python做统计分析_Python统计分析模块statistics用法示例

本文实例讲述了Python统计分析模块statistics用法。分享给大家供大家参考，具体如下：

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"", line 1,in

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

希望本文所述对大家Python程序设计有所帮助。