使用Jupyter笔记本时，情节不显示正确的颜色

发布于 2025-02-09 12:21:37 字数 1769 浏览 2 评论 0原文

对于我的数据集，我想更改3D散点图中显示的“标签”数据的颜色，但是我没有成功。

我不断获得这些默认颜色：

这是我使用的代码：

import numpy as np
import os
import pandas as pd
from matplotlib import pyplot
import matplotlib.pyplot as plt
import plotly.express as px
import seaborn as sns

# Data
data = pd.read_csv('SamplePlotlyData.csv')
labels = data['Label'].values
data = data.drop(columns=['Label']).values

fig = px.scatter_3d(data,
            x= data[:,0], y= data[:,1], z = data[:,2], 
            labels={'x':'PCA-1', 'y':'PCA-2','z':'PCA-3'},
            color=labels,
            color_discrete_sequence=["blue", "goldenrod", "magenta"],
            title='3d Plot of Top 3 PCA components')
fig.show()

您能否帮助我正确更改3D散点图的调色板？

我正在使用Jupyter笔记本6.0.3，带有Seaborn版本0.11.2

这是我的数据集：

36  37  38  39  Label
0.22717583  -0.1028256  -0.041157354    0.047657568 0
-1.242205   2.611936    1.5563084   -0.64137465 0
0.39261582  0.40208274  0.2835228   0.26541463  0
-4.296567   -1.3980201  -0.67690927 -0.941123   0
-1.5278594  1.103121    -1.4688232  -1.139884   0
2.35497 -1.3783572  0.4808609   -1.4851115  1
-0.055658106    -0.19007513 -0.40134305 -0.34722504 1
0.051404    -0.6016376  0.26404122  -0.42829922 1
-0.47935575 -0.049984064    0.67335206  0.123305336 1
0.57357675  0.9523434   -0.05714764 -0.6305638  1
0.1044371   1.2541072   0.1957058   0.083972946 2
0.47575372  0.18598396  0.069036044 0.63252586  2
-0.7613742  0.81920165  0.43508404  0.280004    2
-0.16776349 0.9296196   -1.1710609  0.86310846  2
-0.20844702 0.3536006   0.01729327  -0.28363776 2

原文

For my dataset, I wanted to change the colors of the "Labels" data that is shown in the 3d scatter plot, but I have been unsuccessful.

I keep getting these default colors:

This is the code that I am using:

import numpy as np
import os
import pandas as pd
from matplotlib import pyplot
import matplotlib.pyplot as plt
import plotly.express as px
import seaborn as sns

# Data
data = pd.read_csv('SamplePlotlyData.csv')
labels = data['Label'].values
data = data.drop(columns=['Label']).values

fig = px.scatter_3d(data,
            x= data[:,0], y= data[:,1], z = data[:,2], 
            labels={'x':'PCA-1', 'y':'PCA-2','z':'PCA-3'},
            color=labels,
            color_discrete_sequence=["blue", "goldenrod", "magenta"],
            title='3d Plot of Top 3 PCA components')
fig.show()

Can you assist me in correctly changing the color palette of the 3d scatter plot?

I am using jupyter notebook 6.0.3 with seaborn version 0.11.2

Here is my dataset:

36  37  38  39  Label
0.22717583  -0.1028256  -0.041157354    0.047657568 0
-1.242205   2.611936    1.5563084   -0.64137465 0
0.39261582  0.40208274  0.2835228   0.26541463  0
-4.296567   -1.3980201  -0.67690927 -0.941123   0
-1.5278594  1.103121    -1.4688232  -1.139884   0
2.35497 -1.3783572  0.4808609   -1.4851115  1
-0.055658106    -0.19007513 -0.40134305 -0.34722504 1
0.051404    -0.6016376  0.26404122  -0.42829922 1
-0.47935575 -0.049984064    0.67335206  0.123305336 1
0.57357675  0.9523434   -0.05714764 -0.6305638  1
0.1044371   1.2541072   0.1957058   0.083972946 2
0.47575372  0.18598396  0.069036044 0.63252586  2
-0.7613742  0.81920165  0.43508404  0.280004    2
-0.16776349 0.9296196   -1.1710609  0.86310846  2
-0.20844702 0.3536006   0.01729327  -0.28363776 2

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心是晴朗的。 2025-02-16 12:21:37

看到颜色的原因之一是因为您的标签列是整数。 Seaborn认为它是数字的，并且使用连续的颜色。因此，您需要使用.astype（str）将其更改为分类。另外，我认为您将标签移动到标签并删除列，这是不需要的。因此，我已经按照以下更新。还附加了输出图。

import numpy as np
import os
import pandas as pd
from matplotlib import pyplot
import matplotlib.pyplot as plt
import plotly.express as px
import seaborn as sns

# Data
data = pd.read_csv('SamplePlotlyData.csv')

data['Label'] = data['Label'].astype(str) #Make it string
#data = data.drop(columns=['Label']).values

fig = px.scatter_3d(data,
            x= 36, y= 37, z = 38, #Updated here - just use column names
            labels={'x':'PCA-1', 'y':'PCA-2','z':'PCA-3'},
            color='Label', #Column name of Label
            color_discrete_sequence=["blue", "goldenrod", "magenta"],
            title='3d Plot of Top 3 PCA components')
fig.show()

输出

One of the reasons you are seeing the colors is because your Label column is integer. Seaborn thinks it is numerical and uses continuous colors. So, you will need to change that to categorical using .astype(str). Also, I think you are moving Label to a labels and deleting the column, which is not required. So, I have updated it as below. Also attached the output plot.

import numpy as np
import os
import pandas as pd
from matplotlib import pyplot
import matplotlib.pyplot as plt
import plotly.express as px
import seaborn as sns

# Data
data = pd.read_csv('SamplePlotlyData.csv')

data['Label'] = data['Label'].astype(str) #Make it string
#data = data.drop(columns=['Label']).values

fig = px.scatter_3d(data,
            x= 36, y= 37, z = 38, #Updated here - just use column names
            labels={'x':'PCA-1', 'y':'PCA-2','z':'PCA-3'},
            color='Label', #Column name of Label
            color_discrete_sequence=["blue", "goldenrod", "magenta"],
            title='3d Plot of Top 3 PCA components')
fig.show()

Output