Python Data Science Cheat Sheet - Matplotlib Plotting

Python Data Science Cheat Sheet - Matplotlib Plotting is a Chinese translation in DataCamp's official Cheat Sheet series and one of the visualization-themed installments in the larger "Python Data Science Cheat Sheet" set. Matplotlib is the most fundamental and widely used two-dimensional plotting library in the Python ecosystem: it turns NumPy arrays and Pandas data directly into publication-quality line plots, scatter plots, bar charts, histograms, pie charts, box plots, heatmaps, and more, and can save them in a variety of image formats, making it a general-purpose tool for presenting the results of data analysis and scientific computing. This cheat sheet is a one-page reference designed for visual memory: taking the PyPlot plotting workflow as its main thread, it summarizes the object hierarchy (Figure, Axes, Axis, and the various Artist objects), common plotting functions, parameters, and plot styles, so that learners or coders can quickly locate syntax. The Chinese version was translated by community volunteers and circulates as PDFs or images on platforms such as GitHub, often bundled with more than a dozen other cheat sheets covering NumPy, Pandas, Seaborn, Scikit-Learn, and the rest. Most are shared free of charge, and no stand-alone published edition has been identified, so there is no publisher, ISBN, or other publication information. The content here is the "Matplotlib Plotting" sheet from the set, focused on plotting basics and common chart syntax rather than more complex interactive visualization tools. It works well as a handy reference at the introductory stage of data analysis, and is best used alongside a tutorial book or online course.