seaborn（python）中具有多个带宽的打印线

在seaborn中，是否也有一种方法可以使用带宽制作线条图？Lineplot具有显示置信区间的选项（另请参见：和文档）。或者有人会建议我用精心设计的/不同的软件包来做这件事吗

但我想要的是用一个信号画一条线，并用填充颜色在它周围画几个带（当带离信号越远时，透明度越高）

基于这个主题，我在Matplotlib中做了一些事情：

# Imports
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
import matplotlib.lines as mlines
# Create dataset
mean = np.random.randint(1,101,24)
max_val = np.random.randint(101,150,24)
min_val = np.random.randint(-50,1,24)
std = np.random.randint(10,30,24)
df = pd.DataFrame({'min': min_val, 
                   '-3std': -3*std+mean,
                   '-2std': -2*std+mean,
                   '-1std': -1*std+mean,
                   'mean': mean, 
                   '1std': 1*std+mean,
                   '2std': 2*std+mean,
                   '3std': 3*std+mean,
                    'max':max_val})
# function for plot
def plot_bandwidth(df, set_labels=True, colortone='blue', ax=None, show=False):
    """
    Method to create a plot from a dataframe with the required columns [] and index
    :param (pd.DataFrame) df: Dataframe with numeric values
    :param (bool) set_labels: Boolean value to choose if labels are shown
    :param (string) colortone: String with the color to use as base for different lines/areas
    :param (ax) ax: Option to add axes to combine multiple plots
    :param (bool) show: Boolean to show plot or return figure
    :return plot/fig
    """
    # TODO: Assert if required columns not available
    if not ax:
        _, ax = plt.subplots()
    quarters_of_day = df.index
    ax.plot(quarters_of_day, df['mean'], color=colortone)
    ax.fill_between(quarters_of_day, df['-3std'], df['3std'], alpha=.1, color=colortone)
    ax.fill_between(quarters_of_day, df['-2std'], df['2std'], alpha=.1, color=colortone)
    ax.fill_between(quarters_of_day, df['-1std'], df['1std'], alpha=.1, color=colortone)
    ax.plot(quarters_of_day, df['min'], color='dark'+colortone, ls='--', alpha=.4)
    ax.plot(quarters_of_day, df['max'], color='dark'+colortone, ls='--', alpha=.4)
    if set_labels == True:
        ax.set_title("Example plot")
        ax.set_xlabel("Hour")
        ax.set_ylabel("Value")
        legend_mean = mlines.Line2D([], [], color=colortone, label='Mean')
        legend_bandwidth_std1 = mpatches.Patch(alpha=.3, color=colortone, label='Bandwidth of 1 sigma')
        legend_bandwidth_std2 = mpatches.Patch(alpha=.2, color=colortone, label='Bandwidth of 2 sigma')
        legend_bandwidth_std3 = mpatches.Patch(alpha=.1, color=colortone, label='Bandwidth of 3 sigma')
        legend_minmax = mlines.Line2D([], [], color='dark'+colortone, ls='--', alpha=.4, label='Minimum or Maximum')
        plt.legend(handles=[legend_mean, legend_bandwidth_std1, legend_bandwidth_std2, legend_bandwidth_std3, legend_minmax], loc='center left', bbox_to_anchor=(1, 0.5))     
    if show:
        return plt.show()
plot_bandwidth(df)

这导致了这样一个情节：

---

@Yatin这是我的第一篇文章，作为一个新的投稿人，你还没有这个选择。我认为你不能仅仅使用

seaborn.lineplot

。然而，seaborn本质上只是matplotlib的包装器。因此，您可以使用seaborn的

lineplot

，也可以在seaborn绘制的轴上执行

ax.fill\u。