3D scatterplots in Python with hue colormap and legend

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攒了一身酷
攒了一身酷 2021-02-13 10:42

I have been searching for 3D plots in python with seaborn and haven\'t seen any. I would like to 3D plot a dataset that I originally plotted using seaborn pairplot. Can anyone

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  • 2021-02-13 10:42

    There is no color palette specification for fig 2 but it looks like it is the Paired qualitative colormap from matplotlib (from here). So you need to specify that in your code for the 3D plot with the cmap argument and with the palette option in your pairplot.

    The legend is harder. You can make one from legend_elements. Better explained here.

    So your code would look like this (I got rid of the unused imports):

    import seaborn as sns, numpy as np, pandas as pd, random
    import matplotlib.pyplot as plt
    from mpl_toolkits.mplot3d import Axes3D
    sns.set_style("whitegrid", {'axes.grid' : False})
    
    fig = plt.figure(figsize=(6,6))
    
    ax = Axes3D(fig)
    
    x = np.random.uniform(1,20,size=20)
    y = np.random.uniform(1,100,size=20)
    z = np.random.uniform(1,100,size=20)
    
    
    g = ax.scatter(x, y, z, c=x, marker='o', depthshade=False, cmap='Paired')
    ax.set_xlabel('X Label')
    ax.set_ylabel('Y Label')
    ax.set_zlabel('Z Label')
    
    # produce a legend with the unique colors from the scatter
    legend = ax.legend(*g.legend_elements(), loc="lower center", title="X Values", borderaxespad=-10, ncol=4)
    ax.add_artist(legend)
    
    plt.show()
    
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  • 2021-02-13 11:01
    1. The color palette from Seaborn can be turned into a Matplotlib color map from an instance of a ListedColorMap class initialized with the list of colors in the Seaborn palette with the as_hex() method (as proposed in this original answer).

    2. From the Matplotlib documentation, you can generate a legend from a scatter plot with getting the handles and labels of the output of the scatter function.

    The result of the code is shown in the picture below. Note that I generated more data points in order to better see that the colormap is the same. Also, the output of ListedColorMap outputs a color map with transparency variations, so I had to manually set alpha to 1 in the scatter plot.

    import re, seaborn as sns
    import numpy as np
    
    from matplotlib import pyplot as plt
    from mpl_toolkits.mplot3d import Axes3D
    from matplotlib.colors import ListedColormap
    
    # generate data
    n = 200
    x = np.random.uniform(1, 20, size=n)
    y = np.random.uniform(1, 100, size=n)
    z = np.random.uniform(1, 100, size=n)
    
    # axes instance
    fig = plt.figure(figsize=(6,6))
    ax = Axes3D(fig)
    
    # get colormap from seaborn
    cmap = ListedColormap(sns.color_palette("husl", 256).as_hex())
    
    # plot
    sc = ax.scatter(x, y, z, s=40, c=x, marker='o', cmap=cmap, alpha=1)
    ax.set_xlabel('X Label')
    ax.set_ylabel('Y Label')
    ax.set_zlabel('Z Label')
    
    # legend
    plt.legend(*sc.legend_elements(), bbox_to_anchor=(1.05, 1), loc=2)
    
    # save
    plt.savefig("scatter_hue", bbox_inches='tight')
    

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