统计分析模块statistics

一 计算平均数函数mean()

1. >>>import statistics
2. >>> statistics.mean([1,2,3,4,5,6,7,8,9])#使用整数列表做参数
3. 5
4. >>> statistics.mean(range(1,10))#使用range对象做参数
5. 5
6. >>>import fractions
7. >>> x =[(3,7),(1,21),(5,3),(1,3)]
8. >>> y =[fractions.Fraction(*item)for item in x]
9. >>> y
10. [Fraction(3,7),Fraction(1,21),Fraction(5,3),Fraction(1,3)]
11. >>> statistics.mean(y)#使用包含分数的列表做参数
12. Fraction(13,21)
13. >>>import decimal
14. >>> x =('0.5','0.75','0.625','0.375')
15. >>> y = map(decimal.Decimal, x)
16. >>> statistics.mean(y)
17. Decimal('0.5625')

二 中位数函数median()、median_low()、median_high()、median_grouped()

1. >>> statistics.median([1,3,5,7])#偶数个样本时取中间两个数的平均数
2. 4.0
3. >>> statistics.median_low([1,3,5,7])#偶数个样本时取中间两个数的较小者
4. 3
5. >>> statistics.median_high([1,3,5,7])#偶数个样本时取中间两个数的较大者
6. 5
7. >>> statistics.median(range(1,10))
8. 5
9. >>> statistics.median_low([5,3,7]), statistics.median_high([5,3,7])
10. (5,5)
11. >>> statistics.median_grouped([5,3,7])
12. 5.0
13. >>> statistics.median_grouped([52,52,53,54])
14. 52.5
15. >>> statistics.median_grouped([1,3,3,5,7])
16. 3.25
17. >>> statistics.median_grouped([1,2,2,3,4,4,4,4,4,5])
18. 3.7
19. >>> statistics.median_grouped([1,2,2,3,4,4,4,4,4,5], interval=2)
20. 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()

1. >>> statistics.mode([1,3,5,7])#无法确定出现次数最多的唯一元素
2. Traceback(most recent call last):
3. File"<pyshell#27>", line 1,in<module>
4. statistics.mode([1,3,5,7])#无法确定出现次数最多的唯一元素
5. File"D:\Python36\lib\statistics.py", line 507,in mode
6. 'no unique mode; found %d equally common values'% len(table)
7. statistics.StatisticsError: no unique mode; found 4 equally common values
8. >>> statistics.mode([1,3,5,7,3])
9. 3
10. >>> statistics.mode(["red","blue","blue","red","green","red","red"])
11. 'red'

四 

pstdev()，返回总体标准差（population standard deviation ，the square root of the population variance)

1. >>> statistics.pstdev([1.5,2.5,2.5,2.75,3.25,4.75])
2. 0.986893273527251
3. >>> statistics.pstdev(range(20))
4. 5.766281297335398

五 pvariance()，返回总体方差（population variance）或二次矩（second moment）

1. >>> statistics.pvariance([1.5,2.5,2.5,2.75,3.25,4.75])
2. 0.9739583333333334
3. >>> x =[1,2,3,4,5,10,9,8,7,6]
4. >>> mu = statistics.mean(x)
5. >>> mu
6. 5.5
7. >>> statistics.pvariance([1,2,3,4,5,10,9,8,7,6], mu)
8. 8.25
9. >>> statistics.pvariance(range(20))
10. 33.25
11. >>> statistics.pvariance((random.randint(1,10000)for i in range(30)))
12. >>>import random
13. >>> statistics.pvariance((random.randint(1,10000)for i in range(30)))
14. 7117280.4