In this talk about Jupyter Notebooks for beginners, I provided a comprehensive tutorial on the tool, covering everything from basic setup to advanced tricks and the plugin ecosystem. Given at PyData Berlin 2017.
In this talk about Jupyter Notebooks for beginners, I provided a comprehensive tutorial on the tool, covering everything from basic setup to advanced tricks and the plugin ecosystem. My goal was to highlight the power of Jupyter Notebooks for collaboration, presentation generation, and reproducibility.
I began by sharing a brief history of the tool, noting that it was forked from IPython in 2014 and its name is a portmanteau of Julia, Python, and R. From there, I walked through the practical aspects, including how to set up the environment, create and run cells, import libraries, and execute shell commands directly within the notebook. I then delved into more advanced features, such as auto-reloading modules, editing tricks for efficiency, and customizing the notebook’s appearance with themes. I also emphasized the importance of using high-quality vector graphics for presentations to ensure your work looks professional.
I also showcased the growing ecosystem of Jupyter extensions, mentioning useful plugins for creating a table of contents, formatting code, and displaying execution times. I included examples of working with data using Pandas and visualizing it with Matplotlib and Seaborn, and I offered tips on how to improve the visual quality of plots. Finally, I discussed the importance of using tools like Docker to create isolated, reproducible environments, which is essential for collaborative teamwork. All the materials and examples I presented are available in a GitHub repository for you to explore.