NumPy pad(): Constant, Edge, Reflect, and Array Padding
Use NumPy pad to add values around arrays with constant, edge, reflect, and statistic modes while controlling pad widths and axes.
Numpy
Learn NumPy with array operations, random sampling, math functions, shapes, dtypes, plotting examples, and fixes for common NumPy errors.
NumPy memmap: Memory-Mapped Arrays, Modes, and Flush
Use NumPy memmap for large array files with the right mode, dtype, shape, flush behavior, and memory expectations without loading the whole file at once.
NumPy Kronecker Delta: eye(), equal(), where(), and kron()
Build a NumPy Kronecker delta with eye(), equal(), or where(), and distinguish the elementwise delta from np.kron().
NumPy quantile(): q, axis, method, NaN, and Examples
Use NumPy quantile() with q probabilities, axes, interpolation methods, nanquantile, keepdims, weights, and distribution summaries.
NumPy choose: Select Values by Index Arrays and Conditions
Use numpy.choose for indexed selection with compatible arrays, modes, broadcasting, bounds, dtypes, and clearer alternatives.
NumPy Determinant: Compute and Check Matrix Determinants
Calculate matrix determinants with NumPy, understand square-array requirements, numerical stability, stacked inputs, and practical validation.
NumPy polyfit: Polynomial Fit, Coefficients, and Diagnostics
Fit polynomial models with NumPy polyfit(), evaluate them with polyval(), and inspect residuals, rank, weights, and conditioning.
NumPy fliplr: Flip Arrays Left to Right with Examples
Use NumPy fliplr to reverse array columns from left to right, understand axis behavior and views, and test shapes, strides, and multidimensional inputs.
NumPy argwhere(): Find Nonzero Coordinates
Use NumPy argwhere() for readable coordinate rows, compare it with nonzero() and where(), and handle empty or high-dimensional results.
NumPy median(): Calculate Medians by Axis
Use NumPy median() to calculate robust central values across arrays, axes, outputs, keepdims, NaNs, and memory-sensitive inputs.