Seaborn Relplot未显示误差条

Question

使用这段代码，我创建了一个 Seaborn 图表，以可视化长格式数据集中的多个变量。

import pandas as pd
import seaborn as sns

data = {'Patient ID': [11111, 11111, 11111, 11111, 22222, 22222, 22222, 22222, 33333, 33333, 33333, 33333, 44444, 44444, 44444, 44444, 55555, 55555, 55555, 55555],
        'Lab Attribute': ['% Saturation- Iron', 'ALK PHOS', 'ALT(SGPT)', 'AST (SGOT)', '% Saturation- Iron', 'ALK PHOS', 'ALT(SGPT)', 'AST (SGOT)', '% Saturation- Iron', 'ALK PHOS', 'ALT(SGPT)', 'AST (SGOT)', '% Saturation- Iron', 'ALK PHOS', 'ALT(SGPT)', 'AST (SGOT)', '% Saturation- Iron', 'ALK PHOS', 'ALT(SGPT)', 'AST (SGOT)'],
        'Baseline': [46.0, 94.0, 21.0, 18.0, 56.0, 104.0, 31.0, 12.0, 50.0, 100.0, 33.0, 18.0, 46.0, 94.0, 21.0, 18.0, 46.0, 94.0, 21.0, 18.0],
        '3 Month': [33.0, 92.0, 19.0, 25.0, 33.0, 92.0, 21.0, 11.0, 33.0, 102.0, 18.0, 17.0, 23.0, 82.0, 13.0, 17.0, 23.0, 82.0, 13.0, 17.0],
        '6 Month': [34.0, 65.0, 10.0, 14.0, 34.0, 65.0, 10.0, 14.0, 34.0, 65.0, 10.0, 14.0, 34.0, 65.0, 10.0, 14.0, 34.0, 65.0, 10.0, 14.0]}

df = pd.DataFrame(data)

# reshape the dataframe
dfm = df_labs.melt(id_vars=['Patient_ID', 'Lab_Attribute'], var_name='Months')

# change the Months values to numeric
dfm.Months = dfm.Months.map({'Baseline': 0, '3 Month': 3, '6 Month': 6})

# plot a figure level line plot with seaborn
p = sns.relplot(data=dfm, col='Lab_Attribute', x='Months', y='value', hue='Patient_ID', kind='line', col_wrap=5, marker='o', palette='husl',facet_kws={'sharey': False, 'sharex': True},err_style="bars", ci=95,)

plt.savefig('gmb_nw_labs.jpg')

图表很棒，但由于某种原因，误差条未显示，即使添加了以下内容：

err_style="bars", ci=95,

转换到 sns.replot()

p = sns.relplot(data=dfm, col='Lab_Attribute', x='Months', y='value', hue='Patient_ID', kind='line', col_wrap=5, marker='o', palette='husl',facet_kws={'sharey': False, 'sharex': True},err_style="bars", ci=95,)

有人能告诉我为什么会这样吗？也许我的数据集中数据点太少了？

- John Conor

Answer 1

• 每个数据点都被hue分开，因此没有误差线，因为没有合并的数据。删除hue = 'Patient ID'，只显示平均线和误差线。
• 或者，可以将seaborn.lineplot映射到seaborn.relplot上。通过不指定hue，API将创建误差线
  • linestyle=''被指定，因此不会绘制平均线
• 在python3.8.12，pandas1.3.4，matplotlib3.4.3，seaborn0.11.2中进行了测试

data = {'Patient ID': [11111, 11111, 11111, 11111, 22222, 22222, 22222, 22222, 33333, 33333, 33333, 33333, 44444, 44444, 44444, 44444, 55555, 55555, 55555, 55555],
        'Lab Attribute': ['% Saturation- Iron', 'ALK PHOS', 'ALT(SGPT)', 'AST (SGOT)', '% Saturation- Iron', 'ALK PHOS', 'ALT(SGPT)', 'AST (SGOT)', '% Saturation- Iron', 'ALK PHOS', 'ALT(SGPT)', 'AST (SGOT)', '% Saturation- Iron', 'ALK PHOS', 'ALT(SGPT)', 'AST (SGOT)', '% Saturation- Iron', 'ALK PHOS', 'ALT(SGPT)', 'AST (SGOT)'],
        'Baseline': [46.0, 94.0, 21.0, 18.0, 56.0, 104.0, 31.0, 12.0, 50.0, 100.0, 33.0, 18.0, 46.0, 94.0, 21.0, 18.0, 46.0, 94.0, 21.0, 18.0],
        '3 Month': [33.0, 92.0, 19.0, 25.0, 33.0, 92.0, 21.0, 11.0, 33.0, 102.0, 18.0, 17.0, 23.0, 82.0, 13.0, 17.0, 23.0, 82.0, 13.0, 17.0],
        '6 Month': [34.0, 65.0, 10.0, 14.0, 34.0, 65.0, 10.0, 14.0, 34.0, 65.0, 10.0, 14.0, 34.0, 65.0, 10.0, 14.0, 34.0, 65.0, 10.0, 14.0]}

df = pd.DataFrame(data)

# reshape the dataframe
dfm = df.melt(id_vars=['Patient ID', 'Lab Attribute'], var_name='Months')

# change the Months values to numeric
dfm.Months = dfm.Months.map({'Baseline': 0, '3 Month': 3, '6 Month': 6})

# plot a figure level line plot with seaborn
p = sns.relplot(data=dfm, col='Lab Attribute', x='Months', y='value', hue='Patient ID', kind='line', col_wrap=3, marker='o', palette='husl', facet_kws={'sharey': False, 'sharex': True}, err_style="bars", ci=95,)
p.map(sns.lineplot, 'Months', 'value',  linestyle='', err_style="bars", color='k')

• 未使用 hue='Patient ID' 的原始实现

p = sns.relplot(data=dfm, col='Lab Attribute', x='Months', y='value', kind='line', col_wrap=3, marker='o', palette='husl', facet_kws={'sharey': False, 'sharex': True}, err_style="bars", ci=95)

- Trenton McKinney

---

好的，我升级了seaborn和matplotlib，并重新启动了内核，完美解决了问题。再次感谢您今天的帮助。这对我的数据分析技能提升是一个重要的步骤。 - John Conor