目标：不做蜡烛图，只用折线图绘图，绘出四条线之间的关系。
注：未使用接口，仅爬虫学习，不做任何违法操作。
1 """
2 新浪财经，爬取历史股票数据 3 """
4
5 # -*- coding:utf-8 -*-
6
7 import numpy as np 8 import urllib.request, lxml.html 9 from urllib.request import urlopen 10 from bs4 import BeautifulSoup 11 import re, time 12 import matplotlib.pyplot as plt 13 from datetime import datetime 14 # 绘图显示中文设置
15 plt.rcParams['font.sans-serif'] = ['SimHei'] 16 plt.rcParams['axes.unicode_minus'] = False 17
18
19 # 公共模块，请求头信息
20 def public(link): 21 r = urllib.request.Request(link) 22
23 ug = 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/49.0.2623.221 Safari/537.36 SE 2.X MetaSr 1.0'
24
25 r.add_header('User-Agent', ug) 26
27 cookie = "SUB=_2AkMsqZjif8NxqwJRmfkRxG7nZYpzyg_EieKa9Wk5JRMyHRl-yD83qkJatRB6Bym2DDqPE870e3uMsySIjHjrMbMNxNqk; " \ 28 "SUBP=0033WrSXqPxfM72-Ws9jqgMF55529P9D9WFXmxLGpAG5k05lCJw6qgYe; " \ 29 "SINAGLOBAL=172.16.92.24_1542789082.401113; " \ 30 "Apache=172.16.92.24_1542789082.401115; UOR=www.baidu.com,blog.sina.com.cn,; " \ 31 "ULV=1542789814434:1:1:1:172.16.92.24_1542789082.401115:; U_TRS1=000000d1.1f4d3546.5bf53673.955fa32e; " \ 32 "U_TRS2=000000d1.1f593546.5bf53673.736853cc; FINANCE2=661413ac85cadaab72ec7e3d842d6a3a; _s_upa=1"
33
34 r.add_header("Cookie", cookie) 35
36 html = urllib.request.urlopen(r, timeout=500).read() 37
38 bsObj = BeautifulSoup(html, "lxml") # 将html对象转化为BeautifulSoup对象
39
40 return bsObj 41
42
43 # 获取股票价格
44 def shares_price(code, year, quarter): 45 link = "http://money.finance.sina.com.cn/corp/go.php/vMS_MarketHistory/stockid/%s.phtml?year=%d&jidu=%d" % (code, year, quarter) 46
47 bsObj = public(link) 48 # print(bsObj)
49
50 a = 0 51 # date_list为日期列表，open_list为开盘价列表，high_list为最高价列表，close_list为收盘价列表，low_list为最低价列表
52 price_list, date_list, open_list, high_list, close_list, low_list = [], [], [], [], [], [] 53 # 获取股票信息
54 jpg_title = re.findall("(.*?\))", bsObj.title.text) 55
56 prices_bs = bsObj.find_all(name='div', attrs={"align": 'center'}) 57 # 获取并处理价格信息
58 for price_bs in prices_bs: 59 # 去除空格
60 price_bs_1 = price_bs.text.replace("\n\r\n\t\t\t", "") 61 price_bs_2 = price_bs_1.replace("\t\t\t\n", "") 62
63 # 6个字符串为一个列表
64 if a != 6: 65 price_list.append(price_bs_2) 66 a = a + 1
67 else: 68 date_list.append(price_list[0]) 69 open_list.append(price_list[1]) 70 high_list.append(price_list[2]) 71 close_list.append(price_list[3]) 72 low_list.append(price_list[4]) 73 a = 0 74 price_list = [] 75 # 删除列表头
76 for b in (date_list, open_list, high_list, close_list, low_list): 77 b.pop(0) 78
79 # 全部倒序排列（由日期远到近，从左到右排列）
80 for c in (date_list, open_list, high_list, close_list, low_list): 81 c.reverse() 82
83 return date_list, open_list, high_list, close_list, low_list, jpg_title 84
85
86 # 输入股票代码，年份，季度
87 code = "002925"
88 year = "2018"
89 quarter = 4
90 # 以下为手动输入模式，因调试方便默认上面固定模式。
91 # code = input("code：") # 002925
92 # year = input("year：") # 2018
93 # quarter = int(input("quarter："))
94
95 # 列表字符串转为数值date
96 x = [datetime.strptime(d, '%Y-%m-%d').date() for d in shares_price(code, int(year), quarter)[0]] 97 # 将爬取的数据（字符串）转化为浮点型
98 open_list = [float(i) for i in shares_price(code, int(year), quarter)[1]] 99 high_list = [float(i) for i in shares_price(code, int(year), quarter)[2]] 100 close_list = [float(i) for i in shares_price(code, int(year), quarter)[3]] 101 low_list = [float(i) for i in shares_price(code, int(year), quarter)[4]] 102
103 # 线条设置
104 plt.plot(x, open_list, label='open', linewidth=1, color='red', marker='o', markerfacecolor='blue', markersize=2) 105 plt.plot(x, high_list, label='high', linewidth=1, color='green', marker='o', markerfacecolor='blue', markersize=2) 106 plt.plot(x, close_list, label='close', linewidth=1, color='blue', marker='o', markerfacecolor='blue', markersize=2) 107 plt.plot(x, low_list, label='low', linewidth=1, color='black', marker='o', markerfacecolor='blue', markersize=2) 108
109 # 取数列最大数值与最小值做图表的边界值。
110 plt.ylim(min(low_list)-1, max(high_list)+1) 111 plt.gcf().autofmt_xdate() # 自动旋转日期标记
112
113 # 打印表头
114 plt.xlabel('time') 115 plt.ylabel('price') 116 # shares_price(code, int(year), quarter)[5][0]为title中的股票名称与代码
117 plt.title('gp_1_{0}.jpg'.format(shares_price(code, int(year), quarter)[5][0])) 118 plt.legend() 119 plt.show()
效果如下：
是不是有另一种看法的感觉？如：黑线下跌后向上的第一个大拐点为买入点。