Implementing Policy for Missing Values in Python
This course offers a deep dive into addressing dataset incompleteness. From basic drop methods to intricate regression imputations, emerge equipped to tackle any missing data challenge with confidence.
What you'll learn
Every dataset, no matter its origin, often faces the issue of missing values. Such gaps can skew analysis, lead to erroneous conclusions, and even derail machine learning models.
In this course, Implementing Policy for Missing Values in Python, you’ll gain the ability to effectively handle and impute missing values in any dataset.
First, you’ll explore the implications of missing data and understand foundational strategies like dropping instances or attributes.
Next, you’ll discover the art and science of imputation, diving deep into techniques involving mean, median, and mode.
Finally, you’ll learn how to utilize regression models and other advanced methods to intelligently predict and fill these data voids.
When you’re finished with this course, you’ll have the skills and knowledge of data imputation needed to ensure dataset integrity and boost the quality of your data-driven decisions.
Table of contents
- Course and Module Introduction 2m
- What Is Missing Data and What Causes It? 4m
- The Impact of Missing Data 1m
- The Decision Crossroads – To Drop or Not? 2m
- Introduction to Imputation 1m
- Exploring Imputation with Mean 2m
- Balancing Data with Median 2m
- Catering to Categoricals: Imputing with Mode 2m
- Sequencing Solutions: Forward and Backward Fill 2m
- Demo: Introduction to the Dataset 3m
- Demo: Setting up Your Environment 2m
- Demo: Dealing with Missing Data - Part 1 5m
- Demo: Dealing with Missing Data - Part 2 5m
- Module Summary 1m
About the author
Pratheerth is a Data Scientist who has entered the field after an eclectic mix of educational and work experiences. He has a Bachelor's in Engineering in Mechatronics from India, Masters in Engineering Management from Australia and then a couple of years of work experience as a Production Engineer in the Middle East. Then when the A.I bug bit him, he dropped everything to dedicate his life to the field. He is currently working on mentoring, course creation and freelancing as a Data Scientist.