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 It's Time to Uncover and Apply For centuries, electricity was thought to be the domain of sorcerers, and magicians who perplexed audiences as to where it did come from and how it was engendered. Although Ben Franklin and his colleagues were all well conscious of the phenomenon when he demonstrated the connection between both electricity and lightning in 1752, he had difficulty imagining a practical application for it. His more prized invention, the lightning rod, has more to do with ignoring electricity. All new inventions are subjected to a similar system of rejection, avoidance, fear, and, possibly, acceptance. Just about two centuries after Franklin's lightning experiment, the man had been habitually harnessing power, despite our lack of complete knowledge of its origins. The Lineman's Handbook of 1928 begins, "What is electricity?" Nobody knows." Understanding the composition of electricity, however, was not important, according to this guidebook for ear...

Python has become one of the most popular programming languages in the world, renowned for its versatility and ease of use. Its extensive range of libraries and frameworks, coupled with the availability of Python training courses, make it a powerful tool for data analytics. In this article, we will explore the features and applications of Python in the realm of data analytics. Python is an interpreted, high-level programming language known for its simplicity and readability. It provides a wide array of data structures and supports multiple programming paradigms, including procedural, object-oriented, and functional programming. Python's versatility lies in its ability to integrate seamlessly with other languages and platforms, making it an excellent choice for data analytics projects of varying scales. Watch this video: Python vs Scala, What is the difference? pros and cons 1. Data Manipulation and Analysis : Python offers robust libraries such as NumPy and Pandas, which provide ef...