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。
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.csdn.net/yang6464158/article/details/18546871#comments
安装 scipy,然后把C:Python27Libsite-packagesscipylib中的six.py six.pyc six.pyo三个文件拷贝到C:Python27Libsite-packages目录下。
1 import numpy as np 2 import matplotlib.pyplot as plt 3 4 N = 5 5 menMeans = (20, 35, 30, 35, 27) 6 menStd = (2, 3, 4, 1, 2) 7 8 ind = np.arange(N) # the x locations for the groups 9 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()
运行上面代码,执行后如下图所示。