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[Tut] How to Convert List of Lists to NumPy Array? - Printable Version +- Sick Gaming (https://sickgaming.net) +-- Forum: Programming (https://sickgaming.net/forum-76.html) +--- Forum: Python (https://sickgaming.net/forum-83.html) +--- Thread: [Tut] How to Convert List of Lists to NumPy Array? (/thread-94748.html) |
[Tut] How to Convert List of Lists to NumPy Array? - xSicKxBot - 04-27-2020 How to Convert List of Lists to NumPy Array? Short answer: Convert a list of lists—let’s call it Code: lCode: np.array(l)Convert List of Lists to 2D Array Problem: Given a list of lists in Python. How to convert it to a 2D NumPy array? Example: Convert the following list of lists Code: [[1, 2, 3], [4, 5, 6]]into a NumPy array Code: [[1 2 3] [4 5 6]]Solution: Use the Code: np.array(list)Code: # Import the NumPy library
import numpy as np # Create the list of lists
lst = [[1, 2, 3], [4, 5, 6]] # Convert it to a NumPy array
a = np.array(lst) # Print the resulting array
print(a) '''
[[1 2 3] [4 5 6]] '''Try It Yourself: Here’s the same code in our interactive code interpreter: Code: <iframe height="700px" width="100%" src="https://repl.it/@finxter/numpylistoflists?lite=true" scrolling="no" frameborder="no" allowtransparency="true" allowfullscreen="true" sandbox="allow-forms allow-pointer-lock allow-popups allow-same-origin allow-scripts allow-modals"></iframe>Hint: The NumPy method Code: np.array()Convert a List of Lists With Different Number of Elements Problem: Given a list of lists. The inner lists have a varying number of elements. How to convert them to a NumPy array? Example: Say, you’ve got the following list of lists: Code: [[1, 2, 3], [4, 5], [6, 7, 8]]What are the different approaches to convert this list of lists into a NumPy array? Solution: There are three different strategies you can use. (source) (1) Use the standard Code: np.array()Code: # Import the NumPy library
import numpy as np # Create the list of lists
lst = [[1, 2, 3], [4, 5], [6, 7, 8]] # Convert it to a NumPy array
a = np.array(lst) # Print the resulting array
print(a) '''
[list([1, 2, 3]) list([4, 5]) list([6, 7, 8])] '''This creates a NumPy array with three elements—each element is a list type. You can check the type of the output by using the built-in Code: type()Code: >>> type(a)
<class 'numpy.ndarray'>(2) Make an array of arrays. Code: # Import the NumPy library
import numpy as np # Create the list of lists
lst = [[1, 2, 3], [4, 5], [6, 7, 8]] # Convert it to a NumPy array
a = np.array([np.array(x) for x in lst]) # Print the resulting array
print(a) '''
[array([1, 2, 3]) array([4, 5]) array([6, 7, 8])] '''This is more logical than the previous version because it creates a NumPy array of 1D NumPy arrays (rather than 1D Python lists). (3) Make the lists equal in length. Code: # Import the NumPy library
import numpy as np # Create the list of lists
lst = [[1, 2, 3], [4, 5], [6, 7, 8, 9]] # Calculate length of maximal list
n = len(max(lst, key=len)) # Make the lists equal in length
lst_2 = [x + [None]*(n-len(x)) for x in lst]
print(lst_2)
# [[1, 2, 3, None], [4, 5, None, None], [6, 7, 8, 9]] # Convert it to a NumPy array
a = np.array(lst_2) # Print the resulting array
print(a) '''
[[1 2 3 None] [4 5 None None] [6 7 8 9]] '''You use list comprehension to “pad” Code: NoneWhere to Go From Here? Enough theory, let’s get some practice! To become successful in coding, you need to get out there and solve real problems for real people. That’s how you can become a six-figure earner easily. And that’s how you polish the skills you really need in practice. After all, what’s the use of learning theory that nobody ever needs? Practice projects is how you sharpen your saw in coding! Do you want to become a code master by focusing on practical code projects that actually earn you money and solve problems for people? Then become a Python freelance developer! It’s the best way of approaching the task of improving your Python skills—even if you are a complete beginner. Join my free webinar “How to Build Your High-Income Skill Python” and watch how I grew my coding business online and how you can, too—from the comfort of your own home. Join the free webinar now! |