PyCafe - Vizro - Interactive Iris Dataset Analysis with Click and Selection Feedback

app.py
requirements.txt
app.py
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import dash
import json
from dash import dcc, html, ctx
from dash.dependencies import Input, Output, State
import plotly.express as px
import pandas as pd

# Sample data
df = px.data.iris()

# Initialize the app
app = dash.Dash(__name__, suppress_callback_exceptions=True)

# Define the layout of the app
app.layout = html.Div(children=[
    html.H1(children='Dash App with a Graph and Filter'),

    # Dropdown filter
    dcc.Dropdown(
        id='variable-dropdown',
        options=["setosa", "virginica", "versicolor"],
        multi=False,
        value="setosa"
    ),

    html.Div([
        # Source interaction
        html.Div([
            dcc.Store(id="store_1", data=0),
            dcc.Graph(
                id="graph_1",
                figure=px.scatter(df, x="sepal_length", y="petal_length", color="species", custom_data="species", title="Source interaction refreshed 0 times"),
            ),
        ], style={"flex": "2"}),

        # JSON output container
        html.Div([
            html.H4("clickData Output"),
            html.Pre(id="json_clickData_output", style={
                "whiteSpace": "pre-wrap",
                "wordBreak": "break-word",
                "background": "#f8f8f8",
                "padding": "10px",
                "border": "1px solid #ccc",
                "borderRadius": "5px",
                "height": "300px",
                "overflowY": "scroll"
            })
        ], style={"flex": "1", "paddingLeft": "20px"}),

        html.Div([
            html.H4("selectedData Output"),
            html.Pre(id="json_selectedData_output", style={
                "whiteSpace": "pre-wrap",
                "wordBreak": "break-word",
                "background": "#f8f8f8",
                "padding": "10px",
                "border": "1px solid #ccc",
                "borderRadius": "5px",
                "height": "300px",
                "overflowY": "scroll"
            })
        ], style={"flex": "1", "paddingLeft": "20px"}),

    ], style={
        "display": "flex",
        "flexDirection": "row",
        "alignItems": "flex-start",
        "marginBottom": "30px"
    }),

    html.Div([
        # clickData target
        dcc.Store(id="store_2", data=0),
        dcc.Graph(
            id="graph_2",
            figure=px.scatter(df, x="sepal_length", y="petal_length", color="species", title="clickData target refreshed 0 times"),
        ),

        # selectedData target
        dcc.Store(id="store_3", data=0),
        dcc.Graph(
            id="graph_3",
            figure=px.scatter(df, x="sepal_length", y="petal_length", color="species", title="selectedData targetc refreshed 0 times"),
        )
    ],
    style={
        "display": "flex",
        "flexDirection": "row",
        "justifyContent": "space-between",
        "alignItems": "center"
    })
])


@app.callback(
    Output('graph_1', 'figure'),
    Output('store_1', 'data'),
    Input('variable-dropdown', 'value'),
    State('store_1', 'data'),
    prevent_callback_call=True,
)
def update_graph_1(selected_variable, store):
    if not ctx.triggered_id:
        raise dash.exceptions.PreventUpdate

    filtered_df = df[df['species'] == selected_variable]
    fig = px.scatter(filtered_df, x="sepal_length", y="petal_length", color="species", custom_data="species", title=f"Source interaction refreshed {store + 1} times")
    return fig, store + 1


@app.callback(
    Output('json_clickData_output', 'children'),
    Output('json_selectedData_output', 'children'),
    Input('graph_1', 'clickData'),
    Input('graph_1', 'selectedData'),
)
def display_click_selected_data(click_data, selected_data):
    return json.dumps(click_data, indent=2), json.dumps(selected_data, indent=2)


@app.callback(
    Output('graph_2', 'figure'),
    Output('store_2', 'data'),
    Input('graph_1', 'clickData'),
    State('store_2', 'data'),
    prevent_callback_call=True,
)
def update_graph_2(click_data, store):
    if not ctx.triggered_id:
        raise dash.exceptions.PreventUpdate

    if click_data:
        clicked_point = click_data['points'][0]['customdata'][0]
        filtered_df = df[df['species'].isin([clicked_point])]
    else:
        filtered_df = df

    fig = px.scatter(filtered_df, x="sepal_width", y="petal_width", color="species", title=f"clickData target refreshed {store + 1} times")
    return fig, store + 1


@app.callback(
    Output('graph_3', 'figure'),
    Output('store_3', 'data'),
    Input('graph_1', 'selectedData'),
    State('store_3', 'data'),
    prevent_callback_call=True,
)
def update_graph_2(selected_data, store):
    if not ctx.triggered_id:
        raise dash.exceptions.PreventUpdate

    if selected_data:
        selected_points = [point['customdata'][0] for point in selected_data['points']]
        filtered_df = df[df['species'].isin(selected_points)]
    else:
        filtered_df = df

    fig = px.scatter(filtered_df, x="sepal_width", y="petal_width", color="species", title=f"selectedData target refreshed {store + 1} times")
    return fig, store + 1


# Run the app
app.run(debug=True)
Py.Cafe

dash-clickData-vs-selectedData-on-graph-refresh

Interactive Iris Dataset Analysis with Click and Selection Feedback
