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：