Why Your Python Code is SO SLOW! 🐢 (NumPy dtype trick) #shorts #python #coding

In NumPy, dtype stands for data type object.

Unlike standard Python lists, which can hold a mix of different data types (e.g., integers, strings, and floats all in one list), NumPy arrays are homogeneous—meaning every element in the array must be of the exactly same data type.

The dtype tells NumPy exactly how to interpret the bytes in memory for that array, including the type of data (integer, float, etc.) and the size (how many bytes it takes up).
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