fig,ax=plt.subplots()x=np.linspace(0,10,100)y=np.exp(x)ax.plot(x,y,label='exp(x)')ax.set_xlim(0,5)ax.set_ylim(0,100)ax.set_title('Setting limits with Axes object - how2matplotlib.com')ax.legend()plt.show() Python Copy Output: 在这个示例中,我们首先创建了一个Figure和Axes对...
我们可以使用set_xticklabels()和set_yticklabels()函数来设置坐标轴的刻度标签。下面是一个示例代码: importmatplotlib.pyplotaspltimportnumpyasnp x=np.linspace(0,10,100)y=np.sin(x)plt.plot(x,y)plt.xticks([0,5,10],['起始','中间','结束'])plt.yticks([-1,0,1],['最小','中间','最...
x = np.linspace(-3, 3, 20) y1 = 2*x + 1 y2 = x**2 plt.figure() #set x limits plt.xlim((-1, 2)) plt.ylim((-2, 3)) # set new sticks new_sticks = np.linspace(-1, 2, 5) plt.xticks(new_sticks) # set tick labels plt.yticks([-2, -1.8, -1, 1.22, 3], [r...
# Create the figure and the axesfig, ax = plt.subplots()# Plot the data and get the averagedtop_10.plot(kind='barh', y="Sales", x="Name", ax=ax)avg = top_10['Sales'].mean()# Set limits and labelsax.set_xlim([-10000,140000])ax.set(title='2014 Revenue', xlabel='Total ...
# set x limits 设置x y的范围 plt.xlim((-1, 2)) plt.ylim((-2, 3)) plt.xlabel('I am x')# x y 的label plt.ylabel('I am y') # set new sticks #设置新的刻度 new_ticks = np.linspace(-1, 2, 5) print(new_ticks)
Add an entry to a dictionary of boolean flags that are set to True when the mappable is changed. autoscale(self)[source] Autoscale the scalar limits on the norm instance using the current array autoscale_None(self)[source] Autoscale the scalar limits on the norm instance using the current...
importnumpyasnpimportmatplotlib.pyplotasplt# Create a figure of size 8x6 inches, 80 dots per inchplt.figure(figsize=(8,6),dpi=80)# Create a new subplot from a grid of 1x1plt.subplot(1,1,1)# Set x limitsplt.xlim(-4.0,4.0)# Set x ticksplt.xticks(np.linspace(-4,4,9...
matplotlib所绘制的图表的每个组成部分都和一个对象对应,我们可以通过调用这些对象的属性设置方法set_*()或者pyplot模块的属性设置函数setp()设置它们的属性值。 因为matplotlib实际上是一套面向对象的绘图库,因此也可以直接获取对象的属性 配置文件 绘制一幅图需要对许多对象的属性进行配置,例如颜色、字体、线型等等。我...
使用.spines设置边框:y轴;使用.set_position设置边框位置:x=0的位置;(位置所有属性:outward,axes,data) 使用plt.show显示图像. legend图例 importmatplotlib.pyplot as pltimportnumpy as np x= np.linspace(-3, 3, 50) y1= 2*x + 1y2= x**2plt.figure()#set x limitsplt.xlim((-1, 2)) ...
top_10.plot(kind='barh', y="Sales", x="Name", ax=ax) ax.set_xlim([-10000, 140000]) ax.set(title='2014 Revenue', xlabel='Total Revenue', ylabel='Customer') formatter = FuncFormatter(currency) ax.xaxis.set_major_formatter(formatter) ax.legend().set_visible(False) 这张图美观多了...