A minimal Dash app will typically look like this:
This example has not been ported to R yet - showing the Python version instead.
Visit the old docs site for R at: https://community.plotly.com/c/dash/r/21
from dash import Dash, html, dcc, callback, Output, Input
import plotly.express as px
import pandas as pd
df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/gapminder_unfiltered.csv')
app = Dash()
app.layout = [
html.H1(children='Title of Dash App', style={'textAlign':'center'}),
dcc.Dropdown(df.country.unique(), 'Canada', id='dropdown-selection'),
dcc.Graph(id='graph-content')
]
@callback(
Output('graph-content', 'figure'),
Input('dropdown-selection', 'value')
)
def update_graph(value):
dff = df[df.country==value]
return px.line(dff, x='year', y='pop')
if __name__ == '__main__':
app.run(debug=True)
To run the app, copy the above code into a new file named app.py
and type into your terminal the command python app.py
.
Then, go to the http link.
Dash is running on <a href="http://127.0.0.1:8050/">http://127.0.0.1:8050/</a>
* Serving Flask app 'app' (lazy loading)
* Environment: production
WARNING: This is a development server. Do not use it in a production deployment.
Use a production WSGI server instead.
* Debug mode: on
* Running on <a href="http://127.0.0.1:8050">http://127.0.0.1:8050</a> (Press CTRL+C to quit)
Alternatively, you can run the app in a Jupyter Notebook cell.
The next section will cover the main elements of a Dash app. Dash in 20 minutes tutorial!
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