饼图
# Make a pie chart # This script is written by Vamei, http://www.cnblogs.com/vamei # you may freely use it. import matplotlib.pyplot as plt # quants: GDP # labels: country name labels = [] quants = [] # Read data for line in file('major_country_gdp'): info = line.split() labels.append(info[0]) quants.append(float(info[1])) # make a square figure plt.figure(1, figsize=(6,6)) # For China, make the piece explode a bit def explode(label, target='China'): if label == target: return 0.1 else: return 0 expl = map(explode,labels) # Colors used. Recycle if not enough. colors = ["pink","coral","yellow","orange"] # Pie Plot # autopct: format of "percent" string; plt.pie(quants, explode=expl, colors=colors, labels=labels, autopct='%1.1f%%',pctdistance=0.8, shadow=True) plt.title('Top 10 GDP Countries', bbox={'facecolor':'0.8', 'pad':5}) plt.show()直方图
import numpy as np import matplotlib.pyplot as plt mu, sigma = 100, 15 x = mu + sigma * np.random.randn(10000) # the histogram of the data n, bins, patches = plt.hist(x, 50, normed=1, facecolor='g', alpha=0.75) plt.xlabel('Smarts') plt.ylabel('Probability') plt.title('Histogram of IQ') plt.text(60, .025, r'$\mu=100,\ \sigma=15$') plt.axis([40, 160, 0, 0.03]) plt.grid(True) plt.show() 子图 import numpy as np import matplotlib.pyplot as plt def f(t): return np.exp(-t) * np.cos(2*np.pi*t) t1 = np.arange(0.0, 5.0, 0.1) t2 = np.arange(0.0, 5.0, 0.02) plt.figure(1) plt.subplot(211) plt.plot(t1, f(t1), 'bo', t2, f(t2), 'g') plt.subplot(212) plt.plot(t2, np.cos(2*np.pi*t2), 'r--') #plt.show() plt.figure(2) plt.plot(t1, f(t1), 'bo', t2, f(t2), 'g',label='f1') plt.plot(t2, np.cos(2*np.pi*t2), 'r--',label='f2') plt.legend(shadow=True) plt.show()