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This article mainly introduces "what are the methods used by Python data types". In daily operation, I believe that many people have doubts about the methods used by Python data types. The editor consulted all kinds of materials and sorted out simple and easy-to-use operation methods. I hope it will be helpful to answer the doubts about "what methods are used by Python data types?" Next, please follow the editor to study!

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Overview | data types of No. 6 Middle School

There are six basic data types provided by Python:

Digital (Number)

String (String)

Tuple (Tuple)

Collection (Sets)

List (List)

Dictionary (Dictionary)

The built-in type () function can be used to query the object type referred to by the variable.

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Tuple | T.method ()

Tuple: tuple ()

The concept and basic usage of tuples are not repeated here.

You can use tuple () to create a new tuple directly, or you can use tuple () to convert an object into a tuple.

The property of a tuple is that the elements in it cannot be modified.

There are two methods involved here: tuple.count () and tuple.index ().

1. Tuple.count (value): returns the number of value in the tuple.

2. Tuple.index (value, [start, [stop]]): returns the first index of value. If value does not exist, ValueError is thrown. You can set start and stop to limit the scope of index retrieval.

Let's look at an example.

Press the index method of the tuple to set the range represented by the interval, which is consistent with the list type (list).

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Collection | set.method ()

Collection: set ()

The concept and basic usage of sets are not repeated here.

You can use set () to create a new tuple directly, or you can use set (object) to convert an object into a tuple.

The characteristic of a set is the uniqueness of its elements.

1. Set.add (): adds an element to the collection, which is invalid if it already exists. Only one element can be added at a time.

2. Set.pop (): deletes and returns an arbitrary collection element. If set to empty, a KeyError is thrown.

3. Set.copy (): returns a shallow copy of the collection. The concept of latent copying is not repeated here.

4. Set.difference (): returns elements that set1 has elements that set2 does not have.

Press: if set1 is a subset of set2, an empty collection is returned.

5. Set.difference_update (): update set1 with elements that set1 has and set2 does not have.

6. Set.discard (): if it is a member, remove an element from the collection. If the element is not a member, do nothing.

7. Set.intersection (): returns the intersection of two sets as a new collection.

8. Set.intersection_update (): update a collection with the intersection of yourself and another.

9. Set.isdisjoint (): returns True if the intersection of two sets is empty.

10. Set.issubset (): reports whether another collection contains this collection. Is to return True.

11. Set.issuperset (): reports whether this collection contains another collection. Is to return True.

12. Set.clear (): removes all elements from the collection.

13. Set.remove (): removes an element from the collection; if the element is not in the collection, a KeyError is thrown.

14. Set.symmetric_difference (): returns the symmetric difference between two sets as a new set.

15. Set.symmetric_difference_update (): updates a set with its own symmetric difference and another.

The symmetric difference between two sets is a set of elements that only belong to one set and not to the other.

16. Set.union (): returns the union of the collection as a new collection.

17. Set.update (): returns the union of the collection and updates a collection.

Press:

Set basic operations and corresponding methods:

Union: set.union (), set.update ()

Intersection: set.intersection (), set.intersection_update ()

Supplementary set: set.symmetric_difference (), set.symmetric_difference_update ()

Difference: set.difference (), set.difference_update ()

At this point, the study of "what methods are used for Python data types" is over. I hope to be able to solve your doubts. The collocation of theory and practice can better help you learn, go and try it! If you want to continue to learn more related knowledge, please continue to follow the website, the editor will continue to work hard to bring you more practical articles!

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