python第七天

一、python中的生成表达式

1. 列表推导式

用途:快速生成一个列表
格式

# 格式 [表达式 for 临时变量 in 可迭代对象 [条件语句]]

与普通for循环创建列表进行对比:

# 使用普通for循环创建列表
# 生成一个空列表
li = []
# for 临时变量 in 可迭代对象:
#     循环体
for i in range(10):
    # 向列表中添加元素
    li.append(i)
print(li)

用列表推导式创建列表

# 以上我们使用4行代码显示一个0-9的列表
print([i for i in range(10)])

示例1:

# 生成随机数
from random import randint
print(randint(60, 100))
# 生成一个列表['序号:998','序号:992', '序号:993' ]
# [100,999]共十个元素
# for循环
from random import randint
l1 = []
# _ 是给读代码的人看的,表示下面将不使用 _
for _ in range(10):
    seq = '序号:{}'.format(randint(100, 999))
    l1.append(seq)
print(l1) # ['序号:948', '序号:475', '序号:727', '序号:291', '序号:788', '序号:708', '序号:554', '序号:217', '序号:407', '序号:594']
# 列表推导式
l2 = ['序号:{}'.format(randint(100, 999)) for _ in range(10)]
# print(l2) # ['序号:177', '序号:568', '序号:518', '序号:878', '序号:523', '序号:526', '序号:938', '序号:556', '序号:137', '序号:432']

示例2:

# 生成一个列表
from random import randint
li = []
for _ in range(10):
    li.append(randint(30, 100))
print(li)
# 已知列表li ,然后筛选所有的偶数
li = [92, 53, 84, 54, 82, 92, 95, 38, 52, 42]
# for 循环 遍历这个列表
result = []
for x in li:
    if x%2 == 0:
        result.append(x)
print(result) # [92, 84, 54, 82, 92, 38, 52, 42]
# 格式 [表达式 for 临时变量 in 可迭代对象 [条件语句]]
[x for x in li if x%2==0]

练习:使用列表推导式生成一个含有二十个元素的随机数列表[],再筛选出所有的奇数。

from random import randint
li = [randint(0, 100) for _ in range(20)]
print([i for i in li if i%2 == 1]) # [33, 79, 45, 65, 59, 95, 57, 65, 97]

2. 三目运算符

用途:可以使用一行的 if else
格式

# 格式: 返回值 if 满足条件的表达式 else 不满足时要执行的事情

示例1:

li = ['dada']
if len(li)==0:
    li = 'aa'
else:
    li = li[0]
print(li)
# 三目运算符
# 格式: 返回值 if 满足条件的表达式 else 不满足时要执行的事情
s = 'aa' if len(li) == 0 else li[0]
print(s)

二、爬取当当图书信息(优化后)

import requests
from lxml import html
# 安装pandas
# pip install pandas
# 导入pandas
import pandas as pd
def spider(isbn):
    """:param   #param是参数
    当当网图书信息爬虫
    """
    # url = "http://search.dangdang.com/?key=python%B4%D3%C8%EB%C3%C5%B5%BD%CA%B5%BC%F9&act=input"
    # isbn 国际标准书号(唯一的) 9787115428028
    url = "http://search.dangdang.com/?key={}&act=input".format(isbn)
    print(url)
    # 获取网页的源代码
    headers = {
        'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.131 Safari/537.36'}
    html_data = requests.get(url, headers=headers).text
    print(html_data)
    #使用xpath语法提取我们想要的内容
    selector = html.fromstring(html_data)
    ul_list = selector.xpath('//div[@id="search_nature_rg"]/ul/li')
    print('有{}家商铺售卖此书'.format(len(ul_list)))
    # 用于存储图书的所有信息,每一家是一个字典
    # [{},{},{}]
    book_info_list = []
    # 遍历
    for li in ul_list:
        # 爬取所有书籍的标题
        title = li.xpath('a/@title')[0]
        # print(title)
        # 获取所有购买链接
        link = li.xpath('a/@href')[0]
        # print(link)
        # 获取价格
        price = li.xpath('p[@class="price"]/span[@class="search_now_price"]/text()')[0]
        # print(price)
        # 去掉¥符号
        price = price.replace('¥', ' ')
        # print(price)
        # 爬取除了当当自营以外的所有店铺(作业)
        # //标签1[@属性1=属性值1]/.../text()
        # //标签1[@属性1=属性值1]/.../@属性的名字
        # store = li.xpath('p[@class="search_shangjia"]/a/text()')
        store = li.xpath('p[4]/a/@title')
        # store列表是当当自营的时候是空的
        # if len(store) == 0:
        #     # 当当自营
        #     store = "当当自营"
        # else:
        #     store = store[0]
        # 代码优化
        store = '当当自营' if len(store) == 0 else store[0]
        print(store)
        # print(store)
        book_info_list.append({
            'title': title,
            'link': link,
            'price': price,
            'store': store
        })
    # 排序
    book_info_list.sort(key=lambda x: float(x['price']), reverse=True)
    # 遍历图书列表
    for book in book_info_list:
        print(book)
    # import pandas as pd
    # 转化成dataframe格式
    df = pd.DataFrame(book_info_list)
    # 存储成csv   ,csv 是逗号分隔值文件
    df.to_csv('当当图书信息.csv')
isbn = input('请输入您要查询的书号')
spider(isbn)

三、爬取豆瓣即将上映电影信息(优化后)

多了个下载电影图片功能

from xpinyin import Pinyin
import requests
from lxml import html
import pandas as pd
# pip install xpinyin
def spider(city):
    # splitter 是分隔使用符号,默认是‘-’
    city_pinyin = Pinyin().get_pinyin(city, splitter='')
    url = 'https://movie.douban.com/cinema/later/{}/'.format(city_pinyin)
    print('您要爬取的目标站点是', url)
    print('爬虫进行中,请稍后...')
    # 请求头信息, 目的是伪装成浏览器进行爬虫
    headers = {'User-Agent': 'Mozillsa/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.131 Safari/537.36'}
    # 获取网页的源代码
    response = requests.get(url, headers=headers)
    html_data = response.text
    # 提取我们想要的内容
    selector = html.fromstring(html_data)
    div_list = selector.xpath('//div[@id="showing-soon"]/div') # xpath爬取的是一个列表
    print('您好,{}市共查询到{}部即将上映的电影'.format(city,len(div_list)))
    movie_info_list = []
    for div in div_list:
        movie_name = div.xpath('div[1]/h3/a/text()')
        # if len(movie_name)==0:
        #     movie_name = '没有查询到数据'
        # else:
        #     movie_name = movie_name[0]
        # 代码优化   ,可以使程序错误也继续运行
        movie_name = '没有查询到数据' if len(movie_name) == 0 else movie_name[0]
        # print(movie_name)
        # 上映日期
        date = div.xpath('div[1]/ul/li[1]/text()')
        date = '没有查询到数据' if len(date) == 0 else date[0]
        # print(date)
        # 类型
        type = div.xpath('div[1]/ul/li[2]/text()')
        type = '没有查询到数据' if len(type) == 0 else type[0]
        # print(type)
        # 国家
        country = div.xpath('div[1]/ul/li[3]/text()')
        country = '没有查询到数据' if len(country) == 0 else country[0]
        # print(country)
        # 想看人数
        want_see = div.xpath('div[1]/ul/li[4]/span/text()')
        want_see = '没有查询到数据' if len(want_see) == 0 else want_see[0]
        want_see = int(want_see.replace('人想看', ''))
        # print(want_see)
        # 图片链接
        img_link = div.xpath('a/img/@src')
        img_link = '没有查询到数据' if len(img_link) == 0 else img_link[0]
        # 将信息放入一个列表中 [{}, {}, {}]
        movie_info_list.append({
            "movie_name": movie_name,
            "date": date,
            "type": type,
            "country": country,
            "want_see": want_see,
            "img_link": img_link
        })
    # 排序
    movie_info_list.sort(key=lambda x: x['want_see'])
    # 遍历
    for movie in movie_info_list:
        print(movie)
        # 图片爬取
        with open('./douban_img/{}.jpg'.format(movie['movie_name']), 'wb') as f:
            f.write(requests.get(movie['img_link']).content)
    pd.DataFrame(movie_info_list).to_csv('{}douban_movie_info.csv'.format(city_pinyin))
# 再屏幕中输入‘请输入您要查看即将上映电影信息的城市’
city = input('请输入您要查看即将上映电影信息的城市:')
# 调用函数
spider(city)

四、数据可视化

安装并导入matplotlib、numpy库

# matplotlib # 用于绘图的库
# 安装
# pip install matplotlib、numpy
# 导入
from matplotlib import pyplot as plt
# 导入numpy
import numpy as np

设置支持中文字体

# 设置支持中文字体
plt.rcParams["font.sans-serif"] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False
1. 绘制 正弦曲线(线形图)
# 绘制 正弦曲线
# 选取100个等间距的点(x,y)然后进行绘制曲线图
# 生成[0,2π]区间100个等间距的点
x = np.linspace(0, 2*np.pi, num=100) # linspace 可以生成等间距的范围
y = np.sin(x)
cosy = np.cos(x)
# 绘制线形图
plt.plot(x, y,
        color='r', # 线的颜色
        linestyle = ':', # 线的风格
         # - 实线, -- 虚线, : 点化线
        marker='o',# 标记点的样式
         # o 实心圆, *,+
        markerfacecolor='r', # 标记点的颜色
        alpha=0.8, # 设置透明度
        label='代表正弦曲线' # 标签
)
plt.plot(x, cosy,
         label='cos(x)',
         linestyle='-',
         color='g',
         marker='*',
         markerfacecolor='r',
         alpha=0.6
)
plt.xlabel('time(s)')
plt.ylabel('电压(v)')
plt.title('电压随时间变化曲线')
plt.legend() # 设置图例
plt.show()

输出线形图:


输出线形图

2. 绘制条形图
from random import randint
x = ['口红{}'.format(i) for i in range(1, 7)]
print(x)
y = [randint(200, 1000) for _ in range(6)]
print(y)
plt.bar(x, y)
plt.grid() # 带网格
plt.xlabel('口红品牌')
plt.ylabel('口红价格(元)')
plt.show()

输出条形图:


输出条形图

五、作业

1. 三国人物分析top10绘制条形图

import jieba
from matplotlib import pyplot as plt
plt.rcParams["font.sans-serif"] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False
import numpy
# 读取文件
with open('novel/threekingdom.txt', 'r', encoding='UTF-8') as f:
    data = f.read()
    # 分词
    words_list = jieba.lcut(data)
    # print(words_list)
    # print(type(words_list)) # <class 'list'>
    # 构建一个集合,定义无关词   ,用集合因为可以去重
    excludes = {"将军", "却说", "二人", "不可", "荆州", "不能", "如此", "丞相",
                "商议", "如何", "主公", "军士", "军马", "左右", "次日", "引兵",
                "大喜", "天下", "东吴", "于是", "今日", "不敢", "魏兵", "陛下",
                "都督", "人马", "不知", "孔明曰", "玄德曰", "刘备", "云长"}
                # , ""
    #构建一个容器,存储我们要的数据
    #{"夏侯渊":34,"害怕":33...}\
    counts = {}
    print(type(counts)) # <class 'dict'>
    # 遍历wordlist 目标是筛选出人名
    for word in words_list:
        # print(word)
        if len(word) <= 1:
            # 过滤无关词语即可
            continue
        else:
            # 向字典counts里更新值
            # counts[word] = 字典中原来该词出现的次数 + 1
            # counts[word] = counts[word] + 1
            # counts["正文"] = count["正文"] + 1
            counts[word] = counts.get(word, 0) + 1
    # print(counts)
    # 指向同一个词的人进行合并 , 记得把合并的词变为无关词,放到excludes中
    counts['孔明'] = counts['孔明'] + counts['孔明曰']
    counts['玄德'] = counts['玄德'] + counts['玄德曰'] + counts['刘备']
    counts['关公'] = counts['关公'] + counts['云长']
    # 删除无关的词语
    for word in excludes:
        del counts[word]
    # 排序筛选
    # 把字典转化成列表[(),()]  [{}]
    items = list(counts.items())
    print(items)
    # 按照词频次数进行排序
    items.sort(key=lambda x: x[1], reverse=True)
    print(items)
    # 显示出现词语前10的词
    x = []
    y = []
    for i in range(10):
        # 将返回的数据拆开,拆包
        role, count = items[i]
        x.append(role)
        y.append(count)
    plt.bar(x, y)
    plt.xlabel('人物')
    plt.ylabel('频次')
    plt.title('三国人物出现次数top10')
    plt.grid()
    plt.show()

输出:


三国人物分析top10

2. 豆瓣中最想看的即将上映电影top5条形图

from xpinyin import Pinyin
import requests
from lxml import html
from matplotlib import pyplot as plt
import numpy
import pandas as pd
# pip install xpinyin
def spider(city):
    # splitter 是分隔使用符号,默认是‘-’
    city_pinyin = Pinyin().get_pinyin(city, splitter='')
    url = 'https://movie.douban.com/cinema/later/{}/'.format(city_pinyin)
    print('您要爬取的目标站点是', url)
    print('爬虫进行中,请稍后...')
    # 请求头信息, 目的是伪装成浏览器进行爬虫
    headers = {'User-Agent': 'Mozillsa/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.131 Safari/537.36'}
    # 获取网页的源代码
    response = requests.get(url, headers=headers)
    html_data = response.text
    # 提取我们想要的内容
    selector = html.fromstring(html_data)
    div_list = selector.xpath('//div[@id="showing-soon"]/div') # xpath爬取的是一个列表
    print('您好,{}市共查询到{}部即将上映的电影'.format(city,len(div_list)))
    movie_info_list = []
    for div in div_list:
        movie_name = div.xpath('div[1]/h3/a/text()')
        # if len(movie_name)==0:
        #     movie_name = '没有查询到数据'
        # else:
        #     movie_name = movie_name[0]
        # 代码优化   ,可以使程序错误也继续运行
        movie_name = '没有查询到数据' if len(movie_name) == 0 else movie_name[0]
        # print(movie_name)
        # 上映日期
        date = div.xpath('div[1]/ul/li[1]/text()')
        date = '没有查询到数据' if len(date) == 0 else date[0]
        # print(date)
        # 类型
        type = div.xpath('div[1]/ul/li[2]/text()')
        type = '没有查询到数据' if len(type) == 0 else type[0]
        # print(type)
        # 国家
        country = div.xpath('div[1]/ul/li[3]/text()')
        country = '没有查询到数据' if len(country) == 0 else country[0]
        # print(country)
        # 想看人数
        want_see = div.xpath('div[1]/ul/li[4]/span/text()')
        want_see = '没有查询到数据' if len(want_see) == 0 else want_see[0]
        want_see = int(want_see.replace('人想看', ''))
        # print(want_see)
        # 图片链接
        img_link = div.xpath('a/img/@src')
        img_link = '没有查询到数据' if len(img_link) == 0 else img_link[0]
        # 将信息放入一个列表中 [{}, {}, {}]
        movie_info_list.append({
            "movie_name": movie_name,
            "date": date,
            "type": type,
            "country": country,
            "want_see": want_see,
            "img_link": img_link
        })
    # 排序
    movie_info_list.sort(key=lambda x: x['want_see'],reverse=True)
    print(movie_info_list)
    # 绘制想看人数前五的条形图
    plt.rcParams["font.sans-serif"] = ['SimHei']
    plt.rcParams['axes.unicode_minus'] = False
    # 笨方法:
    # a = []
    # b = []
    # for movie in movie_info_list:
    #     movie_name = movie['movie_name']
    #     want_see = movie['want_see']
    #     a.append(movie_name)
    #     b.append(want_see)
    # x = []
    # y = []
    # for i in range(5):
    #     x.append(a[i])
    #     y.append(b[i])
    # 优化方法:
    x = [movie['movie_name'] for movie in movie_info_list]
    x = [x[i] for i in range(5)]
    y = [movie['want_see'] for movie in movie_info_list]
    y = [y[i] for i in range(5)]
    plt.bar(x, y)
    plt.xlabel('电影名称')
    plt.ylabel('想看人数')
    plt.title('豆瓣即将上映电影想看人数TOP5')
    plt.grid()
    plt.show()
# 再屏幕中输入‘请输入您要查看即将上映电影信息的城市’
city = input('请输入您要查看即将上映电影信息的城市:')
# 调用函数
spider(city)

输出:


豆瓣中最想看的即将上映电影top5
https://www.jianshu.com/p/8e8601b52e1e

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