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Learning NumPy Array by Ivan Idris

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NumPy numerical types

Python has an integer type, a float type, and a complex type; however, this is not enough for scientific computing. In practice, we need even more data types with varying precision, and therefore, different memory size of the type. For this reason, NumPy has a lot more data types. The majority of NumPy numerical types end with a number. This number indicates the number of bits associated with the type. The following table (adapted from the NumPy user guide) gives an overview of NumPy numerical types:

Type

Description

bool

This stores boolean (True or False) as a bit

inti

This is a platform integer (normally either int32 or int64)

int8

This is an integer ranging from-128 to 127

int16

This is an integer ranging ...

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