A Brief History¶
- 2001: IPython project started by Fernando Pérez.
- Originally: An enhanced interactive Python shell.
- 2014: Jupyter Project born (JUlia, PYthon, R).
- Goal: Language-agnostic interactive computing.
Modern Data Science loves Jupyter¶
- Integrates code, results, narrative, and visualization.
- Open-source & community-driven.
- Used in:
- Data Science & Machine Learning
- Scientific Computing
- Education & Communication
In [2]:
import matplotlib.pyplot as plt
import numpy as np
x = np.linspace(0, 10, 100)
y = np.sin(x)
plt.plot(x, y)
plt.title("Inline Plot Example")
plt.xlabel("x")
plt.ylabel("sin(x)")
plt.show()
The Jupyter Ecosystem Today¶
- JupyterLab (Single-User)
- JupyterHub (multi-user)
- JupyterBook
- nbconvert (PDF, slides, HTML export)
- Interactive Widgets (
ipywidgets
) - Supports 100+ languages
Jupyter in Scientific Research¶
- Integrate findings with Narrative.
- Climate modeling
- Machine learning in Earth Sciences
- Computational physics and biology
- Reproducible workflows
Customize it for you!¶
Can change things:
- Theme (dark,light)
- Autocomplete (Let's go to settings)
Ton's of Extensions and Plug-ins¶
- git
- Spellchecker (i needz)
- Awesome List of Extensions
Summary¶
- Jupyter is more than just a notebook.
- Supports open, reproducible, interactive, and visual computing.
- Widely adopted in academia and industry.
- You'll use it throughout this course!