ax.set_title('3D Scatter Plot with Two Points') ax.legend() plt.show() Output: This code creates a 3D scatter plot with two points: Amr (red) and Fatma (blue). The points are positioned at (1, 2, 3) and (4, 5, 6
>>> import matplotlib.pyplot Traceback (most recent call last): File "D:\python\Lib\site-packages\matplotlib\font_manager.py", line 1353, in <module> fontManager = json_load(_fmcache) File "D:\python\Lib\site-packages\matplotlib\font_manager.py", line 888, in json_load with open(...
Parameter 1 is an array containing the points on thex-axis. Parameter 2 is an array containing the points on they-axis. If we need to plot a line from (1, 3) to (8, 10), we have to pass two arrays [1, 8] and [3, 10] to the plot function. ...
caplines: 一个 Line2D 实例的元组,表示误差棒帽。 barlinecols: 一个包含水平和垂直误差范围的 LineCollection 元组。 其他参数通过 **kwargs 接收,并传递给绘制标记的 plot 调用。例如,可以通过这种方式定制标记的属性,如大小、颜色等。 连续误差线 from sklearn.gaussian_process import GaussianProcessRegressor ...
import numpy as np import matplotlib.pyplot as plt from matplotlib.animation import FuncAnimation # 创建图形和轴 fig, ax = plt.subplots() x = np.linspace(0, 2 * np.pi, 100) line1, = ax.plot(x, np.sin(x), label='sin(x)') line2, = ax.plot(x, np.cos(x), label='cos(x)...
(0, 2*np.pi, 0.01) line, =ax.plot(x, np.sin(x)) def animate(i): line.set_ydata(np.sin(x+i/10)) return line, def init(): line.set_ydata(np.sin(x)) return line, # 生成动画 ''' 函数FuncAnimation(fig,func,frames,init_func,interval,blit)是绘制动图的主要函数,其参数如下:...
2.用 plot 方法画出 x=(0,10)间 sin 的图像 3.用点加线的方式画出 x=(0,10)间 sin 的图像 4.用 scatter 方法画出 x=(0,10)间 sin 的点图像 5.用饼图的面积及颜色展示一组 4 维数据 6.绘制一组误差为 ±0.8 的数据的误差条图 7.绘制一个柱状图 8.绘制一个水平方向柱状图 ...
from mpl_toolkits import mplot3d fig = plt.figure() ax = plt.axes(projection='3d') 代码语言:javascript 代码运行次数:0 运行 AI代码解释 ax = plt.axes(projection='3d') # Data for a three-dimensional line zline = np.linspace(0, 15, 1000) xline = np.sin(zline) yline = np.cos(...
Continuing my series on using matplotlib and python to generate figures, I’d like to get now to the meat of the topic: actually making a figure or two. I’ll be starting with the simplest kind of figure: a line plot, with points plotted on an X-Y Cartesian plane. What Kind of Dat...
plotNum:选中当前要操作的区域。 第6章 数据可视化工具——Matplotlib Python数据分析基础教程(第2版) Matplotlib 概述 Matplotlib 参数配置 分析变量间关系 分析变量数据分布和分散状况 项目实践 本章小结 创建子图 subplot()函数的作用是将整个绘图区域等分为 numRows × numCols 个子区域,然后按照从左到右、...