# Sets Methods In Python

In today’s topic, **Python sets methods** are discussed with examples, hoping to meet the learning needs.

- Sets Methods In Python:
- Python Sets Methods:
- Set add() Method:
- Set clear() Method:
- Set copy() Method:
- Set difference() Method:
- Set difference_update() Method:
- Set discard() Method:
- Set intersection() Method:
- Set intersection_update() Method:
- Set isdisjoint() Method:
- Set issubset() Method:
- Set issuperset() Method:
- Set pop() Method:
- Set remove() Method:
- Set symmetric_difference() Method:
- Set symmetric_difference_update() Method:
- Set union() Method:
- Set update() Method:
- Python Set Methods Importance:

## Python Sets Methods

When it comes to **Python sets methods**, Python comes with a number of built-in methods.

Method | Overview |
---|---|

add() | A Python set method adds an item to the set. |

clear() | This function removes all the items from a set. |

copy() | This method returns a copy of the set. |

difference() | Provides a set including the difference between two or more sets. |

difference_update() | This set is removed if it contains items that are included in another set mentioned in this one. |

discard() | Delete the chosen item. |

intersection() | Provides a set whose intersection is two other sets. |

intersection_update() | This set should be removed if it contains items not found in other specified sets. |

isdisjoint() | A function that returns whether or not two sets intersect. |

issubset() | This method returns whether or not another set contains this set. |

issuperset() | This method returns whether the set includes another set or not. |

pop() | Delete an item from the set. |

remove() | Delete the chosen item. |

symmetric_difference() | This function returns a set with two sets that are symmetrically different. |

symmetric_difference_update() | Add the symmetric differences between this set and another. |

union() | This method returns a set containing the union of all sets. |

update() | Combine this set with others and update the set. |

In order to make it easier for you, we have defined each **Python sets methods** in detail with examples.

## Set add() Method

A new element is added to the set with the **add()** method.

The **add()** method does not add the element if it already exists.

**Syntax**

set.add(element)

Parameter |
Description |

element |
It is essential. The element is assigned to the set |

Include an element to the nfl_teams set:

#### Example:

Add two elements to the nfl_teams set:

#### Example:

Now add an existing element:

#### Example:

Add an existing element then add a new element in a set:

#### Example:

## Set clear() Method

By calling **clear()** method, all elements in a set are removed.

### Syntax

set.clear()

Delete all elements from the nfl_teams set:

#### Example:

Delete all elements from the nfl_teams1 and nfl_teams2 set:

#### Example:

## Set copy() Method

Sets are copied through the **copy()** method.

### Syntax

set.copy()

Copy all the elements of the nfl_teams set:

#### Example:

In the nfl_teams1 and nfl_teams2 sets, copy all the elements:

#### Example:

## Set difference() Method

**Difference()** generates a set containing the difference between two sets.

As a result, the returned set contains only items from the first set and not from the second set.

### Syntax

set.difference(set)

#### Parameter Values

Parameter |
Description |

set |
It is essential. The set compares for differences in |

Provide a set that includes items that only occur in set nfl_teams1, but not in set nfl_teams2:

#### Example:

Return a set that includes items that only occur in set nfl_teams1, but not in sets nfl_teams2 and nfl_teams3:

#### Example:

You can reverse the first example. Provide a set that includes items that only occur in set nfl_teams2, but not in set nfl_teams1:

#### Example:

You can also reverse the second example. Return a set that includes items that only occur in set nfl_teams3, but not in sets nfl_teams1 and nfl_teams2:

#### Example:

## Set difference_update() Method

**Difference_update()** eliminates items that are present in both sets.

It differs from the **difference()** method in that the **difference()** method returns a new set without the unwanted items, while the **difference_update()** method removes them.

### Syntax

set.difference_update(set)

#### Parameter Values

Parameter |
Description |

set | It is essential. The set compares for differences in |

Delete the items that are present in both sets:

#### Example:

Eliminate the elements that are found in both three sets:

#### Example:

## Set discard() Method

The **discard()** method eliminates the given item from the set.

There is a difference between the **discard()** method and the remove() method in that the remove() method will raise an error if the specified item does not exist, but the discard() method will not.

### Syntax

set.discard(value)

#### Parameter Values

Parameter |
Description |

set |
It is essential. To delete the item, search for it and remove it |

From the nfl_teams set, delete “Atlanta Falcons”:

#### Example:

From the nfl_teams set, delete “Atlanta Falcons” and “Arizona Cardinals”:

#### Example:

## Set intersection() Method

If two or more sets are similar, the **intersection()** method returns their similarity.

When comparing more than two sets, the returned set only contains items that are present in both sets.

### Syntax

set.intersection(set1, set2 ... etc)

#### Parameter Values

Parameter |
Description |

set1 | This is essential. It looks for items that are equal in the set |

set2 | A choice. Make a search for equal items in the other set. You can compare as many sets as you like. Use a comma to separate the sets. |

Provide a set that includes items that occur in both set nfl_teams1, and set nfl_teams2:

#### Example:

Return a set that includes items that occur in both set nfl_teams1, set nfl_teams2 and nfl_teams3:

#### Example:

You can reverse the first example. Provide a set that includes items that occur in both set nfl_teams1, and set nfl_teams2:

#### Example:

You can reverse the second example. Return a set that includes items that occur in both set nfl_teams1, set nfl_teams2 and nfl_teams3:

#### Example:

## Set intersection_update() Method

In the **intersection_update()** method, items that are not present in both sets are removed (or all sets in the case of a comparison of more than two sets).

In contrast to the **intersection()** method, the intersection_update() method removes unwanted items from the original set, whereas the intersection() method returns a new set.

### Syntax

set.intersection_update(set1, set2 ... etc)

#### Parameter Values

Parameter |
Description |

set1 |
This is essential. It looks for items that are equal in the set |

set2 | A choice. Make a search for equal items in the other set. You can compare as many sets as you like. Use a comma to separate the sets. |

Delete the elements that are not present in both set nfl_teams1, and set nfl_teams2:

#### Example:

Delete the elements that are not present in both set nfl_teams1, set nfl_teams2 and set nfl_teams3:

#### Example:

You can reverse the first example. Delete the elements that are not present in both set nfl_teams1, and set nfl_teams2:

#### Example:

You can reverse the second example. Delete the elements that are not present in both set nfl_teams1, set nfl_teams2 and set nfl_teams3:

#### Example:

## Set isdisjoint() Method

If not one of the items is found in both sets, **isdisjoint()** returns True, otherwise it returns **False**.

### Syntax

set.isdisjoint(set)

#### Parameter Values

Parameter |
Description |

set |
This is essential. In this set, we are looking for items that are equal. |

When set nfl_teams1 is not present in set nfl_teams2, return True:

#### Example:

If set nfl_teams2 is not present in set nfl_teams1, return True:

#### Example:

If neither set contains any items, what should you do? If both sets contain the same item, return False:

#### Example:

What should you do if neither set contains any items? Provide False if the two sets include the identical item:

#### Example:

## Set issubset() Method

If all items in the set exist in the specified set, the **issubset()** method returns True, otherwise it returns **False**.

### Syntax

set.issubset(set)

#### Parameter Values

Set

If all elements in set nfl_teams1 are available in set nfl_teams2, return True:

#### Example:

Return True if all elements in set nfl_teams2 are also available in set nfl_teams1:

#### Example:

If the specified set does not contain all items, what should be done?

If set nfl_teams2 does not contain all items in set nfl_teams1, return False:

#### Example:

What should be done if the given set does not include all items?

Return False if set nfl_teams1 does not include all elements in set nfl_teams2:

#### Example:

## Set issuperset() Method

If all items in the specified set exist in the original set, then the **issuperset()** method returns True, otherwise it returns False.

### Syntax

set.issuperset(set)

#### Parameter Values

Set

Delete the elements that are not present in both set nfl_teams1, and set nfl_teams2:

#### Example:

Delete the elements that are not present in both set nfl_teams1, set nfl_teams2 and set nfl_teams3:

#### Example:

You can reverse the first example. Delete the elements that are not present in both set nfl_teams1, and set nfl_teams2:

#### Example:

You can reverse the second example. Delete the elements that are not present in both set nfl_teams1, set nfl_teams2 and set nfl_teams3:

#### Example:

## Set pop() Method

By calling **pop()** method, you can remove a random item from the set.

Returns the item that was removed using this method.

### Syntax

set.pop()

From the nfl_teams set, eliminate a random item:

#### Example:

Take out a random item from the set nfl_teams1 and nfl_teams2:

#### Example:

Get the element that was removed:

#### Example:

Delete the element from two sets and return it:

#### Example:

## Set remove() Method

In the remove() method, the selected element is eliminated from the set.

The remove() method throws an error if the selected item does not exist, whereas the discard() method does not.

### Syntax

set.remove(item)

#### Parameter Values

Parameter |
Description |

item |
It is necessary. The element to search for, and eliminate. |

Take out “Chicago Bears” from the nfl_teams set:

#### Example:

Delete three items from the nfl_teams set:

#### Example:

## Set symmetric_difference() Method

**symmetric_difference()** method returns a set that includes all items from both sets, but not those that are present in both sets.

Result: Items that are not present in both sets appear in the returned set.

### Syntax

set.symmetric_difference(set)

#### Parameter Values

Set

Create a set that includes all items from both sets, except those present in both sets:

#### Example:

Provide a set that includes all items from both sets, except for those in both sets:

#### Example:

## Set symmetric_difference_update() Method

**symmetric_difference_update()** removes items from both sets, and inserts other items into the original set.

### Syntax

set.symmetric_difference_update(set)

#### Parameter Values

Set

Insert the items that are not included in both sets, and eliminate the items that are present in both sets:

#### Example:

Take out the items that are found in both sets, and insert the items that are absent:

#### Example:

## Set union() Method

Union() returns a set containing all items from the original set and all items from the specified set(s).

By using commas, you can specify as many sets as you’d like.

Any iterable object can be used, not just sets.

The result will contain only one appearance of an item if it appears in more than one set.

### Syntax

set.union(set1, set2...)

#### Parameter Values

Parameter |
Description |

set1 |
It is necessary. To unify with the iterable |

set2 |
A choice. Unify with the other iterable.
It is possible to compare as many iterables as you like. Use commas to separate each iteration. |

Provide a set that includes all items from both sets, without duplicates:

#### Example:

All items from both sets should be included in a single set without any duplicates:

#### Example:

Now bringing together more than 3 sets:

#### Example:

Combining more than three sets:

#### Example:

## Set update() Method

By calling the **update()** method, you can update the current set by adding items from another set (or any other iterable).

In the updated set, only one appearance of an item will appear if it appears in both sets.

### Syntax

set.update(set)

#### Parameter Values

Set

Add the elements from set nfl_teams2 to set nfl_teams1:

#### Example:

Insert the elements from set nfl_teams2, nfl_teams3 and nfl_teams4 into set nfl_teams1:

#### Example:

## Python Set Methods Importance

Python set methods are important for several reasons:

- Sets ensure that each element is unique. By using set methods, you can easily eliminate duplicates and work with collections of distinct values. This is particularly useful when dealing with data that requires unique elements.
- Sets provide fast membership testing. The methods
`add()`

,`remove()`

,`discard()`

, and others allow you to efficiently check if an element is present in a set and perform operations accordingly. - Set methods provide functionality for set operations such as union, intersection, difference, and symmetric difference. These operations enable you to combine, compare, and extract elements from sets based on set theory principles.
- Sets are useful for mathematical modeling and solving problems involving sets. The set methods facilitate operations such as finding subsets, checking for superset relationships, and performing set comparisons.
- Sets are effective for removing duplicate values from data collections. By converting a list or any other iterable to a set and back, you can easily eliminate duplicates and obtain a unique collection.
- Sets can be valuable in data analysis and data science workflows. They can be used to perform set-based operations on data, filter unique elements, identify common elements across multiple datasets, and more.
- Sets have a highly optimized implementation for handling operations such as adding, removing, and checking for membership. They are designed for efficient set-based operations, which can lead to improved performance in certain scenarios.