Python之科学计算模块学习

以下为学习科学计算模块时的一些代码（回顾学习时参考）：

# -*- coding: utf-8 -*-"""Created on Fri Jun 30 13:32:27 2017@author: Administrator"""import pandas as pdimport numpy as npimport matplotlib.pyplot as plt#定义资料集df1 = pd.DataFrame(np.ones((3,4))*0,columns=['a','b','c','d'])df2 = pd.DataFrame(np.ones((3,4))*1,columns=['a','b','c','d'])df3 = pd.DataFrame(np.ones((3,4))*2,columns=['a','b','c','d'])#contact纵向合并res1 = pd.concat([df1,df2,df3],axis=0)print(res1)#======================================================df4 = pd.DataFrame(np.ones((3,4))*0,columns=['a','b','c','d'],index=[1,2,3])df5 = pd.DataFrame(np.ones((3,4))*1,columns=['b','c','d','e'],index=[2,3,4])#join,['inner','outer']  默认为outer#res = pd.concat([df1,df2])res2 = pd.concat([df4,df5],join='inner',ignore_index=True)print(res2)#======================================================df1 = pd.DataFrame(np.ones((3,4))*0,columns=['a','b','c','d'],index=[1,2,3])df2 = pd.DataFrame(np.ones((3,4))*1,columns=['a','b','c','d'])df3 = pd.DataFrame(np.ones((3,4))*1,columns=['b','c','d','e'],index=[2,3,4])res = df1.append(df2,ignore_index=True)res = df1.append([df2,df3])s1 =pd.Series([1,2,3,4],index=['a','b','c','d'])#res = df1.append(s1,ignore_index=True)print(res)#======================================================A = np.array([1,1,1])B = np.array([2,2,2])C = np.vstack((A,B))  #Vertical stack    上下合并D = np.hstack((A,B))  #horziontal stack  左右合并（序列）print(D)print(A.shape,D.shape)print(A.T.shape)print(A[np.newaxis,:].shape)   #在行上加了一个维度print(A[:,np.newaxis].shape)   #在纵向加了维度A = np.array([1,1,1])[:,np.newaxis]B = np.array([2,2,2])[:,np.newaxis]print(np.vstack((A,B)))print(np.hstack((A,B)))C = np.concatenate((A,B,B,A),axis=1)print(C)#======================================================A = np.arange(12).reshape((3,4))print(A)B = np.split(A,3,axis=0)print(B)print(np.vsplit(A,3))print(np.hsplit(A,2))#======================================================left = pd.DataFrame({'key1':['K0','K0','K1','K2'],                     'key2':['K0','K1','K0','K1'],                     'A':['A0','A1','A2','A3'],                     'B':['B0','B1','B2','B3']})right = pd.DataFrame({'key1':['K0','K1','K1','K2'],                      'key2':['K0','K0','K0','K0'],                     'C':['C0','C1','C2','C3'],                     'D':['D0','D1','D2','D3']})print(left)print(right)res = pd.merge(left,right,on=['key1','key2'],how='outer')print(res)#======================================================df1 = pd.DataFrame({'coll':[0,1],                     'col_left':['a','b']})df2 = pd.DataFrame({'coll':[1,2,2],                     'col_right':[2,2,2]})print(df1)print(df2)#res = pd.merge(df1,df2,on='coll',how='outer',indicator=True)res = pd.merge(df1,df2,on='coll',how='outer',indicator='indicator_column')print(res)#======================================================#plot data#Seriesdata = pd.Series(np.random.randn(1000),index=np.arange(1000))data = data.cumsum()#DataFramedata = pd.DataFrame(np.random.randn(1000,4),index=np.arange(1000),columns=list('ABCD'))data = data.cumsum()print(data.head())#plot methods:#'bar','hist','box','kde','area','hexbin','pie'#data.plot()ax = data.plot.scatter(x='A',y='B',color='Red',label='Class 1')data.plot.scatter(x='A',y='C',color='DarkGreen',label='Class 2',ax=ax)plt.show()#matplotlibx = np.linspace(-3,3,50)y1 = 2*x + 1y2 = x**2plt.figure()plt.plot(x,y1)plt.figure(3,figsize=(4,3))plt.plot(x,y2)plt.plot(x,y1,color='red',linewidth=5.0,linestyle='--')plt.show()#======================================================x = np.linspace(-3,3,50)y1 = 2*x + 1y2 = x**2plt.figure(3,figsize=(4,3))l1, = plt.plot(x,y2,label='up')l2, = plt.plot(x,y1,color='red',linewidth=1.0,linestyle='--',label='down')plt.xlim((-1,2))plt.ylim((-2,3))plt.xlabel('I am x')plt.ylabel('I am y')plt.legend(handles=[l1,l2],labels=['aaa','bbb'],loc='best')new_ticks = np.linspace(-1,2,5)#print(new_ticks)plt.xticks(new_ticks)plt.yticks([-2,-1.8,-1,1.22,3],           [r'$really\ bad$',r'$bad$',r'$normal$',r'$good$',r'$really\ good$'])#gca = 'get current axis'ax = plt.gca()ax.spines['right'].set_color('none')ax.spines['top'].set_color('none')ax.xaxis.set_ticks_position('bottom')ax.yaxis.set_ticks_position('left')ax.spines['bottom'].set_position(('data',0))  # outward,axesax.spines['left'].set_position(('data',0))x0 = 1y0 = 2*x0 + 1plt.scatter(x0,y0,s=50,color='b')plt.plot([x0,x0],[y0,0],'k--',lw=2.5)#method 1plt.annotate(r'$2x+1=%s$'%y0,xy=(x0,y0),xycoords='data',xytext=(+30,-30),textcoords='offset points',fontsize=16,arrowprops=dict(arrowstyle='->',connectionstyle='arc3,rad=.2'))#method 2plt.text(-3.7,3,r'$This\ is\ the\ some\ text$',fontdict={'size':16,'color':'r'})plt.show()#======================================================x = np.linspace(-3,3,50)y = 0.5*x + 1plt.figure()plt.plot(x,y,linewidth=10)plt.ylim((-2,2))#gca = 'get current axis'ax = plt.gca()ax.spines['right'].set_color('none')ax.spines['top'].set_color('none')ax.xaxis.set_ticks_position('bottom')ax.yaxis.set_ticks_position('left')ax.spines['bottom'].set_position(('data',0))  # outward,axesax.spines['left'].set_position(('data',0))for label in ax.get_xticklabels() + ax.get_yticklabels():    label.set_fontsize(12)    label.set_bbox(dict(facecolor='white',edgecolor='None',alpha=0.7))plt.show()#======================================================n = 1024X = np.random.normal(0,1,n)Y = np.random.normal(0,1,n)T = np.arctan2(Y,X)#plt.scatter(X,Y,s=75,c=T,alpha=0.5)plt.scatter(np.arange(5),np.arange(5))#plt.xlim((-1.5,1.5))#plt.ylim((-1.5,1.5))plt.xticks(())plt.yticks(())plt.show()#======================================================n = 12X = np.arange(n)Y1 = (1-X/float(n))*np.random.uniform(0.5,1.0,n)Y2 = (1-X/float(n))*np.random.uniform(0.5,1.0,n)plt.bar(X,+Y1,facecolor='#9999ff',edgecolor='white')plt.bar(X,-Y2,facecolor='#ff9999',edgecolor='white')for x,y in zip(X,Y1):    #ha:hoeizontal alignment    plt.text(x+0.4,y+0.05,'%.2f'%y,ha='center',va='bottom')for x,y in zip(X,Y2):    #ha:hoeizontal alignment    plt.text(x+0.4,-y-0.05,'-%.2f'%y,ha='center',va='top')plt.xlim((-.5,n))plt.ylim((-1.5,1.5))plt.xticks(())plt.yticks(())plt.show()#======================================================def f(x,y):    return (1 - x/2 + x**5 + y**3) * np.exp(-x**2 - y**2)n = 256x = np.linspace(-3,3,n)y = np.linspace(-3,3,n)X,Y = np.meshgrid(x,y)plt.contourf(X,Y,f(X,Y),8,alpha=0.75,cmap=plt.cm.hot)C = plt.contour(X,Y,f(X,Y),8,colors='black',linewidth=.5)plt.clabel(C,inline=True,fontsize=10)plt.xticks(())plt.yticks(())plt.show()#======================================================a = np.array([0.313660827978, 0.365348418405, 0.423733120134,              0.365348418405, 0.439599930621, 0.525083754405,              0.423733120134, 0.525083754405, 0.651536351379]).reshape(3,3)plt.imshow(a,interpolation='nearest',cmap='bone',origin='upper')plt.colorbar(shrink=.92)plt.xticks(())plt.yticks(())plt.show()#======================================================fig = plt.figure()ax = Axes3D(fig)x = np.arange(-4,4,0.25)y = np.arange(-4,4,0.25)X,Y = np.meshgrid(x,y)R = np.sqrt(X**2 + Y**2)Z = np.sin(R)ax.plot_surface(X,Y,Z,rstride=1,cstride=1,cmap=plt.get_cmap('rainbow'))ax.contourf(X,Y,Z,zdir='z',offset=-2,cmap='rainbow')ax.set_zlim(-2,2)plt.show()#======================================================plt.figure()plt.subplot(2,1,1)plt.plot([0,1],[0,1])plt.subplot(2,3,4)plt.plot([0,1],[0,2])plt.subplot(235)plt.plot([0,1],[0,3])plt.subplot(236)plt.plot([0,1],[0,4])plt.show()#======================================================import numpy as npplt.figure()ax1 = plt.subplot2grid((3,3),(0,0),colspan=3,rowspan=1)ax1.plot([1,2],[1,2])ax1.set_title('ax1_title')ax2 = plt.subplot2grid((3,3),(1,0),colspan=2,rowspan=1)ax2.plot(np.sin(np.arange(0,2*np.pi,0.01)))ax3 = plt.subplot2grid((3,3),(1,2),colspan=2,rowspan=1)ax4 = plt.subplot2grid((3,3),(2,0))ax5 = plt.subplot2grid((3,3),(2,1))ax6 = plt.subplot2grid((3,3),(2,2))plt.tight_layout()plt.show()#======================================================import matplotlib.gridspec as gridspecplt.figure()gs = gridspec.GridSpec(3,3)ax1 = plt.subplot(gs[0,:])ax2 = plt.subplot(gs[1,:2])ax3 = plt.subplot(gs[1,-1])ax4 = plt.subplot(gs[2,0])ax5 = plt.subplot(gs[2,1])ax6 = plt.subplot(gs[2,2])plt.tight_layout()plt.show()#======================================================f,((ax11,ax12),(ax21,ax22)) = plt.subplots(2,2,sharex=True,sharey=True)ax11.scatter([1,2],[1,2])plt.tight_layout()plt.show()#======================================================from matplotlib import pyplot as pltfig = plt.figure()x = [1,2,3,4,5,6,7]y = [1,3,4,2,5,8,6]left, bottom, width, height = 0.1, 0.1, 0.8, 0.8ax1 = fig.add_axes([left, bottom, width, height])ax1.plot(x, y, 'r')ax1.set_xlabel('x')ax1.set_ylabel('y')ax1.set_title('title')left, bottom, width, height = 0.2, 0.6, 0.25, 0.25ax2 = fig.add_axes([left, bottom, width, height])ax2.plot(y, x, 'b')ax2.set_xlabel('x')ax2.set_ylabel('y')ax2.set_title('title inside 1')plt.axes([0.6, 0.2, 0.25, 0.25])plt.plot(y[::-1], x, 'g') # 注意对y进行了逆序处理plt.xlabel('x')plt.ylabel('y')plt.title('title inside 2')plt.show()#======================================================x = np.arange(0,10,0.1)y1 = 0.05*x**2y2 = -1*y1fig,ax1 = plt.subplots()ax2 = ax1.twinx()ax1.plot(x, y1, 'g-')   # green, solid lineax1.set_xlabel('X data')ax1.set_ylabel('Y1 data', color='y')ax2.plot(x, y2, 'b-') # blueax2.set_ylabel('Y2 data', color='r')plt.show()