如何在 seaborn 散点图图例中放置颜色条

Question

I have the next scatterplot

But i want to change the dots on the legend by continuos color map like this:

This is my code:

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

sns.set_style("whitegrid")

gene_list = pd.read_csv('interseccion.csv', header=None)
glist = gene_list.squeeze().str.strip().tolist()

names = gp.get_library_name() 

enr = gp.enrichr(gene_list= glist,
                 gene_sets=['KEGG_2019_Human'],
                 organism='Human', # don't forget to set organism to the one you desired! e.g. Yeast
                 description='KEGG',
                 # no_plot=True,
                 cutoff=0.5 # test dataset, use lower value from range(0,1)
                )

resultados = enr.results.head(15)
resultados['-log10(FDR)'] = -np.log10(resultados['Adjusted P-value'])
resultados['Genes'] = resultados['Genes'].str.split(';')
resultados['Genes'] = resultados['Genes'].apply(lambda x: len(x))

g = sns.scatterplot(data=resultados, x="-log10(FDR)", y="Term", hue='-log10(FDR)', palette="seismic"
                , size="Genes", sizes=(30, 300), legend=True)

g.legend(loc=6, bbox_to_anchor=(1, 0.5), ncol=1)
g.fig.colorbar()
plt.ylabel('')
plt.xlabel('-log10(FDR)')

When i try to put a color bar with the funcion plt.colorbar() is not possible

Answer 1

I customized the code in the official sample with the understanding that I wanted to add a legend and color bars to the Seaborn scatterplot. A colormap has been created to match the colors of the sample graph, but it can be drawn without problems by specifying the colormap name. The color bar is customized by getting its position and adjusting it manually in the legend. The height of the color bar is halved to match the legend.

import seaborn as sns
import matplotlib.pyplot as plt

tips = sns.load_dataset("tips")
fig, ax = plt.subplots()
g = sns.scatterplot(
    data=tips, x="total_bill", y="tip", hue="size", size="size",
    sizes=(20, 200), legend="full", ax=ax)
g.legend(loc='upper right', bbox_to_anchor=(1.2, 1.0), ncol=1)

norm = plt.Normalize(tips['size'].min(), tips['size'].max())
cmap = sns.cubehelix_palette(light=1, as_cmap=True)
sm = plt.cm.ScalarMappable(cmap=cmap, norm=norm)
sm.set_array([])

cax = fig.add_axes([ax.get_position().x1+0.05, ax.get_position().y0, 0.06, ax.get_position().height / 2])
ax.figure.colorbar(sm, cax=cax)

plt.show()