The number after the data type, ex. int64, represents the bitsize of the data type of a numpy array.

Question

Can someone please explain to me what this bitsize means and why it differs for some data e.g int32 for some and int64 for others

Answer 1

Every value in memory takes some space. A 32 bit integer, takes 32 bits, or 32 zeroes or ones. Divide that by 8 and you get the number of bytes, in this case 4.
The smaller the data type (i.e the smaller the bitsize) the smaller the maximum value.
An unsigned Int32 (32 bit integer) can hold numbers from 0 to 4 billion something.

Answer 2

Thank you, so integers are not just integers and can be further classified to be 32 bit and 64 bit integers