Python Seaborn 图表 - 阴影区域 [英] Python Seaborn Chart - Shadow Area

问题描述

抱歉我的菜鸟问题，但是如何在 seaborn 图表的上下线之间添加阴影区域/颜色?

我正在处理的主要代码如下:

plt.figure(figsize=(18,10))sns.set(style="darkgrid")调色板= sns.color_palette(mako_r"，3)sns.lineplot(x=日期"，y=值"，hue='Std_Type'，style='Value_Type'，尺寸=(.25，2.5)，调色板=调色板，数据=tbl4)

我们的想法是获得如下效果(来自 seaborn 网站的示例):但是我无法复制效果，尽管我的数据结构与 fmri(seaborn 示例)

的方式几乎相同

来自 seaborn

你有什么想法吗?我尝试更改图表样式，但是如果我转到 distplot 或 relplot，例如，x_axis 无法显示时间范围...

解决方案

检查此代码:

# 导入将 numpy 导入为 np导入 matplotlib.pyplot 作为 plt将 seaborn 作为 sns 导入将熊猫导入为 pdsns.set(style = 'darkgrid')# 数据生成时间 = pd.date_range(开始 = '2006-01-01'，结束 = '2020-01-01'，频率 = 'M')tbl4 = pd.DataFrame({'Date': 时间，'向下':1 - 0.5*np.random.randn(len(time)),'向上':4 + 0.5*np.random.randn(len(time))})tbl4 = tbl4.melt(id_vars = '日期',value_vars = ['down', 'up'],var_name = 'Std_Type',value_name = '值')# 图形图, ax = plt.subplots(figsize=(18,10))sns.lineplot(ax = ax,x = '日期',y = '值',色调 = 'Std_Type',数据 = tbl4)# 填充区域plt.fill_between(x = tbl4[tbl4['Std_Type'] == 'down']['Date'],y1 = tbl4[tbl4['Std_Type'] == 'down']['Value'],y2 = tbl4[tbl4['Std_Type'] == 'up']['Value'],α = 0.3，facecolor = '绿色')plt.show()

这给了我这个情节:

由于我无法访问您的数据，因此我生成了随机数据.用你的替换它们.
阴影区域使用 plt.fill_between 完成(文档 此处)，其中指定x数组(两条曲线通用)，区域的上限和下限为y1和y2 和可选的颜色及其透明度，分别带有 facecolor 和 alpha 参数.

---

您不能通过 ci 参数来实现，因为它用于显示 置信区间 您的数据.

Sorry to my noob question, but how can I add a shadow area/color between the upper and lower lines in a seaborn chart?

The primary code I've working on is the following:

plt.figure(figsize=(18,10))
sns.set(style="darkgrid")
palette = sns.color_palette("mako_r", 3)
sns.lineplot(x="Date", y="Value",  hue='Std_Type', style='Value_Type', sizes=(.25, 2.5), palette = palette, data=tbl4)

The idea is to get some effect like below (the example from seaborn website): But I could not replicate the effect although my data structure is pretty much in the same fashion as fmri (seaborn example)

from seaborn link:

 import seaborn as sns
 sns.set(style="darkgrid")

 # Load an example dataset with long-form data
 fmri = sns.load_dataset("fmri")

 # Plot the responses for different events and regions
 sns.lineplot(x="timepoint", y="signal",
         hue="region", style="event",
         data=fmri)

Do you have some ideas? I tried to change the chart style, but if I go to a distplot or relplot, for example, the x_axis cannot show the timeframe...

解决方案

Check this code:

# import
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
sns.set(style = 'darkgrid')

# data generation
time = pd.date_range(start = '2006-01-01', end = '2020-01-01', freq = 'M')
tbl4 = pd.DataFrame({'Date': time,
                     'down': 1 - 0.5*np.random.randn(len(time)),
                     'up': 4 + 0.5*np.random.randn(len(time))})

tbl4 = tbl4.melt(id_vars = 'Date',
                 value_vars = ['down', 'up'],
                 var_name = 'Std_Type',
                 value_name = 'Value')

# figure plot
fig, ax = plt.subplots(figsize=(18,10))

sns.lineplot(ax = ax,
             x = 'Date',
             y = 'Value',
             hue = 'Std_Type',
             data = tbl4)

# fill area
plt.fill_between(x = tbl4[tbl4['Std_Type'] == 'down']['Date'],
                 y1 = tbl4[tbl4['Std_Type'] == 'down']['Value'],
                 y2 = tbl4[tbl4['Std_Type'] == 'up']['Value'],
                 alpha = 0.3,
                 facecolor = 'green')

plt.show()

which gives me this plot:

Since I do not have access to your data, I generated random ones. Replace them with yours.
The shadow area is done with plt.fill_between (documentation here), where you specify the x array (common to both curves), the upper and lower limits of the area as y1 and y2 and, optionally a color and its transparency with the facecolor and alpha parameters respectively.

---

You cannot do it through ci parameter, since it is used to show the confidence interval of your data.

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