import math from dash import Dash, dcc, html, Input, Output import plotly.express as px import numpy as np import pandas as pd import dash_bootstrap_components as dbc app = Dash(__name__, external_stylesheets=[dbc.themes.BOOTSTRAP]) # generate random normal distributed data for x and y # and store it in a pandas DataFrame df = pd.DataFrame({'y': np.random.normal(loc=0, scale=10, size=1000), 'x': np.random.normal(loc=10, scale=2, size=1000)}) app.layout = html.Div( [ html.H1("Dashboard 2"), dbc.Row( [ dbc.Col( [ dcc.Dropdown( options=["red", "green", "blue"], value="red", id="color", multi=False, ) ], width=6, ), dbc.Col( [ dcc.RangeSlider( min=math.floor(df["y"].min()), max=math.ceil(df["y"].max()), value=[math.floor(df["y"].min()), math.ceil(df["y"].max())], id="range", ) ], width=6, ), ] ), dbc.Row( [ dbc.Col([dcc.Graph(id="graph_1")], width=6), dbc.Col([dcc.Graph(id="graph_2")], width=6), ] ), ], className="m-4", ) @app.callback(Output("graph_1", "figure"), Input("color", "value")) def update_graph_1(dropdown_value_color): fig = px.histogram(df, x="y", color_discrete_sequence=[dropdown_value_color]) fig.update_layout() return fig @app.callback(Output("graph_2", "figure"), Input("range", "value")) def update_graph_2(range): dff = df[(df['y'] > range[0]) & (df['y'] < range[1])] fig = px.scatter(dff, x='x', y='y') fig.update_layout() return fig if __name__ == '__main__': app.run_server(debug=True, port=8000)