LigPlot+ vs. PyQtGraph vs. broot vs. python-docx Comparison Chart

PyQtGraph is a pure-python graphics and GUI library built on PyQt/PySide and NumPy. It is intended for use in mathematics/scientific/engineering applications. Despite being written entirely in python, the library is very fast due to its heavy leverage of NumPy for number crunching and Qt's GraphicsView framework for fast display. PyQtGraph is distributed under the MIT open-source license. Basic 2D plotting in interactive view boxes. Line and scatter plots. Data can be panned/scaled by mouse. Fast drawing for real-time data display and interaction. Displays most data types (int or float; any bit depth; RGB, RGBA, or luminance). Functions for slicing multidimensional images at arbitrary angles (great for MRI data). Rapid update for video display or real-time interaction. Image display with interactive lookup tables and level control. Mesh rendering with isosurface generation. Interactive viewports rotate/zoom with mouse. Basic 3D scenegraph for easier programming.

python-docx is a Python library for creating and updating Microsoft Word (.docx) files. Paragraphs are fundamental in Word. They’re used for body text, but also for headings and list items like bullets. You’re free to specify both width and height, but usually, you wouldn’t want to. If you specify only one, python-docx uses it to calculate the properly scaled value of the other. This way the aspect ratio is preserved and your picture doesn’t look stretched. If you don’t know what a Word paragraph style is you should definitely check it out. Basically, it allows you to apply a whole set of formatting options to a paragraph at once. python-docx allows you to create new documents as well as make changes to existing ones. Actually, it only lets you make changes to existing documents; it’s just that if you start with a document that doesn’t have any content, it might feel at first like you’re creating one from scratch.