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# 首先我们需要导入 requests 库
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import requests
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# 若是本地没有安装 requests 可以通过“pip install requests”来安装
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# 设置请求头信息
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headers = {
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"user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/95.0.4638.69 Safari/537.36"
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}
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# 导入 re 模快
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import re
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# 存储内容
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message = []
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# 总共16个页面的数据
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for page in range(20):
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# 组装url
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if page == 0:
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url = "https://top.chinaz.com/gongsi/index_zhuce.html"
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else:
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url = "https://top.chinaz.com/gongsi/index_zhuce_{}.html".format(page + 1)
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# 使用reqeusts模快发起 GET 请求
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response = requests.get(url, headers=headers)
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html = response.text
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# 使用 findall 函数来获取数据
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# 公司名
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company = re.findall('<a.*?target="_blank">(.+?)</a></h3>', html)
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# 注册资金
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signMoney = re.findall('<div class="CoDate"><em>(.+?)</em>注册资本</div>', html)
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pageOne = list(zip(company,signMoney))
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# 合并列表
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message.extend(pageOne)
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# 导入python中的内置模块csv
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import csv
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with open("content.csv", "w") as f:
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w = csv.writer(f)
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w.writerows(message)
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import pandas as pd
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# 读取数据
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df = pd.read_csv("content.csv", names=["company", "signMoney"],encoding='gbk')
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df1 = df.drop(0).head(20)
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import matplotlib.pyplot as plt
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# 在spyter中直接展示图像
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%matplotlib inline
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# 设置中文显示
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plt.rcParams['font.sans-serif'] = ['SimHei']
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plt.rcParams['figure.figsize'] = (30, 5) # 设置figure_size尺寸
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# x轴坐标
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x = df1["company"].values
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# y轴坐标
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y = df1["signMoney"].values
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# 绘制柱状图
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plt.bar(x, y)
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# 设置x轴名称
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plt.xlabel("公司",fontsize=14)
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# 设置x轴名称
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plt.ylabel("注册资本",fontsize=14)
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plt.show()
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