Python Data Science Cheat Sheet - Jupyter Notebook

The Python Data Science Cheat Sheet - Jupyter Notebook is a single-page quick-reference resource for Python data science learners and part of the widely circulated Chinese-community "Python Data Science Cheat Sheet" series. The original series was produced by the online data education platform DataCamp and later translated and compiled by the Chinese translator Dainiao (iamseancheney), comprising more than a dozen sheets covering Python basics, data importing, Jupyter Notebook, NumPy, Pandas, SciPy, Matplotlib, Seaborn, Bokeh, Scikit-Learn, Keras, and Spark SQL/RDD. This volume focuses specifically on Jupyter Notebook, the most commonly used interactive programming environment in data science: it organizes code, output, charts, and explanatory text into a single document, so you can write, run, and revise as you go. The cheat sheet lists high-frequency operations in categorized tables and short code snippets under practical headings such as "Installation and Launch," "Interface and Cell Operations," "Common Shortcuts," "Magic Commands," and "Export and Sharing," saving the time spent digging through documentation or search engines. It does not explain underlying principles or proceed chapter by chapter; rather, it is meant to be kept at hand for quick reference while actually working. This volume suits readers new to Jupyter Notebook who need a clear operational index, as well as experienced users who cannot remember specific shortcuts and command-line parameters. As open-source electronic material, it has no formal ISBN or price; please respect the original author's licensing terms when reading and sharing.