Mutability Vs Immutability:
===========================
All primitive datatypes ==> Immutable Datatypes

after the definition of the data, the modification is not allowed
if the modification is triggered, that modification reserve with new address

a = 123 # initeger
b = 12.234  # float
c = 12-24j  # complex
d = True    # Boolean

"""
id(): ==> use to get the address of the data
Syntax:
    id(value)
"""

print(id(a))
print(id(b))
print(id(c))
print(id(d))

a = 1203
b = 0.00097
c = 0.9 + 7.9j
d = False

print(id(a))
print(id(b))
print(id(c))
print(id(d))

Mutability:
===========
after the definition, we can make the change within the original address.
Ex: List, dictionary, set etc.


Collection Datatypes:
====================
group of values can define with one variable.
ex: a = (1,2,3,4)
1) String Datatype:
===================
==> collection of or group of characters which can be enclosed with "single quotes" or "double quotes" called as "string".

Ex: 'A' ==> Character
In Python:
	'a', 'ababab'	
	"a", "aabaaa" ==> String data
==> Inbuilt datatype
	a pre-defined class ==> "str".

==> Ordered.
==> Sequence based.
	we can allow to use the index to get the individual elements from the string.
	python can support:
		positive indexing: access the string data with positive index values
		range: 0 to length - 1
		can allow to access the characters of string in forward direction (left to right)
		negative indexing: access the string data with negative index values
		range: -1 to -length
		can allow to access the characters of the string in reverse direction (right to left)
==> Slicing is also possible on string data.
	[start-index: stop-index: step]
==> Immutable datatype.

d1 = 'a'
d2 = 'abababa'
d3 = "a"
d4 = "abababbab"
d5 = "Python Programming Language"

print(type(d1))
print(type(d2))
print(type(d3))
print(type(d4))

print(d2)
print(d4)

# positive indexing ==> Forward Accessing
print(d2[0])
print(d2[1])
print(d2[2])
print(d2[3])
print(d2[4])
print(d2[5])
print(d2[6])

print()
# Negative indexing ==> Reverse Accessing
print(d2[-1])
print(d2[-2])
print(d2[-3])
print(d2[-4])
print(d2[-5])
print(d2[-6])
print(d2[-7])

print(d5)
# slicing
print(d5[0:6])
print(d5[:6])
print(d5[::])
print(d5[::1])
print(d5[::-1])

"""
if the start-index ==> absent,
    the slicing can begin with first character (0) by default 
if the step factor ==> absent,
    the slicing can be considered with the index difference of '1' by default.
if the stop-index ==> absent,
    the slicing can be considered till the last index by default.
"""
# d5[1] = 'Y'
d6 = d5.upper()

print(d5)
print(d6)