Updating DataFrame globally from dropdown callback

Dash Python
1

Hello everyone!

I’m developing a dash app with graphs, sliders, dropdowns, and tables. I feel it is an easy yet efficient framework + library to design interactive web apps (dashboards).

I came across a use case where I need to update the DataFrame based on the input from the dropdown. After digging the internet for a couple of days somehow I managed to do that (in an appropriate way).

I believe that there will be a simple way to achieve my requirement than the one I’m following right now.

This is the sample code that reflects my approach

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

df1 = pd.read_csv('dataset1.csv')
df2 = pd.read_csv('dataset2.csv')
final_df=[df1,df2]

app = dash.Dash(__name__)
app.layout = html.Div(id='container',children=[
    dcc.Dropdown(
                id='user',
                options=[{'label': 'User 1','value': 'u1'},
                         {'label': 'User 2','value': 'u2'},
                         {'label': 'User 3','value': 'u3'}],
                value='u1',
            ),
    dcc.Graph(id='graph'),
],
                     )

@app.callback(
    Output('graph', 'figure'),
    [Input('user', 'value')])
def update_graph_1(user_value) :
    if user_value == 'u1':
        df = final_df[0][final_df[0]['col3 ##categoryCol##'].eq(input_value)]
        fig = (px.line(df, x='col1',y='col2').update_traces(mode='lines+markers'))
        return fig
    elif user_value == 'u2' :
        df = final_df[1][final_df[1]['col3 ##categoryCol##'].eq(input_value)]
        fig = (px.line(df, x='col1',y='col2').update_traces(mode='lines+markers'))
        return fig
    elif user_value == 'u3' :
        df = final_df[3][final_df[3]['col3 ##categoryCol##'].eq(input_value)]
        fig = (px.line(df, x='col1',y='col2').update_traces(mode='lines+markers'))
        return fig

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

FYI, col1, col2 & col3 are the names of the columns I’ve in my dataset where the only col3 is a categorical column rest are numerical columns.

By following the above approach I can able to get the desired result for now. But, I believe this is not the proper way to sort my requirement.

I hope my question is clear and any help here would be greatly appreciated.

Thanks