If you haven't installed NumPy yet, you can do so using pip:

%pip install numpy

Importing NumPy

To get started with NumPy, you need to import it in your Python script:

import numpy as np

Creating Arrays

NumPy arrays are created with the np.array() function. You can pass any sequence-like object into this function, and it will be converted into an ndarray (N-dimensional array).

# Create a 1D array
arr1 = np.array([1, 2, 3, 4, 5])
print(arr1)

# Create a 2D array (matrix)
arr2 = np.array([[1, 2, 3], [4, 5, 6]])
print(arr2)

Array Attributes

Some basic attributes of an ndarray object are:

• ndim: the number of dimensions
• shape: the size of each dimension
• size: the total number of elements
• dtype: the data type of the elements

arr2 = np.array([[1, 2, 3], [4, 5, 6]])
print("Dimensions:", arr2.ndim)         # 2 (Row and Col)
print("Shape:", arr2.shape)             # (2, 3), 
print("Size:", arr2.size)               # 6=2*3
print("Data type:", arr2.dtype)         # int64

Introduction to NumPy Array Operations (A)

Basic Operations

NumPy arrays support element-wise operations, which can be performed directly with operators like +, -, *, /.

a = np.array([1, 2, 3])
b = np.array([4, 5, 6])
# Element-wise addition
print(a + b)
# Element-wise multiplication
print(a * b)

Broadcasting