This video examines a variety of data exploration and preparation tasks you should consider after loading a data a set to prepare it for analysis, an examples of how to perform those tasks in Python.
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This is lesson 14 of a 30-part introduction to the Python programming language for data analysis and predictive modeling. Link to the code notebook below:
Python for Data Analysis: Exploring and Cleaning Data
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This guide does not assume any prior exposure to Python, programming or data science. It is intended for beginners with an interest in data science and those who might know other programming languages and would like to learn Python.
I will create the videos for this guide such that you should be able to learn a lot just watching on YouTube, but to get the most out of the guide, it is recommended that you create a Kaggle account so that you can copy and edit each lesson so that you can follow along and run code yourself.
Introduction to Python Playlist:
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Link to the Python for Data Analysis written guide index page:
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⭐ Kite is a free AI-powered coding assistant that integrates with popular editors and IDEs to give you smart code completions and docs while you’re typing. It is a cool application of machine learning that can also help you code faster! Check it out here: [ Ссылка ]
Python for Data Analysis: Exploring and Cleaning Data
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