Python for Data Analysis: Preparing Numeric Data
This video examines a variety of techniques for preprocessing and preparing numeric data for analysis in Python. It covers centering and scaling data, dealing with skewed data, identifying and dealing with highly correlated features and imputing missing data with the sklearn package.
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This is lesson 16 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: Preparing Numeric Data
https://www.kaggle.com/hamelg/python-...
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:
• Python for Data Analysis
Link to the Python for Data Analysis written guide index page:
https://www.kaggle.com/hamelg/python-... .
⭐ 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: https://www.kite.com/get-kite/?utm_me...
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