Python offers three types of numerical data types: integer type, float type, and complex type. In practice, we need more data types for scientific computing operations with precision, range, and size. NumPy offers a bulk of data types with mathematical types and numbers. Let's see the following table of NumPy numerical types:
|
Data Type |
Details |
|
bool |
This is a Boolean type that stores a bit and takes True or False values. |
|
inti |
Platform integers can be either int32 or int64. |
|
int8 |
Byte store values range from -128 to 127. |
|
int16 |
This stores integers ranging from -32768 to 32767. |
|
int32 |
This stores integers ranging from -2 ** 31 to 2 ** 31 -1. |
|
int64 |
This stores integers ranging from -2 ** 63 to 2 ** 63 -1. |
|
uint8 |
This stores unsigned integers ranging from 0 to 255. |
|
uint16 |
This stores unsigned integers ranging from 0 to 65535. |
|
uint32 |
This stores unsigned integers ranging from 0 to 2 ** 32 –... |
