ax.set_yticks([data_mean], minor=True) #设置y次要刻度 major_yticklabels_list = ax.set_yticklabels(yticks_label, fontdict=dict(fontsize=15)) #设置y主要刻度标签 minor_yticklabels_list = ax.set_yticklabels([str(data_mean) + '万元'], fontdict=dict(fontsize=15, color='#ff0000'), ...
.xaxis.set_ticks_position:设置x坐标刻度数字或名称的位置 .yaxis.set_ticks_position:设置y坐标刻度数字或名称的位置 .set_position:设置边框位置 x = np.linspace(-3, 3, 50) y1 = 2*x + 1 y2 = x**2 plt.figure() plt.plot(x, y2) plt.plot(x, y1, color='red', linewidth=1.0, linest...
x=[1,2,3,4,5]y1=[10,20,30,40,50]y2=[5,15,25,35,45]fig,ax1=plt.subplots()ax1.plot(x,y1,'r-')ax1.set_ylabel('Y1',color='r')ax2=ax1.twinx()ax2.plot(x,y2,'b-')ax2.set_ylabel('Y2',color='b')plt.show() Python Copy Output: 在上面的示例代码中,我们使用twiny(...
‘Set_xticks’和set_xticklabels’改变x轴刻度; ‘Set_yticks’和set_yticklabels’改变y轴刻度; Set_title '为绘图添加标题。 fig, ax = plt.subplots(1, 1) ax.plot(np.random.randn(1000).cumsum()) ticks = ax.set_xticks([0, 200, 400, 600, 800, 1000]) labels = ax.set_xticklabels(...
ax.set_yticks(np.linspace(0,1,8)) ax.set_yticklabels( ('0.60','0.65','0.70','0.75','0.80','0.85','0.90','0.95')) #显示colorbar cbar = plt.colorbar(gci) cbar.set_label('$T_B(K)$',fontdict=font) cbar.set_ticks(np.linspace(160,300,8)) ...
import matplotlib.pyplot as plt plt.axis([3,7,-0.5,3]) plt.plot(4+np.arange(3),[0,1,0],color = "blue",linewidth=4,linestyle="-") plt.show() 控制坐标轴刻度显示 有两种方法可以控制坐标轴刻度的显示,一种是利用matplotlib的面向对象的Axes.set_xticks()和Axes.set_yticks();一种是调用模...
plt.yticks(y) plt.show() 综上,可以设计一个x轴为月份,y为星期的图像: importnumpyasnpimportmatplotlib.pyplotaspltimportcalendarfromdatetimeimport* x =range(1,13,1) y =range(1,13,1) plt.plot(x,y) plt.xticks(x, calendar.month_name[1:13],color='blue',rotation=60) ...
5)#有y轴刻度线间隔ax.yaxis.set_major_locator(y_major_locator)ax.xaxis.set_major_locator(x_...
ax.yaxis.set_major_locator(ticker.NullLocator())ax.spines['right'].set_color('none')ax.spines['left'].set_color('none')ax.spines['top'].set_color('none')ax.xaxis.set_ticks_position('bottom')ax.tick_params(which='major',width=1.00,length=5)ax.tick_params(which='minor',width=0.75...
plt.yticks([-1,0,1]) # 隐藏不需要的框线 ax=plt.gca() #获取Axes对象 ax.spines['right'].set_color('none') #隐藏右边界 ax.spines['top'].set_color('none') #隐藏上边界 # 添加标题和备注信息 plt.title("使用matplotlib绘制正弦曲线",fontsize=24,color="red") plt.text(+2.5,-1.3,"...