Python for Data Science. Filtering and Selecting Data with Pandas in Jupyter Notebook (Anaconda).
This is the 1st Video of Python for Data Science Course! In This series I will explain to you Python and Data Science all the time! It is a deep rooted fact, Python is the best programming language for data analysis because of its libraries for manipulating, storing, and gaining understanding from data. Watch this video to learn about the language that make Python the data science powerhouse. Jupyter Notebooks have become very popular in the last few years, and for good reason. They allow you to create and share documents that contain live code, equations, visualizations and markdown text. This can all be run from directly in the browser. It is an essential tool to learn if you are getting started in Data Science, but will also have tons of benefits outside of that field. Harvard Business Review named data scientist "the sexiest job of the 21st century." Python pandas is a commonly-used tool in the industry to easily and professionally clean, analyze, and visualize data of varying sizes and types. We'll learn how to use pandas, Scipy, Sci-kit learn and matplotlib tools to extract meaningful insights and recommendations from real-world datasets.
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Python Data Science Practice Jupyter notebooks and Data Sets:
https://github.com/theengineeringworld/Python-data-science 🔷🔷🔷🔷🔷🔷🔷🔷
*** Complete Python Programming Playlists ***
* Python Statistics Tutorials
https://www.youtube.com/watch?v=GMxCL0PBHzA&list=PLZ7s-Z1aAtmLsianmwFlutJA_ZHiYfaoL* Python Data Science
https://www.youtube.com/watch?v=Uct_EbThV1E&list=PLZ7s-Z1aAtmIbaEj_PtUqkqdmI1k7libK* NumPy Data Science Essential Training with Python 3
https://www.youtube.com/playlist?list=PLZ7s-Z1aAtmIRpnGQGMTvV3AGdDK37d2b* Python 3.6.4 Tutorial can be fund here:
https://www.youtube.com/watch?v=D0FrzbmWoys&list=PLZ7s-Z1aAtmKVb0fpKyINNeSbFSNkLTjQ* Python Smart Programming in Jupyter Notebook:
https://www.youtube.com/watch?v=FkJI8np1gV8&list=PLZ7s-Z1aAtmIVV0dp08_X-yDGrIlTExd2* Python Coding Interview:
https://www.youtube.com/watch?v=wwtzs7vTG50&list=PLZ7s-Z1aAtmJqtN1A3ydeMk0JoD3Lvt9g-~-~~-~~~-~~-~-
Please watch: "How to Calculate Age from Date of Birth in Excel in Years Months and Days (Simple Formula)"
https://www.youtube.com/watch?v=Jy-EO724its-~-~~-~~~-~~-~-
About the Site 🌐
This site provides links to random videos hosted at YouTube, with the emphasis on random. 🎥
Origins of the Idea 🌱
The original idea for this site stemmed from the need to benchmark the popularity of a video against the general population of YouTube videos. 🧠
Challenges Faced 🤔
Obtaining a large sample of videos was crucial for accurate ranking, but YouTube lacks a direct method to gather random video IDs.
Even searching for random strings on YouTube doesn't yield truly random results, complicating the process further. 🔍
Creating Truly Random Links 🛠️
The YouTube API offers additional functions enabling the discovery of more random videos. Through inventive techniques and a touch of space-time manipulation, we've achieved a process yielding nearly 100% random links to YouTube videos.
About YouTube 📺
YouTube, an American video-sharing website based in San Bruno, California, offers a diverse range of user-generated and corporate media content. 🌟
Content and Users 🎵
Users can upload, view, rate, share, and comment on videos, with content spanning video clips, music videos, live streams, and more.
While most content is uploaded by individuals, media corporations like CBS and the BBC also contribute. Unregistered users can watch videos, while registered users enjoy additional privileges such as uploading unlimited videos and adding comments.
Monetization and Impact 🤑
YouTube and creators earn revenue through Google AdSense, with most videos free to view. Premium channels and subscription services like YouTube Music and YouTube Premium offer ad-free streaming.
As of February 2017, over 400 hours of content were uploaded to YouTube every minute, with the site ranking as the second-most popular globally. By May 2019, this figure exceeded 500 hours per minute. 📈
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