Plot multiple DataFrame columns in Seaborn FacetGrid

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

import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt

# Generate synthetic data
omega = np.linspace(0, 50)

A0s = [1., 18., 40., 100.]

dfs = []
for A0 in A0s:
    V_w_dr = np.sin(A0*omega)
    V_w_tr = np.cos(A0*omega)
    dfs.append(pd.DataFrame({'omega': omega,
                             'V_w_dr': V_w_dr,
                             'V_w_tr': V_w_tr,
                             'A0': A0}))
df = pd.concat(dfs, axis=0)

Then you can do what you want. Thanks to @mwaskom in the comments for sharey='row', and margin_titles=True:

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

This results in

enter image description here

Update

  • As of this update, the correct method is to use seaborn.relplot, which plots a FacetGrid.
sns.relplot(data=dfm, x='omega', y='value', col='A0', hue='A0', row='variable', kind='line')

enter image description here

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arccos
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arccos

Updated on September 15, 2022

Comments

  • arccos
    arccos over 1 year

    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()
    

    to make a seaborn facet plot like this: Example facet plot

    Now I would like to add another row to this plot with a different variable, call it Y2, on the y axis. The result should look similar to vertically stacking the two plots obtained by

    g = sns.FacetGrid(dataframe, col='A', hue='A')
    g.map(plt.plot, 'X', 'Y1')
    plt.show()
    
    g = sns.FacetGrid(dataframe, col='A', hue='A')
    g.map(plt.plot, 'X', 'Y2')
    plt.show()
    

    Example plot with two rows

    but in a single plot, without the duplicate x axis and titles ("A=<value>") and without creating a new FacetGrid object.

    Note that

    g = sns.FacetGrid(dataframe, col='A', hue='A')
    g.map(plt.plot, 'X', 'Y1')
    g.map(plt.plot, 'X', 'Y2')
    plt.show()
    

    does not achive this, because it results in both the curve for Y1 and Y2 being displayed in the same subplot for each value of A.