在使用NumPy进行学习统计计算时是枯燥的,大量的数据令我们很头疼,所以我们需要把它图形化显示。
Matplotlib是一个Python的图形框架,类似于MATLAB和R语言。
安装 scipy ,然后把C:\Python27\Lib\site-packages\scipy\lib中的six.py six.pyc six.pyo三个文件拷贝到C:\Python27\Lib\site-packages目录下。
运行上面代码,执行后如下图所示。
Matplotlib是一个Python的图形框架,类似于MATLAB和R语言。
Matplotlib的官网地址是 http://matplotlib.org/ ,下载地址为 http://matplotlib.org/downloads.html,选择对应的版本即可安装,我选择的版本为 matplotlib-1.3.1.win32-py2.7.exe。
由于我之前已经安装过NumPy1.8,所以安装Matplotlib后只需要安装 dateutil 和 pyparsing,win32的安装文件可以在这里找到 http://www.lfd.uci.edu/~gohlke/pythonlibs/。
所有配套组件都安装成功后如果执行 import matplotlib.pyplot as plt 出错,请参考这篇文章 http://blog.youkuaiyun.com/yang6464158/article/details/18546871#comments安装 scipy ,然后把C:\Python27\Lib\site-packages\scipy\lib中的six.py six.pyc six.pyo三个文件拷贝到C:\Python27\Lib\site-packages目录下。
01 | import numpy as np |
02 | import matplotlib.pyplot as plt |
03 |
04 | N = 5 |
05 | menMeans = ( 20 , 35 , 30 , 35 , 27 ) |
06 | menStd = ( 2 , 3 , 4 , 1 , 2 ) |
07 |
08 | ind = np.arange(N) # the x locations for the groups |
09 | width = 0.35 # the width of the bars |
10 |
11 | fig, ax = plt.subplots() |
12 | rects1 = ax.bar(ind, menMeans, width, color = 'r' , yerr = menStd) |
13 |
14 | womenMeans = ( 25 , 32 , 34 , 20 , 25 ) |
15 | womenStd = ( 3 , 5 , 2 , 3 , 3 ) |
16 | rects2 = ax.bar(ind + width, womenMeans, width, color = 'y' , yerr = womenStd) |
17 |
18 | # add some |
19 | ax.set_ylabel( 'Scores' ) |
20 | ax.set_title( 'Scores by group and gender' ) |
21 | ax.set_xticks(ind + width) |
22 | ax.set_xticklabels( ( 'G1' , 'G2' , 'G3' , 'G4' , 'G5' ) ) |
23 |
24 | ax.legend( (rects1[ 0 ], rects2[ 0 ]), ( 'Men' , 'Women' ) ) |
25 |
26 | def autolabel(rects): |
27 | # attach some text labels |
28 | for rect in rects: |
29 | height = rect.get_height() |
30 | ax.text(rect.get_x() + rect.get_width() / 2. , 1.05 * height, '%d' % int (height), |
31 | ha = 'center' , va = 'bottom' ) |
32 |
33 | autolabel(rects1) |
34 | autolabel(rects2) |
35 |
36 | plt.show() |
来自:http://my.oschina.net/bery/blog/203595