What are data types in Python
Python supports several data types, each designed for specific purposes. Here’s a descriptive overview of some common data types in Python:
Integer (int):
Integers are whole numbers without any decimal point. They can be positive or negative.
Example:
x = 10
y = -5
Float:
Floats represent real numbers with a decimal point.
Example:
x = 10.5
y = -3.14
String (str):
Strings are sequences of characters, enclosed in single (”) or double (“”) quotes.
Example:
my_string = "Hello, World!"
Boolean (bool):
Booleans represent the truth values True and False.
Example:
x = True
y = False
List:
Lists are ordered collections of items. They can contain items of different data types and are mutable.
Example:
my_list = [1, 'apple', 3.14, True]
Tuple:
Tuples are ordered collections of items, similar to lists, but they are immutable.
Example:
my_tuple = (1, 'banana', 2.71, False)
Dictionary (dict):
Dictionaries are collections of key-value pairs. They are unordered, mutable, and indexed.
Example:
my_dict = {'name': 'Alice', 'age': 25, 'is_student': True}
Set:
Sets are unordered collections of unique items. They are mutable but do not allow duplicate elements.
Example:
my_set = {1, 2, 3, 4, 5}
These are some of the fundamental data types in Python, each serving distinct purposes in programming and data manipulation.
Remember: This is not an exhaustive list, but covers some of the most common data types in Python. You can learn more about additional data types and their functionalities as you delve deeper into programming.
I hope this explanation helps you understand the different data types and their uses in Python! Feel free to ask if you have any further questions about specific data types or want more examples.