统计分析模块statistics
一 计算平均数函数mean()
>>>import statistics
>>> statistics.mean([1,2,3,4,5,6,7,8,9])#使用整数列表做参数
5
>>> statistics.mean(range(1,10))#使用range对象做参数
5
>>>import fractions
>>> x =[(3,7),(1,21),(5,3),(1,3)]
>>> y =[fractions.Fraction(*item)for item in x]
>>> y
[Fraction(3,7),Fraction(1,21),Fraction(5,3),Fraction(1,3)]
>>> statistics.mean(y)#使用包含分数的列表做参数
Fraction(13,21)
>>>import decimal
>>> x =('0.5','0.75','0.625','0.375')
>>> y = map(decimal.Decimal, x)
>>> statistics.mean(y)
Decimal('0.5625')
二 中位数函数median()、median_low()、median_high()、median_grouped()
>>> statistics.median([1,3,5,7])#偶数个样本时取中间两个数的平均数
4.0
>>> statistics.median_low([1,3,5,7])#偶数个样本时取中间两个数的较小者
3
>>> statistics.median_high([1,3,5,7])#偶数个样本时取中间两个数的较大者
5
>>> statistics.median(range(1,10))
5
>>> statistics.median_low([5,3,7]), statistics.median_high([5,3,7])
(5,5)
>>> statistics.median_grouped([5,3,7])
5.0
>>> statistics.median_grouped([52,52,53,54])
52.5
>>> statistics.median_grouped([1,3,3,5,7])
3.25
>>> statistics.median_grouped([1,2,2,3,4,4,4,4,4,5])
3.7
>>> statistics.median_grouped([1,2,2,3,4,4,4,4,4,5], interval=2)
3.4
三 返回最常见数据或出现次数最多的数据（most common data）的函数mode()
>>> statistics.mode([1,3,5,7])#无法确定出现次数最多的唯一元素
Traceback(most recent call last):
File"
statistics.mode([1,3,5,7])#无法确定出现次数最多的唯一元素
File"D:\Python36\lib\statistics.py", line 507,in mode
'no unique mode; found %d equally common values'% len(table)
statistics.StatisticsError: no unique mode; found 4 equally common values
>>> statistics.mode([1,3,5,7,3])
3
>>> statistics.mode(["red","blue","blue","red","green","red","red"])
'red'
四
pstdev()，返回总体标准差（population standard deviation ，the square root of the population variance)
>>> statistics.pstdev([1.5,2.5,2.5,2.75,3.25,4.75])
0.986893273527251
>>> statistics.pstdev(range(20))
5.766281297335398
五 pvariance()，返回总体方差（population variance）或二次矩（second moment）
>>> statistics.pvariance([1.5,2.5,2.5,2.75,3.25,4.75])
0.9739583333333334
>>> x =[1,2,3,4,5,10,9,8,7,6]
>>> mu = statistics.mean(x)
>>> mu
5.5
>>> statistics.pvariance([1,2,3,4,5,10,9,8,7,6], mu)
8.25
>>> statistics.pvariance(range(20))
33.25
>>> statistics.pvariance((random.randint(1,10000)for i in range(30)))
>>>import random
>>> statistics.pvariance((random.randint(1,10000)for i in range(30)))
7117280.4