from numpy import * import matplotlib.pyplot as plt x = arange(0.,10.,0.1) # generate a range of values as an array, using begin, end, step as input y = sin(x) ll = plt.plot(x,y) # this is the simplest plotting idiom plt.show() ll = plt.plot(x,y) xl = plt.xlabel('horizontal axis') yl = plt.ylabel('vertical axis') ttl = plt.title('sine function') ax = plt.axis([-2, 12, -1.5, 1.5]) grd = plt.grid(True) txt = plt.text(0,1.3,'here is some text') ann = plt.annotate('a point on curve',xy=(4.7,-1),xytext=(3,-1.3),arrowprops=dict(arrowstyle='->')) plt.show() x = arange(0.,10,0.1) a = cos(x) b = sin(x) c = exp(x/10) d = exp(-x/10) la = plt.plot(x,a,'b-',label='cosine') lb = plt.plot(x,b,'r--',label='sine') lc = plt.plot(x,c,'gx',label='exp(+x)') ld = plt.plot(x,d,'y-', linewidth = 5,label='exp(-x)') ll = plt.legend(loc='upper left') lx = plt.xlabel('xaxis') ly = plt.ylabel('yaxis') plt.show() a = np.arange(0,3,.02) b = np.arange(0,3,.02) c = np.exp(a) d = c[::-1] fig = plt.figure() ax = fig.add_subplot(111) ax.plot(a,c,'k--',a,d,'k:',a,c+d,'k') leg = ax.legend(('Model length', 'Data length', 'Total message length'), 'upper center', shadow=True) ax.set_ylim([-1,20]) ax.grid(True) ax.set_xlabel('Model complexity --->') ax.set_ylabel('Message length --->') ax.set_title('Minimum Message Length') ax.set_yticklabels([]) ax.set_xticklabels([]) # set some legend properties. All the code below is optional. The # defaults are usually sensible but if you need more control, this # shows you how # the matplotlib.patches.Rectangle instance surrounding the legend frame = leg.get_frame() frame.set_facecolor('0.80') # set the frame face color to light gray # matplotlib.text.Text instances for t in leg.get_texts(): t.set_fontsize('small') # the legend text fontsize # matplotlib.lines.Line2D instances for l in leg.get_lines(): l.set_linewidth(1.5) # the legend line width plt.show() ### Plotting using the OO interface and setting low level parameters import matplotlib.pyplot as plt #1 figsize = (8, 5) #2 fig = plt.figure(figsize=figsize) #3 ax = fig.add_subplot(111) #4 line = ax.plot(range(10))[0] #5 ax.set_title('Plotted with OO interface') #6 ax.set_xlabel('measured') ax.set_ylabel('calculated') ax.grid(True) #7 line.set_marker('o') plt.savefig('oo.png',dpi=150) plt.show() import pandas as pd from pylab import boxplot as bp plt.figure() loansmin = pd.read_csv('../datasets/loanf.csv') data = loansmin['FICO.Score'] arrdata = np.array(data) print(data[1:3]) print("****") print(type(arrdata)) # basic plot b = bp(arrdata) import pandas as pd