我想绘制一个基于经度和纬度的散点图。散点图的大小取决于另一个值“LF”。

longitude = df['evlo']
latitude = df['evla']
lf = df['LF']

# Define the size based on the LF values
size = lf

还有另一个包含日期信息的列，我将其转换为日期时间格式：

df['dates'] = pd.to_datetime(df['fold'].str[0:8], format='%Y%m%d')

df['dates'] = df['dates'].dt.strftime('%Y-%m-%d')

输出格式如下：
我想用一个共享的彩条以15天的间隔绘制散点子图。我已经做了这项工作，但似乎每个子图都有自己的彩条，例如蓝色和红色存在于每个子图中，这不应该在真实的情况下。下面是我的尝试：

`import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import numpy as np
import pandas as pd
import matplotlib.cm as cm
import matplotlib.colors as colors

# Filter data based on LF values

df_lf_more_than_1 = df[df['LF'] > 1]

# Get the minimum and maximum dates in the filtered data
min_date = df_lf_more_than_1['dates'].min()
max_date = df_lf_more_than_1['dates'].max()

# Create a figure with four subplots
fig, axes = plt.subplots(2, 2, figsize=(12, 10),sharex=True, sharey=True)
axes = axes.flatten()    
for i, ax in enumerate(axes):
    # Calculate the start and end dates for the current interval
    start_date = min_date + pd.DateOffset(days=i * 15)
    end_date = start_date + pd.DateOffset(days=14)

    
    # Filter the data for the current interval
    df_interval = df_lf_more_than_1[(df_lf_more_than_1['dates'] >= start_date)
                                    & (df_lf_more_than_1['dates'] <= end_date)]
    # Plot the scatter plot for the current interval
    scatter = ax.scatter(df_interval['evlo'], df_interval['evla'], 
                         s=df_interval['LF']*5,
                         c=mdates.date2num(df_interval['dates']), cmap='jet')
        
 
    # Set the title of the subplot to the start and end dates
    ax.set_title(f'Interval: {start_date.strftime("%Y-%m-%d")} - {end_date.strftime("%Y-%m-%d")}')

    ax.xaxis.set_major_formatter(plt.FormatStrFormatter('%.2f'))
        

cax = fig.add_axes([0.15, 0.05, 0.7, 0.03])  # Position of the colorbar
cbar = fig.colorbar(cm.ScalarMappable(norm=norm, cmap='jet'), cax=cax, orientation='horizontal')

plt.subplots_adjust(bottom=0.09)

plt.show()`