matplotlib绘制三维散点图

１．只有一种点的散点图

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D  # 空间三维画图


# 数据
data = np.arange(24).reshape((8, 3))
# data的值如下：
# [[ 0  1  2]
#  [ 3  4  5]
#  [ 6  7  8]
#  [ 9 10 11]
#  [12 13 14]
#  [15 16 17]
#  [18 19 20]
#  [21 22 23]]
x = data[:, 0]  # [ 0  3  6  9 12 15 18 21]
y = data[:, 1]  # [ 1  4  7 10 13 16 19 22]
z = data[:, 2]  # [ 2  5  8 11 14 17 20 23]


# 绘制散点图
fig = plt.figure()
ax = Axes3D(fig)
ax.scatter(x, y, z)


# 添加坐标轴(顺序是Z, Y, X)
ax.set_zlabel('Z', fontdict={'size': 15, 'color': 'red'})
ax.set_ylabel('Y', fontdict={'size': 15, 'color': 'red'})
ax.set_xlabel('X', fontdict={'size': 15, 'color': 'red'})
plt.show()

三维图散点图如下：

2.有多种点及图例的散点图

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D  # 空间三维画图


# 数据

# 数据１
data1 = np.arange(24).reshape((8, 3))
# data的值如下：
# [[ 0  1  2]
#  [ 3  4  5]
#  [ 6  7  8]
#  [ 9 10 11]
#  [12 13 14]
#  [15 16 17]
#  [18 19 20]
#  [21 22 23]]
x1 = data1[:, 0]  # [ 0  3  6  9 12 15 18 21]
y1 = data1[:, 1]  # [ 1  4  7 10 13 16 19 22]
z1 = data1[:, 2]  # [ 2  5  8 11 14 17 20 23]

# 数据２
data2 = np.random.randint(0, 23, (6, 3))
x2 = data2[:, 0]
y2 = data2[:, 1]
z2 = data2[:, 2]


# 绘制散点图
fig = plt.figure()
ax = Axes3D(fig)
ax.scatter(x1, y1, z1, c='r', label='顺序点')
ax.scatter(x2, y2, z2, c='g', label='随机点')


# 绘制图例
ax.legend(loc='best')


# 添加坐标轴(顺序是Z, Y, X)
ax.set_zlabel('Z', fontdict={'size': 15, 'color': 'red'})
ax.set_ylabel('Y', fontdict={'size': 15, 'color': 'red'})
ax.set_xlabel('X', fontdict={'size': 15, 'color': 'red'})


# 展示
plt.show()

图：

matplotlib绘制三维散点图

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