it is use full for those who want to learn python data type set

1. PYTHON PROGRAMMING
INFORMATION TECHNOLOGY
I SEMESTER
Prepared by:
Mrs. K Laxminarayanamma, Assistant Professor

2. 2
Course Title PYTHON PROGRAMMING
Course Code ACSC01
Class B.Tech I Semester
Section IT A AND B
Name of the Faculty Mrs. K.Laxminarayanamma
Date 22 January, 2021
Course Outcome/s
1. Understand native data types like list, set, tuple,
dictionary use them in data processing applications
Topic Covered
1. Tuple comprehension, Conversion of List
comprehension to Tuple
2. Iterators and Iterables

3. 3
MODULE - III
INTRODUCTION TO PYTHON
CONTAINER DATA TYPES
Lists: Accessing List elements, List operations, List methods, List comprehension;
Tuples: Accessing Tuple elements, Tuple operations, Tuple methods, Tuple
comprehension, Conversion of List comprehension to Tuple, Iterators and
Iterables, zip() function.
Sets: Accessing Set elements, Set operations, Set functions, Set comprehension;
Dictionaries: Accessing Dictionary elements, Dictionary operations, Dictionary
Functions, Nested Dictionary, Dictionary comprehension.
Syllabus

4. 4
There are four collection data types in the Python programming language:
List is a collection which is ordered and changeable. Allows duplicate members.
Tuple is a collection which is ordered and unchangeable. Allows duplicate
members.
Set is a collection which is unordered and unindexed. No duplicate members.
Dictionary is a collection which is unordered, changeable and indexed. No
duplicate members.
Python Collections (Arrays)

5. 5
Tuple comprehension
Tuple comprehension
Example :
T=(-1,2,-3,4,6)
T=tuple(i for i in T if i>0)
Output:
(2,4,6)
List comprehension
Example:
L=[-1,2,-3,4,6]
L2=[i for i in L if i>0]
Output:
[2,4,6]

6. 6
Conversion of List comprehension to Tuple
Example
L=[1,2,3,4,5,6,7]
T=tuple([i for i in L])
Print(T)
Output:
(1,2,3,4,5,6,7)

7. 7
List vs Tuple
List Tuple
1 The literal syntax of list is shown by the
[ ].
The literal syntax of the tuple is
shown by the ().
2 The List is mutable. The tuple is immutable.
3 List iteration is slower and is time
consuming.
Tuple iteration is faster.
4
Lists consume more memory
Tuple consume less memory as
compared to the list
5 The list is used in the scenario in which
we need to store the simple
collections with no constraints where
the value of the items can be changed.
The tuple is used in the cases where
we need to store the read-only
collections i.e., the value of the
items cannot be changed. It can be
used as the key inside the
dictionary.
6 List provides many in-built methods. Tuples have less in-built methods.

8. 8
Python Iterators
An iterator is an object that contains a countable number of values.
An iterator is an object that can be iterated upon, meaning that you can traverse
through all the values.
Technically, in Python, an iterator is an object which implements the iterator
protocol, which consist of the methods __iter__() and __next__().

9. 9
Iterator
In Python, an iterator is an object which implements the iterator
protocol, which consist of the methods __iter__() and
__next__() .
• An iterator is an object representing a stream of data.
• It returns the data one element at a time.
• A Python iterator must support a method called __next__() that
takes no arguments and always returns the next element of the
stream.
• If there are no more elements in the stream, __next__() must
raise the StopIteration exception.
• Iterators don’t have to be finite. It’s perfectly reasonable to
write an iterator that produces an infinite stream of data.

10. 10
Iterable
• In Python, Iterable is anything you can loop over with a for loop.
• An object is called an iterable if u can get an iterator out of it.
• Calling iter() function on an iterable gives us an iterator.
• Calling next() function on iterator gives us the next element.
• If the iterator is exhausted(if it has no more elements), calling next() raises
StopIteration exception.

11. 11
Iterable

12. 12
Iterating through an Iterator
• We use the next() function to manually iterate through all the
items of an iterator.
• When we reach the end and there is no more data to be
returned, it will raise the StopIteration Exception.
# define a list
my_list = [4, 7, 0, 3]
# get an iterator using iter()
my_iter = iter(my_list)
# iterate through it using next()
# Output: 4
print(next(my_iter))

13. 13
Iterating through an Iterator
# Output: 7
print(next(my_iter))
# next(obj) is same as
obj.__next__()
# Output: 0
print(my_iter.__next__())
# Output: 3
print(my_iter.__next__())
# This will raise error, no items left
next(my_iter)

14. 14
Python Iterators
Iterator vs Iterable:
Lists, tuples, dictionaries, and sets are all iterable objects. They are
iterable containers which you can get an iterator from.
All these objects have a iter() method which is used to get an iterator:
Example
Return an iterator from a tuple, and print each value:
mytuple = ("apple", "banana", "cherry")
myit = iter(mytuple)
print(next(myit))
print(next(myit))
print(next(myit))
Output:
apple
banana
cherry

15. 15
Python Iterators
Iterator vs Iterable:
Even strings are iterable objects, and can return an iterator:
Example
Strings are also iterable objects, containing a sequence of characters:
mystr = "banana"
myit = iter(mystr)
print(next(myit))
print(next(myit))
print(next(myit))
print(next(myit))
print(next(myit))
print(next(myit))
Output:
b
a
n
a
n
a

16. 16
Python Iterators
Looping Through an Iterator
We can also use a for loop to iterate through an iterable object:
Example
Iterate the values of a tuple:
mytuple = ("apple", "banana", "cherry")
for x in mytuple:
print(x)
Output:
apple
banana
cherry

17. 17
Python Iterators
Example
Iterate the characters of a string:
mystr = "banana"
for x in mystr:
print(x)
Output:
b
a
n
a
n
a

18. 18
Working of for loop for Iterators
for <var> in <iterable>:
<statement(s)>

19. 19
Python Sets
Sets are used to store multiple items in a single variable.
Set is one of 4 built-in data types in Python used to store collections of data, the
other 3 are List, Tuple, and Dictionary, all with different qualities and usage.
A set is a collection which is both unordered and unindexed.
Sets are written with curly brackets.
Example
Create a Set:
thisset = {"apple", "banana", "cherry"}
print(thisset)
output:
{'apple', 'banana', 'cherry'}

20. 20
Set Items
Set items are unordered, unchangeable, and do not allow duplicate values.
Unordered
Unordered means that the items in a set do not have a defined order.
Set items can appear in a different order every time you use them, and cannot be
referred to by index or key.
Unchangeable
Sets are unchangeable, meaning that we cannot change the items after the set
has been created.
Once a set is created, you cannot change its items, but you can add new items.
Duplicates Not Allowed
Sets cannot have two items with the same value.

21. 21
Set Items
Example
Duplicate values will be ignored:
thisset = {"apple", "banana", "cherry", "apple"}
print(thisset)
Output:
{'banana', 'cherry', 'apple'}

22. 22
Python Dictionaries
Dictionaries are used to store data values in key:value pairs.
A dictionary is a collection which is unordered, changeable and does not allow
duplicates.
Dictionaries are written with curly brackets, and have keys and values:
Example
Create and print a dictionary:
thisdict = {
"brand": "Ford",
"model": "Mustang",
"year": 1964
}
print(thisdict)
Output:
{'brand': 'Ford', 'model': 'Mustang', 'year': 1964}

23. 23
Dictionary Items
Dictionary items are unordered, changeable, and does not allow duplicates.
Dictionary items are presented in key:value pairs, and can be referred to by
using the key name.
Example
Print the "brand" value of the dictionary:
thisdict = {
"brand": "Ford",
"model": "Mustang",
"year": 1964
}
print(thisdict["brand"])
Output:
Ford