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Python Plotly Dash:如何使用多个数据框列筛选仪表板?_Python_Plotly_Plotly Dash_Plotly Python - Fatal编程技术网

Python Plotly Dash:如何使用多个数据框列筛选仪表板?

Python Plotly Dash:如何使用多个数据框列筛选仪表板?,python,plotly,plotly-dash,plotly-python,Python,Plotly,Plotly Dash,Plotly Python,我有一个使用dash构建的Python仪表板,我想在Investor或Fund列中对其进行筛选 Investor Fund Period Date Symbol Shares Value 0 Rick Fund 3 2019-06-30 AVLR 3 9 1 Faye Fund 2 2015-03-31 MEG 11 80 2 Rick Fund 3 2018-12-31 BAC

我有一个使用
dash
构建的Python仪表板,我想在
Investor
Fund
列中对其进行筛选

  Investor    Fund Period Date Symbol  Shares  Value
0     Rick  Fund 3  2019-06-30   AVLR       3      9
1     Faye  Fund 2  2015-03-31    MEG      11     80
2     Rick  Fund 3  2018-12-31    BAC      10    200
3      Dre  Fund 4  2020-06-30   PLOW       2     10
4     Faye  Fund 2  2015-03-31   DNOW      10    100
5     Mike  Fund 1  2015-03-31    JNJ       1     10
6     Mike  Fund 1  2018-12-31    QSR       4     20
7     Mike  Fund 1  2018-12-31  LBTYA       3     12
换句话说,用户应该能够在同一筛选字段中输入一个或多个投资者和/或一个或多个基金,并且仪表板将相应地更新。因此,我认为我需要改变:

options=[{'label':i,'value':i}用于df['Investor']中的i。unique()]

到类似于
groupby
的地方,但我不是积极的?这是我的密码:

import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd

data = {'Investor': {0: 'Rick', 1: 'Faye', 2: 'Rick', 3: 'Dre', 4: 'Faye', 5: 'Mike', 6: 'Mike', 7: 'Mike'},
        'Fund': {0: 'Fund 3', 1: 'Fund 2', 2: 'Fund 3', 3: 'Fund 4', 4: 'Fund 2', 5: 'Fund 1', 6: 'Fund 1', 7: 'Fund 1'},
        'Period Date': {0: '2019-06-30', 1: '2015-03-31', 2: '2018-12-31', 3: '2020-06-30', 4: '2015-03-31', 5: '2015-03-31', 6: '2018-12-31', 7: '2018-12-31'},
        'Symbol': {0: 'AVLR', 1: 'MEG', 2: 'BAC', 3: 'PLOW', 4: 'DNOW', 5: 'JNJ', 6: 'QSR', 7: 'LBTYA'},
        'Shares': {0: 3, 1: 11, 2: 10, 3: 2, 4: 10, 5: 1, 6: 4, 7: 3},
        'Value': {0: 9, 1: 80, 2: 200, 3: 10, 4: 100, 5: 10, 6: 20, 7: 12}}
df = pd.DataFrame.from_dict(data)

def generate_table(dataframe, max_rows=100):
    return html.Table(
        # Header
        [html.Tr([html.Th(col) for col in dataframe.columns])] +

        # Body
        [html.Tr([
            html.Td(dataframe.iloc[i][col]) for col in dataframe.columns
        ]) for i in range(min(len(dataframe), max_rows))]
    )

app = dash.Dash()
app.layout = html.Div(
    children=[html.H4(children='Investor Portfolio'),
    dcc.Dropdown(
        id='dropdown',
        options=[{'label': i, 'value': i} for i in df['Investor'].unique()],
        multi=True, placeholder='Filter by Investor or Fund...'),
    html.Div(id='table-container')
])

@app.callback(dash.dependencies.Output('table-container', 'children'),
    [dash.dependencies.Input('dropdown', 'value')])

def display_table(dropdown_value):
    if dropdown_value is None:
        return generate_table(df)
    dff = df[df.Investor.str.contains('|'.join(dropdown_value))]
    dff = dff[['Investor', 'Period Date', 'Symbol','Shares', 'Value']]
    return generate_table(dff)

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

诚然,我对Dash还很陌生,但据我所知,您可以通过扩展选项列表,然后在Dash应用程序中显示的
dff
中使用
条件来包括
基金
列,从而实现您想要的目标

  Investor    Fund Period Date Symbol  Shares  Value
0     Rick  Fund 3  2019-06-30   AVLR       3      9
1     Faye  Fund 2  2015-03-31    MEG      11     80
2     Rick  Fund 3  2018-12-31    BAC      10    200
3      Dre  Fund 4  2020-06-30   PLOW       2     10
4     Faye  Fund 2  2015-03-31   DNOW      10    100
5     Mike  Fund 1  2015-03-31    JNJ       1     10
6     Mike  Fund 1  2018-12-31    QSR       4     20
7     Mike  Fund 1  2018-12-31  LBTYA       3     12
这有点暴力,一个更好的解决方案是让Dash知道您选择的选项来自哪些列。但是,只有来自不同列的条目包含相同的字符串时(此处
Investor
Fund
的唯一值并不相同),这才是一个问题


谢谢,我想这可能行得通。不过,如果能够进行某种类型的通用搜索,或者能够在下拉列表中更好地描述这两个字段之间的视觉效果,那就太好了。是的,我同意。如果可以在每个下拉选项中传递列名(例如,
Rick-Investor
),那么这可能会起作用。