Plot multiple DataFrame columns in Seaborn FacetGrid

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臣服心动
臣服心动 2021-02-13 22:09

I am using the following code

import seaborn as sns

g = sns.FacetGrid(dataframe, col=\'A\', hue=\'A\')
g.map(plt.plot, \'X\', \'Y1\')
plt.show()
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  • 2021-02-13 22:55

    I used the following code to create a synthetic dataset which appears to match yours:

    import pandas
    import numpy
    import seaborn as sns
    import matplotlib.pyplot as plt
    
    # Generate synthetic data
    omega = numpy.linspace(0, 50)
    
    A0s = [1., 18., 40., 100.]
    
    dfs = []
    for A0 in A0s:
        V_w_dr = numpy.sin(A0*omega)
        V_w_tr = numpy.cos(A0*omega)
        dfs.append(pandas.DataFrame({'omega': omega,
                                     'V_w_dr': V_w_dr,
                                     'V_w_tr': V_w_tr,
                                     'A0': A0}))
    dataframe = pandas.concat(dfs, axis=0)
    

    Then you can do what you want (thanks to @mwaskom in the comments for )sharey='row', margin_titles=True):

    melted = dataframe.melt(id_vars=['A0', 'omega'], value_vars=['V_w_dr', 'V_w_tr'])
    g = sns.FacetGrid(melted, col='A0', hue='A0', row='variable', sharey='row', margin_titles=True)
    g.map(plt.plot, 'omega', 'value')
    

    This results in

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