#coding=utf-8import urllibimport reimport csvimport sys#计数，初始化count = 0#以下定义的与之对应的是球员姓名、赛季、胜负、比赛、首发、时间、投篮命中率、投篮命中数、投篮出手数、三分命中率、三分命中数、三分出手数、罚球命中率、罚球命中数、罚球次数、总篮板数、前场篮板数、后场篮板数、助攻数、抢断数、盖帽数、失误数、犯规数、得分list0 = []list1 = []list2 = []list3 = []list4 = []list5 = []list6 = []list7 = []list8 = []list9 = []list10 = []list11 = []list12 = []list13 = []list14 = []list15 = []list16 = []list17 = []list18 = []list19 = []list20 = []list21 = []list22 = []list23 = []list24 = []list25 = []list26 = []#定义获取页面函数def getHtml(url):    page = urllib.urlopen(url)    html = page.read()    return html#获取数据并存入数据库中for k in range(0,51):    #获取当前页面，该页面只有LBJ的职业生涯常规赛的数据，截止到2016.12.26    html = getHtml(        "http://www.stat-nba.com/query.php?QueryType=game&GameType=season&Player_id=1862&crtcol=season&order=1&page=" + str(            k))    # 获取球员姓名、赛季、胜负、比赛、首发、时间、投篮命中率、投篮命中数、投篮出手数、三分命中率、三分命中数、三分出手数、罚球命中率、罚球命中数、罚球次数、总篮板数、前场篮板数、后场篮板数、助攻数、抢断数、盖帽数、失误数、犯规数、得分    #正则得到相对应的数值    playerdata = re.findall(r'
     
      (.*)'                            r'\s*
      
       (.*)'                            r'\s*(.*)'                            r'\s*
       
        (\D*|76人)(\d+)-(\d+)(\D*)'                            r'\s*(.*)'                            r'\s*(.*)'                            r'\s*(.*%|\s*)'                            r'\s*(.*)'                            r'\s*(.*)'                            r'\s*(.*%|\s*)'                            r'\s*(.*)'                            r'\s*(.*)'                            r'\s*(.*%|\s*)'                            r'\s*(.*)'                            r'\s*(.*)'                            r'\s*(.*)'                            r'\s*(.*)'                            r'\s*(.*)'                            r'\s*(.*)'                            r'\s*(.*)'                            r'\s*(.*)'                            r'\s*(.*)'                            r'\s*(.*)'                            r'\s*(.*)', html)    #获取每条数据，    for data in playerdata:        #将元组数据复制给列表，进行修改，数据中有空值，和含有%号的值，进行处理，得到数值        data1 = [data[0], data[1], data[2], data[3], int(data[4]), data[5], data[6], data[7], data[8], data[9],                 data[10], data[11], data[12], data[13], data[14], data[15], data[16], data[17], data[18], data[19],                 data[20], data[21], data[22], data[23], data[24], data[25], data[26]]#将百分号去掉，只保留数值部分        if (data1[15] == ' '):            data1[15] = 0        else:            data1[15] = float("".join(re.findall(r'(.*)%', data1[15])))        if (data1[9] == ' '):            data1[9] = 0        else:            data1[9] = float("".join(re.findall(r'(.*)%', data1[9])))        if (data1[12] == ' '):            data1[12] = 0        else:            data1[12] = float("".join(re.findall(r'(.*)%', data1[12])))        list0.append(data1[0])        list1.append(data1[1])        list2.append(data1[2])        list3.append(data1[3])        list4.append(data1[4])        list5.append(data1[5])        list6.append(data1[6])        list7.append(data1[7])        list8.append(data1[8])        list9.append(data1[9])        list10.append(data1[10])        list11.append(data1[11])        list12.append(data1[12])        list13.append(data1[13])        list14.append(data1[14])        list15.append(data1[15])        list16.append(data1[16])        list17.append(data1[17])        list18.append(data1[18])        list19.append(data1[19])        list20.append(data1[20])        list21.append(data1[21])        list22.append(data1[22])        list23.append(data1[23])        list24.append(data1[24])        list25.append(data1[25])        list26.append(data1[26])        # 记录数据数量        count += 1#建立csv存储文件，wb写 a+追加模式csvfile = file('nbadata.csv', 'ab+')writer = csv.writer(csvfile)#将提取的数据合并data2 = []for i in range(0,count):    data2.append((list0[i],list1[i],list2[i],list3[i],list4[i],list5[i],list6[i],list7[i],list8[i]                  ,list9[i],list10[i],list11[i],list12[i],list13[i],list14[i],list15[i],list16[i]                  ,list17[i],list18[i],list19[i],list20[i],list21[i],list22[i],list23[i],list24[i]                  , list25[i],list26[i]))#将合并的数据存入csvwriter.writerows(data2)csvfile.close()
       
      
     

import csv#文件路径srcFilePath = "c:/myflask/nbadata.csv"#读取cvs格式的数据文件reader = csv.reader(file(srcFilePath,'rb'))#csv中各列属性代表的含义（1）代表第一列# 球员姓名(1)、赛季(2)、胜负(3)、对手球队名称(4)、对手球队总得分（5）、己方球队总得分（6）# 、己方球队名称（7）、首发（8）【1为首发，0为替补】、上场时间（9）、投篮命中率（10）、投篮命中数（11）# 、投篮出手数（12）、三分命中率（13）、三分命中数（14）、三分出手数（15）、罚球命中率（16）# 、罚球命中数（17）、罚球次数（18）、总篮板数（19）、前场篮板数（20）、后场篮板数（21）、助攻数（22）# 、抢断数（23）、盖帽数（24）、失误数（25）、犯规数（26）、得分（27）records = [line for line in reader]frame = DataFrame(records)#获取得分数对应的场次数目pts_count = frame[26].value_counts()a = []b = []for i in pts_count.keys():    a.append(i)for i in pts_count:    b.append(i)c = {}for i in range(0,len(a)):    c[int(a[i])] = int(b[i])d = sorted(c.items(), key=lambda c:c[0])#存储得分分数e = []#存储相应分数的次数f = []for i in d:    e.append(i[0])    f.append(i[1])#15-16赛季球员得分助攻篮板抢断盖帽平均值records_p1 = [(int(line[26]),int(line[21]),int(line[18]),int(line[22]),int(line[23])) for line in records if line[1] == '03-04']records_p2 = [(int(line[26]),int(line[21]),int(line[18]),int(line[22]),int(line[23])) for line in records if line[1] == '04-05']records_p3 = [(int(line[26]),int(line[21]),int(line[18]),int(line[22]),int(line[23])) for line in records if line[1] == '05-06']records_p4 = [(int(line[26]),int(line[21]),int(line[18]),int(line[22]),int(line[23])) for line in records if line[1] == '06-07']records_p5 = [(int(line[26]),int(line[21]),int(line[18]),int(line[22]),int(line[23])) for line in records if line[1] == '07-08']records_p6 = [(int(line[26]),int(line[21]),int(line[18]),int(line[22]),int(line[23])) for line in records if line[1] == '08-09']records_p7 = [(int(line[26]),int(line[21]),int(line[18]),int(line[22]),int(line[23])) for line in records if line[1] == '09-10']records_p8 = [(int(line[26]),int(line[21]),int(line[18]),int(line[22]),int(line[23])) for line in records if line[1] == '10-11']records_p9 = [(int(line[26]),int(line[21]),int(line[18]),int(line[22]),int(line[23])) for line in records if line[1] == '11-12']records_p10 = [(int(line[26]),int(line[21]),int(line[18]),int(line[22]),int(line[23])) for line in records if line[1] == '12-13']records_p11 = [(int(line[26]),int(line[21]),int(line[18]),int(line[22]),int(line[23])) for line in records if line[1] == '13-14']records_p12 = [(int(line[26]),int(line[21]),int(line[18]),int(line[22]),int(line[23])) for line in records if line[1] == '14-15']records_p13 = [(int(line[26]),int(line[21]),int(line[18]),int(line[22]),int(line[23])) for line in records if line[1] == '15-16']g1 = [float('%0.1f' % i) for i in DataFrame(records_p1).mean()]g2 = [float('%0.1f' % i) for i in DataFrame(records_p2).mean()]g3 = [float('%0.1f' % i) for i in DataFrame(records_p3).mean()]g4 = [float('%0.1f' % i) for i in DataFrame(records_p4).mean()]g5 = [float('%0.1f' % i) for i in DataFrame(records_p5).mean()]g6 = [float('%0.1f' % i) for i in DataFrame(records_p6).mean()]g7 = [float('%0.1f' % i) for i in DataFrame(records_p7).mean()]g8 = [float('%0.1f' % i) for i in DataFrame(records_p8).mean()]g9 = [float('%0.1f' % i) for i in DataFrame(records_p9).mean()]g10 = [float('%0.1f' % i) for i in DataFrame(records_p10).mean()]g11 = [float('%0.1f' % i) for i in DataFrame(records_p11).mean()]g12 = [float('%0.1f' % i) for i in DataFrame(records_p12).mean()]g13 = [float('%0.1f' % i) for i in DataFrame(records_p13).mean()]app = Flask(__name__)#引入bootstrap前端框架bootstrap = Bootstrap(app)@app.route('/')def hello_world():    return render_template('index.html', a=e, b=f, c1=g1,c2=g2,c3=g3,c4=g4,c5=g5,c6=g6,c7=g7,c8=g8,c9=g9,c10=g10,c11=g11,c12=g12,c13=g13)if __name__ == '__main__':    app.run(debug=True)

index.html{
     % extends "base.html" %}{
     % block title %}Flasky{% endblock %}{
     % block page_content %}
      
       
数据分析
      
    
          
      
    
      
        
       
        
       
    
      
    
              
                  

 

{
    % endblock %}