Compressed Sparse Column
Compressed Sparse Column (CSC) is a data structure and storage format used to efficiently represent sparse matrices, where most elements are zero. It stores only the non-zero values along with their row indices and column pointers, significantly reducing memory usage compared to dense representations. This format is widely used in scientific computing, machine learning, and graph algorithms for operations on large sparse datasets.
Developers should learn CSC when working with sparse matrices in applications like linear algebra solvers, network analysis, or recommendation systems, as it optimizes memory and computational efficiency. It is particularly useful in programming languages like Python (with SciPy), MATLAB, or C++ libraries where handling large sparse matrices is common, enabling faster matrix-vector multiplications and other operations.