Python旅游好帮手：提前15天准备五一旅游景点详细数据

人生苦短，我用python

虽然还是有15天才放五一的假，

但是我的心早已经在旅游的路上了~

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本文源码：点击此处跳转文末名片获取

趁现在，先来用python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:

1. 向目标网站发送网络请求
2. 获取数据 网页源代码
3. 筛选我们需要的数据 所有的详情页链接
4. 向 每一个详情页 链接发送网络请求
5. 获取数据 网页源代码
6. 提取数据
    [出发日期 天数 人均费用 人物 玩法 地点 浏览量...]
7. 保存数据
8. 多页爬取
9. 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

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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='')
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()

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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.info()

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

data.drop_duplicates(inplace=True)

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

data = data.reset_index(drop=True)
data

data = data.reset_index(drop=True)
data

def Month(e):
    m = str(e).split('/')[2]
    if m=='01':
        return '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

import re

def Look(e):
    if '万' in e:
        num1 = re.findall('(.*?)万',e)
        return float(num1[0])*10000
    else:
        return float(e)

data['浏览次数'] = data['浏览量'].apply(Look)
data.drop(['浏览量'],axis = 1,inplace = True)
data['浏览次数'] = data['浏览次数'].astype(int)
data.head()

data1 = data
data1['地点'].value_counts().head(10)

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)
    .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()


data1['天数'].value_counts()


data1['旅行时长'] = data1['天数'].apply(lambda x:str(x) + '天')
data1


data1['人物'].value_counts()

m = data1['浏览次数'].sort_values(ascending=False).index[:].tolist()

data1 = data1.loc[m]
data1 = data1.reset_index(drop = True)
data1

data1['旅行月份'].value_counts()

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] = 1
        else:
            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()