Digging into Python: Data Types

Python is a dynamically typed language, which means that the data type of a variable is determined at runtime based on the value it holds. 

Python provides a number of built-in data types, each with its own set of operations and methods.

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Here's an overview of some of the most used data types in Python:

Numeric:

• Integers (int): Integers are whole numbers without decimal points. They can be positive or negative, and there is no limit to their size.
• Floats (float): Floats are numbers with decimal points. They can also be positive or negative, and there is no limit to their precision.

	# int
	number1 = 1
	print(number1, 'is of type', type(number1))
	# float
	number2 = 3.5
	print(number2, 'is of type', type(number2))
	# complex
	number3 = 5+7j
	print(number3, 'is of type', type(number3))

view raw pythonDataTypes1.py hosted with ❤ by GitHub

String:

• Strings (str): Strings are sequences of characters enclosed in quotation marks (either single or double). They can be indexed and sliced like lists, and there are a number of built-in methods for working with strings.

	# String
	message = 'Keep on coding'
	# Print String value
	print(message)

view raw pythonDataTypes2.py hosted with ❤ by GitHub

Boolean:

• bool: holds either True or False

	# bool
	A = true
	# Print Boolean value
	print(type(A))

view raw pythonDataTypes3.py hosted with ❤ by GitHub

Sequence:

• Lists (list): Lists are ordered sequences of elements, which can be of any data type. They are mutable, meaning that you can add, remove, or modify elements in place.
• Tuples (tuple): Tuples are similar to lists, but are immutable, meaning that their elements cannot be changed once they are created.

	# List
	fruits = ["Apple", "Banana", "Lemon"]
	# access element at index 1 in List
	print(fruits[1]) # Banana
	# Tuple
	values = ('Python', 'Tuple', 1)
	# access element at index 0 in Tuple
	print(values[0]) # Python

view raw pythonDataTypes4.py hosted with ❤ by GitHub

Mapping:

• Dictionaries (dict): Dictionaries are unordered collections of key-value pairs. The keys are typically strings or integers, and the values can be of any data type. Dictionaries are mutable and can be modified in place.

	# create a dictionary named months
	months = {1: 'January', 2: 'February', 3:'March', 4:'April', 5:'May', 6:'June', 7:'July', 8:'August', 9:'September',
	10:'October', 11:'November', 12:'December'}
	# print dictionary
	print(months)

view raw pythonDataTypes5.py hosted with ❤ by GitHub

Set:

• Sets (set): Sets are unordered collections of unique elements. They are mutable and can be modified in place.

	# create a set named person_id
	person_id = {1, 2, 3, 4, 5}
	# display person_id elements
	print(person_id)
	# display type of person_id
	print(type(person_id))

view raw pythonDataTypes6.py hosted with ❤ by GitHub

In addition to these built-in data types, Python also provides a number of other specialized data types, such as byte arrays, ranges, and complex numbers.

Understanding Python's data types is essential. By choosing the right data type for a given task, you can ensure that your code is easy to read, maintain, and scale.