Draw Rectangles in Matplotlib with Rectangle and add_patch
Draw Matplotlib rectangles with Rectangle, add_patch, data coordinates, styling, rotation, image boxes, zorder, and readable limits.
Python Blog: Tutorials, Fixes, and Projects
Browse practical Python tutorials, error fixes, library guides, data science examples, and project ideas from Python Pool.
Matplotlib Aspect Ratio: set_aspect() and set_box_aspect()
Control Matplotlib plot aspect ratios with set_aspect(), axis(‘equal’), imshow(), set_box_aspect(), and figure sizing.
Check if a NumPy Array Is Empty: size, shape, and Safe Tests
Check whether a NumPy array is empty with size, avoid ambiguous truth-value errors, distinguish zero-size shapes from NaN values, and handle dimensions explicitly.
NumPy arctan2(): Angles, Quadrants, Zeros, and Arrays
Use NumPy arctan2() for signed angles with correct quadrants, broadcasting, degrees, zero inputs, infinities, and vectorized arrays.
Autocorrelation in Python: Formula, Lags, and Reliable Analysis
Compute autocorrelation in Python with centered series, lag conventions, missing values, normalization, confidence limits, and time-series checks.
Gaussian Elimination in Python: Solve Linear Systems Clearly
Implement Gaussian elimination in Python with pivoting, row operations, numerical stability, singular matrices, and NumPy alternatives.
Python shelve: Persistent Dictionary Storage and Safety
Use Python shelve for small persistent mappings, choose modes, manage sync and keys, and understand dbm, pickle, concurrency, and trust limits.
Round Down in Python: floor, //, and Decimal Choices
Round numbers down in Python with math.floor and floor division, understand negative values, and choose Decimal when exact decimal rules matter.
NumPy Shuffle: Randomize Arrays Without Losing Control
Shuffle NumPy arrays with Generator.shuffle, reproducible seeds, in-place mutation, axes, copies, and safe data-pair handling.
Matplotlib gca(): Get the Current Axes
Understand matplotlib.pyplot.gca(), current Axes state, gca() versus gcf(), and why explicit subplots are clearer in new code.