Array creation and member access
NumPy
arrays are objects of the ndarray
class, which represents a fixed-size multidimensional collection of homogeneous data.
Here, we will assume that the NumPy
library has been imported using the following command line:
import numpy as np
Once we have done that, we can create ndarray
(from now on, informally called array object or simply array) from a list of lists as indicated in the following command line:
a = np.array([[-2,3,-4,0],[2,-7,0,0],[3,-4,2,1]],dtype=np.float64) print a
Contrary to Python lists and tuples, all entries of an array object must be of the same type. The types themselves are represented by NumPy
objects and are referred to as dtype
(from data type) of the array. In the preceding example, we explicitly specify dtype
as float64
, which represents a 64-bit floating-point value.
Arrays have several attributes that give information about the data layout. The more commonly used ones are as follows:
- The shape of the array is computed using...