# Convert two lists into a Dictionarymy_keys=['a','b','c']my_values=[1,2,3]my_dict=dict(zip(my_keys,my_values))print(my_dict)# Output:# {'a': 1, 'b': 2, 'c': 3} If the lists have different lengths, thezip()function will truncate the longer list to match the length...
It sometimes becomes necessary to convert lists into a key-value pair array. Your lists must be same in length. Now, we will discuss and take two lists and mark them together to create a Python dictionary using three different ways. Convert two lists to a dictionary using loop and remove(...
You can convert a Python list to a dictionary using the dict.fromkeys() method, a dictionary comprehension, or the zip() method. The zip() method is useful if you want to merge two lists into a dictionary. Let’s quickly summarize these methods: dict.fromkeys(): Used to create a dicti...
As seen, we have two lists defined under the names: keys and values. Now let’s continue with the first example of the tutorial! Example 1: Transform the Lists into a Dictionary with dict() & zip() FunctionsIn this example, we will use Python’s dict() function to convert the lists...
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As you can see, the elements from the two different lists have been merged to form a Python Dictionary. Conclusion A list of types can be converted into a Python dictionary by using the dict() constructor with either the list comprehension approach or by using the map() method within the ...
When we use these two statements, the outcome will be the same. Let’s use an implicit element selector, as shown below. Example code: #Csharpvar seasonsById=seasonList.ToDictionary(keySelector:s=>s.Id,elementSelector:s=>s); Let’s use an explicit element selector, as shown below. ...
Convert List Pairs to a Dictionary using dict() and zip() In this example, there are two lists of equal lengths (p_namesandp_born). Note: The first list element (p_names[0]) contains the name of the poet (p_names) and becomes the unique dictionarykey. The second element (p_born...
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There are two primary types of dictionary orientations which are calledColumnsandindex. It is to make the distinction between the different types of dictionary orientations with theorient='columns'. # Dictionary orientations of column df=pd.DataFrame.from_dict(technologies, orient='columns') ...