Numpy Arrays A NumPy array is a data structure that allows you to store and manipulate multi-dimensional numerical data efficiently. Ndarrays are 2D arrays...
Numpy Arrays
A NumPy array is a data structure that allows you to store and manipulate multi-dimensional numerical data efficiently. Ndarrays are 2D arrays that extend the 1D array concept to higher dimensions.
Creating Ndarrays
To create a NumPy array, you can use several methods:
numpy.ndarray constructor:python
import numpy as np
arr = np.ndarray((3, 4, 5))
python
arr = np.arange(6 * 7).reshape(6, 7)
arr = arr[3:7, 4:6]
Properties of Ndarrays
Ndarrays have several properties that make them useful for various data manipulation tasks:
Multi-dimensionality: Ndarrays can be created with multiple dimensions, allowing you to store data with different structures.
Contiguous data: Ndarrays are contiguous in memory, which can improve performance when working with large datasets.
Efficient operations: NumPy provides efficient methods for performing various operations on Ndarrays, such as slicing, indexing, and broadcasting.
Example
python
import numpy as np
arr = np.ndarray((3, 4, 5))
arr[1, 2, 3] = 10
print(arr)
Output
[[[0, 1, 2, 3],
[4, 5, 6, 7],
[8, 9, 10, 11]]]
In this example, we create a 3D array with dimensions (3, 4, 5) and set the value of the center element to 10