从带有 Plotly Dash for Python 的回调中将 Pandas DataFrame 作为 data_table 返回 [英] Return a Pandas DataFrame as a data_table from a callback with Plotly Dash for Python

问题描述

我想读取一个 .csv 文件并返回一个 groupby 函数作为回调，以显示为带有dash_table"库的简单数据表.@Lawliet 的有用答案显示了如何使用dash_table_experiments"库来做到这一点.这就是我卡住的地方:

I would like to read a .csv file and return a groupby function as a callback to be displayed as a simple data table with "dash_table" library. @Lawliet's helpful answer shows how to do that with "dash_table_experiments" library. Here is where I’m stuck:

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

df = pd.read_csv(
        'https://gist.githubusercontent.com/chriddyp/'
        'c78bf172206ce24f77d6363a2d754b59/raw/'
        'c353e8ef842413cae56ae3920b8fd78468aa4cb2/'
        'usa-agricultural-exports-2011.csv')

app = dash.Dash()
application = app.server

app.layout = html.Div([
    dash_table.DataTable(
        id = 'datatable',        
    ),

    html.Div([
        html.Button(id='submit-button',                
                children='Submit'
    )
    ]),    

])

@app.callback(Output('datatable','data'),
            [Input('submit-button','n_clicks')],
                [State('submit-button','n_clicks')])

def update_datatable(n_clicks,csv_file):            
    if n_clicks:                            
        dfgb = df.groupby(['state']).sum()
        return dfgb.to_dict('rows')

if __name__ == '__main__':
    application.run(debug=False, port=8080)

推荐答案

当您尝试将回调 Output 组件注册为 DataTable 时，所有必需的/强制的DataTable 组件的属性应该在回调中更新并返回.在您的代码中，您只更新 DataTable.data 而不是 DataTable.column，一种简单的方法是返回整个 Datatable 组件，它是预先填充了所有必需的属性值.

When you are trying to register the callback Output component as a DataTable, all the required / mandatory attributes for the DataTable component should be updated in the callback and returned. In your code, you are updating just DataTable.data and not DataTable.column, one easy way is to return the whole Datatable component which is prepopulated with all the required attribute values.

这是一个例子，

import dash_html_components as html
import dash_core_components as dcc
import dash
import dash_table
import pandas as pd
import dash_table_experiments as dt

app = dash.Dash(__name__)

#data to be loaded
data = [['Alex',10],['Bob',12],['Clarke',13],['Alex',100]]
df = pd.DataFrame(data,columns=['Name','Mark'])

app.layout = html.Div([
    dt.DataTable(
            rows=df.to_dict('records'),
            columns=df.columns,
            row_selectable=True,
            filterable=True,
            sortable=True,
            selected_row_indices=list(df.index),  # all rows selected by default
            id='2'
     ),
    html.Button('Submit', id='button'),
    html.Div(id="div-1"),
])


@app.callback(
    dash.dependencies.Output('div-1', 'children'),
    [dash.dependencies.Input('button', 'n_clicks')])
def update_output(n_clicks):

    df_chart = df.groupby('Name').sum()

    return [
        dt.DataTable(
            rows=df_chart.to_dict('rows'),
            columns=df_chart.columns,
            row_selectable=True,
            filterable=True,
            sortable=True,
            selected_row_indices=list(df_chart.index),  # all rows selected by default
            id='3'
        )
    ]

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

看起来 dash-table-experiments 已被弃用.

编辑 1:这是使用 dash_tables

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

df = pd.read_csv(
        'https://gist.githubusercontent.com/chriddyp/'
        'c78bf172206ce24f77d6363a2d754b59/raw/'
        'c353e8ef842413cae56ae3920b8fd78468aa4cb2/'
        'usa-agricultural-exports-2011.csv')

app = dash.Dash()
application = app.server

app.layout = html.Div([
    dt.DataTable(
        id = 'dt1', 
        columns =  [{"name": i, "id": i,} for i in (df.columns)],

    ),
    html.Div([
        html.Button(id='submit-button',                
                children='Submit'
        )
    ]),    

])

@app.callback(Output('dt1','data'),
            [Input('submit-button','n_clicks')],
                [State('submit-button','n_clicks')])

def update_datatable(n_clicks,csv_file):            
    if n_clicks:                            
        dfgb = df.groupby(['state']).sum()
        data_1 = df.to_dict('rows')
        return data_1

if __name__ == '__main__':
    application.run(debug=False, port=8080)

另一种方式:返回整个DataTable

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

df = pd.read_csv(
        'https://gist.githubusercontent.com/chriddyp/'
        'c78bf172206ce24f77d6363a2d754b59/raw/'
        'c353e8ef842413cae56ae3920b8fd78468aa4cb2/'
        'usa-agricultural-exports-2011.csv')

app = dash.Dash()
application = app.server

app.layout = html.Div([
    html.Div(id="table1"),

    html.Div([
        html.Button(id='submit-button',                
                children='Submit'
    )
    ]),    

])

@app.callback(Output('table1','children'),
            [Input('submit-button','n_clicks')],
                [State('submit-button','n_clicks')])

def update_datatable(n_clicks,csv_file):            
    if n_clicks:                            
        dfgb = df.groupby(['state']).sum()
        data = df.to_dict('rows')
        columns =  [{"name": i, "id": i,} for i in (df.columns)]
        return dt.DataTable(data=data, columns=columns)


if __name__ == '__main__':
    application.run(debug=False, port=8080)

我参考了这个例子:https://github.com/plotly/dash-table/blob/master/tests/cypress/dash/v_copy_paste.py#L33

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