How to create lists from a Dictionary in Python
In Python, a dictionary is a collection of keys and values. A key is a unique identifier for an item in a dictionary, and a value is the item itself. Dictionaries are commonly used to store data that is related to one another, such as a list of names and their corresponding ages.
Sometimes, you may want to extract certain values from a dictionary and store them in a list. This can be done by creating a list from the dictionary in Python.
One way to create a list from a dictionary is by using the values() method. This method returns a list of all the values in the dictionary. For example, if you have a dictionary called “ages” that contains the names of people as keys and their corresponding ages as values, you can create a list of all the ages by calling the values() method on the dictionary like this: ages.values().
Another way to create a list from a dictionary is by using a for loop. This method involves iterating through the dictionary and appending the values to a list. For example, if you have a dictionary called “ages” that contains the names of people as keys and their corresponding ages as values, you can create a list of all the ages by using a for loop like this:
ages_list = []
for age in ages.values():
ages_list.append(age)
Additionally, you can use the dictionary comprehension to create a list from the dictionary. This method is similar to the for loop method but it’s more concise and readable. For example, you can use the following code to create a list of all the ages from the dictionary “ages”:
ages_list = [age for age in ages.values()]
Another way to create a list from a dictionary is by using the items() method. This method returns a list of all the key-value pairs in the dictionary as tuples. For example, if you have a dictionary called “ages” that contains the names of people as keys and their corresponding ages as values, you can create a list of all the key-value pairs by calling the items() method on the dictionary like this: ages.items().
In conclusion, you can create lists from dictionaries in Python by using the values() method, the items() method, a for loop or dictionary comprehension. The values() method and the items() method return a list of all the values or key-value pairs respectively, a for loop and dictionary comprehension can be used to iterate through the dictionary and append the values to a list. It’s important to choose the method that fits the problem and the data best, depends on the task you’re trying to accomplish and the data you’re working with.
Here’s an example of creating a list from a dictionary using different methods:
# Example dictionary
ages = {'John': 25, 'Mike': 30, 'Sara': 35, 'Jane': 40}
# Using the values() method
ages_list = list(ages.values())
print(ages_list) # Output: [25, 30, 35, 40]
# Using a for loop
ages_list = []
for age in ages.values():
ages_list.append(age)
print(ages_list) # Output: [25, 30, 35, 40]
# Using dictionary comprehension
ages_list = [age for age in ages.values()]
print(ages_list) # Output: [25, 30, 35, 40]
# Using the items() method
ages_list = list(ages.items())
print(ages_list)
# Output: [('John', 25), ('Mike', 30), ('Sara', 35), ('Jane', 40)]
Latest end-to-end Learn by Coding Projects (Jupyter Notebooks) in Python and R:
All Notebooks in One Bundle: Data Science Recipes and Examples in Python & R.
End-to-End Python Machine Learning Recipes & Examples.
End-to-End R Machine Learning Recipes & Examples.
Applied Statistics with R for Beginners and Business Professionals
Data Science and Machine Learning Projects in Python: Tabular Data Analytics
Data Science and Machine Learning Projects in R: Tabular Data Analytics
Python Machine Learning & Data Science Recipes: Learn by Coding
R Machine Learning & Data Science Recipes: Learn by Coding
Comparing Different Machine Learning Algorithms in Python for Classification (FREE)
There are 2000+ End-to-End Python & R Notebooks are available to build Professional Portfolio as a Data Scientist and/or Machine Learning Specialist. All Notebooks are only $29.95. We would like to request you to have a look at the website for FREE the end-to-end notebooks, and then decide whether you would like to purchase or not.