Hi! My name is Martin. I’m a Master of Science in Economic and Social Sciences from Bocconi University in Milan, Italy but to all my students, I am also the author and instructor of the Python, SQL, and Integration courses in the 365 Data Science Program. And I am excited to share that we just launched the latest addition to our training – Data Cleaning and Preprocessing with pandas Course!
I wrote this brief post to share with you the main course features, its structure, and the hands-on skills it will help you build up. I’ll also tell you a bit more about myself and the projects I’ve worked on here, at 365 Data Science.
The 365 Data Science Data Cleaning and Preprocessing with pandas Course
Why pandas?
The pandas library is one of the go-to Python tools for data manipulation and analysis. It is fast, flexible, and super valuable because it allows you to import large datasets efficiently and manipulate all sorts of information, including numerical tables, time series data, and text. By the time you finish the course, you’ll be comfortable cleaning data from all types of sources (not just flawless ones) and preprocess it for actual visualizations and analysis by implementing the right statistical tools and advanced pandas techniques.
Who Is This pandas Course for?
The Data Cleaning and Preprocessing with pandas course is a perfect fit not only for beginners, but for anyone who wants to take their Python programming skills to the next level and learn how to use pandas second-to-none features to produce a complete and consistent data analysis independently.
What Is the Structure of the pandas Course?
The course comprises 28 lectures, 105 exercises, and 10 downloadables. If you’d like to explore all topics in the course curriculum, you can find them on the Data Cleaning and Preprocessing with pandas course page.
What Will You Learn?
This course covers all the pandas basics you need to know - from installation and running, to mastering and applying its rich methods and functions in your tasks.
You will learn how to:
- Install and run pandas
- Work with pandas Series
- Work with Attributes in Python
- Use an Index in pandas
- Compare Label-based and Position-based Indexing
- Use methods in Python
- Distinguish between Parameters vs Arguments
- Make the most of the pandas documentation
- Create and use pandas DataFrame from scratch
About the Author
As I mentioned, I have MSc in Economic and Social Sciences. Over the years, I have built advanced knowledge of Python programming, SQL, Mathematics, Statistics, Econometrics, Time-Series, and Behavioral Economics & Finance. My experience includes assisting in empirical research for Innocenzo Gasparini Institute of Economic Research. I've also worked for DG Justice and Consumers at the European Commission where I dealt with data preprocessing; data quality checking; econometric and statistical analyses. You can learn more about me and my overview of the most in-demand programming languages in my 365 Meet-the-Team Interview.
The Data Cleaning and Preprocessing with pandas Course is part of the 365 Data Science Program, so enrolled students can access the courses at no extra cost.
Not a current subscriber? You can try the Data Cleaning and Preprocessing with pandas Course for free!
