双数据对比图表（股债性价比）

import pandas as pd
import plotly.graph_objects as go


def plot_dataframes(df1_path, df1_column, df2_path, df2_column, custom_function1, custom_function2, write_html=False):
    # 读取DataFrame1
    df1 = pd.read_excel(df1_path)
    df1['日期'] = pd.to_datetime(df1['日期'])

    # 读取DataFrame2
    df2 = pd.read_excel(df2_path)
    df2['日期'] = pd.to_datetime(df2['日期'])

    # # 对df1和df2进行日期列的排序
    # df1.sort_values('日期', inplace=True)
    # df2.sort_values('日期', inplace=True)

    # 应用自定义函数到df1和df2的指定列
    df1['计算结果'] = df1[df1_column].apply(custom_function1)
    df2['计算结果'] = df2[df2_column].apply(custom_function2)

    # 创建图表
    fig = go.Figure()

    # 添加df1的数据到y1轴
    fig.add_trace(go.Scatter(x=df1['日期'], y=df1['计算结果'], name=df1_column, yaxis='y1'))

    # 添加df2的数据到y2轴
    fig.add_trace(go.Scatter(x=df2['日期'], y=df2['计算结果'], name=df2_column, yaxis='y1'))

    # 设置图表布局
    fig.update_layout(
        title='股债性价比（1/上证50历史PE vs 中债国债1年到期利率)',
        xaxis_title='日期',
        xaxis=dict(title = '日期', showgrid=True, showspikes=True),
        yaxis=dict(title='收益率', side='left', showgrid=True, tickformat='.2%', zeroline=True),
        #yaxis2=dict(title='中债国债1年到期利率走势分析', side='right', overlaying='y', showgrid=False, zeroline=False)
        hovermode='x'
        # xaxis=dict(showspikes=True),
        # yaxis2=dict(showspikes=False)
    )

    # 保存图表为HTML文件
    fig.show()
    if write_html:
        fig.write_html('股债性价比.html')


# 示例用法
df1_path = r'D:\PythonProjects\layui-admin\macro_chart\上证50历史PE(000016.SH)-月.xlsx'
df1_column = '市盈率(TTM)'
df2_path = r'D:\PythonProjects\layui-admin\macro_chart\中债国债1年到期利率走势分析-月.xlsx'
df2_column = '利率'


def pe_to_yield(x):  # 市盈率to收益率：取倒数
    return 1 / x


def to_percent(x):  # 取百分比
    return x/100


plot_dataframes(df1_path, df1_column, df2_path, df2_column, pe_to_yield, to_percent, True)
# 调用函数生成图表