【Python】Python进阶系列教程--statistics 模块（二十一）

- 日理万妓 2023-10-12 14:46 23阅读 0赞

#### 文章目录 ####

*  前言
 *  math 模块方法

## 前言 ##

往期回顾：

*  [Python进阶系列教程-- Python3 正则表达式（一）][Python_-- Python3]
 *  [Python进阶系列教程-- Python3 CGI编程（二）][Python_-- Python3 CGI]
 *  [Python进阶系列教程-- Python3 MySQL - mysql-connector 驱动（三）][Python_-- Python3 MySQL - mysql-connector]
 *  [Python进阶系列教程-- Python3 MySQL 数据库连接 - PyMySQL 驱动][Python_-- Python3 MySQL _ - PyMySQL]
 *  [Python进阶系列教程-- Python3 网络编程（五）][Python_-- Python3 1]
 *  [Python进阶系列教程-- Python3 SMTP发送邮件（六）][Python_-- Python3 SMTP]
 *  [Python进阶系列教程-- Python3 多线程（七）][Python_-- Python3 2]
 *  [Python进阶系列教程-- Python3 XML 解析（八）][Python_-- Python3 XML]
 *  [Python进阶系列教程-- Python3 JSON 数据解析（九）][Python_-- Python3 JSON]
 *  [Python进阶系列教程-- Python3 日期和时间（十）][Python_-- Python3 3]
 *  [Python进阶系列教程-- 内置函数（十一）][Python_--]
 *  [Python进阶系列教程-- MongoDB（十二）][Python_-- MongoDB]
 *  [Python进阶系列教程-- urllib（十三）][Python_-- urllib]
 *  [Python进阶系列教程-- uWSGI 安装配置（十四）][Python_-- uWSGI]
 *  [Python进阶系列教程–pip（十五）][Python_pip]
 *  [Python进阶系列教程–operator 模块（十六）][Python_operator]
 *  [Python进阶系列教程–math 模块（十七）][Python_math]
 *  [Python进阶系列教程–random 模块（十八）][Python_random]
 *  [Python进阶系列教程–requests 模块（十九）][Python_requests]
 *  [Python进阶系列教程–Python AI 绘画（二十）][Python_Python AI]

Python statistics 是标准库中的一个模块，模块提供了许多基本统计计算的函数。

statistics 模块是在 Python 3.4 版本中新增加的，可以帮助我们分析和计算数据集的统计特征。

要使用 statistics 函数必须先导入：

import statistics

查看 statistics 模块中的内容:

>>> import statistics
    >>> dir(statistics)
    ['Counter', 'Decimal', 'Fraction', 'NormalDist', 'StatisticsError', '__all__', '__builtins__', '__cached__', '__doc__', '__file__', '__loader__', '__name__', '__package__', '__spec__', '_coerce', '_convert', '_exact_ratio', '_fail_neg', '_find_lteq', '_find_rteq', '_isfinite', '_normal_dist_inv_cdf', '_ss', '_sum', 'bisect_left', 'bisect_right', 'erf', 'exp', 'fabs', 'fmean', 'fsum', 'geometric_mean', 'groupby', 'harmonic_mean', 'hypot', 'itemgetter', 'log', 'math', 'mean', 'median', 'median_grouped', 'median_high', 'median_low', 'mode', 'multimode', 'numbers', 'pstdev', 'pvariance', 'quantiles', 'random', 'sqrt', 'stdev', 'tau', 'variance']

## math 模块方法 ##

<table> 
 <thead> 
  <tr> 
   <th align="left">方法</th> 
   <th align="left">描述</th> 
  </tr> 
 </thead> 
 <tbody> 
  <tr> 
   <td align="left">statistics.harmonic_mean()</td> 
   <td align="left">计算给定数据集的调和平均值。</td> 
  </tr> 
  <tr> 
   <td align="left">statistics.mean()</td> 
   <td align="left">计算数据集的平均值</td> 
  </tr> 
  <tr> 
   <td align="left">statistics.median()</td> 
   <td align="left">计算数据集的中位数</td> 
  </tr> 
  <tr> 
   <td align="left">statistics.median_grouped()</td> 
   <td align="left">计算给定分组数据集的分组中位数</td> 
  </tr> 
  <tr> 
   <td align="left">statistics.median_high()</td> 
   <td align="left">计算给定数据集的高位中位数</td> 
  </tr> 
  <tr> 
   <td align="left">statistics.median_low()</td> 
   <td align="left">计算给定数据集的低位中位数。</td> 
  </tr> 
  <tr> 
   <td align="left">statistics.mode()</td> 
   <td align="left">算数据集的众数（出现频率最高的值）</td> 
  </tr> 
  <tr> 
   <td align="left">statistics.pstdev()</td> 
   <td align="left">计算给定数据集的样本标准偏差</td> 
  </tr> 
  <tr> 
   <td align="left">statistics.stdev()</td> 
   <td align="left">计算数据集的标准差</td> 
  </tr> 
  <tr> 
   <td align="left">statistics.pvariance()</td> 
   <td align="left">计算给定数据集的样本方差</td> 
  </tr> 
  <tr> 
   <td align="left">statistics.variance()</td> 
   <td align="left">计算数据集的方差</td> 
  </tr> 
  <tr> 
   <td align="left">statistics.quantiles()</td> 
   <td align="left">计算数据集的分位数，可指定分位数的数量（默认为四分位数）</td> 
  </tr> 
 </tbody> 
</table>

[Python_-- Python3]: https://writer.blog.csdn.net/article/details/131116286
[Python_-- Python3 CGI]: https://blog.csdn.net/u011397981/article/details/131116745
[Python_-- Python3 MySQL - mysql-connector]: https://writer.blog.csdn.net/article/details/131117076
[Python_-- Python3 MySQL _ - PyMySQL]: https://blog.csdn.net/u011397981/article/details/131117240
[Python_-- Python3 1]: https://blog.csdn.net/u011397981/article/details/131137870
[Python_-- Python3 SMTP]: https://blog.csdn.net/u011397981/article/details/131137895
[Python_-- Python3 2]: https://blog.csdn.net/u011397981/article/details/131138199
[Python_-- Python3 XML]: https://blog.csdn.net/u011397981/article/details/131138242
[Python_-- Python3 JSON]: https://writer.blog.csdn.net/article/details/131149733
[Python_-- Python3 3]: https://blog.csdn.net/u011397981/article/details/131149771
[Python_--]: https://writer.blog.csdn.net/article/details/131150020
[Python_-- MongoDB]: https://blog.csdn.net/u011397981/article/details/131150106
[Python_-- urllib]: https://blog.csdn.net/u011397981/article/details/131150208
[Python_-- uWSGI]: https://blog.csdn.net/u011397981/article/details/131161438
[Python_pip]: https://writer.blog.csdn.net/article/details/131161738
[Python_operator]: https://blog.csdn.net/u011397981/article/details/131162120
[Python_math]: https://blog.csdn.net/u011397981/article/details/131162430
[Python_random]: https://blog.csdn.net/u011397981/article/details/131180446
[Python_requests]: https://writer.blog.csdn.net/article/details/131180463
[Python_Python AI]: https://blog.csdn.net/u011397981/article/details/131180472