plotly.express - 置信区间如 sns.lineplot

plotly.express - confidence intervals like in sns.lineplot

这是带有置信区间的 seaborn 图示例:

import plotly.express as px
import seaborn as sns
import pandas as pd
import numpy as np

np.random.seed(1)
df = pd.DataFrame({'x': np.tile(np.arange(5), 6), 'y': np.random.randn(30), 'hue': np.repeat(['foo', 'bar'], [15, 15])})

sns.lineplot(data=df, x='x', y='y', hue='hue')

输出

下面是尝试在 plotly 中做同样的事情:

group = ['hue', 'x']
err = df.groupby(group)['y'].std() / np.sqrt(df.groupby(group)['y'].size())
pdf = df.groupby(group)['y'].mean().reset_index()
pdf['2'] = pdf['y'] + 1.96*pdf.set_index(group).index.map(err)
pdf['1'] = pdf['y'] - 1.96*pdf.set_index(group).index.map(err)
pdf['0'] = pdf['y']
pdf = pdf.drop('y', axis=1)
pdf = pd.melt(pdf, id_vars=['x', 'hue'])
pdf = pdf.sort_values(['x', 'variable', 'hue'], ascending = True)

fig = px.line(
    pdf[pdf['hue']=='foo'],
    line_group='hue', 
    x = 'x',
    y = 'value',
    color='variable',
    color_discrete_map = {'0': 'blue', '1': 'blue', '2': 'blue'}
)

fig.update_traces(name = 'interval', selector = dict(name = '2'), showlegend=False)
fig.update_traces(fill = 'tonexty')
fig.update_traces(fillcolor = 'rgba(0,0,0,0)', selector = dict(name = '0'))
fig.update_traces(fillcolor = 'rgba(0,0,0,0)', line_color = 'rgba(0, 0, 255, 0.5)',
                  showlegend = False, selector = dict(name = '1'))

fig

输出:

因此,这与 seaborn 情节相同,但只是其中一种色调。我怎样才能将另一个色调的相同图放到同一个图上,使其看起来像 seaborn 的图?

我花了很多时间试图解决这个问题,所以我最终整理了一个小包来解决这个问题,API 与 seaborn 的相同:https://github.com/MarcoGorelli/bornly

示例:

import bornly as bns

fmri = bns.load_dataset("fmri")
bns.lineplot(data=fmri, x="timepoint", y="signal", hue="event")