Seaborn displot 'FacetGrid' object is not callable

Question

I wrote the following code in order to plot a 2x2 displot with seaborn:

df = pd.DataFrame(
    {'Re'    : x,
     'n'     : y,
     'Type'  : tp,
     'tg'    : tg,
     'gt'    : gt
    })

g = sns.FacetGrid(df, row='gt', col='tg', margin_titles=False, height=2.5, aspect=1.65)
g.map(sns.displot(df, x='Re', y='n', hue='Type', kind='kde',log_scale=True, palette=customPalette, fit_reg=False, x_jitter=.1))

However I get this error that I cannot fix:

func(*plot_args, **plot_kwargs)

TypeError: 'FacetGrid' object is not callable

The x, y, tp, tg and gt imported in the df are lists.

Does anyone have any clue what I might do to fix this? Thank you in advance! :)

*This is how the df looks like: [1]: https://i.stack.imgur.com/H6J9c.png

Answer 1

Well, sns.displot is already a FacetGrid . You can't give it as a parameter to g.map . Moreover, the parameter to g.map is meant to be a function without evaluating it (so, without brackets, and the parameters given as parameters to g.map ). See the examples at Seaborn's FacetGrid page .

The most common FacetGrid parameters (such as row , col , height and aspect ) can be provided directly to sns.displot() . Less common parameters go into facet_kws=... .

Here is an example:

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

df = pd.DataFrame({'Re': np.random.rand(100),
                   'n': np.random.rand(100),
                   'Type': np.random.choice([*'abc'], 100),
                   'tg': np.random.choice(['ETG', 'LTG'], 100),
                   'gt': np.random.randint(0, 2, 100)})
g = sns.displot(df, x='Re', y='n', hue='Type', kind='kde',
                row='gt', col='tg', height=2.5, aspect=1.65,
                log_scale=True, palette='hls',
                facet_kws={'margin_titles': False})
plt.show()

To directly work with FacetGrid (not recommended), you could create a similar plot with:

g = sns.FacetGrid(df, row='gt', col='tg', hue='Type', palette='hls',
                  margin_titles=False, height=2.5, aspect=1.65)
g.map_dataframe(sns.kdeplot,
                x='Re', y='n',
                log_scale=True)
g.add_legend()