This document summarizes the different datatypes in Python. There are numeric, set, boolean, none, sequence, and mapping datatypes. Numeric datatypes represent values with numbers and can be integer, float, or complex. Sequence datatypes maintain order and include strings, bytes, bytearrays, lists, tuples, and ranges. Mapping datatypes like dictionaries are unordered key-value pairs. The document provides examples and definitions of each datatype.

1. Datatypes
In Python
Mrs.N.Kavitha
Head,Department of Computer Science,
E.M.G.Yadava Women’s College
Madurai-14.

2. Content
Introduction
Types of datatype
Numeric
Set
Boolean
None
Sequence
Mapping

3. Introduction
 Data types are the classification or categorization of data items. It
represents the kind of value that tells what operations can be performed on
a particular data. Since everything is an object in Python programming
data types are actually classes and variables are instances (object) of these
classes.
 To define the values ​​of various data types and check their data types
we use the type() function.

4. Types of Datatype

5. Numeric
 The numeric data type in Python represents the data that has a numeric value. A
numeric value can be an integer , float or complex.
 Integers – This value is represented by int class. It contains positive or negative
whole numbers (without fractions or decimals). In Python, there is no limit to
how long an integer value can be.
 Float – This value is represented by the float class. It is a real number with a
floating-point representation. It is specified by a decimal point. Optionally, the
character e or E followed by a positive or negative integer may be appended to
specify scientific notation.
 Complex Numbers – Complex number is represented by a complex class. It is
specified as (real part) + (imaginary part) j.

6. For Example
a = 5
print("Type of a: ", type(a))
b = 5.0
print("nType of b: ", type(b))
c = 2 + 4j
print("nType of c: ", type(c))
Output
Type of a: <class ‘int’>
Type of b: <class ‘float’>
Type of c: <class ‘complex’>

7. Sets
 A set is an unordered collection of elements much like a set in Mathematics.
 The order of elements is not maintained in the sets. It means the elements may
not appear in the same order as they are entered into the set.
 A set does not accept duplicate elements.
 There are two sub types in sets:
set datatype
frozen set datatype

8. Set datatypes
 To create a set , we should enter the elements separated by commas inside
curly braces{}.
 For example
s={12,13,12,14,15} Output
print(s) {14,12,13,15}
 Here the set ‘s’ is not maintaining the order of the elements.
 we repeated the element 12 in the set, but it stored only one 12.

9. Frozenset Datatype
 The frozenset datatype is same as the set datatype.
 The main difference is that the elements in the set datatype can be modified;
the elements of frozen set cannot be modified.
 For example
Output
s={50,60,70,80,90} {80,90,50,60,70}
print(s)
fs=frozenset(s) ({80,90,50,60,70})
print(fs)
fs= frozenset(abcdefg) ({ ‘e’, ’g’, ’f’ , ’d’, ’a’ , ’c’, ’b’})
print(fs)

10. Boolean
 The bool datatype in python represents Boolean values.
 There are only two Boolean values True or False that can be represented by
this datatype.
 Python internally represents True as 1 and False as 0. A blank string like “” is
also represented as False.
 For example
a=10 Output
b=20 Hello
if (a<b):
print(‘Hello’)

11. None
 In python, the ‘None’ datatype represents an object that does not contain any
values.
 In languages like Java, it is called ‘Null’ object . But in Python, it is called ‘None’
object.
 One of the uses of ‘None’ is that it is used inside a function as a default value of
the arguments.
 When calling the function, if no value is passed , then the default value will be
taken as ‘None’.

12. Sequence
 A Sequence represents a group of elements or item.
 For example , a group of integer numbers will form a sequence.
 There are six types of sequences in Python:
str
bytes
bytearray
list
tuple
range

13. str
 In Python , str represents string datatype.
 A string is represented by a group of characters.
 String are enclosed in single quotes ’’ or double quotes “”.
 For example
Output
str=“Hai” Hai
str=‘Hi’ Hi

14. For Example
s=‘Lets learn python’ Output
print(s) Lets learn python
print(s[0]) L
print(s[0:5]) Lets
print(s[12: ]) python
print(s[-2]) o

15. Bytes
 The bytes represents a group of byte numbers just like an array does.
 A byte number is any positive integer from 0 to 255
 Bytes array can store numbers in the range from 0 to 255 and it cannot even
store negative numbers.
 For example
elements =[10,20,0,40,15] Output
x=bytes(elements) 10
print(x[0])

16. Bytearray
 The bytearray datatype is similar to bytes datatype.
 The difference is that the bytes type array cannot be modified but the
bytearray type array can be modified.
 For example
elements=[10,20,0,40,15] Output
x=bytearray(elements)
print (x[0]) 10
x[0]=88
x[1]=99 88,99,0,40,50
print(x)

17. List
 A list is a collection of different types of datatype values or items.
 Since Python lists are mutable, we can change their elements after forming.
 The comma (,) and the square brackets [enclose the List's items] serve as
separators.
 Lists are created using square brackets.
 For example
list = ["apple", "banana", "cherry"]
print(list)

18. For Example
list1 = [1, 2, "Python", "Program", 15.9] Output
list2 = ["Amy", "Ryan", "Henry", "Emma"]
[1, 2,”Python”, “Program”, 15.9]
print(list1) [“Amy ”, ”Ryan ”,” Henry” ,” Emma”]
print(list2)
2
print(list1[1]) Amy
print(list2[0])

19. Tuple
 A tuple is a collection of objects which ordered and immutable.
 Tuples are sequences, just like lists. The differences between tuples and
lists are, the tuples cannot be changed and the lists can be change.
 Unlike lists and tuples use parentheses, whereas lists use square
brackets.
 Tuples are immutable which means you cannot update or change the
values of tuple elements. You are able to take portions of existing tuples
to create new tuples

20. For Example
tup1 = ('physics', 'chemistry', 1997, 2000) Output
tup2 = (1, 2, 3, 4, 5, 6, 7 )
print (tup1[0]) physics
print (tup2[1:5]) [2, 3, 4, 5]

21. Range
 Python range() is an in-built function in Python which returns a sequence of
numbers starting from 0 and increments to 1 until it reaches a specified number.
 We use range() function with for and while loop to generate a sequence of
numbers. Following is the syntax of the function:
 range(start, stop, step)
 Here is the description of the parameters used:
start: Integer number to specify starting position, (Its optional, Default: 0)
stop: Integer number to specify starting position (It's mandatory)
step: Integer number to specify increment, (Its optional, Default: 1)

22. For Example
for i in range(5): Output
print(i) 0 1 2 3 4
for i in range(1, 5):
print(i) 1 2 3 4
for i in range(1, 5, 2):
print(i) 1 3

23. Mapping
 Python Dictionary is an unordered sequence of data of key-value pair
form. It is similar to the hash table type.
 Dictionaries are written within curly braces in the form {key : value} .
 It is very useful to retrieve data in an optimized way among a large
amount of data.
dict={001: RDJ}
Key Value

24. For Example
a = {1:“RDJ", 2:“JD“ , "age":33} Output
print(a[1]) RDJ
print(a[2]) JD
print(a["age"]) 33