Exercise 1: A glimpse into the financial ratios of some industriesExercise 2: Using margins in pivot tables and making a bar plotExercise 3: Preparing data for a facet grid plot Exercise 4: Making a facet grid
# Make the plot. myplot = pd.DataFrame({'欧文': [1,2,3], '比尔': [1,2,3]}).plot(x='欧文') # Show the plot. plt.show()
If you make multiple lines with one plot call, the kwargs apply to all those lines. 下面是可用的 Line2D 属性列表: 也可以看看 散点 XY 散点 plot 带有大小和/或颜色不同的标记 ( 有时也称为气泡图). 注释 Format Strings 格式化字符串 A format string consists of a part for color, marker an...
p1.plot(x,y,label="sinx",marker='o') plt.legend(loc='best') plt.grid(c='r',linestyle=':') p2=huaban.add_subplot(222) x1=np.linspace(-np.pi*2,np.pi*2,1000) y1=np.sin(x1) p2.plot(x1,y1,label="sinx",color='blue') plt.legend(loc='best') plt.grid(c='b',linestyle=...
linspace(1, 4, 300) a_BSpline = interpolate.make_interp_spline(x, y) y_new = a_BSpline(x_new) ax[1].plot(x_new, y_new) 箱形图 箱线图是查看数据分布方式的好方法。 顾名思义,它有一个盒子。盒子的一端位于数据的第 25个百分位。第25个百分位数是绘制的线,其中 25% 的数据点位于...
fig = plt.figure() ax = fig.gca(projection='3d') # Makedata. X = np.arange(-5, 5, 0.25) Y = np.arange(-5, 5, 0.25) X, Y = np.meshgridX, Y) R = npsqrt(X**2 + Y**2) Z = np.sin(R # Plot the surface. surf = ax.plotsurface(X, Y, Z, cmap=cm...
(shapley_values_rf)shap.summary_plot(shapley_values_rf,plot_type="bar")### 导入SHAPfromsklearn.preprocessingimportStandardScalerfromsklearn.neural_networkimportMLPRegressorfromsklearn.pipelineimportmake_pipelinenn=make_pipeline(StandardScaler(),MLPRegressor(hidden_layer_sizes=(5,),activation='logistic',max...
( title=go.layout.Title(text="Election results", x=0.5), yaxis_title="Seats", xaxis_tickmode="array", xaxis_tickvals=list(range(27)), xaxis_ticktext=tuple(df['year'].values), ) # Make the multi-bar plot fig = go.Figure(data=bar_plots, layout=layout) # Tell Plotly to render...
# Compute z to make the pringle surface. z = np.sin(-x*y) fig = plt.figure() ax = fig.gca(projection='3d') ax.plot_trisurf(x, y, z, linewidth=0.2, antialiased=True) plt.show() 七、等高线(Contour plots) 基本用法: 1 ax.contour(X, Y, Z, *args, **kwargs) code: 1 2...
plt.plot([10,20,30]) plt.xlabel('tiems') plt.ylabel('numbers') plt.show() 测试: 2.饼图: #!/usr/bin/env python# -*- coding: utf-8 -*-frompylabimport*# make a square figure and axesfigure(1, figsize=(6,6)) ax = axes([0.1,0.1,0.8,0.8]) ...