Summary of Python dictionary operations (with examples)
This article brings you a summary of the operation of Python dictionary (with examples). It has certain reference value. Friends in need can refer to it. I hope it will be helpful to you.
The dictionary (dict) structure is a commonly used data structure in Python. Based on my actual use experience, the author makes a summary of the relevant knowledge about dictionaries, hoping to give some inspiration to readers~
Create a dictionary
The common way to create a dictionary is to first create an empty dictionary, and then add the keys and values one by one, such as creating a dictionary person={'name':'Tome', 'age' :22, 'city':'Shanghai, 'ID': '073569'}, you can use the following code:
person = {} person['name'] = 'Tom' person['age'] = 22 person['city'] = 'Shanghai' person['ID'] = '073569' print(person)
The output result is:
{'name': 'Tom', 'age': 22, 'city': 'Shanghai', 'ID': '073569'}
This creation method is simple and original, the code Not simple and elegant enough. We use the zip function to create this dictionary simply and quickly:
attrs = ['name', 'age', 'city', 'ID'] values = ['Tom', 22, 'Shanghai', '073569'] person = dict(zip(attrs, values)) print(person)
The output result is consistent with the original code.
Traverse the dictionary
In practical applications, we often need to traverse the dictionary. For the implementation method, please refer to the following code:
attrs = ['name', 'age', 'city', 'ID'] values = ['Tom', 22, 'Shanghai', '073569'] person = dict(zip(attrs, values)) for key, value in person.items(): print('Key:%-6s, Value:%s'%(key, value))
The output result is:
Key:name , Value:Tom Key:age , Value:22 Key:city , Value:Shanghai Key:ID , Value:073569
Swapping key-value pairs
In practical applications, sometimes we need to find the key (key) corresponding to a certain value (value) in the dictionary. Traversing the dictionary is one option, and swapping key-value pairs is another. choice. The implementation code for swapping key-value pairs is as follows:
attrs = ['name', 'age', 'city', 'ID'] values = ['Tom', 22, 'Shanghai', '073569'] person = dict(zip(attrs, values)) print('对调前:') print(person) Person = {v:k for k,v in person.items()} print('对调后:') print(Person)
The output result is:
对调前: {'name': 'Tom', 'age': 22, 'city': 'Shanghai', 'ID': '073569'} 对调后: {'Tom': 'name', 22: 'age', 'Shanghai': 'city', '073569': 'ID'}
Ordered DictionaryOrderedDict
The dictionary in Python is unordered. The key is unordered because it is stored as a hash. Sometimes, we need the items or keys of the dictionary to be stored in order. At this time, we can use the OrderedDict
in the collections
module, which is an ordered dictionary structure.
The sample code is as follows (Python version is 3.5.2):
from collections import OrderedDict d = {} d['Tom']='A' d['Jack']='B' d['Leo']='C' d['Alex']='D' print('无序字典(dict):') for k,v in d.items(): print(k,v) d1 = OrderedDict() d1['Tom']='A' d1['Jack']='B' d1['Leo']='C' d1['Alex']='D' print('\n有序字典(OrderedDict):') for k,v in d1.items(): print(k,v)
The output result is:
无序字典(dict): Leo C Jack B Tom A Alex D 有序字典(OrderedDict): Tom A Jack B Leo C Alex D
Default dictionary collections.defaultdict
collections. defaultdict
is a subclass of Python's built-in dict
class. The first parameter provides the initial value for the default_factory attribute, which defaults to None
. It overrides a method and adds a writable instance variable. Its other functions are the same as dict
, but it will provide a default value for a non-existent key, thereby avoiding KeyError
exceptions.
We take the word frequency of words in the statistical list as an example to demonstrate the advantages of collections.defaultdict
.
Normally, the word frequency code in our statistical list is:
words = ['sun', 'moon', 'star', 'star',\ 'star', 'moon', 'sun', 'star'] freq_dict = {} for word in words: if word not in freq_dict.keys(): freq_dict[word] = 1 else: freq_dict[word] += 1 for key, val in freq_dict.items(): print(key, val)
The output result is as follows:
sun 2 moon 2 star 4
Using collections.defaultdict
, the code can be optimized:
from collections import defaultdict words = ['sun', 'moon', 'star', 'star',\ 'star', 'moon', 'sun', 'star'] freq_dict = defaultdict(int) for word in words: freq_dict[word] += 1 for key, val in freq_dict.items(): print(key, val)
Other default initial values can be set, list, dict, etc.
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