Data Types

• Data type represent the type of data present inside a variable.
• In python we are not required to specify the type explicitly. Based on value provided, the type will be assigned automatically. Hence python is Dynamically Typed Language.

Python contains the following inbuilt data types;

1. Int
2. Float
3. Complex
4. Bool
5. Str
6. Bytes
7. Bytearray
8. Range
9. List
10. Tuple
11. Set
12. Frozenset
13. Dict
14. None

Remark

• In python everything is an object.
• Python contains several inbuilt functions:
  • type(): To check the type of variable.
  • id(): To get address of the object.
  • print(): To print the value.

Example

num = 10
print(type(num))
print(id(num))

Output

10
1673698634320

Int data type

• We can use int data type to represent whole numbers (integral values).

Example

num = 10
print(type(num))

Output

<class 'int'>

Remark

• In python2 we have long data type to represent very large integral values. But in python3 there is no long type explicitly and we can represent long values also by using int type only.

We can represent int values in the following ways;

1. Decimal form
2. Binary form
3. Octal form
4. Hexa decimal form

Decimal form (Base-10)

• It is the default number system in python
• The allowed digits are: 0 to 9

Example

num = 10
print(num)

Output

10

Binary form (Base-2)

• The allowed digits are : 0 & 1
• Literal value should be prefixed with 0b or 0B

Example

num = 0B1111
print(num, type(num))

Output

15 <class 'int'>

Example

num = 0b123
print(num)

Output

SyntaxError: invalid digit '2' in binary literal

Octal Form (Base-8)

• The allowed digits are : 0 to 7
• Literal value should be prefixed with 0o or 0O.

Example

num = 0O123
print(num)

Output

83

Example

num = 0O786
print(num)

Output

SyntaxError: invalid digit '8' in octal literal

Hexa Decimal Form (Base-16)

• The allowed digits are : 0 to 9, a-f (both lower and upper cases are allowed)
• Literal value should be prefixed with 0x or 0X

Example

num1 = 0XFACE
num2 = 0XBeef

print(num1, num2)

Output

64206 48879

Example

num = 0XBeer
print(num)

Output

SyntaxError: invalid hexadecimal literal

Remark

• Being a programmer we can specify literal values in decimal, binary, octal and hexa decimal forms. But PVM will always provide values only in decimal form.

Example

num1 = 10
num2 = 0o10
num3 = 0X10
num4 = 0B10

print(num1)
print(num2)
print(num3)
print(num4)

Output

10
8
16
2

Base Conversions

Python provide the following in-built functions for base conversions

bin()

• We can use bin() to convert from any base to binary.

Example

num = 15
print(bin(num))

num = 0o11
print(bin(num))

num = 0X10
print(bin(num))

Output

0b1111
0b1001
0b10000

oct()

• We can use oct() to convert from any base to octal.

num = 10
print(oct(num))

num = 0B1111
print(oct(num))

num = 0X123
print(oct(num))

Output

0o12
0o17
0o443

hex()

• We can use hex() to convert from any base to hexa decimal.

num = 100
print(hex(num))

num = 0B111111
print(hex(num))

num = 0o12345
print(hex(num))

Output

0x64
0x3f
0x14e5

Float data type

• We can use float data type to represent floating point values (decimal values).

Example

num = 1.234
print(type(num))

Output

<class 'float'>

• We can also represent floating point values by using exponential form (scientific notation).
• The main advantage of exponential form is we can represent big values in less memory.

Example

num = 1.2e3
print(num)

Output

1200.0

Remark

• We can represent int values in decimal, binary, octal and hexa decimal forms. But we can represent float values only by using decimal form.

Example

num = 0B11.01
print(num) # SyntaxError: invalid syntax

num = 0o123.456
print(num) # SyntaxError: invalid syntax

num = 0X123.456
print(num) # SyntaxError: invalid syntax

Complex Data Type

• A complex number is of the form a + bj where ‘a’ and ‘b’ contain integers or floating point values.

Example

num = 3 + 5j
print(num)

num = 10 + 5.5j
print(num)

num = 0.5 + 0.1j
print(num)

Output

(3+5j)
(10+5.5j)
(0.5+0.1j)

• In the real part if we use int value the we can specify that either by decimal, octal, binary or hexa decimal form.
• But imaginary part should be specified only by using decimal form.

Example

num = 0B11 + 5j
print(num)

num = 3 + 0B11j
print(num)

Output

(3+5j)
SyntaxError: invalid binary literal

• We can perform operations on complex type values.

Example

num1 = 10 + 1.5j
num2 = 20 + 2.5j

print(num1+num2)

Output

(30+4j)

• Complex data type has inbuilt attributes to retrieve the real part and imaginary part.

Example

num = 10.5 + 3.6j

print(num.real)
print(num.imag)

Output

10.5
3.6

Remark

• We can use complex type generally in scientific Applications and electrical engineering applications.

Bool data type

• We can use this data type to represent Boolean values.
• The only allowed values for this data type are: True and False

Example

num = True

print(type(num))

Output

<class 'bool'>

• Internally Python represents True as 1 and False as 0

Example

num1 = True
num2 = False

print(num1+num1)
print(num1-num2)

Output

2
1

String data type

• A String is a sequence of characters enclosed within single quotes or double quotes.

Example

str1 = 'ajay'
str2 = "ajay"

print(str1, type(str1))
print(str1, type(str1))

Output

ajay 
ajay 

• By using single quotes or double quotes we cannot represent multi line string literals.

str1 = "ajay
        shukla"

Output

SyntaxError: unterminated string literal (detected at line 1)

• For multi line string literals we should go for triple single quotes(”’) or triple double quotes(“””).

str1 = '''ajay
shukla'''
str2 = """ajay
shukla"""
print(str1)
print(str2)

Output

ajay
shukla
ajay
shukla

• We can also use triple quotes to use single quote or double quote in our String.

str1 = '''This is "character"'''
str2 = """This is 'character'"""

print(str1)
print(str2)

Output

This is "character"
This is 'character'

Slicing of Strings

• Slice means a piece.
• [ ] operator is called slice operator, which can be used to retrieve parts of string.
• In python strings follows zero based index.
• The index can be either +ve or -ve.
• +ve index means forward direction from left to right.
• -ve index means backward direction from right to left.

Example

str1 = 'ajay shukla'

# Forward direction slicing
print(str1[0])
print(str1[1])
print(str1[1:40])
print(str1[1:])
print(str1[:])
print(str1[40])

Output

'a'
'j'
'jay shukla'
'jay shukla'
'ajay shukla'
IndexError: string index out of range

Example

str1 = 'ajay shukla'

# Backward direction slicing
print(str1[-1])
print(str1[-3:-1])
print(str1[-3:])
print(str1[-30])

Output

a
kl
ERROR!
kla
IndexError: string index out of range

Remark

• In Python the following data types are considered as Fundamental Data types.
  • int
  • float
  • complex
  • bool
  • str
• In python, we can represent char values also by using str type and explicitly char type is not available.

str1 = 'a'
print(type(str1))

Output

<class 'str'>

• long data type is available in Python2 but not in Python3. In Python3 long values also we can represent by using int type only.

Bytes Data Type

• Bytes data type represents a group of byte numbers just like an array.

list1 = [10, 20, 30, 40]
b = bytes(list1)

print(type(b))
print(b[0])
print(b[-1])

for i in b: print(i)

Output

<class 'bytes'>
10
40
10
20
30
40

Remark

• The only allowed values for byte data type are 0 to 255. By mistake if we are trying to provide any other values then we will get value error.

list1 = [10, 255]
for i in bytes(list1): print(i)


list2 = [10, 256]
for i in bytes(list2): print(i)

Output

10
255
ValueError: bytes must be in range(0, 256)

• Once we creates bytes data type value, we cannot change its values, otherwise we will get TypeError. It means bytes is immutable.

list1 = [10, 20, 30, 40]
b = bytes(list1)
b[0] = 100

Output

TypeError: 'bytes' object does not support item assignment

Bytearray Data type

• Bytearray is exactly same as bytes data type except that its elements can be modified.

list1 = [10,20,30,40]
b = bytearray(list1)

for i in b : print(i)

# modify 0th element
b[0]=100

for i in b: print(i)

Output

10
20
30
40
100
20
30
40

List data type

• If we want to represent a group of values as a single entity where insertion order required to preserve and duplicates are allowed then we should go for list data type.
• In list;
  • Insertion order is preserved.
  • Heterogeneous objects are allowed.
  • Duplicates are allowed.
  • Growable in nature.
  • Values should be enclosed within square brackets.

Example

list1 = [10, 10.5, 'ajay', True, 10]
print(list1)

Output

[10, 10.5, 'ajay', True, 10]

• Slicing is applicable in list.

Example

list1 = [10, 20, 30, 40]

print(list1[0])
print(list1[-1])
print(list1[1:3])

# list assignment
list1[0] = 100

print(list1)

Output

10
40
[20, 30]
[100, 20, 30, 40]

• List is growable in nature. i.e. based on our requirement we can increase or decrease the size.

Example

list1 = [10, 20, 30]
# push new element
list1.append("ajay")
print(list1)

# pop element
list1.remove(20)
print(list1) # [10, 30, 'ajay']

# multiply constant term
list2 = list1*2
print(list2) # [10, 30, 'ajay', 10, 30, 'ajay']

Output

[10, 20, 30, 'ajay']
[10, 30, 'ajay']
[10, 30, 'ajay', 10, 30, 'ajay']

Remark

• An ordered, mutable, heterogenous collection of elements is nothing but list, where duplicates also allowed.

Tuple data type

• Tuple data type is exactly same as list data type except that it is immutable i.e. we cannot change values.
• Tuple elements can be represented within parenthesis “()”.

Example

tuple1 = (10, 20, 30, 40)
print(type(tuple1))

# Try to change 0th value
tuple1[0] = 100

# Try to push new element
tuple1.append("ajay")

# Try to remove element
tuple1.remove(10)

Output

<class 'tuple'>
# TypeError: 'tuple' object does not support item assignment
# AttributeError: 'tuple' object has no attribute 'append'
# AttributeError: 'tuple' object has no attribute 'remove'

Remark

• Tuple is the read only version of list.
• Indexing and slicing operation allowed.

Range Data Type

• Range data type represents a sequence of numbers.
• The elements present in range data type are not modifiable. i.e. range data type is immutable.

Form-1: range(10)

• Generate numbers from 0 to 9.

Example

for index in range(10): print(index)

Output

0
1
2
3
4
5
6
7
8
9

Form-2: range(10,20)

• Generate numbers from 10 to 19.

Example

for index in range(10, 20): print(index)

Output

10
11
12
13
14
15
16
17
18
19

Form-3: range(10,20,2)

• 2 means increment value.

Example

for index in range(10, 20, 2): print(index)

Output

10
12
14
16
18

• Slicing and indexing applicable in range data type.

rangeObj = range(10, 20)

print(rangeObj[0])
print(rangeObj[10])

Output

10
# IndexError: range object index out of range

• We cannot modify the values of range data type.

rangeObj = range(10, 20)

rangeObj[0] = 100

Output

TypeError: 'range' object does not support item assignment

• We can create a list of values with range data type.

list1 = list(range(10))

print(type(list1))
print(list1)

Output

<class 'list'>
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]

• Range not work with float number.

range(1, 10.5)

Output

TypeError: 'float' object cannot be interpreted as an integer

Set Data Type

• If we want to represent a group of values without duplicates where order is not important then we should go for set data type.
• In set;
  • Insertion order is not preserved.
  • Duplicates are not allowed.
  • Heterogeneous objects are allowed.
  • Index concept is not applicable.
  • It is mutable collection.
  • Growable in nature.

Example

set1 = {100, 0, 10, 200, 10, 'ajay'}
print(set1)

# print first element
print(set1[0])

Output

{0, 100, 'ajay', 10, 200}
# TypeError: 'set' object is not subscriptable

• Set is growable in nature, based on our requirement we can increase or decrease the size.

set1 = {100, 0, 10, 200, 10, 'ajay'}

# Add new element
set1.add(60)

print(set1)

# Remove 100 from set
set1.remove(100)

print(set1)

Output

{0, 100, 'ajay', 200, 10, 60}
{0, 'ajay', 200, 10, 60}

Frozenset Data Type

• It is exactly same as set except that it is immutable. Hence we cannot use add or remove functions.

Example

set1 = {10, 20, 30, 40}
frozenset1 = frozenset(set1)

print(type(frozenset1))
print(frozenset1)

for num in frozenset1: print(num)

# Add new element
frozenset1.add(70)

# Remove element 10
frozenset1.remove(10)

Output

<class 'frozenset'>
frozenset({40, 10, 20, 30})
40
10
20
30
# AttributeError: 'frozenset' object has no attribute 'add'
# AttributeError: 'frozenset' object has no attribute 'remove'

Dict Data Type

• If we want to represent a group of values as key-value pairs then we should go for dict data type.

Example

dict1 = {101:'kuldeep',102:'ajay',103:'amit'}
print(type(dict1))

Output

<class 'dict'>

• Duplicate keys are not allowed but values can be duplicated. If we are trying to insert an entry with duplicate key then old value will be replaced with new value.

dict1 = {101:'kuldeep',102:'ajay',103:'amit'}
# Assign new value
dict1[101] = 'sunny'
print(dict1)

# We can create empty dictionary as follows
dict2 = { }
# We can add key-value pairs as follows
dict2['a'] = 'apple'
dict2['b'] = 'banana'
print(dict2)

Output

{101: 'sunny', 102: 'ajay', 103: 'amit'}
{'a': 'apple', 'b': 'banana'}

Remark

• Dict is mutable and the order wont be preserved.
• In general we can use bytes and bytearray data types to represent binary information like images, video files etc.
• In Python2 long data type is available. But in Python3 it is not available and we can represent long values also by using int type only.
• In Python there is no char data type. Hence we can represent char values also by using str type.

None Data Type

• None means Nothing or No value associated.
• If the value is not available, then to handle such type of cases None introduced.
• It is something like null value in Java.

Example

def myFunction():
  num1 = 10
  
print(myFunction())

Output

None

Summary of data types

Ungraded Questions

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