如何返回由 2 个下拉列表更新的数据表作为 Plotly Python 中的输入 [英] How to return a datatable updated by 2 dropdowns as inputs in Plotly Python

问题描述

如标题所示，我正在创建一个仅包含数据表的绘图仪表板.将有 2 个下拉列表作为输入，数据表将根据下拉列表更新.如何设置布局和回调?

As titled, i am creating a plotly dashboard with a data-table only. There will be 2 drop-downs as inputs, and the data-table will update according to the drown-downs. How do I set the layout and callbacks?

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(data, header=0, encoding = 'utf8')

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

dropdown = html.Div([html.Label('district'),
             dcc.Dropdown(id='dropdown_d',
                          options=[{'label': i, 'value': i} for i in df["district"].unique()], value='none'),
             html.Label('address'),
             dcc.Dropdown(id='dropdown_a',
                          options=[{'label': i, 'value': i} for i in df["address"].unique()], value='none')])

final_table = html.Div([dash_table.DataTable(id="final_table")])

app.layout = html.Div([dropdown, final_table])

@app.callback(Output('final_table', 'data'),
          [Input('dropdown_d', 'value'),
           ])

def update_table(selected_value):
    df = pd.read_csv(data, header=0, encoding = 'utf8')
    df_updated = df[df["district"] == selected_value]
    columns = [{'name': i, 'id': i} for i in df_updated.columns]
    data = df.to_dict('records')
    return columns, data

if __name__ == "__main__":
    app.run_server(debug=True, port=8055)

这是我能得到的最远的距离.上面的代码只是尝试从 1 个下拉值更新数据表，但我的目标是更新 2 个下拉值.

This is the farthest i can get. The code above is only trying to update the data-table from 1 dropdown value, but my goal is to update by 2 dropdown values.

非常感谢任何帮助.如果需要数据文件，这里是数据的链接.

any help is very much appreciated. in case the data file is needed, here is the link to the data.

推荐答案

这是工作代码的片段，我添加了注释以供澄清，

Here is the snippet of the working code, I have added comments for clarification,

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://elartedm.com/wp-content/uploads/2020/03/data_hk.csv", header=0, encoding = 'utf8')

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

dropdown = html.Div([
    html.Label('district'),
    dcc.Dropdown(id='dropdown_d1', options=[{'label': i, 'value': i} for i in df["District"].unique()], value=None),
    html.Label('address'),
    dcc.Dropdown(id='dropdown_d2', options=[], value=None)
])


#its better to have a Div here so that you can update the entire div in the callback and add the necessary properties in the callback
final_table = html.Div(id="final_table")

app.layout = html.Div([dropdown, final_table])


#callback to update second dropdown based on first dropdown
#This callback is used to update the second dropdown based on the value selected in the first dropdown so that its dynamically updated (this is a good  practice rather than having a static list of options).
@app.callback(Output('dropdown_d2', 'options'),
          [
            Input('dropdown_d1', 'value'),
          ])
def update_dropdown_2(d1):
    print(d1)
    if(d1 != None):
        df_filtered = df[(df["District"]==d1)]
        return [{'label': i, 'value': i} for i in df_filtered["Address"].unique()]
    else:
        return []


#this callback to update the final table should be based on both the input dropdown values, so the input parameters are two dropdown_d1, dropdown_d2
#based on these values filter the dataframe and update the table
#since dataframe is a global declaration you don't need to again consume it here.
@app.callback(Output('final_table', 'children'),
          [
            Input('dropdown_d1', 'value'),
            Input('dropdown_d2', 'value'),
          ])
def update_table(d1, d2):

    if(d1 != None and d2 != None):
        df_filtered = df[(df["District"]==d1) & (df["Address"]==d2)]

        return [dt.DataTable(
            id='table',
            columns=[{"name": i, "id": i} for i in df_filtered.columns],
            data=df_filtered.to_dict('records'),
        )]
    else:
        print("none")
        return []


if __name__ == "__main__":
    app.run_server(debug=True, port=8055)

希望有帮助.

这篇关于如何返回由 2 个下拉列表更新的数据表作为 Plotly Python 中的输入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！