https://github.com/persiyanov/streamlit-geodata-visualization

Geospatial data parsing and visualization (Mapbox + Streamlit)
https://github.com/persiyanov/streamlit-geodata-visualization

data-visualization geocoding geospatial mapbox mapbox-geocoding pydeck streamlit visualization

Last synced: 2 months ago
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Geospatial data parsing and visualization (Mapbox + Streamlit)

• Host: GitHub
• URL: https://github.com/persiyanov/streamlit-geodata-visualization
• Owner: persiyanov
• License: mit
• Created: 2022-11-13T19:01:54.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2022-11-17T21:20:06.000Z (over 2 years ago)
• Last Synced: 2024-01-30T09:15:08.840Z (over 1 year ago)
• Topics: data-visualization, geocoding, geospatial, mapbox, mapbox-geocoding, pydeck, streamlit, visualization
• Language: Python
• Homepage:
• Size: 3.5 MB
• Stars: 2
• Watchers: 3
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Geospatial Data Visualization (Streamlit + Mapbox)

## Live Demo

**Available here:** https://streamlit-geodata-visualization-jyiexkhtva-lm.a.run.app/

![](./app-screenshot.png)

## Description

This repo is a demonstration of parsing geo-coordinates from address data using Mapbox.com and visualizing via awesome [Streamlit](https://streamlit.io/) library.

Repo consists of two parts:

1. Geocoding of text addresses using Mapbox.com (see `scripts` folder)

2. Visualization of geocoded data using Streamlit and its pydeck integration (`streamlit_app.py`)

**Dataset**: [NYC-Housing-Data-2003-2019](https://www.openml.org/search?type=data&status=active&sort=match&id=43633)

## Setup

### Docker

1. Run `docker build -t geodata .`

2. Run `docker run -it -p 80:80 geodata`

3. Open http://127.0.0.1:80/

### Virtual Environment

1. Create virtual environment using your favorite tool (e.g. [pyenv](https://github.com/pyenv/pyenv)). I used Python 3.9.15 for development, but code should work for all 3.8+ versions.

2. Run `pip install -r requirements.txt`

3. Run `streamlit run streamlit_app.py`

## Deploy

1. Set up an account on [Google Cloud Platform](https://cloud.google.com/)

2. Install [gcloud cli](https://cloud.google.com/sdk/docs/install)

3. Run `gcloud run deploy` (deployment via Cloud Run)

4. **Note**: make sure to reply `y` when prompted `Allow unauthenticated invocations to [streamlit-geodata-visualization] (y/N)?`