Data Types

A data type simply tells us what kind of data a variable is designed to hold. When we create variables in our program, the type of data we assign to it determines the variable’s type.
Examples
  • If we write a = 10, it means the variable a carries numeric or integer data (a whole number).
  • If we assign f = 10.23, then f holds floating-point or decimal data.
  • If we assign a set of characters within double quotes to a variable called s (e.g., s = “Hello”), then s is of type string—it holds a sequence of characters.

Python's Main Data Type Categories

In Python, the data types are primarily organized into five main categories:
Category Description Examples
1. None Type This is an object that does not contain any value. None
2. Numeric Types Used for working with numbers. integer, floating point (decimals), complex
3. Sequence Types These hold an ordered sequence of other data types. String (sequence of characters), bytes, bytearray, list, tuple, range
4. Set Types These are collections that do not allow duplicate values. set, frozenset
5. Mapping Type Used for storing data in key-value pairs (like a dictionary). dict (dictionary)

Data Types Description

  • int: Integer data type represents whole numbers without a fractional part.
  • float: Floating-point data type represents real numbers with a fractional part.
  • list: List is an ordered, mutable collection of items that can contain duplicates.
  • tuple: Tuple is an ordered, immutable collection of items that can contain duplicates.
  • range: Range represents an immutable sequence of numbers, commonly used for looping a specific number of times.
  • str: String is a sequence of characters used to represent text.
  • set: Set is an unordered collection of unique items.
  • frozenset: Frozenset is an immutable version of a set, which means its elements cannot be changed after creation.
  • dict: Dictionary is an unordered collection of key-value pairs, where each key is unique.
  • bool: Boolean data type represents one of two values: True or False.

Numeric Types Examples

a=13
b=100
c=1234
print(a,b,c) #printing values
print(type(a),type(b),type(c))  #int

x=23.54
y=0.001
z=3.14159
print(x,y,z) #printing values
print(type(x),type(y),type(z)) #float
 
# Output:
# 13 100 1234
# <class 'int'> <class 'int'> <class 'int'>
# 23.54 0.001 3.14159
# <class 'float'> <class 'float'> <class 'float'>

Sequence Types Examples

lst=[1,2,3,4,5] #list
tup=(10,20,30,40,50) #tuple
rng=range(1,11) #range
st="Hello, World!" #string
print(lst) #printing list
print(tup) #printing tuple
print(rng) #printing range
print(st) #printing string
print(type(lst)) #list
print(type(tup)) #tuple
print(type(rng)) #range
print(type(st)) #string

# Output:
# [1, 2, 3, 4, 5]
# (10, 20, 30, 40, 50)
# range(1, 11)
# Hello, World!
# <class 'list'>
# <class 'tuple'>
# <class 'range'>
# <class 'str'>

Set Types Examples

st_set={1,2,3,4,5} #set
frz_set=frozenset([10,20,30,40,50]) #frozenset
print(st_set) #printing set
print(frz_set) #printing frozenset
print(type(st_set)) #set
print(type(frz_set)) #frozenset

# Output:
# {1, 2, 3, 4, 5}
# frozenset({10, 20, 30, 40, 50})
# <class 'set'>
# <class 'frozenset'>

Set Types Examples

dct={"a":1,"b":2,"c":3} #dictionary
bl_true=True #boolean true
bl_false=False #boolean false
print(dct) #printing dictionary
print(bl_true) #printing boolean true
print(bl_false) #printing boolean false
print(type(dct)) #dictionary
print(type(bl_true)) #boolean
print(type(bl_false)) #boolean

# Output:
# {'a': 1, 'b': 2, 'c': 3}
# True
# False
# <class 'dict'>
# <class 'bool'>

Immutable and Mutable Types

Immutable (Cannot be changed) Mutable (Can be changed)
int, float, complex, bool list
str, bytes bytearray
tuple, range set
frozenset dict
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