importmatplotlib.pyplotaspltdefplot_with_double_y():x=[1,2,3,4,5]y1=[10,20,25,30,40]y2=[100,200,300,400,500]fig,ax1=plt.subplots()ax1.set_xlabel('X data')ax1.set_ylabel('Y1 data',color='tab:blue')ax1.plot(x,y1,
double_y geom_line(aes(y=temperature), size=1.5, color=temperatureColor) + geom_line(aes(y=price / coeff), size=1.5, color=priceColor) + #设置双轴关键代码 scale_y_continuous( # first axis name name = "Temperature (C°)", # 定制化设置第二个图例属性 sec.axis = sec_axis(trans = ~...
x = np.arange(0., np.e, 0.01) y1 = np.exp(-x) y2 = np.log(x) fig = plt.figure() ax1 = fig.add_subplot(111) ax1.plot(x, y1) ax1.set_ylabel('Y values for exp(-x)') ax1.set_title("Double Y axis") ax2 = ax1.twinx() # this is the important function ax2.plot...
ylabel('Y values for exp(-x)')ax1.set_title("Double Y axis")ax2 = ax1.twinx() # this is the important function ax2.plot(x, y2, 'r')ax2.set_xlim([0, np.e])ax2.set_ylabel('Y values for ln(x)')ax2.set_xlabel('Same X for both exp(-x) and ln(x)')plt.show()
plt.tick_params(axis='x',labelsize=8)# 设置x轴标签大小 plt.bar(df['sport_type'],df['score']) 绘图结果: 方法三:横纵颠倒 只要我们将纵向柱状图改成横向柱状图,那么就不会存在这种问题。 代码语言:javascript 代码运行次数:0 运行 AI代码解释 ...
ax.xaxis.set_minor_locator(x_minor_locator)ax.xaxis.set_major_locator(x_major_locator) 刻度形式操作 代码语言:javascript 代码运行次数:0 运行 AI代码解释 ax.tick_params(axis='y',direction='in',labelsize=8,length=3.5)ax.tick_params(axis='x',which="major",direction='in',bottom=False,label...
1importmatplotlib.pyplot as plt2importnumpy as np34x = np.arange(3,8,1)#x轴数据5y1 = x*26y2 = x**27plt.figure(figsize=(5,3.5))8plt.plot(x, y1,'r',marker='o',label='y1:double x')#关键句,前两个参数是X、Y轴数据,其他参数指定曲线属性,如标签label,颜色color,线宽linewidth或lw...
The first value is the x-axis position, and the second value is the y-axis position. Code Example import matplotlib.pyplot as plt from drawarrow import fig_arrow fig, ax = plt.subplots() fig_arrow( tail_position=[0.3, 0.3], head_position=[0.8, 0.8] ) plt.show() ...
Matplotlib柱状图标签重叠问题的解决方案 参考:matplotlib bar chart labels overlap Matplotlib是Python中最流行的数据可视化库之一,它提供了强大的工具来创建各种类型的图表,包括柱状图。然而,在创建柱状图时,经常会遇到标签重叠的问题,特别是当数据点较多或标签
plt.axis([-1,2,-1,2]) plt.show() 效果图展示 Note: 设置直线相应位置的值显示:plt.text(max_x, 0, str(round(max_x, 2)))。也就是直接在指定坐标写文字。不知道有没有其他方法? [matplotlib.pyplot.axhline] 另一种绘制直线的方式