What are the restrictions on data in numpy arrays?
Most NumPy arrays have some restrictions. When these conditions are met, NumPy exploits these characteristics to make the array faster, more memory efficient, and more convenient to use than less restrictive data structures.
For instance:
All elements of the array must be of the same type of data.
Once created, the total size of the array can’t change.
The shape must be “rectangular”, not “jagged”; e.g., each row of a two-dimensional array must have the same number of columns.