Plotly- dash :-上传文件后，在plotly dash中进行多列过滤

import dash
import dash_html_components as html
import dash_core_components as dcc
from dash.dependencies import Input, Output
import pandas as pd

app = dash.Dash(__name__)

data = pd.read_csv("data.csv")

app.layout = html.Div([
    dcc.Upload(
        id='upload-data',
        children=html.Div([
            '拖放文件或',
            html.A('选择文件')
        ]),
        style={
            'width': '100%',
            'height': '60px',
            'lineHeight': '60px',
            'borderWidth': '1px',
            'borderStyle': 'dashed',
            'borderRadius': '5px',
            'textAlign': 'center',
            'margin': '10px'
        },
        multiple=False
    ),
    html.Div(id='output-data')
])

@app.callback(
    Output('output-data', 'children'),
    [Input('upload-data', 'contents')]
)
def update_output(contents):
    if contents is not None:
        # 解析上传的文件内容
        content_type, content_string = contents.split(',')

        # 根据文件内容创建数据帧
        df = pd.read_csv(io.StringIO(base64.b64decode(content_string).decode('utf-8')))

        # 执行多列过滤操作
        filtered_data = df[['column1', 'column2', 'column3']]  # 替换为需要过滤的列名

        # 显示过滤结果
        return html.Table([
            html.Thead(html.Tr([html.Th(col) for col in filtered_data.columns])),
            html.Tbody([
                html.Tr([
                    html.Td(filtered_data.iloc[i][col]) for col in filtered_data.columns
                ]) for i in range(min(len(filtered_data), 10))  # 限制显示的行数
            ])
        ])

    else:
        return ''

if __name__ == '__main__':
    app.run_server(debug=True)