要求:
1. 参考教材实例20,编写Python爬虫程序,获取江西省所有高校的大学排名数据记录,并打印输出。
2. 使用numpy和matplotlib等库分析数据,并绘制南昌大学、华东交通大学、江西理工大学三个高校的总分排名、生源质量(新生高考成绩得分)、培养结果(毕业生就业率)、顶尖成果(高被引论文·篇)等四个指标构成的多指标柱形图。
3. 对江西各高校的顶尖成果(高被引论文数量)进行分析,使用matplotlib绘制各高校顶尖成果数构成的饼状图,并突出江西理工大学所在的饼状块。
实例代码:
import requests from bs4 import BeautifulSoup import numpy as np import matplotlib.pyplot as plt allUniv = [] def getHTMLText(url): try: r = requests.get(url, timeout=30) r.raise_for_status() r.encoding = ‘utf-8‘ return r.text except: return "" def fillUnivList(soup): data = soup.find_all(‘tr‘) for tr in data: ltd = tr.find_all(‘td‘) if len(ltd) == 0: continue singleUniv = [] for td in ltd: singleUniv.append(td.string) allUniv.append(singleUniv) return len(allUniv) def printUnivList(num): print("{0:^4}\t{1:^20}\t{2:^5}\t{3:^8}\t{4:^8}\t{5:^8}\t{6:^8}".format("排名", "学校名称", "省市", "总分", "生源质量", "培养结果", "顶尖成果")) for i in range(num): u = allUniv[i] if u[2] == "江西": print("{0:^4}\t{1:^20}\t{2:^5}\t{3:^8}\t{4:^8}\t{5:^8}\t{6:^8}".format(u[0], u[1], u[2], u[3], str(u[4]), str(u[5]), str(u[9]))) def drawBarChart(num): jxlg = [] ncdx = [] hdjd = [] for i in range(num): u = allUniv[i] if u[1] == "江西理工大学": jxlg.append(float(u[3])) jxlg.append(float(u[4])) jxlg.append(float(str(u[5]).replace(‘%‘, ‘‘))) jxlg.append(float(u[9])) if u[1] == "南昌大学": ncdx.append(float(u[3])) ncdx.append(float(u[4])) ncdx.append(float(str(u[5]).replace(‘%‘, ‘‘))) ncdx.append(float(u[9])) if u[1] == "华东交通大学": hdjd.append(float(u[3])) hdjd.append(float(u[4])) hdjd.append(float(str(u[5]).replace(‘%‘, ‘‘))) hdjd.append(float(u[9])) name_list = [‘总分‘, ‘生源质量‘, ‘培养结果‘, "顶尖成果"] x = list(range(len(name_list))) total_width, n = 0.8, 4 width = total_width / n fig, ax = plt.subplots() plt.rcParams[‘font.sans-serif‘] = ‘SimHei‘ plt.bar(x, jxlg, width=width, label=‘江西理工大学‘, tick_label=name_list, fc=‘r‘) for i in range(len(x)): x[i] = x[i] + width plt.bar(x, ncdx, width=width, label=‘南昌大学‘, fc=‘y‘) for i in range(len(x)): x[i] = x[i] + width plt.bar(x, hdjd, width=width, label=‘华东交通大学‘, fc=‘b‘) # plt.xticks(np.arange(len(name_list))) plt.legend() plt.show() def drawBar(num): djcg = [] name = [] explode = [] for i in range(num): u = allUniv[i] if u[2] == "江西": djcg.append(u[9]) name.append(u[1]) if u[1] == "江西理工大学": explode.append(0.5) else: explode.append(0) plt.rcParams[‘font.sans-serif‘] = ‘SimHei‘ fig1, ax1 = plt.subplots() ax1.pie(djcg, explode=explode, labels=name, autopct=‘%1.1f%%‘, shadow=True, startangle=90) ax1.axis(‘equal‘) plt.legend() plt.show() def main(): url = "http://www.zuihaodaxue.com/zuihaodaxuepaiming2018.html" html = getHTMLText(url) soup = BeautifulSoup(html, "html.parser") num = fillUnivList(soup) printUnivList(num) drawBarChart(num) drawBar(num) if __name__ == ‘__main__‘: main()
江西省高校排名结果如下:
三校部分数据对比如下:
江西各高校的顶尖成果(高被引论文数量)对比分析如下:
原文地址:https://www.cnblogs.com/shixinzei/p/10180733.html
时间: 2024-10-10 11:05:12