Python Lists in Algorithmic Trading & Crypto Strategies 4/100 Days

/ algo trading, algorithmic trading, Python, Quizzes
Python lists

Welcome back to Day 4 of 100 Days of Hell with Python Algo Trading! Today, we’ll dive deep into Python lists, a crucial data structure for quantitative traders. We’ll compare lists with arrays, explore their characteristics, and implement crypto trading strategies using lists. Plus, we’ll discuss memory storage, advantages, and disadvantages of lists in quantitative analysis for trading in Singapore. Let’s get started!

I have few important updates so let me explain them one by one the first update is the mcqs are very very important we have researched and curated all of those questions very diligently so if you attempt those you will feel that you are having much more better understanding of the topic and if you really want to learn fast and quick you have to attempt those questions it will not cost you anything second is Task all the task questions also researched similarly as mcqs and we have also included python mini projects for each and every topic so you can think the process which we have discussed in the first introduction video right the process is three-stage process first we are learning and then you are applying that knowledge at three places.

MCQS python task and then mini project so it will cement that task in your brain for Generations now the Discord and telegram so it’s not mandatory if you have questions if you have any queries you can come and you can ask us okay we’ll try our best to resolve your all queries but it’s not mandatory for you to come and join it’s just a community so where we can discuss and we can resolve our issues okay you just have to focus on your learning that’s it then we have the fourth that is doubt clearing session for that if you really have some doubts you can let us know in the Des Discord or Telegram and accordingly.

Python lists
Python lists1

We will create some sessions on weekends okay or we can have some live sessions also so we can plan that in future so that was quick update now let’s quickly move to the python list okay so in this session first we will cover the introduction then we’ll compare the list with the arrays and then we will see how lists are stored in the memory right then the characteristics of python list and then we will see some examples with all the operations and last but not the least least disadvantages of the Python list okay so now we quickly understand.

What are the list so list is a data type where you can store multiple items under one name okay I’ll just quickly explain how then more technically list act like Dynamic arrays which means you can add more items on the Fly then we’ll understand why lists are required in programming okay so let’s create an example of list so let’s say we have a list which contains the details of any trade so we will name it as trade logs okay this is hyphen so in that list we have let’s say the opening price then a string so the name of the stock Apple correct then we can say the selling price okay so it could be 11.6 which is a flot and then let’s say we have a Boolean value so which can be true right for example.

If the buy was true or false so it can be true so this is integer this is string this is float and this is aoan value and this list is able to store all those data types right so which makes it so flexible and so adaptable okay now let’s compare the list with arrays so let’s say we create a table okay so the first is for arrays and this is for the list okay then now let’s compare it okay so the first point is fixed versus Dynamic why because when we create an array so how do we do that we have to give the size beforehand for example.

Let’s say you are creating an array of int and the size is 50 so here you have to mention that we will be creating an array with the size 50 means it is fixed correct we can say it is fixed but in list you don’t have to do that you can create an empty list or you can create a list which consists multiple values there is no restriction like that then the second point is the arrays are homogeneous means these can store only one data type so here we know that this is integer if we want an array with a string values then we have to create another array similarly for float and so on so forth so means these are homogeneous the second difference is these are homogeneous.

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Day 4: Python Lists

1. Python lists and arrays are similar but have a key difference. What is it?

2. How are lists represented in Python’s memory?

3. Which of the following are characteristics of Python lists? (Choose all that apply)

4. What’s the output of this code?
Python
my_list = [1, 2, “hello”]
print(my_list[1])

5. What’s the difference between the append() and extend() methods for lists?

6. What does my_list.insert(2, “new”) do?

7. How can you delete the element at index 1 from a list named numbers?

8. What is the result of [1, 2, 3] * 2?

9. How do you check if the value 5 is present in a list named my_list?

10. What does the len() function do when used with a list?

11. What does the my_list.sort() method do?

12. How would you find the minimum value in a list called numbers?

13. What does the list.reverse() method do?

14. What’s a concise way to create a list of squares of numbers 1 to 10?

15. How would you iterate through a list named colors and print both the index and value of each element?

16. Consider these lists: names = [“Alice”, “Bob”] and ages = [25, 30]. What’s the output of list(zip(names, ages))?

17. List as heterogeneous containers: Which code demonstrates that Python lists can store different data types?

18. What is a potential disadvantage of using Python lists?

19. For scenarios focusing heavily on search operations, what might be a better alternative to a Python list?

20. In which situation might using a NumPy array be more advantageous than a Python list?