import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
#个股
data_stock = pd.read_table(r'C:\Users\tang\AnacondaProjects\gupiao\600917.txt',header=1,usecols=range(6), parse_dates=[0], index_col=0,encoding='gb2312')
data_stock.index.rename('date', inplace=True)
data_stock.rename(columns={' 开盘':'open', ' 最高':'high', ' 最低':'low', ' 收盘':'close',' 成交量':'vol'}, inplace=True)
data_stock = data_stock.drop('数据来源:通达信')
data_stock.index = data_stock.index.astype(np.datetime64)
data_stock = data_stock['2016-01-04':]
stock_lower_price = data_stock.close.rolling(window=15,center=False).min()
stock_lower_vol = data_stock.vol.rolling(window=15,center=False).min()
x = data_stock.index[14:]
plt.subplot(4,1,1)
plt.ylabel('close')
y = data_stock.close[14:]
plt.ylim(y.min(),y.max())
plt.plot(x,y,color='green')
plt.subplot(4,1,2)
plt.ylabel('lower_price')
z = stock_lower_price[14:]
plt.ylim(z.min(),z.max())
plt.plot(x,z,color='red')
plt.subplot(4,1,3)
plt.ylabel('lower_vol')
m = stock_lower_vol[14:]
plt.ylim(m.min(),m.max())
plt.plot(x,m,color='green')
c = stock_lower_price.corr(stock_lower_vol)
#上证指数
data_sh = pd.read_table(r'C:\Users\tang\AnacondaProjects\gupiao\999999.txt',header=1,usecols=range(6), parse_dates=[0], index_col=0,encoding='gb2312')
data_sh.index.rename('date', inplace=True)
data_sh.rename(columns={' 开盘':'open', ' 最高':'high', ' 最低':'low', ' 收盘':'close',' 成交量':'vol'}, inplace=True)
data_sh = data_sh.drop('数据来源:通达信')
data_sh.index = data_sh.index.astype(np.datetime64)
data_sh = data_sh['2016-01-04':]
plt.subplot(4,1,4)
plt.ylabel('sh')
n = data_sh.close[15:]
plt.ylim(n.min(),n.max())
plt.plot(data_sh.index[15:],n,color='blue')
plt.show()
以600917为例，观察移动最low price与最low vol之间的相关性，以及与close，上证指数之间的关系，结果如下：
