着色3D散点图

发布于 2025-02-13 18:48:58 字数 819 浏览 3 评论 0原文

我有一个绘制3D散点图的功能，它可以正常工作，但是我看不出如何根据条件为特定数据点给出颜色：

在以下代码中，我绘制了3个功能； NbactionsD30，AvgactionsMonth和Actionhr。

数据点给出特定的颜色

我想为actionshr值＆gt; = 50函数的参数为f1，f2，f3的。数据是数据框其中包含功能。

这是我函数的代码：

def plot3D(f1, f2, f3, data):

%matplotlib widget
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt

xs = data[f1]
ys = data[f2]
zs = data[f3]

fig = plt.figure()
ax = Axes3D(fig)

plot = ax.scatter(xs, ys, zs, s=50, color = 'blue', edgecolors = "white")
ax.set_xlabel(f1)
ax.set_ylabel(f2)
ax.set_zlabel(f3)
plt.show()

plot3D("avgActionsMonth", "nbActionsD30", "actionSHR", data)

原文

I have a function to plot 3D scatter plots, it works fine but I don't see how I can give a color to specific data points based on a condition for example:

in The following code I am plotting 3 features; nbActionsD30, avgActionsMonth and actionSHR.

I want to give a specific color to the data points where actionsSHR value >= 50

the parameters of the function are f1, f2, f3 the feature names. data is the dataframe
that contains the features.

here is my function's code :

def plot3D(f1, f2, f3, data):

%matplotlib widget
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt

xs = data[f1]
ys = data[f2]
zs = data[f3]

fig = plt.figure()
ax = Axes3D(fig)

plot = ax.scatter(xs, ys, zs, s=50, color = 'blue', edgecolors = "white")
ax.set_xlabel(f1)
ax.set_ylabel(f2)
ax.set_zlabel(f3)
plt.show()

plot3D("avgActionsMonth", "nbActionsD30", "actionSHR", data)

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第七度阳光i 2025-02-20 18:48:58

import matplotlib.pyplot as plt
import numpy as np

fig, ax = plt.subplots(subplot_kw=dict(projection="3d"))
x, y, z = np.random.normal(size=(3, 1000))
ax.scatter(x, y, z, c=z>1)
plt.show()

给出

import matplotlib.pyplot as plt
import numpy as np

fig, ax = plt.subplots(subplot_kw=dict(projection="3d"))
x, y, z = np.random.normal(size=(3, 1000))
ax.scatter(x, y, z, c=z>1)
plt.show()

gives