Looking to level up your Python and Pandas fluency? Over the coming month, I'll be offering a wide variety of live, online classes aimed at all levels.
If you feel overwhelmed or frustrated when writing Python and Pandas, then you'll want to join me.
All courses are:
- 100% live coding into Jupyter, no slides
- You can download my Jupyter notebook when the class is done
- Lots of hands-on exercises
- Plenty of time for questions and comments
- Recorded for viewing and re-viewing whenever you want
What do people think of my classes? Here is some feedback from the last few weeks: - It was amazing. Reuven is one of the best instructors I know. It is always so great to get a course from him.
- Instructor gave insight into some smaller things that I've looked passed in all the years of using Python and explained why they matter so much. I don't think I would have discovered them on my own.
- Reuven took the time to explain things very well specially for someone like me who is new to programming.
- I like the explanations of the instructor. he was clear, and it was easy to understand him.
Upcoming live courses are included, free of charge, in my membership program at https://LernerPython.com. (The Pandas courses are in my Python+Data plan; Python courses are for all subscribers.)
Of course, if you prefer, you can also buy these courses individually.
As always, all purchases and memberships are discounted for students, retirees/pensioners, and people from non-rich countries; contact me if you're eligible for one of these.
Here are the classes I'm offering in the coming week:
Data cleaning in Pandas
Real-world data is messy. We'll review techniques for identifying, removing, repairing, and replacing bad data, so that your analysis will be as accurate as possible. This is an intermediate-level Pandas course; it assumes that you have a working familiarity with data frames, dtypes, and basic Pandas methods.
Signup link: https://store.lerner.co.il/data-cleaning-in-pandas
Method chaining in Pandas
Method chaining is growing in popularity among Pandas users, and for good reason: It allows you to break long queries into multi-line expressions, adding to them incrementally. In this class, we'll explore what method chaining is, how it works, and the methods that Pandas provides to enable chaining, including "append" and "pipe", as well as the combination of "loc" and "lambda". This is an advanced-level Pandas course.
Signup link: https://store.lerner.co.il/complex-queries-with-method-chaining-in-pandas
Design patterns in Python
Creating objects in Python isn't too difficult. But any serious project will use more than one class. Design patterns provide us with proven mental models for connecting classes together into a single application, and a vocabulary that's shared among many software engineers. In this class, I'll introduce a variety of different design patterns that you can incorporate into your own day-to-day work. This intermediate-level class assumes experience and familiarity with object-oriented Python, including classes, methods, attributes, and inheritance.
Signup link: https://store.lerner.co.il/design-patterns-in-python-aug-2024
Python decorators
Decorators are one of the topics that most confuses Python developers. In this class, I'll break down what decorators are, how they work, and the many ways in which we can use them. If you're comfortable writing Python functions, then you can definitely learn to write and use decorators.
Signup link: https://store.lerner.co.il/python-decorators-aug-2024
Textual data in Pandas
We often assume that Pandas is only for numeric data. But it turns out that Pandas has a great deal of string functionality, as well. In this class, we'll see just what Pandas has to offer when it comes to strings, and how we can best use those capabilities to explore, analyze, and filter our data. This is a beginner-level Pandas course, suitable for anyone who has just started to use the library.
Signup link: https://store.lerner.co.il/textual-data-in-pandas-aug-2024
CSV files in Pandas
Data is commonly distributed in CSV format. Pandas can handle such files just fine, thanks to "read_csv", which returns a new data frame. But as you might have noticed, read_csv has a huge number of options — it's hard to know where to start, and which are actually important to remember. In this case, we'll look at read_csv, explore many of its options, and learn how to read CSV data efficiently and idiomatically.
Signup link: https://store.lerner.co.il/working-with-csv-files-in-pandas
This is just the start!
These are just the first of many courses I'll be offering over the coming month or two. The full list of courses I'm offering (so far!) is at https://lerner.co.il/2024/08/08/level-up-your-python-skills-this-august/
Questions? Just e-mail me at reuven@lerner.co.il. Your message will go straight to my inbox.
Reuven