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。
import numpy as np import matplotlib.pyplot as plt N = 5 menMeans = (20, 35, 30, 35, 27) menStd = (2, 3, 4, 1, 2) ind = np.arange(N) # the x locations for the groups width = 0.35 # the width of the bars fig, ax = plt.subplots() rects1 = ax.bar(ind, menMeans, width, color='r', yerr=menStd) womenMeans = (25, 32, 34, 20, 25) womenStd = (3, 5, 2, 3, 3) rects2 = ax.bar(ind+width, womenMeans, width, color='y', yerr=womenStd) # add some ax.set_ylabel('Scores') ax.set_title('Scores by group and gender') ax.set_xticks(ind+width) ax.set_xticklabels( ('G1', 'G2', 'G3', 'G4', 'G5') ) ax.legend( (rects1[0], rects2[0]), ('Men', 'Women') ) def autolabel(rects): # attach some text labels for rect in rects: height = rect.get_height() ax.text(rect.get_x()+rect.get_width()/2., 1.05*height, '%d'%int(height), ha='center', va='bottom') autolabel(rects1) autolabel(rects2) plt.show()
运行上面代码,执行后如下图所示。
来自:http://my.oschina.net/bery/blog/203595