如何用Python自定义函数从宽格式DataFrame生成多子图并导出图表

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages

# 示例数据集
df= {
    'Gen':['M','M','M','M','F','F','F','F','M','M','M','M','F','F','F','F'],
    'Site':['FRX','FRX','FRX','FRX','FRX','FRX','FRX','FRX','FRX','FRX','FRX','FRX','FRX','FRX','FRX','FRX'],
    'Type':['L','L','L','L','L','L','L','L','R','R','R','R','R','R','R','R'],
     'UID':[1001,1002,1003,1004,1001,1002,1003,1004,1001,1002,1003,1004,1001,1002,1003,1004],
    'Time1':[100.78,112.34,108.52,139.19,149.02,177.77,79.18,89.10,106.78,102.34,128.52,119.19,129.02,147.77,169.18,170.11],
    'Time2':[150.78,162.34,188.53,197.69,208.07,217.76,229.48,139.51,146.87,182.54,189.57,199.97,229.28,244.73,269.91,249.19],
     'Time3':[250.78,262.34,288.53,297.69,308.07,317.7,329.81,339.15,346.87,382.54,369.59,399.97,329.28,347.73,369.91,349.12],
     'Time4':[240.18,232.14,258.53,276.69,338.07,307.74,359.16,339.25,365.87,392.48,399.97,410.75,429.08,448.39,465.15,469.33],
     'Time5':[270.84,282.14,298.53,306.69,318.73,327.47,369.63,389.59,398.75,432.18,449.78,473.55,494.85,509.39,515.52,539.23]
}
df = pd.DataFrame(df,columns = ['Gen','Site','Type','UID','Time1','Time2','Time3','Time4','Time5'])

def graph2pdf(inputdata, export_type='pdf', export_path='turbidity_result', dpi=300, transparent=False):
    # 宽表转长表，保留所有需要的维度字段
    df_long = pd.melt(inputdata, 
                      id_vars=['Gen', 'Type', 'UID', 'Site'],
                      var_name='Time_str',
                      value_name='Turbidity')
    # 提取时间数值，将X轴转为连续数值格式
    df_long['Time'] = df_long['Time_str'].str.extract('(\d+)').astype(int)
    # 拼接生成图例标签
    df_long['group'] = df_long['Gen'] + '+' + df_long['Type']
    # 获取所有唯一UID
    uids = df_long['UID'].unique()
    # 配置白色基础样式
    sns.set_style("whitegrid")
    
    # 导出PDF逻辑
    if export_type == 'pdf':
        with PdfPages(f'{export_path}.pdf') as pdf:
            # 每页2行2列，固定放4张图
            fig, axes = plt.subplots(nrows=2, ncols=2, figsize=(12, 10), facecolor='white' if not transparent else 'none')
            axes = axes.flatten()
            for idx, uid in enumerate(uids):
                ax = axes[idx]
                # 筛选当前UID对应的数据
                uid_data = df_long[df_long['UID'] == uid]
                # 绘制折线图，每个分组对应一条曲线
                sns.lineplot(data=uid_data, x='Time', y='Turbidity', hue='group', marker='o', ax=ax)
                # 自动获取对应Site值生成标题
                site = uid_data['Site'].iloc[0]
                ax.set_title(f'UID:{uid} + Site:{site}', fontsize=12)
                # 设置坐标轴标签
                ax.set_xlabel('Time', fontsize=10)
                ax.set_ylabel('Turbidity', fontsize=10)
                # 调整图例位置
                ax.legend(loc='upper left', title='Group')
            # 调整子图间距避免重叠
            plt.tight_layout()
            # 保存到PDF
            pdf.savefig(fig, dpi=dpi, facecolor='white' if not transparent else 'none')
            plt.close()
    # 导出图片格式逻辑
    else:
        fig, axes = plt.subplots(nrows=2, ncols=2, figsize=(12, 10), facecolor='white' if not transparent else 'none')
        axes = axes.flatten()
        for idx, uid in enumerate(uids):
            ax = axes[idx]
            uid_data = df_long[df_long['UID'] == uid]
            sns.lineplot(data=uid_data, x='Time', y='Turbidity', hue='group', marker='o', ax=ax)
            site = uid_data['Site'].iloc[0]
            ax.set_title(f'UID:{uid} + Site:{site}', fontsize=12)
            ax.set_xlabel('Time', fontsize=10)
            ax.set_ylabel('Turbidity', fontsize=10)
            ax.legend(loc='upper left', title='Group')
        plt.tight_layout()
        plt.savefig(f'{export_path}.{export_type}', dpi=dpi, facecolor='white' if not transparent else 'none')
        plt.close()

# 测试调用，可根据需要修改参数
# 导出PDF
graph2pdf(df, export_type='pdf', export_path='turbidity_result', transparent=False)
# 导出JPEG
# graph2pdf(df, export_type='jpeg', export_path='turbidity_result', dpi=300)
# 导出TIFF
# graph2pdf(df, export_type='tiff', export_path='turbidity_result', dpi=300)

• export_type：支持传入pdf/jpeg/tiff三种导出格式
• export_path：自定义导出文件的保存路径和文件名
• dpi：导出图片的分辨率，默认300满足印刷需求
• transparent：设置为True即可导出透明背景图，默认白色背景

内容的提问来源于stack exchange，提问作者RayX500