剧情Dash表回调 [英] Plotly Dash table callback

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问题描述

我正在尝试获取滑块，用户输入和工作表之间的依赖关系.我尝试输出数据并使用回调对其进行更新.建议我仅在回调中创建表，然后使用"Div".定义其在显示器中的位置.

I am trying to get the dependency between a slider, user input and a table to work. I have tried outputting the data and using a callback to update it. I was advised to just create the table in a callback and just use a "Div." to define its location in the display.

其他信息:

  • 表是使用dash_table库从pandas DataFrame创建的.
  • 数据采用字典格式.
  • 其中变量threshold是由用户输入(滑块或输入)调整的值
  • table is created from a pandas DataFrame, using dash_table library.
  • data is in dictionary format.
  • with a the variable threshold being the value adjusted by user input (slider or input)

如果有人能帮助我找出表格未显示的原因，我将不胜感激?

I would be grateful if someone could help me find out why the table is not displaying?

这是我的代码:


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

threshold = 0.5
################################################################
###################### Table Data ##############################
################################################################

metrics_index = ["AUC", "Accuracy", "Kappa", "Sensitivity (Recall)", "Specificity", "Precision", "F1"]

algo_columns = ["Test-SVM+Naïve B", "RF"]

table_data = {"AUC": [threshold * 0.8, threshold * 0.83],
              "Accuracy": [threshold * 0.85, threshold * 0.86],
              "Kappa": [threshold * 0.66, threshold * 0.69],
              "Sensitivity (Recall)": [threshold * 0.82, threshold * 0.83],
              "Specificity": [threshold * 0.78, threshold * 0.79],
              "Precision": [threshold * 0.78, threshold * 0.79],
              "F1": [threshold * 0.81, threshold * 0.82]}

data = [i for i in table_data]
table = pd.DataFrame(columns=algo_columns, index=metrics_index, data=[table_data[i] for i in metrics_index])
# display(table)


################################################################
########################  Body  ################################
################################################################


body = dbc.Container(
    [
        dbc.Row(
            [
                dbc.Col(
                    [
                        html.H2("Slider + Manual entry test"),
                        dcc.Slider(
                            id='my-slider',
                            min=0,
                            max=1,
                            step=0.01,
                            marks={"0": "0", "0.5": "0.5", "1": "1"},
                            value=threshold
                        ),
                        html.Div(id='update-table')
                    ]
                ),
                dbc.Col(
                    [
                        html.Div(
                            [
                                html.Div(
                                    dcc.Input(id='input-box', type='float', max=0, min=1, step=0.01, value=threshold)
                                    ),
                                 html.Div(id='slider-output-container')
                            ]
                        )
                    ]
                )
            ]
        )
    ]
)

app = dash.Dash(__name__, external_stylesheets=[dbc.themes.BOOTSTRAP])

app.layout = html.Div([body])


##############################################################
######################## callbacks ###########################
##############################################################

@app.callback(
    dash.dependencies.Output('slider-output-container', 'children'),
    [dash.dependencies.Input('my-slider', 'value')]
)
def update_output(value):
    threshold = float(value)
    return threshold


# call back for slider to update based on manual input
@app.callback(
    dash.dependencies.Output(component_id='my-slider', component_property='value'),
    [dash.dependencies.Input('input-box', 'value')]
)
def update_output(value):
    threshold = float(value)
    return threshold


# call back to update table

@app.callback(
    dash.dependencies.Output('update-table', 'children'),
    [dash.dependencies.Input('my-slider', 'value')]
)
def update_output(value):
    threshold = float(value)
    table_data = {"AUC": [threshold * 0.8, threshold * 0.83],
                  "Accuracy": [threshold * 0.85, threshold * 0.86],
                  "Kappa": [threshold * 0.66, threshold * 0.69],
                  "Sensitivity (Recall)": [threshold * 0.82, threshold * 0.83],
                  "Specificity": [threshold * 0.78, threshold * 0.79],
                  "Precision": [threshold * 0.78, threshold * 0.79],
                  "F1": [threshold * 0.81, threshold * 0.82]}


    return dash_table.DataTable(
                            id='update-table',
                            data= table_data.to_dict('records'),
                            columns=[{'id': x, 'name': x} for x in table.columns]
                )


if __name__ == "__main__":
    app.run_server()

推荐答案

[屏幕截图表实时动态编辑] 

import dash
import dash_bootstrap_components as dbc
import dash_core_components as dcc
import dash_html_components as html
import dash_table
import pandas as pd

from dash.dependencies import Input, Output

threshold = 0.5
################################################################
###################### Table Data ##############################
################################################################

metrics_index = [
    "AUC",
    "Accuracy",
    "Kappa",
    "Sensitivity (Recall)",
    "Specificity",
    "Precision",
    "F1",
]

algo_columns = ["Test-SVM+Naïve B", "RF"]

table_data = {
    "AUC": [threshold * 0.8, threshold * 0.83],
    "Accuracy": [threshold * 0.85, threshold * 0.86],
    "Kappa": [threshold * 0.66, threshold * 0.69],
    "Sensitivity (Recall)": [threshold * 0.82, threshold * 0.83],
    "Specificity": [threshold * 0.78, threshold * 0.79],
    "Precision": [threshold * 0.78, threshold * 0.79],
    "F1": [threshold * 0.81, threshold * 0.82],
}

data = [i for i in table_data]
table = pd.DataFrame(
    columns=algo_columns,
    index=metrics_index,
    data=[table_data[i] for i in metrics_index],
)
# display(table)


################################################################
########################  Body  ################################
################################################################


body = dbc.Container(
    [
        dbc.Row(
            [
                dbc.Col(
                    [
                        html.H2("Slider + Manual entry test"),
                        dcc.Slider(
                            id="my-slider",
                            min=0,
                            max=1,
                            step=0.01,
                            marks={"0": "0", "0.5": "0.5", "1": "1"},
                            value=threshold,
                        ),
                        html.Div(id="update-table"),
                    ]
                ),
                dbc.Col(
                    [
                        html.Div(
                            [
                                html.Div(
                                    dcc.Input(
                                        id="input-box",
                                        max=0,
                                        min=1,
                                        step=0.01,
                                        value=threshold,
                                    )
                                ),
                                html.Div(id="slider-output-container"),
                            ]
                        )
                    ]
                ),
            ]
        )
    ]
)

app = dash.Dash(__name__, external_stylesheets=[dbc.themes.BOOTSTRAP])

app.layout = html.Div([body])


##############################################################
######################## callbacks ###########################
##############################################################


@app.callback(
    dash.dependencies.Output("slider-output-container", "children"),
    [dash.dependencies.Input("my-slider", "value")],
)
def update_output(value):
    threshold = float(value)
    return threshold


# call back for slider to update based on manual input
@app.callback(
    dash.dependencies.Output(component_id="my-slider", component_property="value"),
    [dash.dependencies.Input("input-box", "value")],
)
def update_output(value):
    threshold = float(value)
    return threshold


# call back to update table


@app.callback(
    dash.dependencies.Output("update-table", "children"),
    [dash.dependencies.Input("my-slider", "value")],
)
def update_output(value):
    threshold = float(value)
    table_data = pd.DataFrame.from_dict(
        {
            "AUC": [threshold * 0.8, threshold * 0.83],
            "Accuracy": [threshold * 0.85, threshold * 0.86],
            "Kappa": [threshold * 0.66, threshold * 0.69],
            "Sensitivity (Recall)": [threshold * 0.82, threshold * 0.83],
            "Specificity": [threshold * 0.78, threshold * 0.79],
            "Precision": [threshold * 0.78, threshold * 0.79],
            "F1": [threshold * 0.81, threshold * 0.82],
        }
    )

    return html.Div(
        [
            dash_table.DataTable(
                data=table_data.to_dict("rows"),
                columns=[{"id": x, "name": x} for x in table_data.columns],
            )
        ]
    )


if __name__ == "__main__":
    app.run_server(host="0.0.0.0", port=8050, debug=True, dev_tools_hot_reload=True)

我尝试过&似乎在上面的代码稍作修改的情况下工作；我必须进行的更改是:

I tried this out & seems to be working w/ slightly modified code above; the changes I had to make were:

  1. 将dict table_data转换为数据框(这使.to_dict()方法是pd.DataFrame方法有效！)
  1. Transform dict table_data into a dataframe (this allows the .to_dict() method which is a pd.DataFrame method to work!)

    table_data = pd.DataFrame.from_dict(
        {
            "AUC": [threshold * 0.8, threshold * 0.83],
            "Accuracy": [threshold * 0.85, threshold * 0.86],
            "Kappa": [threshold * 0.66, threshold * 0.69],
            "Sensitivity (Recall)": [threshold * 0.82, threshold * 0.83],
            "Specificity": [threshold * 0.78, threshold * 0.79],
            "Precision": [threshold * 0.78, threshold * 0.79],
            "F1": [threshold * 0.81, threshold * 0.82],
        }
    )

  1. 也在update_output回调fxn中:

  • A.将df .to_dict方法调用
    • 的记录"更改为行"
  • B.您使用table而不是table_data作为列参数
  • C.在这里删除id Dash参数的使用，因为它已经在布局中
  • A. change 'records' to 'rows' for df .to_dict method call
  • B. you had table instead of table_data for the columns param
  • C. remove the use of the id Dash param here, b/c it's already in the layout

    return html.Div(
        [
            dash_table.DataTable(
                data=table_data.to_dict("rows"),
                columns=[{"id": x, "name": x} for x in table_data.columns],
            )
        ]
    )

  1. 好像您已切换了最大和最小！ (最大为零不会留下很多可能的输入！[实际上，没有..])；放置小数点和匹配精度也很重要，以防万一.

                                html.Div(
                                    dcc.Input(
                                        id="input-box",
                                        max=1.00,
                                        min=0.00,
                                        step=0.01,
                                        value=threshold,
                                        type="number"
                                    )
                                ),

这篇关于剧情Dash表回调的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！

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