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13.3扩展库 pandas

• Python Data Analysis Library)基于numpy,
• pandas是使得 Python能够成为高效且强大的数据分析环境的重要因素

• pandas提供

• Series,带标签的一维数组;

• DataFrame,带标签且大小可变的二维表格结构;

• Panel,带标签且大小可变的三维数组

• 命令提示符环境用pip工具下载安装pandas

1.生成一维数组

2 生成二维数组

import pandas as pddates = pd.date_range(start='20120101',end='20131231',freq='M')print (dates)print (type(dates))DatetimeIndex(['2012-01-31', '2012-02-29', '2012-03-31', '2012-04-30',               '2012-05-31', '2012-06-30', '2012-07-31', '2012-08-31',               '2012-09-30', '2012-10-31', '2012-11-30', '2012-12-31',               '2013-01-31', '2013-02-28', '2013-03-31', '2013-04-30',               '2013-05-31', '2013-06-30', '2013-07-31', '2013-08-31',               '2013-09-30', '2013-10-31', '2013-11-30', '2013-12-31'],              dtype='datetime64[ns]', freq='M')
   

import pandas as pddates = pd.date_range(start='20120101',end='20131203',freq='M')print (dates)print (type(dates))DatetimeIndex(['2012-01-31', '2012-02-29', '2012-03-31', '2012-04-30',               '2012-05-31', '2012-06-30', '2012-07-31', '2012-08-31',               '2012-09-30', '2012-10-31', '2012-11-30', '2012-12-31',               '2013-01-31', '2013-02-28', '2013-03-31', '2013-04-30',               '2013-05-31', '2013-06-30', '2013-07-31', '2013-08-31',               '2013-09-30', '2013-10-31', '2013-11-30'],              dtype='datetime64[ns]', freq='M')
   

13.5 matplotlib

• 依赖 numpy和 tkinter,
• 可绘制,
• 线图、直方图、併状图、散点图、误差线图,
• 图形质量可满足出版要求

13.5.1 绘制正弦曲线

import numpy as npimport pylab as plt=np.arange (0.0, 2.0 *np.pi,0.01)s=np.sin(t)pl.plot(t, s)pl.xlabel('x')pl.ylabel('y')pl.title('sin')pl.show()

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