Working with Lists (Arrays) in Python
Creating a List
You can create a list in Python by enclosing a comma-separated sequence of values within square brackets []:
my_list = [1, 2, 3, 4, 5]
words = ["apple", "banana", "cherry"]
mixed_types = [1, "hello", 3.14]
empty_list = []
Accessing Elements
You can access elements of a list by using square brackets with an index:
first_item = my_list[0]
second_item = words[1]
List Comprehensions
List comprehensions allow you to create new lists by applying an expression to each element of an existing list:
squared_numbers = [x ** 2 for x in my_list]
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Arrays in Python
Lists
Lists in Python are a versatile and commonly used data structure. They are ordered collections of items, and the items can be of different data types (integers, strings, other lists, etc.). Lists are defined using square brackets [], and elements are separated by commas.
my_list = [1, 2, 3, 4, 5]
You can access elements in a list using indexing, add or remove elements, and perform various operations on them.
# Accessing elements
first_element = my_list[0]
# 1
# Adding elements
my_list.append(6)
# [1, 2, 3, 4, 5, 6]
# Removing elements
my_list.remove(3)
# [1, 2, 4, 5]
NumPy Arrays
If you need to work with arrays for numerical and scientific computing, you should consider using NumPy (Numerical Python). NumPy provides an efficient array object called numpy.ndarray. These arrays are homogeneous, meaning all elements are of the same data type, and they offer various mathematical operations optimized for speed.
To use NumPy, you need to import the library:
import numpy as np
You can perform element-wise operations on NumPy arrays, perform linear algebra operations, and use NumPy's vast array of functions.
import numpy as np
my_array = np.array([1, 2, 3, 4, 5])
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