如何向 seaborn FacetGrid 添加附加图并指定 colors

Question

Is there a way to create a Seaborn line plot with all the lines gray and the mean as a red line? I'm trying to do this with relplot but I don't know how to separate the mean from the data (and it appears the mean isn't being plotted?).

Make reproducible data frame

np.random.seed(1)
n1 = 100
n2 = 10
idx = np.arange(0,n1*2)
x, y, cat, id2 = [], [], [], []

x1 = list(np.random.uniform(-10,10,n2))
for i in idx: 
    x.extend(x1)
    y.extend(list(np.random.normal(loc=0, scale=0.5, size=n2)))
    cat.extend(['A', 'B'][i > n1])
    id2.append(idx[i])

id2 = id2 * n2
id2.sort()
df1 = pd.DataFrame(list(zip(id2, x, y, cat)), 
                  columns =['id2', 'x', 'y', 'cat']
                 )

Plotting attempt

g = sns.relplot(
    data=df1, x='x', y='y', hue='id2',
    col='cat', kind='line',
    palette='Greys',
    facet_kws=dict(sharey=False, 
                   sharex=False
                  ),
    legend=False
)

Answer 1

I think you want units in the call to relplot and then add a layer of lineplot using map :

import seaborn as sns
import pandas as pd

fm = sns.load_dataset('fmri').query("event == 'stim'")
g = sns.relplot(
    data=fm, kind='line',
    col='region', x='timepoint', y='signal', units='subject',
    estimator=None, color='.7'
)
g.data = fm  # Hack needed to work around bug on v0.11, fixed in v0.12.dev
g.map(sns.lineplot, 'timepoint', 'signal', color='r', ci=None, lw=3)

Answer 2

• It depends on the desired result. Theseaborn.relplot documentation has an example for the fmri dataset that only shows the mean and the ci , so the result depends on how you set the hue and event parameters.
• To specify a single color for all the lines, use units instead of hue or style (as pointed out by mwaskom ), and then set color='grey' .
• For the requirements of this OP, the accepted answer is the best option. However, in cases which require adding data from a source that isn't the data used to create the relplot , this solution may be more appropriate, as it allows for accessing each axes of the figure, and adding something from a different data source.

import seaborn as sns
import pandas as pd

# load and select data only where event is stim
fm = sns.load_dataset('fmri').query("event == 'stim'")

# groupby to get the mean for each region by timepoint
fmg = fm.groupby(['region', 'timepoint'], as_index=False).signal.mean()

# plot the fm dataframe
g = sns.relplot(data=fm, col='region', x='timepoint', y='signal',
                units='subject', kind='line', ci=None, color='grey', estimator=None)

# extract and flatten the axes from the figure
axes = g.axes.flatten()

# iterate through each axes
for ax in axes:
    # extract the region
    reg = ax.get_title().split(' = ')[1]
    
    # select the data for the region
    data = fmg[fmg.region.eq(reg)]
    
    # plot the mean line
    sns.lineplot(data=data, x='timepoint', y='signal', ax=ax, color='red', label='mean', lw=3)
    
# fix the legends
axes[0].legend().remove()
axes[1].legend(title='Subjects', bbox_to_anchor=(1, 1), loc='upper left')

Resources

• Also see the following answers for other ways to add information to a seaborn FacetGrid
  • Draw a line at specific position/annotate a Facetgrid in seaborn
  • Overlay a vertical line on seaborn scatterplot with multiple subplots

Answer 3

I came here from Seaborn's relplot: Is there a way to assign a specific color to all lines and another color to another single line when using the hue argument? and can't post there.

But I find the simplest solution is to simply pass a hue_order as well as a palette argument to the relplot call. See below:

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


sim = ['a'] * 100 + ['b'] * 100 + ['c'] * 100
var = (['u'] * 50 + ['v'] * 50)*3

x = np.linspace(0, 50, 50)
x = np.hstack([x]*6)

y = np.random.rand(300)

df = pd.DataFrame({'x':x, 'y':y, 'sim':sim, 'var':var})

hueOrder = ["a", "b", "c"] # Specifies the order for the palette
hueColor = ["r", "r", "b"] # Specifies the colors for the hueOrder (just make two the same color, and one different)

sbn.relplot(data=df, x='x', y='y', kind='line', col='var', hue='sim', hue_order=hueOrder, palette=hueColor)
plt.show()

This is a bit different then the accepted answer. But again, I came here from another question that is closed. This also doesn't use any for loops and should be more straight forward.

Output: