# -*- coding: utf-8 -*-
"""
Created on Sun May 26 16:51:35 2019
@author: User
"""
import pandas as pd
import numpy as np
from scipy import stats
stock=np.dtype([('id',np.str,5),
('time',np.str,10),
('code',np.str,10),
('open_p',np.float64),
('close_p',np.float64),
('low_p',np.float64),
('vol',np.int32),
('high_p',np.float64),
('col',np.int32)])
print('\n jd_stock:')
jd_stock=np.loadtxt('data\stock.csv',delimiter=',',dtype=stock)
print(jd_stock)
print('\n jddf:')
jddf=pd.read_csv('data\stock.csv',sep=',',header=None,
names=['id','time','code','open_p','colse_p','low_p','vol','high_p','col'])
print(jddf.head())
print("\n 方差 ddof表示计算方差时分母为n-ddof:")
print(np.var(jd_stock['open_p'],ddof=1))
print("\n numpy 方差2:")
print(jd_stock['open_p'].var(ddof=1))
print("\n numpy 标准差 np.std(jd_stock['open_p'],ddof=1):")
print(np.std(jd_stock['open_p'],ddof=1))
print("\n pandas 方差，标准差:")
print(jddf['open_p'].var(),jddf['open_p'].std())
print("\n scipy 方差，标准差2:")
print(stats.tvar(jddf['open_p']),stats.tstd(jddf['open_p']))
运行：
jd_stock: [('1', '20130902', '600028', 4.41, 4.43, 4.37, 17275, 4.41, 392662) ('2', '20130903', '600028', 4.41, 4.46, 4.4 , 19241, 4.45, 434177) ('3', '20130904', '600028', 4.44, 4.49, 4.42, 20106, 4.47, 451470) ... ('1356', '20190327', '600028', 5.71, 5.75, 5.69, 63601, 5.72, 1112544) ('1357', '20190328', '600028', 5.69, 5.7 , 5.62, 65692, 5.64, 1162484) ('1358', '20190329', '600028', 5.65, 5.75, 5.61, 112785, 5.74, 1981482)]
jddf: id time code open_p colse_p low_p vol high_p col 0 1 20130902 600028 4.41 4.43 4.37 17275.39 4.41 392662 1 2 20130903 600028 4.41 4.46 4.40 19241.84 4.45 434177 2 3 20130904 600028 4.44 4.49 4.42 20106.30 4.47 451470 3 4 20130905 600028 4.47 4.48 4.42 15582.48 4.47 349997 4 5 20130906 600028 4.46 4.52 4.45 19101.41 4.50 425777
方差 ddof表示计算方差时分母为n-ddof: 0.6956978412269116
numpy 方差2: 0.6956978412269116
numpy 标准差 np.std(jd_stock['open_p'],ddof=1): 0.8340850323719469
pandas 方差，标准差: 0.6956978412269099 0.8340850323719459
scipy 方差，标准差2: 0.6956978412269116 0.8340850323719469
