bobbyiliev/materialize-jupyter-in-vs-code

How to show graph in VS Code with Jupyter and Materialize

How to Show Graphs in VS Code with Matplotlib, Jupyter, Materialize, and Plotly

This is a simple example of how to show graphs in VS Code using Matplotlib, Jupyter, Materialize, and Plotly.

Requirements

• Visual Studio Code
• Python
• Materialize

Install the Required Extensions in VS Code

• Install the Jupyter extension in VS Code.
• Install the Python extension in VS Code.

Create a Virtual Environment

• Create a new virtual environment:

  python -m venv .venv
  

• Activate the virtual environment:

  • On Windows:

    .venv\Scripts\Activate.ps1
    

  • On macOS and Linux:

    source .venv/bin/activate
    

• Install the necessary packages:

  pip install psycopg2-binary matplotlib plotly pandas python-dotenv nbformat
  

Create a .env File

Copy the .env.example file to a new file named .env and fill in the necessary information.

Create Some Demo Data

Run the SQL statements in the demo.sql file to create the necessary table, view, and insert some data.

Demo 1: Matplotlib Graph

This demo will show you how to create and display a graph using Matplotlib in VS Code.

Run the Demo

1. Open the demo_matplotlib.py file and run the code.

2. Right-click on the code and select "Run in Interactive Window" -> "Run current file in Interactive Window".

3. VS Code will open a new tab with the graph:

   

4. To display your own graph, change the SQL query in the demo_matplotlib.py file to query your own data and the Matplotlib code to display the graph you want to show.

Demo 2: Plotly with Pandas

This demo will show you how to create and display a graph using Plotly and Pandas in VS Code. Plotly provides interactive and visually appealing charts, which can be a great alternative to Matplotlib.

Run the Demo

1. Open the demo_plotly.py file in VS Code.

2. Right-click on the code and select "Run in Interactive Window" -> "Run current file in Interactive Window".

3. VS Code will open a new tab or your web browser with the interactive graph.

4. To display your own graph, change the SQL query in the demo_plotly.py file to query your own data and the Plotly code to display the graph you want to show.