Skip to main content

Python - Set Functions - add, clear, difference, discard, intersection, checks, union, update

🐍 Advanced Sets

Let's create a blank set and learn by example.
Input
s = Set()

Add Elements to Set

Input
s.add(1)
s.add(2)
s
Output
{1, 2}
This adds new elements to our existing set.

Clear

Input
s.clear()
s
Output
set()
This empties the set. It deletes all elements.

Copy

Input
s = {1,2,3}
sc = s.copy()
print(s,sc)
Output
{1, 3, 4} {1, 2, 3}
This copies elements from one set to another.

Difference

Syntax
set1.difference(set2)
Input
s.add(4)
s.difference(sc)
Output
{4}
This returns elements that are not common in the two sets.

Difference Update

Syntax
set1.difference_update(set2)
Input
s1 = {1,2,3}
s2 = {1,4,5}
s1.difference_update(s2)
s1
Output
{2, 3}
This updates set1 to the difference between set1 and set2.

Discard

Syntax
set.discard(element)
Input
s = {1,2,3,4}
s.discard(2)
s
Output
{1, 3, 4}
This deletes an element from the set, if that element exists in the set.

Intersection

Syntax
set1.intersection(set2)
Input
s1 = {1,2,3}
s2 = {2,3,4}
s1.intersection(s2)
Output
{2, 3}
It returns the elements that are common in the two sets. It does NOT update any of the two sets.

Intersection Update

Syntax
set1.intersection_update(set2)
Input
s1 = {1,2,3}
s2 = {2,3,4}
s1.intersection(s2)
s1
Output
{2, 3}
It updates set1 with common elements between the two sets.

Is Disjoint?

Syntax
set1.isdisjoint(set2)
Input
s1 = {1,2,3}
s2 = {2,3,4}
s1.isdisjoint(s2)
Output
False
Input
s1 = {1,2,3}
s3 = {4,5,6}
s1.isdisjoint(s3)
Output
True
It returns True or False. Returns True if both sets are unique to each other, i.e. no common element in the two sets, else it returns false.

Is Subset?

Syntax
set1.issubset(set2)
Input
s1 = {1,2}
s2 = {1,2,3}
s1.issubset(s2)
Output
True
Input
s2.issubset(s1)
Output
False
It returns True or False. Returns True if set1 is subset of set2, else it returns false.

Is Superset?

Syntax
set1.issuperset(set2)
Input
s1 = {1,2,3}
s2 = {1,2}
s1.issuperset(s2)
Output
True
Input
s2.issuperset(s1)
Output
False
It returns True or False. Returns True if set1 is superset of set2, else it returns false.

Symmetric Difference?

Syntax
set1.symmetric_difference(set2)
Input
s1 = {1,2,3}
s2 = {1,2,4}
s1.symmetric_difference(s2)
Output
{3, 4}
It returns a set. A set of all the elements that are not common is returned.

Union?

Syntax
set1.union(set2)
Input
s1 = {1,2,3}
s2 = {1,2,4}
s1.union(s2)
Output
{1, 2, 3, 4}
It returns a set. A set of all the elements in both the sets, but just one occurrence of each element, is returned. Note that the returned set is not saved in set1 or set2.

Update?

Syntax
set1.update(set2)
Input
s1 = {1,2,3}
s2 = {1,2,4}
s1.update(s2)
s1
Output
{1, 2, 3, 4}
It saves a set in set1. A set of all the elements in both the sets, but just one occurrence of each element, is returned. This is similar to union, just that in this it updates set1 with the new set created.

Comments

Popular posts from this blog

Python - List - Append, Count, Extend, Index, Insert, Pop, Remove, Reverse, Sort

🐍 Advance List List is widely used and it's functionalities are heavily useful. Append Adds one element at the end of the list. Syntax list1.append(value) Input l1 = [1, 2, 3] l1.append(4) l1 Output [1, 2, 3, 4] append can be used to add any datatype in a list. It can even add list inside list. Caution: Append does not return anything. It just appends the list. Count .count(value) counts the number of occurrences of an element in the list. Syntax list1.count(value) Input l1 = [1, 2, 3, 4, 3] l1.count(3) Output 2 It returns 0 if the value is not found in the list. Extend .count(value) counts the number of occurrences of an element in the list. Syntax list1.extend(list) Input l1 = [1, 2, 3] l1.extend([4, 5]) Output [1, 2, 3, 4, 5] If we use append, entire list will be added to the first list like one element. Extend, i nstead of considering a list as one element, it joins the two lists one after other. Append works in the following way. Input l1 = [1, 2, 3] l1.append([4, 5]) Output...

Difference between .exec() and .execPopulate() in Mongoose?

Here I answer what is the difference between .exec() and .execPopulate() in Mongoose? .exec() is used with a query while .execPopulate() is used with a document Syntax for .exec() is as follows: Model.query() . populate ( 'field' ) . exec () // returns promise . then ( function ( document ) { console . log ( document ); }); Syntax for .execPopulate() is as follows: fetchedDocument . populate ( 'field' ) . execPopulate () // returns promise . then ( function ( document ) { console . log ( document ); }); When working with individual document use .execPopulate(), for model query use .exec(). Both returns a promise. One can do without .exec() or .execPopulate() but then has to pass a callback in populate.

Python Class to Calculate Distance and Slope of a Line with Coordinates as Input

🐍  Can be run on Jupyter Notebook #CLASS DESIGNED TO CREATE OBJECTS THAT TAKES COORDINATES AND CALCULATES DISTANCE AND SLOPE class Line:     def __init__(self,coor1,coor2):         self.coor1=coor1         self.coor2=coor2 #FUNCTION CALCULATES DISTANCE     def distance(self):         return ((self.coor2[0]-self.coor1[0])**2+(self.coor2[1]-self.coor1[1])**2)**0.5 #FUNCTION CALCULATES SLOPE         def slope(self):         return (self.coor2[1]-self.coor1[1])/(self.coor2[0]-self.coor1[0]) #DEFINING COORDINATES coordinate1 = (3,2) coordinate2 = (8,10) #CREATING OBJECT OF LINE CLASS li = Line(coordinate1,coordinate2) #CALLING DISTANCE FUNCTION li.distance() #CALLING SLOPE FUNCTION li.slope()