What is NumPy?
This lesson gives a brief introduction to what is NumPy and explains data types in NumPy.
We'll cover the following
NumPy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.
Data type
| Type | Name | Bytes | Description |
|---|---|---|---|
bool |
b |
1 | Boolean (True or False) stored as a byte |
int |
l |
4-8 | Platform (long) integer (normally either int32 or int64) |
intp |
p |
4-8 | Integer used for indexing (normally either int32 or int64) |
int8 |
i1 |
1 | Byte (-128 to 127) |
int16 |
i2 |
2 | Integer (-32768 to 32767) |
int32 |
i4 |
4 | Integer (-2147483648 to 2147483647) |
int64 |
i8 |
8 | Integer (-9223372036854775808 to 9223372036854775807) |
uint8 |
u1 |
1 | Unsigned integer (0 to 255) |
uint16 |
u2 |
2 | Unsigned integer (0 to 65535) |
uint32 |
u4 |
4 | Unsigned integer (0 to 4294967295) |
uint64 |
u8 |
8 | Unsigned integer (0 to 18446744073709551615) |
float |
f8 |
8 | Shorthand for float64 |
float16 |
f2 |
2 | Half precision float: sign bit, 5 bits exponent, 10 bits mantissa |
float32 |
f |
4 | Single precision float: sign bit, 8 bits exponent, 23 bits mantissa |
float64 |
d |
8 | Double precision float: sign bit, 11 bits exponent, 52 bits mantissa |
complex |
c16 |
16 | Shorthand for complex128. |
complex64 |
c8 |
8 | Complex number, represented by two 32-bit floats |
complex128 |
c16 |
16 | Complex number, represented by two 64-bit floats |
NumPy knows that int refers to np.int_, bool means np.bool_, that float is np.float_ and complex is np.complex_. The other data-types do not have Python equivalents.
Additionally, the names such as intc,
long, or double used in the C programming language are defined.
Now that the concept of data types is clear, let’s move on to the next lesson “Creation in NumPy”.