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Python Algotrading eBook - https://linktr.ee/kuldeepsinghalgo MCQs +Mini Projects - https://linktr.ee/kuldeepsinghalgo Python Algotrading Book (Hard Copy ) - https://www.amazon.com/dp/B0F3S8FQ7C Download code from Skool Community - https://www.skool.com/the-quantitative-elite-1670 Python lists | 4/100 Days of Python Algo trading 100 Days Schedule Link https://1drv.ms/w/s!AkJTmoKJV3m4gTGCTKeeYPQLp0iJ?e=cd2vQu MCQs Link https://gotraddy.com/python-lists-4-100-days-of-python-algo-trading/ Coding Task Link https://github.com/thekuldeepsingh/100-Days-Of-Hell-With-Python-Algotrading/tree/main/Day_4_Python_Lists Welcome to Day 4 of our 100-day Python algo trading challenge! In today's video, we're unraveling the power of Python lists, a versatile data structure that's essential for managing collections of information in your trading algorithms. Here's a breakdown of what you'll learn: 00:00 Introduction: Get ready to explore the capabilities of Python lists! 00:01:42 Topics we cover in this Video: A quick overview of the essential concepts you'll master. 00:02:02 Python Lists: Discover what makes lists so useful for organizing data. 00:03:24 Array vs List (Theory): Understand the key differences between these two structures in Python. 00:09:28 Array vs List (Practical): See real-world examples to solidify your understanding. 00:12:27 Types of List: Explore different types of lists you can create in Python. 00:17:57 Create and access a list (Theory): Learn the syntax and techniques for building and accessing lists. 00:23:53 Create and access a list (Practical): Get hands-on experience with list creation and manipulation. 00:34:37 Editing items in a list: Discover how to modify existing elements within your lists. 00:37:07 Deleting items from a list: Learn techniques for removing unwanted items. 00:41:38 Operations on Lists: Explore operations like concatenation, repetition, and more. 00:43:51 List functions: Dive into built-in functions for sorting, reversing, counting, and more. 00:49:36 List Comprehension: Master this concise way to create and modify lists. 01:00:45 Disadvantages of Python Lists: Get a balanced perspective by understanding the limitations of lists. By the end of this video, you'll be proficient in using lists to store, organize, and analyze financial data, laying a solid foundation for your algo trading journey. Let's get started! Connect with us Youtube www.youtube.com/@KuldeepSinghAlgo Instagram https://www.instagram.com/kuldeepsinghalgo/ Facebook www.facebook.com/Kuldeepsinghalgo/ X ( twitter ) https://twitter.com/Kuldeepalgo Linkedin https://www.linkedin.com/in/kuldeepsinghalgo/ Discord https://discord.gg/TVdMnvR8Pb Telegram https://web.telegram.org/k/#@kuldeepsinghalgo Whatsapp https://whatsapp.com/channel/0029VaMXvPvK5cDDnQeIsg0s Github https://github.com/thekuldeepsingh/100-Days-Of-Hell-With-Python-Algotrading/ Tags python for beginners python for finance python for trading python algo trading tutorial AI in trading machine learning for beginners machine learning algorithms for trading deep learning for finance algorithmic trading strategies how to build a trading bot with python trading bot tutorial algo trading for beginners machine learning for beginners course AI for beginners course python for algo trading beginners machine learning for algo trading strategies how to build an AI trading bot with python Python mini projects Data science projects Data analysis projects Algotrading projects #python #pythonprogramming #pythontrading #pythonalgotrading #artificialintelligence #AI #machinelearning #ML #deeplearning #algorithms #algotrading #algorithmictrading #trading #finance #cryptocurrency #bitcoin #Algo strategies for option trading #Python algo trading tutorial #Machine learning projects in algo trading #Option trading strategies in python advanced #Machine learning trading strategies #Intraday algo trading strategies #Technical analysis with python #Advance python for machine learning #How to create algo trading software #Deep learning python tutorial #Python algorithms for interviews #Algo trading #Quanttrading #Quantreasearch #Quantitative researcher #Quantitative trading
