Python爬虫与数据图表的实现

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：

巴特西

Python爬虫与数据图表的实现

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