python statistics python statistics fit

statistics模块的作用

statistics模块实现了很多常用的统计公式，允许使用Python的各种数值类型(int,float,Decimal和Fraction)来完成高效的计算。

 1、求一个列表的平均数

from statistics import *

data = [1, 2, 2, 5, 10, 12]
print('{:0.2f}'.format(mean(data)))

statistics_mean.py

运行效果

5.33

2、显示一个元素在列表中出现次数最多的，如果数次相同则抛出异常statistics.StatisticsError

from statistics import *

data = [1, 2, 2, 5, 10, 12]
print('{}'.format(mode(data)))

statistics_mode.py

运行效果

2

 3、计算中间最小，最大值，和中数的平均值

from statistics import *

data = [1, 2, 2, 5, 10, 12]

print('median     : {:0.2f}'.format(median(data)))  # 取两个中数的平均值
print('low        : {:0.2f}'.format(median_low(data)))  # 取中数最小值
print('high       : {:0.2f}'.format(median_high(data)))  # 取中数最大值

statistics_median.py

运行效果

median     : 3.50
low        : 2.00
high       : 5.00

4、取中间值，每次减少0.5的示例

from statistics import *

data = [10, 20, 30, 40]

print('1: {:0.2f}'.format(median_grouped(data, interval=1)))
print('2: {:0.2f}'.format(median_grouped(data, interval=2)))
print('3: {:0.2f}'.format(median_grouped(data, interval=3)))

statistics_median_grouped.py

运行效果

1: 29.50
2: 29.00
3: 28.50

5、方差计算

from statistics import *
import subprocess


def get_line_lengths():
    cmd = 'wc -l ../[a-z]*/*.py'
    out = subprocess.check_output(
        cmd, shell=True).decode('utf-8')
    for line in out.splitlines():
        parts = line.split()
        if parts[1].strip().lower() == 'total':
            break
        nlines = int(parts[0].strip())
        if not nlines:
            continue  # skip empty files
        yield (nlines, parts[1].strip())


data = list(get_line_lengths())

lengths = [d[0] for d in data]
sample = lengths[::2]

print('Basic statistics:')
print('  count     : {:3d}'.format(len(lengths)))
print('  min       : {:6.2f}'.format(min(lengths)))
print('  max       : {:6.2f}'.format(max(lengths)))
print('  mean      : {:6.2f}'.format(mean(lengths)))

print('\nPopulation variance:')  # 方差
print('  pstdev    : {:6.2f}'.format(pstdev(lengths)))
print('  pvariance : {:6.2f}'.format(pvariance(lengths)))

print('\nEstimated variance for sample:')  # 标准差
print('  count     : {:3d}'.format(len(sample)))
print('  stdev     : {:6.2f}'.format(stdev(sample)))
print('  variance  : {:6.2f}'.format(variance(sample)))

statistics_variance.py

运行效果

[root@localhost ~]# python
python     python2    python2.6  python3    
[root@YZS_3WYY_WEB ~]# python3 p.py 
Basic statistics:
  count     :   4
  min       :   7.00
  max       : 134.00
  mean      :  46.75

Population variance:
  pstdev    :  51.89
  pvariance : 2692.69

Estimated variance for sample:
  count     :   2
  stdev     :  89.10
  variance  : 7938.00