爬取诗词名句网数据并做简单数据分析

爬取诗词总量为二十九万两千六百零二条数据

一、爬虫编写

目标网站：诗词名句网

环境

window10；

python3.7；

scrapy框架；

mysql数据库;

数据库设计

根据要爬取的字段定义，爬取内容为诗词链接，简介，标题，作者，朝代，内容，注释，作者发表的文章数量，图片url

如图

1.创建项目和爬虫文件

scrapy startproject scmjw

cd scmjw

scrapy genspider scmj www.xxx.com

2.定义爬取字段

items.py

import scrapy


class ScmjwItem(scrapy.Item):
    # define the fields for your item here like:
    # name = scrapy.Field()
    table = ‘scmjw‘
    url = scrapy.Field()
    category = scrapy.Field()
    title = scrapy.Field()
    auther = scrapy.Field()
    dynasty = scrapy.Field()
    content = scrapy.Field()
    contents = scrapy.Field()
    amount = scrapy.Field()
    beiyong1 = scrapy.Field()

3.编写爬虫规则

scmj.py

# -*- coding: utf-8 -*-
import scrapy
from scmjw.items import ScmjwItem

class ScmjSpider(scrapy.Spider):
    name = ‘scmj‘
    # allowed_domains = [‘www.shicimingju.com‘]
    start_urls = [‘http://www.shicimingju.com‘]

    def parse(self, response):
        list_urls = response.xpath(‘//div[@id="top_left_menu"]/ul/li‘)
        for list_url in list_urls:
            main_list = ‘http://www.shicimingju.com‘ + list_url.xpath(‘./a/@href‘).extract_first()
            if ‘shicimark‘ in main_list:
                print(main_list)
                yield scrapy.Request(url=main_list,callback=self.get_list)
            if ‘category‘ in main_list:
                print(main_list)
                yield scrapy.Request(url=main_list,callback=self.get_list_cate)

    """爬取分类类别"""
    def get_list(self,response):
        div_lists = response.xpath(‘//div[@class="mark_card"]‘)
        for d in div_lists:
            item = ScmjwItem()
            next_url = ‘http://www.shicimingju.com‘ + d.xpath(‘./a/@href‘).extract_first()
            images = d.xpath(‘./a/img/@src‘).extract_first()
            item[‘beiyong1‘] = images
            yield scrapy.Request(url=next_url,callback=self.get_cate,meta={‘item‘:item})

    def get_cate(self,response):
        item = response.meta[‘item‘]
        next_urls = response.xpath(‘//a[contains(text(), "《") and contains(text(), "》")]‘)
        item[‘amount‘] = response.xpath(‘//div[@class="card"]/h1/text()‘).re_first(‘\d+‘)
        for n in next_urls:
            next_url = ‘http://www.shicimingju.com‘ + n.xpath(‘./@href‘).extract_first()
            yield scrapy.Request(url=next_url,callback=self.get_detail,meta={‘item‘:item})
        self_urls = response.xpath(‘//a[contains(text(), "下一页")]/@href‘).extract_first()
        if self_urls:
            self_url = ‘http://www.shicimingju.com‘ + self_urls
            yield scrapy.Request(url=self_url, callback=self.get_cate, meta={‘item‘: item})

    def get_detail(self,response):
        item = response.meta[‘item‘]
        item[‘url‘] = response.request.url
        item[‘category‘] = response.xpath(‘//div[@class="shici-mark"]/a/text()‘).extract_first()
        item[‘title‘] = response.xpath(‘//div[@id="item_div"]/h1/text()‘).extract_first()
        item[‘auther‘] = response.xpath(‘//div[@class="niandai_zuozhe"]/a/text()‘).extract_first()
        item[‘dynasty‘] = response.xpath(‘//div[@class="niandai_zuozhe"]/text()‘).extract_first()
        contents = response.xpath(‘//div[@class="item_content"]//text()‘).extract()
        content = ‘‘
        for c in contents:
            content += c.strip() + ‘\n‘
        item[‘content‘] = content
        shangxi_contents = response.xpath(‘//div[@class="shangxi_content"]//text()‘).extract()
        contents = ‘‘
        for s in shangxi_contents:
            contents += s.strip()
        item[‘contents‘] = contents
        yield item

    """爬取作者类别"""
    def get_list_cate(self,response):
        div_lists = response.xpath(‘//div[@class="card zuozhe_card"]‘)
        for d in div_lists:
            next_url = ‘http://www.shicimingju.com‘ + d.xpath(‘./div[@class="zuozhe_list_item"]/h3/a/@href‘).extract_first()
            yield scrapy.Request(url=next_url,callback=self.get_zuozhe)
        self_urls = response.xpath(‘//a[contains(text(), "下一页")]/@href‘).extract_first()
        if self_urls:
            self_url = ‘http://www.shicimingju.com‘ + self_urls
            yield scrapy.Request(url=self_url, callback=self.get_list_cate)

    def get_zuozhe(self,response):
        item = ScmjwItem()
        item[‘amount‘] = response.xpath(‘//div[@class="card shici_card"]/h1/text()‘).re_first(‘\d+‘)
        next_urls = response.xpath(‘//div[@class="shici_list_main"]‘)
        for n in next_urls:
            next_url = ‘http://www.shicimingju.com‘ + n.xpath(‘./h3/a/@href‘).extract_first()
            yield scrapy.Request(url=next_url,callback=self.get_z_detail,meta={‘item‘:item})
        self_urls = response.xpath(‘//a[contains(text(), "下一页")]/@href‘).extract_first()
        if self_urls:
            self_url = ‘http://www.shicimingju.com‘ + self_urls
            yield scrapy.Request(url=self_url, callback=self.get_zuozhe)

    def get_z_detail(self,response):
        item = response.meta[‘item‘]
        item[‘url‘] = response.request.url
        item[‘category‘] = response.xpath(‘//div[@class="shici-mark"]/a/text()‘).extract_first()
        item[‘title‘] = response.xpath(‘//div[@id="item_div"]/h1/text()‘).extract_first()
        item[‘auther‘] = response.xpath(‘//div[@class="niandai_zuozhe"]/a/text()‘).extract_first()
        item[‘dynasty‘] = response.xpath(‘//div[@class="niandai_zuozhe"]/text()‘).extract_first()
        contents = response.xpath(‘//div[@class="item_content"]//text()‘).extract()
        content = ‘‘
        for c in contents:
            content += c.strip() + ‘\n‘
        item[‘content‘] = content
        shangxi_contents = response.xpath(‘//div[@class="shangxi_content"]//text()‘).extract()
        contents = ‘‘
        for s in shangxi_contents:
            contents += s.strip()
        item[‘contents‘] = contents
        by1 = response.xpath(‘//div[@id="item_div"]/img/@src‘).extract_first()
        if by1:
            item[‘beiyong1‘] = by1
        else:
            item[‘beiyong1‘] = ‘‘
        yield item

4.pipline.py中编写写入数据库和下载图片到本地规则

# -*- coding: utf-8 -*-

# Define your item pipelines here
#
# Don‘t forget to add your pipeline to the ITEM_PIPELINES setting
# See: https://docs.scrapy.org/en/latest/topics/item-pipeline.html
import pymysql
from scrapy import Request
from scrapy.exceptions import DropItem
from scrapy.pipelines.images import ImagesPipeline

class ScmjwPipeline:
    def process_item(self, item, spider):
        return item

class MysqlPipeline:
    def __init__(self,host,database,user,password):
        self.host = host
        self.database = database
        self.user = user
        self.password = password

    def open_spider(self,spider):
        self.conn = pymysql.connect(self.host,self.user,self.password,self.database,charset=‘utf8‘)
        self.cursor = self.conn.cursor()
        # self.old_url = set()
        # search_sql = "select url from scmjw"
        # self.cursor.execute(search_sql)
        # for i in self.cursor.fetchall():
        #     self.old_url.add(i[0])

    def process_item(self,item,spider):
        # if item[‘url‘] in self.old_url:
        #     print(‘数据已入库‘,item[‘title‘])
        #     raise DropItem
        print(‘数据下载中‘,item[‘title‘])
        data = dict(item)
        keys = ‘, ‘.join(data.keys())
        values = ‘, ‘.join([‘% s‘] * len(data))
        sql = ‘insert into % s (% s) values (% s)‘ % (item.table, keys, values)
        self.cursor.execute(sql, tuple(data.values()))
        self.conn.commit()
        return item


    def close_spider(self,spider):
        self.cursor.close()
        self.conn.close()

    @classmethod
    def from_crawler(cls,crawler):
        return cls(
            host=crawler.settings.get(‘MYSQL_HOST‘),
            database=crawler.settings.get(‘MYSQL_DATABASE‘),
            user=crawler.settings.get(‘MYSQL_USER‘),
            password=crawler.settings.get(‘MYSQL_PASSWORD‘),
        )


class ImagePipeline(ImagesPipeline):
    def file_path(self, request, response=None, info=None):
        url = request.url
        file_name = url.split(‘?‘)[0].split(‘/‘)[-1]
        return file_name

    def item_completed(self, results, item, info):
        image_paths = [x[‘path‘] for ok, x in results if ok]
        if not image_paths:
            raise DropItem(‘Image Downloaded Failed‘)
        return item

    def get_media_requests(self, item, info):
        if item[‘beiyong1‘]:
            yield Request(item[‘beiyong1‘])

5.settings.py中设置，空值日志输出，数据库信息，开启相应管道文件等

# -*- coding: utf-8 -*-

# Scrapy settings for scmjw project
#
# For simplicity, this file contains only settings considered important or
# commonly used. You can find more settings consulting the documentation:
#
#     https://docs.scrapy.org/en/latest/topics/settings.html
#     https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
#     https://docs.scrapy.org/en/latest/topics/spider-middleware.html

BOT_NAME = ‘scmjw‘

SPIDER_MODULES = [‘scmjw.spiders‘]
NEWSPIDER_MODULE = ‘scmjw.spiders‘


# Crawl responsibly by identifying yourself (and your website) on the user-agent
#USER_AGENT = ‘scmjw (+http://www.yourdomain.com)‘

# Obey robots.txt rules
ROBOTSTXT_OBEY = False
LOG_LEVEL = ‘ERROR‘
LOG_FILE = ‘log.txt‘
IMAGES_STORE = ‘./image‘

MYSQL_HOST = ‘localhost‘
MYSQL_DATABASE = ‘lf_01‘
MYSQL_USER = ‘root‘
MYSQL_PASSWORD = ‘root‘



# Configure maximum concurrent requests performed by Scrapy (default: 16)
#CONCURRENT_REQUESTS = 32

# Configure a delay for requests for the same website (default: 0)
# See https://docs.scrapy.org/en/latest/topics/settings.html#download-delay
# See also autothrottle settings and docs
#DOWNLOAD_DELAY = 3
# The download delay setting will honor only one of:
#CONCURRENT_REQUESTS_PER_DOMAIN = 16
#CONCURRENT_REQUESTS_PER_IP = 16

# Disable cookies (enabled by default)
#COOKIES_ENABLED = False

# Disable Telnet Console (enabled by default)
#TELNETCONSOLE_ENABLED = False

# Override the default request headers:
#DEFAULT_REQUEST_HEADERS = {
#   ‘Accept‘: ‘text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8‘,
#   ‘Accept-Language‘: ‘en‘,
#}

# Enable or disable spider middlewares
# See https://docs.scrapy.org/en/latest/topics/spider-middleware.html
#SPIDER_MIDDLEWARES = {
#    ‘scmjw.middlewares.ScmjwSpiderMiddleware‘: 543,
#}

# Enable or disable downloader middlewares
# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
DOWNLOADER_MIDDLEWARES = {
   # ‘scmjw.middlewares.ScmjwDownloaderMiddleware‘: 543,
   ‘scmjw.middlewares.QuChongMiddleware‘: 542,
}

# Enable or disable extensions
# See https://docs.scrapy.org/en/latest/topics/extensions.html
#EXTENSIONS = {
#    ‘scrapy.extensions.telnet.TelnetConsole‘: None,
#}

# Configure item pipelines
# See https://docs.scrapy.org/en/latest/topics/item-pipeline.html
ITEM_PIPELINES = {
   ‘scmjw.pipelines.ScmjwPipeline‘: 300,
   ‘scmjw.pipelines.MysqlPipeline‘: 301,
   ‘scmjw.pipelines.ImagePipeline‘: 302,
}

# Enable and configure the AutoThrottle extension (disabled by default)
# See https://docs.scrapy.org/en/latest/topics/autothrottle.html
#AUTOTHROTTLE_ENABLED = True
# The initial download delay
#AUTOTHROTTLE_START_DELAY = 5
# The maximum download delay to be set in case of high latencies
#AUTOTHROTTLE_MAX_DELAY = 60
# The average number of requests Scrapy should be sending in parallel to
# each remote server
#AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0
# Enable showing throttling stats for every response received:
#AUTOTHROTTLE_DEBUG = False

# Enable and configure HTTP caching (disabled by default)
# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings
#HTTPCACHE_ENABLED = True
#HTTPCACHE_EXPIRATION_SECS = 0
#HTTPCACHE_DIR = ‘httpcache‘
#HTTPCACHE_IGNORE_HTTP_CODES = []
#HTTPCACHE_STORAGE = ‘scrapy.extensions.httpcache.FilesystemCacheStorage‘

6.middleware.py文件中使用下载中间件去重，防止重复下载

# -*- coding: utf-8 -*-

# Define here the models for your spider middleware
#
# See documentation in:
# https://docs.scrapy.org/en/latest/topics/spider-middleware.html

from scrapy import signals
import pymysql
from scrapy.exceptions import IgnoreRequest

class QuChongMiddleware:
    def __init__(self,host,database,user,password):
        self.conn = pymysql.connect(host, user, password, database, charset=‘utf8‘)
        self.cursor = self.conn.cursor()
        self.old_url = set()
        search_sql = "select url from scmjw"
        self.cursor.execute(search_sql)
        for i in self.cursor.fetchall():
            self.old_url.add(i[0])

    def process_request(self,request,spider):
        if request.url in self.old_url:
            print(‘中间件判断，数据库已存在‘)
            raise IgnoreRequest()

    @classmethod
    def from_crawler(cls,crawler):
        return cls(
            host=crawler.settings.get(‘MYSQL_HOST‘),
            database=crawler.settings.get(‘MYSQL_DATABASE‘),
            user=crawler.settings.get(‘MYSQL_USER‘),
            password=crawler.settings.get(‘MYSQL_PASSWORD‘),
        )


class ScmjwSpiderMiddleware:
    # Not all methods need to be defined. If a method is not defined,
    # scrapy acts as if the spider middleware does not modify the
    # passed objects.

    @classmethod
    def from_crawler(cls, crawler):
        # This method is used by Scrapy to create your spiders.
        s = cls()
        crawler.signals.connect(s.spider_opened, signal=signals.spider_opened)
        return s

    def process_spider_input(self, response, spider):
        # Called for each response that goes through the spider
        # middleware and into the spider.

        # Should return None or raise an exception.
        return None

    def process_spider_output(self, response, result, spider):
        # Called with the results returned from the Spider, after
        # it has processed the response.

        # Must return an iterable of Request, dict or Item objects.
        for i in result:
            yield i

    def process_spider_exception(self, response, exception, spider):
        # Called when a spider or process_spider_input() method
        # (from other spider middleware) raises an exception.

        # Should return either None or an iterable of Request, dict
        # or Item objects.
        pass

    def process_start_requests(self, start_requests, spider):
        # Called with the start requests of the spider, and works
        # similarly to the process_spider_output() method, except
        # that it doesn’t have a response associated.

        # Must return only requests (not items).
        for r in start_requests:
            yield r

    def spider_opened(self, spider):
        spider.logger.info(‘Spider opened: %s‘ % spider.name)


class ScmjwDownloaderMiddleware:
    # Not all methods need to be defined. If a method is not defined,
    # scrapy acts as if the downloader middleware does not modify the
    # passed objects.

    @classmethod
    def from_crawler(cls, crawler):
        # This method is used by Scrapy to create your spiders.
        s = cls()
        crawler.signals.connect(s.spider_opened, signal=signals.spider_opened)
        return s

    def process_request(self, request, spider):
        # Called for each request that goes through the downloader
        # middleware.

        # Must either:
        # - return None: continue processing this request
        # - or return a Response object
        # - or return a Request object
        # - or raise IgnoreRequest: process_exception() methods of
        #   installed downloader middleware will be called
        return None

    def process_response(self, request, response, spider):
        # Called with the response returned from the downloader.

        # Must either;
        # - return a Response object
        # - return a Request object
        # - or raise IgnoreRequest
        return response

    def process_exception(self, request, exception, spider):
        # Called when a download handler or a process_request()
        # (from other downloader middleware) raises an exception.

        # Must either:
        # - return None: continue processing this exception
        # - return a Response object: stops process_exception() chain
        # - return a Request object: stops process_exception() chain
        pass

    def spider_opened(self, spider):
        spider.logger.info(‘Spider opened: %s‘ % spider.name)

7.在根目录下创建start.py文件用于启动爬虫

from scrapy.crawler import CrawlerProcess
from scrapy.utils.project import get_project_settings

process = CrawlerProcess(get_project_settings())


process.crawl(‘scmj‘)
process.start()

8.爬取结果概览

二、简单对数据进行分析

使用的第三方库为

numpy,pandas,matplotlib

1.代码如下

import pandas as pd
import numpy as np
from sqlalchemy import create_engine
from matplotlib import pyplot as plt
import warnings


‘‘‘
明确分析目标
1.诗词分类前十及占比
2.写诗词数量最多的作者前十分类及占比
3.诗词数量最多的朝代及占比
4.有注释的诗词
5.有图片的诗词
‘‘‘

‘‘‘设置正常显示中文和‘-’号‘‘‘
# 设置正常显示中文
plt.rcParams[‘font.sans-serif‘] = ‘SimHei‘
# 设置正常显示‘-’号
plt.rcParams[‘axes.unicode_minus‘] = False
# 去除顶部轴
plt.rcParams[‘axes.spines.top‘] = False
# 去除右部轴
plt.rcParams[‘axes.spines.right‘] = False
# 屏蔽warning警告
warnings.filterwarnings("ignore")


class Scmj:
    def __init__(self):
        self.conn = create_engine("mysql+pymysql://root::3306/lf_01?charset=utf8mb4")
        self.df = pd.read_sql(‘select * from scmjw‘,self.conn)
        self.conn.dispose()
        # print(self.df.head())
        print(self.df.info())
        # print(self.df.describe())

    ‘‘‘获取一些描述性信息‘‘‘
    def get_ty(self):
        # 数据总量
        self.scmj_all = self.df.shape[0]
        print(‘数据总量为:‘,self.scmj_all)

    ‘‘‘诗词分类前十及占比‘‘‘
    def category_top10(self):
        category = self.df.groupby(‘category‘)
        category_top10 = category.count()[‘id‘].sort_values(ascending=False)[:10]
        print(‘分类前十:\n‘,category_top10)
        # 折线图
        pic = plt.figure(figsize=(12,12),dpi=100)
        pic.add_subplot(2,2,1)
        plt.title(‘诗词分类前十折线图‘)
        plt.xlabel(‘诗词分类‘)
        plt.ylabel(‘数量‘)
        plt.xticks(rotation=90)
        plt.yticks([i for i in range(0,200,10)])
        plt.plot(category_top10)
        # 条形图
        pic.add_subplot(2,2,2)
        plt.title(‘诗词分类前十条形图‘)
        plt.xlabel(‘诗词分类‘)
        plt.ylabel(‘数量‘)
        x = range(10)
        plt.bar(x,height=category_top10.values,width=0.7)
        for i in range(len(category_top10)):
            # print(category_top10.values[i])
            plt.text(i,category_top10.values[i],‘{}首‘.format(category_top10.values[i]),va=‘bottom‘,ha=‘center‘)
        plt.xticks(x,category_top10.index,rotation=90)
        # 饼图
        pic.add_subplot(2,2,3)
        plt.title(‘诗词分类前十饼图‘)
        plt.pie(category_top10,autopct=‘%1.1f%%‘,labels=category_top10.index,explode=[0.01 for i in range(10)])
        # 箱线图
        pic.add_subplot(2,2,4)
        plt.title(‘诗词分类前十箱线图‘)
        plt.boxplot(category_top10)

        plt.savefig(‘./诗词分类前十统计图.png‘)
        plt.show()

    ‘‘‘写诗词数量最多的作者前十及占比‘‘‘
    def auther_top10(self):
        auther_top10 = self.df[‘auther‘].value_counts().iloc[:10]
        print(‘写诗词数量前十作者‘,auther_top10)
        fig = plt.figure(figsize=(12,12),dpi=100)
        # 折线图
        fig.add_subplot(2,2,1)
        plt.title(‘折线图‘)
        plt.xlabel(‘作者‘)
        plt.ylabel(‘写作数量‘)
        for i,j in zip(auther_top10.index,auther_top10.values):
            plt.text(i,j,j,ha=‘center‘, va=‘bottom‘,)
        plt.plot(auther_top10)
        # 条形图
        fig.add_subplot(2,2,2)
        x = range(len(auther_top10))
        plt.title(‘条形图‘)
        plt.xlabel(‘作者‘)
        plt.ylabel(‘写作数量‘)
        plt.xticks(x,auther_top10.index)
        plt.bar(x=x,height=auther_top10.values,width=0.7)
        for i in range(len(auther_top10)):
            plt.text(i,auther_top10.values[i],auther_top10.values[i],va=‘bottom‘,ha=‘center‘)
        # 饼图
        fig.add_subplot(2,2,3)
        plt.title(‘饼图‘)
        plt.pie(auther_top10.values,autopct=‘%1.1f%%‘,labels=auther_top10.index,explode=[0.01 for i in range(len(auther_top10))])
        # 散点图
        fig.add_subplot(2,2,4)
        plt.title(‘散点图‘)
        plt.xlabel(‘作者‘)
        plt.ylabel(‘写作数量‘)
        plt.scatter(x=auther_top10.index,y=auther_top10.values)
        plt.savefig(‘写诗词数量前十作者统计图.png‘)
        plt.show()

    ‘‘‘诗词数量最多的朝代及占比‘‘‘
    def dynasty_top10(self):
        df1 = self.df
        clean_d = df1[‘dynasty‘].fillna(np.nan)
        clean_d[clean_d == ‘ [] ‘] = np.nan
        df1[‘dynasty‘] = clean_d
        # df1[df1[‘dynasty‘] == ‘ [] ‘] = None
        df1.dropna(subset=[‘dynasty‘])
        dynasty = df1[‘dynasty‘].value_counts()[:10]
        fig = plt.figure(dpi=100,figsize=(12,12))
        # 折线图
        fig.add_subplot(2, 2, 1)
        plt.title(‘折线图‘)
        plt.xlabel(‘朝代‘)
        plt.ylabel(‘写作数量‘)
        for i,j in zip(dynasty.index,dynasty.values):
            plt.text(i,j,j,ha=‘center‘,va=‘bottom‘)
        plt.plot(dynasty)
        # 条形图
        fig.add_subplot(2,2,2)
        plt.title(‘条形图‘)
        plt.xlabel(‘朝代‘)
        plt.ylabel(‘写作数量‘)
        plt.bar(x=dynasty.index,height=dynasty.values,width=0.8)
        for i,j in zip(dynasty.index,dynasty.values):
            plt.text(i,j,j,va=‘bottom‘,ha=‘center‘)
        # 饼图
        fig.add_subplot(2,2,3)
        plt.title(‘饼图‘)
        plt.pie(x=dynasty,autopct=‘%1.1f%%‘,labels=dynasty.index,explode=[0.01 for i in range(len(dynasty))])
        # 散点图
        fig.add_subplot(2,2,4)
        plt.title(‘散点图‘)
        plt.xlabel(‘朝代‘)
        plt.ylabel(‘写作数量‘)
        plt.scatter(x=dynasty.index,y=dynasty.values)
        for i,j in zip(dynasty.index,dynasty.values):
            plt.text(i,j,j,ha=‘center‘,va=‘center‘)
        plt.savefig(‘./诗词数量最多的朝代前十及占比.png‘)
        plt.show()

    ‘‘‘有注释&图片的诗词‘‘‘
    def contents_images(self):
        df1 = self.df
        df1[df1[‘contents‘] == ‘‘] = None
        contents = df1.dropna(subset=[‘contents‘]).shape[0]
        print(‘有注释的诗词数量为:‘,contents)
        df2 = self.df
        df2[df2[‘beiyong1‘] == ‘‘] = None
        images = df2.dropna(subset=[‘beiyong1‘]).shape[0]
        print(‘有图片的诗词数量为:‘,images)
        ‘‘‘饼图‘‘‘
        explode = [0.01,0.01]
        fig = plt.figure(figsize=(8,8),dpi=100)
        fig.add_subplot(1,2,1)
        plt.title(‘有注释的诗词占比‘)
        x = [self.scmj_all,contents]
        labels = [‘无注释‘,‘有注释‘]
        plt.pie(x=x,autopct=‘%1.1f%%‘,labels=labels,explode=explode)
        fig.add_subplot(1,2,2)
        plt.title(‘有图片的诗词占比‘)
        x = [self.scmj_all,images]
        labels = [‘无图片‘,‘有图片‘]
        plt.pie(x=x,autopct=‘%1.1f%%‘,labels=labels,explode=explode)
        plt.savefig(‘./图片&诗词占比.png‘)
        plt.show()


    def run(self):
        self.get_ty()
        self.category_top10()
        self.auther_top10()
        self.dynasty_top10()
        self.contents_images()

    def __del__(self):
        pass


if __name__ == ‘__main__‘:
    S = Scmj()
    S.run()

2.分析结果概览

代码已托管github，地址为 https://github.com/terroristhouse/scmjw.git