Create a new Axes instance with an invisible x-axis and an independent y-axis positioned opposite to the original one (i.e. at right). The x-axis autoscale setting will be inherited from the original Axes. 大意就是使用这个函数,在原来的坐标系中新建一个共享x轴的双胞胎坐标系,类似的还有twin...
fig,ax = plt.subplots() #add first line to plot ax.plot(df1.year, df1.sales, color=col1) #add x-axis label ax.set_xlabel('Year', fontsize=14) #add y-axis label ax.set_ylabel('Sales', color=col1, fontsize=16) #define second y-axis that shares x-axis with current plot ax...
# subplots are used to create multiple plots in a single figure# let’s create a single subplot first following by adding more subplotsx = np.random.rand(50)y = np.sin(x*2)#need to create an empty figure with an axis as below, figure and axis are two separate objects in matplotlibf...
plt.plot(x, np.sin(x)) plt.xlim(10,0) plt.ylim(1.2,-1.2); 相关的函数还有plt.axis()(注意:这不是plt.axes()函数,函数名称是 i 而不是 e)。这个函数可以在一个函数调用中就完成 x 轴和 y 轴范围的设置,传递一个[xmin, xmax, ymin, y...
# Move the bar to the right on the x-axis so it doesn't # overlap with previously drawn ones ax.bar(x_data + alteration[i], y_data_list[i], color = colors[i], label = y_data_names[i], width = ind_width) ax.set_ylabel(y_label) ...
plt.plot(data,'k--', label='Default') plt.plot(data,'k-', drawstyle='steps-post', label='steps') plt.legend(loc='best') <matplotlib.legend.Legendat0x28e781103c8> ### Ticks, labels, and legends ### Setting the title, axis labels, ticks, and ticklabels fig...
1plt.plot(x_values, y_values, 'xr') 1. 重新运行程序,效果如下图所示。 可能大家已经注意到了,1和10对应的‘x’记号在图形边角的位置不太明显,要解决这个问题可以通过添加下面的代码调整x轴和y轴的坐标范围。 1plt.axis([0, 12, 0, 120]) ...
(16, 9)) ax.bar(df['Dates'], df['Score'], color='blue', width=2) date_form = DateFormatter("%d/%m/%Y") ax.xaxis.set_major_formatter(date_form) ax.xaxis.set_major_locator(mdates.DayLocator(interval=1)) ax2=ax.twinx() ax2.plot(df['Dates'], df['Price'], color = '...
matplotlib.pyplot as plt # 生成随机数据 x = np.random.rand(50) y = np.random.rand(50) # 绘制散点图 plt.scatter(x, y, color='blue', alpha=0.5) # 设置标题和坐标轴标签 plt.title('Scatter Plot of Random Data') plt.xlabel('X Axis') plt.ylabel('Y Axis') # 显示图表 plt.show(...
之前,在plot()的第三个参数中,用r可以表示红色,g表示绿色,b表示蓝色,这里列举一些常用的颜色字符代表: b 蓝色 g 绿色 r 红色 c 蓝绿色 m 洋红 y 黄色 k 黑色 w 白色 将上图中的x轴变成π的倍数 x=np.arange(-2*np.pi,2*np.pi,0.01)y=np.sin(3*x)/xy2=np.sin(2*x)/xy3=np.sin(1*x...