有没有办法使用 seaborn 在循环的子图图形中创建次要 y 轴？

Question

我已经成功编写了循环数据和创建子图的代码，但是，我希望在 y 轴上显示两个数据集。这些是 y 和 y1 或 ax2。此代码创建了一个辅助 y 轴，但是它没有标记辅助 y 轴，也没有与之关联的任何数据。

nrow = 4
ncol = 3
fig, axes = plt.subplots(nrow, ncol, figsize=(17,17))
plt.subplots_adjust(bottom=.1, right=1.5,top=1.75)
fig.delaxes(axes[3,2])

count = 0
for r in range(nrow):
  for c in range(ncol):

    x = dataobserved[count].index
    x1 = datamodeled[count].index
    y = dataobserved[count]['Average Q cfs']
    y1 = datamodeled[count]['QHistorical']
    y2 = dataobserved[count]['Total Generation Mwh']
    y3 = datamodeled[count]['Historical']

    sns.set_style("white")
    ax2 = ax.twinx()

    ax2 = sns.lineplot(x = x, y = y, color = "black", linestyle = '--', ax = axes[r,c])    
    ax2 = sns.lineplot(x = x1, y = y1, color = "blue", linestyle = '--', ax = axes[r,c]) 
    ax = sns.lineplot(x = x, y = y2, color = "black", ax = axes[r,c]) 
    ax = sns.lineplot(x = x1, y = y3, color = "blue", ax = axes[r,c]) 


    subplot_title = (str(ttl[count]))
    axes[r,c].set_title(subplot_title, size = 20)
    axes[r,c].legend(labels = ['Observed Outflow','Historical Baseline Outflow','Observed Generation','Historical Baseline Generation'], loc = "upper left")

    count+=1
  for ax in axes.flat:
    ax.set_xlabel('Water Year Week', fontsize = 15)
    ax.set_ylabel( 'Weekly Total Generation (Mwh)', fontsize = 15)
    ax2.set_ylabel('Weekly Average Outflow (cfs)')
    ax.set_xticks(range(1,52,10))

example of two subplots produced from the above code

我已经查看了 Share secondary y axis in looped seaborn plots 但它的情况不太一样，因为未共享次要 y 轴。

Answer 1

由于没有展示，我使用了我适当创建的样本数据，并在循环过程中处理了子图。您已经使用了两次循环过程，但是通过展平轴，您只需要执行一次。

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

df = pd.DataFrame({'date':pd.date_range('2021-01-01','2021-12-31',freq='1d'),
                   'y': np.random.randint(100,1000,365),
                   'y1': np.random.randint(200,2000,365),
                   'y2':np.random.rand(365),
                   'y3':np.random.rand(365)})

df['date'] = pd.to_datetime(df['date'])
df['Week'] = df['date'].dt.isocalendar().week
df['month'] = df['date'].dt.month

fig, axes = plt.subplots(4,3, figsize=(17,17))
plt.subplots_adjust(bottom=.1, right=1.5,top=1.75)

sns.set_style("white")

for i,ax in enumerate(axes.flat, start=1):
    dfs = df[df['month'] == i]
    ax2 = ax.twinx()
    sns.lineplot(data=dfs, x = 'Week', y = 'y', color = "black", linestyle = '--', estimator=None, ax=ax)    
    sns.lineplot(data=dfs, x = 'Week', y = 'y1', color = "blue", linestyle = '--', estimator=None, ax=ax) 
    sns.lineplot(data=dfs, x = 'Week', y = 'y2', color = "red", estimator=None, ax=ax2)
    sns.lineplot(data=dfs, x = 'Week', y = 'y3', color = "blue", estimator=None, ax=ax2)
    ax.set_title(i, size = 20)
    ax.legend(labels = ['y1','y2'], loc = "upper left")
    ax.set_xlabel('Water Year Week', fontsize = 15)
    ax.set_ylabel( 'Weekly Total Generation (Mwh)', fontsize = 15)
    ax2.set_ylabel('Weekly Average Outflow (cfs)')
    #ax.set_xticks(range(1,52,10))

有没有办法使用 seaborn 在循环的子图图形中创建次要 y 轴？

Is there a way to create a secondary y axis within a looped subplot figure using seaborn?

python

matplotlib

seaborn

subplot