下面是Matplotlib的一些主要功能: 绘图风格和类型:Matplotlib支持各种绘图风格和类型,包括线图、散点图、柱状图、饼图、等高线图、3D图等,可以根据需要选择适合的图表类型来展示和分析数据。 数据可视化:Matplotlib使得将数据转化为可视化表示变得简单,可以使用Matplotlib绘制图表来展示数据的分布、趋势、关系等,这有助于更好...
最后调用 plot3D() 方法绘制 3d 图形,代码如下: #调用 ax.plot3D创建三维线图 ax.plot3D(x, y, z, 'gray') ax.set_title('3D line plot') plt.show() 完整程序如下所示: from mpl_toolkits import mplot3d import numpy as np import matplotlib.pyplot as plt fig = plt.figure() #从三个维度...
import matplotlib.pyplot as plt import numpy as np x = np.linspace(-3, 3, 100) y1 = 2 * x + 1 y2 = x**2 plt.figure() line1, = plt.plot(x, y1, color='red', linewidth=1.0, linestyle='--') line2, = plt.plot(x, y2, color='blue', linewidth=3.0, linestyle='-') pr...
import matplotlib.pyplot as plt #导入包 fig = plt.figure() #创建空图 x_label = [1,2,3,4,5,6] #x轴的坐标 y_label = [1,3,2,3,2,6] #y轴坐标 plt.plot(x_label,y_label,color = 'r',linewidth=1.0,linestyle='--') #构建折线图,可以设置线宽,颜色属性 plt.title("line") #设置...
import matplotlib.pyplot as plt fig = plt.figure() ax = plt.axes(projection='3d') z = np.linspace(0, 1, 100) x = z * np.sin(30 * z) y = z * np.cos(30 * z) ax.plot3D(x, y, z, 'maroon') ax.set_title('3D line plot') ...
plot画线形图(子图) import numpyas np import matplotlib.pyplotas plt N =25 np.random.seed(100) x = np.linspace(0., 10., N) y = np.sin(x) **2 + np.cos(x) plt.figure(figsize=(15, 10)) rows =2 columns =2 # 定义网格子图数量 两行、两列、间隔0.25 ...
When I plot two pandas dfs together as two line charts, I get them on the same x-axis properly. When I plot one as a bar chart, however, the axis seems to be offset. ax = names_df.loc[:, name].plot(color='black') living_df.loc[:, name].plot(figsize=(12,8), ax=ax)...
import matplotlib.pyplot as plt import numpy as np x = np.linspace(-3, 3, 50) y1 = 2*x + 1 y2 = x**2 ### plt.figure(num=3, figsize=(8, 8)) # 设置图例 plt.plot(x, y2, label='up') plt.plot(x, y1, color='red', linewidth=1.0, linestyle='--', label='down') pl...
Matplotlib 可以绘制线图、散点图、等高线图、条形图、柱状图、3D 图形、甚至是图形动画等等。 matplotlib.pyplot.plot 可选参数列表 Markers 点的类型 参考 https://www.runoob.com/matplotlib/matplotlib-tutorial.html https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html...
1 mport numpy as np 2 import matplotlib.pyplot as plt 3 from mpl_toolkits.mplot3d import Axes3D 4 5 fig = plt.figure() 6 #创建3d绘图区域 7 ax = plt.axes(pro