Jumping into Jupyter Notebooks
summary
Jupyter notebooks show exactly how to mix narrative and runnable code using Google Colab, GitHub and kernels for Python R or Julia and libraries like pandas + folium map and plotly to clean datasets and render interactive maps from Montreal crime CSVs the demo times a simulation of 1,000,000 dice rolls, implements a Manhattan distance recommender, runs Vader sentiment analysis, builds widgets and a choose‑your‑own‑adventure UI and surfaces problems like out‑of‑order execution while the maps and widgets actually work live in the notebook
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chapters (18)
- 0:00Start
- 0:50Jumping to Jupiter Notebooks
- 4:19Introduction
- 7:36Spreadsheets
- 8:52Mathematica Notebooks
- 11:56Netflix
- 12:38Jupiter Notebooks Infrastructure at Netflix
- 15:52Markdown
- 16:47Latex
- 17:49Execute Shell Commands
- 18:12Magic Commands
- 20:45The Manhattan Distance
- 22:04Sentiment Analysis
- 25:23Widgets
- 26:47Text Field
- 29:49Montreal Crime Data
- 34:43Outro
- 35:53Best Way To Learn about Jupiter Notebooks
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