Truly, it is one of the most straightforward and powerful data manipulation libraries, yet, because it is so easy to use, no one really spends much time trying to understand the best, most pythonic way to employ the library to its full extent. Il permet d'approfondir certains points et aborde la bibliothèque d'un point de vue très pratique, ce qui est vraiment appréciable.

I personally don’t think Pandas is the perfect API (certainly there are tough spots for beginners), but it is where we are at today. What do you think are the most common anti-patterns, which might trap people with experience in Python and starting with Pandas? Also, I spent a lot of time creating the index for this book (I feel this is one of the most important features in the physical book). So you come across many of the annoying, hairy, and ugly issues and are shown how to deal with them.Read more about the condition Very Good: A book that has been read and does not look new, but is in excellent condition. Even if you are ultimately going to be working with terabytes of data, you’ll start out doing exploratory data analysis. The Grouper class enhances groupby() by adding features like grouping by frequency for datetime or datetime-compatible data types.

Plus, many of the interview questions you will face during the hiring process will probably involve Pandas. I've learned and used pandas quite a bit mainly by googling problems, but never really knew what the best practices were. In this article, we will explore 5 advanced functions in Pandas to help you improve your efficiency when working with Pandas library.It assumes you know Python (things the Learning Python for Data covers, like basics but also lambdas, comprehensions, and unpacking. Pandas is one of those libraries that suffers from the "guitar principle" (also known as the "Bushnell Principle" in the video game circles): it is easy to use, but difficult to master.

In this video course, you’ll learn how to sort data in a pandas DataFrame using the pandas sort functions sort_values() and sort_index(). The data visualization techniques are based on the same principles that I learned during the scientific visualization course I took during my master’s degree. Used to commit all the ‘sins’ - lots of intermediate dataframes, lots of single cell calculations/transformations in the notebook. He starts with a peek under the covers, so you get a good understanding of the core pandas objects - Series and DataFrames - and how they work. I’ve been following your work for a while and have found your pandas philosophy transformative and super helpful in my own work.This course is based on real-world experience of using Pandas in a variety of domains and teaching Pandas to thousands. There's a lot of good content there around Python and pandas that delivers value at much of the same level as what you'll see in his Effective Pandas book. The book goes beyond explaining the data structures and methods that underpin Pandas, but he also provides a ton of practical advice regarding best practices in data manipulation and transformations. The course has good productivity tips; for working in Jupyter notebooks, for working with Pandas documentation, and for data cleaning and wrangling.