模块

import random
import time
import requests    
import parsel      
import csv

爬取旅游wang数据

1. 向目标网站发送网络请求

csv_qne = open('去哪儿.csv', mode='a', encoding='utf-8', newline='')
完整源码+v：xiaoyuanllsll
csv_writer = csv.writer(csv_qne)
csv_writer.writerow(['地点', '短评', '出发时间', '天数','人均费用','人物','玩法','浏览量','详情页'])
for page in range(1, 201):url = f'https://travel.qunar.com/travelbook/list.htm?page={page}&order=hot_heat'

2. 获取数据网页源代码

html_data = response.text

3. 筛选我们需要的数据所有的详情页链接

selector = parsel.Selector(html_data)
url_list = selector.css('body > div.qn_mainbox > div > div.left_bar > ul > li > h2 > a::attr(href)').getall()
for detail_url in url_list:detail_id = detail_url.replace('/youji/', '')detail_url = '这里放网址' + detail_id

4. 向每一个详情页链接发送网络请求

response_1 = requests.get(detail_url)

5. 获取数据网页源代码

data_html_1 = response_1.text

6. 提取数据

        selector_1 = parsel.Selector(data_html_1)title = selector_1.css('.b_crumb_cont *:nth-child(3)::text').get()comment = selector_1.css('.title.white::text').get()count = selector_1.css('.view_count::text').get()date = selector_1.css('#js_mainleft > div.b_foreword > ul > li.f_item.when > p > span.data::text').get()days = selector_1.css('#js_mainleft > div.b_foreword > ul > li.f_item.howlong > p > span.data::text').get()money = selector_1.css('#js_mainleft > div.b_foreword > ul > li.f_item.howmuch > p > span.data::text').get()character = selector_1.css('#js_mainleft > div.b_foreword > ul > li.f_item.who > p > span.data::text').get()play_list = selector_1.css('#js_mainleft > div.b_foreword > ul > li.f_item.how > p > span.data span::text').getall()play = ' '.join(play_list)print(title, comment, date, days, money, character, play, count, detail_url)csv_writer.writerow([title, comment, date, days, money, character, play, count, detail_url])time.sleep(random.randint(3, 5))
csv_qne.close()

数据分析代码

import pandas as pd
from pyecharts.commons.utils import JsCode
from pyecharts.charts import *
from pyecharts import options as opts

data = pd.read_csv('去哪儿_数分.csv')
data

data = data[~data['地点'].isin(['攻略'])]
data = data[~data['天数'].isin(['99+'])]
data

data['人均费用'].fillna(0, inplace=True)
data['人物'].fillna('独自一人', inplace=True)
data['玩法'].fillna('没有', inplace=True)
data['天数'] = data['天数'].astype(int)
data = data[data['人均费用'].values>200]
data = data[data['天数']<=15]
data

def Month(e):m = str(e).split('/')[2]if m=='01':完整源码+v：xiaoyuanllsllreturn '一月'if m=='02':return '二月'if m=='03':return '三月'if m=='04':return '四月'if m=='05':return '五月'if m=='06':return '六月'if m=='07':return '七月'if m=='08':return '八月'if m=='09':return '九月'if m=='10':return '十月'if m=='11':return '十一月'if m=='12':return '十二月'

data['旅行月份'] = data['出发时间'].apply(Month)
data['出发时间']=pd.to_datetime(data['出发时间'])
data

loc = data1['地点'].value_counts().head(10).index.tolist()
print(loc)
loc_data = data1[data1['地点'].isin(loc)]
price_mean = round(loc_data['人均费用'].groupby(loc_data['地点']).mean(),1)
print(price_mean)
price_mean2 = [1630.1,1862.9,1697.9,1743.4,1482.4,1586.4,1897.0,1267.5,1973.8,1723.7]
m2 = data1['地点'].value_counts().head(10).index.tolist()
n2 = data1['地点'].value_counts().head(10).values.tolist()

bar=(Bar(init_opts=opts.InitOpts(height='500px',width='1000px',theme='dark')).add_xaxis(m2).add_yaxis('目的地Top10',n2,label_opts=opts.LabelOpts(is_show=True,position='top'),itemstyle_opts=opts.ItemStyleOpts(color=JsCode("""new echarts.graphic.LinearGradient(0, 0, 0, 1,[{offset: 0,color: 'rgb(255,99,71)'}, {offset: 1,color: 'rgb(32,178,170)'}])"""))).set_global_opts(title_opts=opts.TitleOpts(title='目的地Top10'),xaxis_opts=opts.AxisOpts(name='景点名称',type_='category',                                           axislabel_opts=opts.LabelOpts(rotate=90),),yaxis_opts=opts.AxisOpts(name='数量',min_=0,max_=120.0,splitline_opts=opts.SplitLineOpts(is_show=True,linestyle_opts=opts.LineStyleOpts(type_='dash'))),tooltip_opts=opts.TooltipOpts(trigger='axis',axis_pointer_type='cross')).set_series_opts(markline_opts=opts.MarkLineOpts(data=[opts.MarkLineItem(type_='average',name='均值'),opts.MarkLineItem(type_='max',name='最大值'),opts.MarkLineItem(type_='min',name='最小值'),]))
)
bar.render_notebook()

bar=(Bar(init_opts=opts.InitOpts(height='500px',width='1000px',theme='dark')).add_xaxis(loc)完整源码+v：xiaoyuanllsll.add_yaxis('人均费用',price_mean2,label_opts=opts.LabelOpts(is_show=True,position='top'),itemstyle_opts=opts.ItemStyleOpts(color=JsCode("""new echarts.graphic.LinearGradient(0, 0, 0, 1,[{offset: 0,color: 'rgb(255,99,71)'}, {offset: 1,color: 'rgb(32,178,170)'}])"""))).set_global_opts(title_opts=opts.TitleOpts(title='各景点人均费用'),xaxis_opts=opts.AxisOpts(name='景点名称',type_='category',                                           axislabel_opts=opts.LabelOpts(rotate=90),),yaxis_opts=opts.AxisOpts(name='数量',min_=0,max_=2000.0,splitline_opts=opts.SplitLineOpts(is_show=True,linestyle_opts=opts.LineStyleOpts(type_='dash'))),tooltip_opts=opts.TooltipOpts(trigger='axis',axis_pointer_type='cross')).set_series_opts(markline_opts=opts.MarkLineOpts(data=[opts.MarkLineItem(type_='average',name='均值'),opts.MarkLineItem(type_='max',name='最大值'),opts.MarkLineItem(type_='min',name='最小值'),]))
)
bar.render_notebook()

word_list = []
for i in data1['玩法']:s = re.split('\xa0',i)word_list.append(s)  
dict = {}
for j in range(len(word_list)):for i in word_list[j]:if i not in dict:dict[i] = 1else:dict[i]+=1
#print(dict)
list = []
for item in dict.items():list.append(item)
for i in range(1,len(list)):for j in range(0,len(list)-1):if list[j][1]<list[j+1][1]:list[j],list[j+1] = list[j+1],list[j]
print(list)

data1['旅行月份'].value_counts()
m1 = data1['人物'].value_counts().index.tolist()
n1 = data1['人物'].value_counts().values.tolist()
pie = (Pie(init_opts=opts.InitOpts(theme='dark', width='1000px', height='800px')).add("", [z for z in zip(m1,n1)],radius=["40%", "65%"]).set_global_opts(title_opts=opts.TitleOpts(title="去哪儿\n\n出游结伴方式", pos_left='center', pos_top='center',title_textstyle_opts=opts.TextStyleOpts(color='#FF6A6A', font_size=30, font_weight='bold'),),visualmap_opts=opts.VisualMapOpts(is_show=False, min_=38,max_=641,is_piecewise=False,dimension=0,range_color=['#9400D3', '#008afb', '#ffec4a', '#FFA500','#ce5777']),legend_opts=opts.LegendOpts(is_show=False, pos_top='5%'),).set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}", font_size=12),tooltip_opts=opts.TooltipOpts(trigger="item", formatter="{b}: {c}"),itemstyle_opts={"normal": {"barBorderRadius": [30, 30, 30, 30],'shadowBlur': 10,'shadowColor': 'rgba(0,191,255,0.5)','shadowOffsetY': 1,'opacity': 0.8}}))
pie.render_notebook()
#%%m3 = data1['出发时间'].value_counts().sort_index()[:]
m4 = m3['2021'].index
n4 = m3['2021'].values
#%%m3['2021'].sort_values().tail(10)``````c
#%% md## 出游时间分析
#%%line = (Line().add_xaxis(m4.tolist()).add_yaxis('',n4.tolist())
)
line.render_notebook()
#%%line = (Line().add_xaxis(m4.tolist()).add_yaxis('',n4.tolist())
)
line.render_notebook()