Dtypes
Dtypes, short for data types, describe the kind of elements stored in array-like structures such as NumPy arrays or Pandas Series and DataFrames, and how those elements are represented in memory. The dtype governs the allowed operations, memory footprint, and numerical precision.
Common categories include integers (with fixed widths like int8, int16, int32, int64; unsigned variants exist), floating-point
Dtypes enable memory-efficient storage and fast vectorized operations. They interact with type promotion rules during arithmetic
Practical guidance: choose a small, appropriate integer or float precision when possible to save memory; use
Dtypes are fundamental to data processing, shaping storage, performance, and the semantics of operations. Understanding them