有关详细说明，请参阅this answer。

from matplotlib.pyplot import show, subplots
# make the twin Axes
fig, ax0 = subplots()
ax1 = ax0.twinx()
# plot two lines in the 1st Axes, label them
ax0.plot((0, 1, 2, 3, 4), color='g', label='green')
ax0.plot((4, 3, 2, 1, 0), color='k', label='black')
# make a scatter in the 2nd Axes, label it
ax1.scatter(( 1,  2,  3),
            (41, 37, 23), color='r', label='red')
# collect handles and labels in a list of lists [[h0, l0], [h1, l1]]
handles_labels = [ax.get_legend_handles_labels() for ax in (ax0, ax1)]
# but Axes.legend needs h=h0+h1 and l=l0+l1, so
# ① transpose hl → [[h0, h1, [l0, l1]]
hl_transposed = zip(*handles_labels)
# ② sum the sub-lists in the list of handles and in the list of labels
handles, labels = [sum(handles_or_labels, [])
                      for handles_or_labels in hl_transposed]
ax0.legend(handles, labels)
show()

代码看起来基本正确，但在创建图例的方式上有一个小问题。您应该直接使用各个图中的句柄和标签创建图例，而不是将两个图例的句柄和标签组合在一起。

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
from datetime import datetime, timedelta
import pandas as pd
# Assuming you have the time series data in numpy arrays named x_values, y_values, and fire_counts
df = pd.read_csv('FireCountPenchMar2012.csv')
print(df)
xaxis = np.arange(0, 248, 1)
yaxis = hdwi
yaxis2 = df.fire_count
print(yaxis2)
# Step 1: Create the dates for the x-axis based on the starting date (1 March 00:00 UTC)
start_date = datetime(2023, 3, 1, 0, 0, 0)
dates = [start_date + timedelta(hours=3 * i) for i in range(len(xaxis))]
plt.figure(figsize=(15, 10))
# Step 2: Plot the first time series with dates on the x-axis
line1, = plt.plot(dates, yaxis, 'o-g', label='HDWI')
# Step 3: Format the first y-axis and add axis labels and a title
plt.ylabel('HDW')
plt.title('HDWI v/s Fire Counts')
# Step 4: Create a second y-axis for the 'fire_counts' variable
ax2 = plt.gca().twinx()
line2, = ax2.plot(dates, yaxis2, 'o-r', label='Fire Counts')
ax2.set_ylabel('Fire Counts')
# Step 5: Create legends for both lines separately
legend1 = plt.legend(handles=[line1], loc='upper left')
legend2 = plt.legend(handles=[line2], loc='upper right')
# Step 6: Add the legends to the plot
plt.gca().add_artist(legend1)
plt.gca().add_artist(legend2)
# Step 7: Format the x-axis to display dates at regular intervals (e.g., every 2 days)
date_format = mdates.DateFormatter('%b %d')
plt.gca().xaxis.set_major_locator(mdates.DayLocator(interval=2))
plt.gca().xaxis.set_major_formatter(date_format)
# Step 8: Rotate the x-axis date labels for better readability
plt.xticks(rotation=45)
# Step 9: Adjust the layout and display the plot
plt.grid()
plt.tight_layout()
plt.show()