#y = 2x + 5x = np.arange(1,11)#x的值y = 2 * x + 5#y的值plt.title("Matplotlib demo")#图的标题plt.xlabel("x axis caption")#x轴的名称plt.ylabel("y axis caption")#y轴的名称plt.plot(x,y)#画图plt.show()#显示#结果 #2.绘制抛物线x = np.arange(-np.pi,np.pi,0.5)#np.pi...
ax2.xaxis.set_major_locator(MaxNLocator(11))xticks = pylab.setp(ax2, xticklabels=['0','10','20','30','40','50','60','70','80','90','100'])ax2.xaxis.grid(True, linestyle='--', which='major', color='grey',alpha=0.25)Plot a solid vertical gridline to ...
x = [1, 2, 3, 4, 5]# Make an array of x values y = [1, 4, 9, 16, 25]# Make an array of y values for each x value pl.plot(x, y)# use pylab to plot x and y pl.title(’Plot of y vs. x’)# give plot a title pl.xlabel(’x axis’)# make axis labels pl.yla...
先创建一个子图并获得其X轴对象axis: Fig, ax = plt.subplots() axis = ax.xaxis 获得axis对象的刻度位置的列表: Axis.get_ticklocs() 获得axis对象的刻度标签以及标签中的文字: axis.get_ticklabels() #获得刻度标签的列表 [x.get_text() for x in axis.get_ticklabels()] 获得轴上表示主刻度线的...
plot(x, np.sin(x - i * np.pi / 2), styles[i], color='black') ax.axis('equal') # Specify the lines and labels of the first legend ax.legend(lines[:2], ['line A', 'line B'], loc='upper right') # Create the second legend and add the artist manually from matplotlib....
foritemin([ax_main.xaxis.label, ax_main.yaxis.label] + ax_main.get_xticklabels + ax_main.get_yticklabels): item.set_fontsize(14) xlabels = ax_main.get_xticks.tolist ax_main.set_xticklabels(xlabels) plt.show 7.边缘箱形图 ...
3. config_axis(self) 4. draw_all(self) 5. get_ticks(self, minor=False) 6. minorticks_off(self) 7. minorticks_on(self) 8. remove(self) 9. set_alpha(self, alpha) 10. set_label(self, label, **kw) 11. set_ticklabels(self, ticklabels, update_ticks=True) ...
autofmt_xdate() :auto formate the dates at x-axis. ” Vertical line on datetime plot “ Read:Matplotlib best fit line Matplotlib draw vertical line between two points Here we are going to learn how we draw a vertical line between two points or data markers. ...
等高线图可以用 plt.contour 来创建。它需要三个参数: x 轴、y 轴和 z 轴三个坐标轴的网格数据,x 轴和 y 轴表示图形中的位置,而 z 轴通过等高线的等级来表示。用 np.meshgrid 函数来准备这些数据可能是最简单的方法,它可以从一维数组构建二维网格数据:...
Axis实例的set_xlabel和set_ylabel方法可以设置轴标签。这两个函数可以接受其他参数用于设置文本属性。可选参数labelpad可以设置轴与标签之间的距离(以磅为单位)。set_title方法的loc参数可以赋值为’left’、‘centered’、‘right’,用于设置标题的对齐方式。