Search Results for "plotting"

...By combining theory with hands-on plotting exercises, the book helps readers build both analytical and presentation skills. Overall, it is intended as a foundational guide for anyone seeking to produce professional-quality data visualizations.

The Scientific Visualization book is a freely available open-access textbook that introduces how to produce effective scientific visualizations using Python, focusing especially on leveraging the popular plotting library Matplotlib (and related tools). It goes beyond simple plotting tutorials and emphasizes design principles: how to choose colors, layout subplots, annotate graphs, and present data in a way that is both accurate and visually compelling. As such, it serves as a guide for researchers, data scientists, and academic authors who need to create publication-quality figures or explanatory graphics, rather than quick exploratory plots. ...

CompPad is a LibreOffice extension that provides live mathematical and engineering calculations within a Writer document. It is intended to provide a free / open-source alternative to Mathcad, but is not intended to be a Mathcad clone. Rather, I hope it might prove more flexible and extensible, and that it might encourage other free / open-source alternatives to a proprietary engineering "Killer App."

PyMathProg is a Python reincarnation of AMPL and GNU MathProg modeling language, implemented in pure Python, connecting to GLPK via swiglpk. Create, optimize, report, change and re-optimize your model with Python, easily integrate database, plotting, etc.

The Matplotlib tutorial repository is designed as a hands-on learning resource to help users — especially Python beginners — get started with Matplotlib for creating plots and charts. It provides a sequence of example scripts and notebooks that cover fundamental plotting tasks: line graphs, histograms, scatter plots, bar charts, customizing axes, labels, legends, and styling. This makes it ideal for someone learning data analysis or exploratory data visualization for the first time and needing concrete, runnable examples rather than abstract explanations. As the tutorial builds progressively, learners can gradually advance from simple static plots to more complex visualizations, learning how to control figure size, add multiple subplots, adjust plot aesthetics, and handle different data types. ...