样本：S = [s1, s2, ..., sn]
平均值：m = (s1+s2+...+sn)/n
离差：D = [d1, d2, ..., dn], di = si-m
离差方：Q = [q1, q2, ..., qn], qi = di**2
总体方差：v = (q1+q2+...+qn)/n
总体标准差：s = sqrt(v)，方均根
样本方差：v' = (q1+q2+...+qn)/(n-1)
样本标准差：s' = sqrt(v')，方均根
np.std(array) # 总体标准差
np.std(array, ddof=1) # 样本标准差
# 中位数
import numpy as np
import datetime as dt
def dmy2ymd(dmy):
"""
把日月年转年月日
:param day:
:return:
"""
dmy = str(dmy, encoding='utf-8')
t = dt.datetime.strptime(dmy, '%d-%m-%Y')
s = t.date().strftime('%Y-%m-%d')
return s
dates, opening_prices, \
highest_prices, lowest_prices, \
closing_prices, volumes = \
np.loadtxt('aapl.csv',
delimiter=',',
usecols=(1, 3, 4, 5, 6, 7),
unpack=True,
dtype='M8[D],f8,f8,f8,f8,f8',
converters={1: dmy2ymd}) # 日月年转年月日
#总体封盘标准差
std_c = np.std(closing_prices)
print(std_c) # 7.080008325481608
#总体开盘标准差
std_o = np.std(opening_prices)
print(std_o) # 7.099438350242144
std_c2 = np.std(closing_prices, ddof=1) # 样本标准差
print(std_c2) # 7.201042876260849
# 手动实现
m = np.mean(closing_prices) #算数平均值
d = closing_prices - m #利差
v = np.mean(d ** 2)#离差方
s = np.sqrt(v)#总体标准差
print(s) # 7.080008325481608
v2 = (d ** 2).sum() / (d.size - 1)
s2 = np.sqrt(v2)
print(s2) # 样本标准差
# 7.201042876260849
