This Dash app updates real-time visual analytics by constantly querying a remote Omnisci(MapD) SQL Engine.

The public dataset used in this app, "flight_2008_10k", includes every single record of US airline flights known by the Bureau of Transportation Statistics from 2008-01-03 to 2008-01-07. By default, it can be loaded from the insert_sample_data script during the Omnisci server installation. A jupyter notebook has been included to showcase tabular structure and query results from this dataset.

• Python 3
• Omnisci server installation Guide to install Omnisci

To run this app, you will need a self-hosted Omnisci SQL engine running on localhost:6274 with the default logins. follow this guide to install a test database locally by dockerfile.

We suggest you to create a virtual environment for running this app with Python 3. Clone this repository and open your terminal/command prompt in the root folder.

git clone https://github.com/plotly/dash-sample-apps.git
cd dash-sample-apps/apps/dash-mapd-demo
python3 -m virtualenv venv

In Unix system:

source venv/bin/activate

In Windows:

venv\Scripts\activate

Install all required packages by running:

pip install -r requirements.txt

Run this app locally by:

python app.py

Click on individual state from choropleth map to visualize state-specific flight delays in other plots and datatable, drag along time-series, click on single bar or drag along scatters to know flight details in the table.

• Dash
• Omnisci Core
• PymapD Python Client
• Inspired by Omnisci Demo app.