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