I'm excited to announce the official release of
bar_chart_race, a python package for creating bar chart races. In this post, I'll cover many of the major available options. Navigate to the official documentation for a full breakdown of all of the options.
Bar chart races have become very popular over the last year and no python package existed to create them. I also built some for my coronavirus dashboard.
This article summarizes the very detailed guide presented in Minimally Sufficient Pandas.
Take my free Intro to Pandas course to begin your journey mastering data analysis with Python.
In this article, I will offer an opinionated perspective on how to best use the Pandas library for data analysis. My objective is to argue that only a small subset of the library is sufficient to complete nearly all of the data analysis tasks that one will encounter. This minimally sufficient subset of the library will benefit both beginners and professionals using Pandas. Not everyone will agree with the suggestions I lay forward, but they are how...
Selecting subsets of data in pandas is not a trivial task as there are numerous ways to do the same thing. Different pandas users select data in different ways, so these options can be overwhelming. I wrote a long frou-part series on it to clarify how its done. For instance, take a look at the following options for selecting a single column of data (assuming it’s the first column):
pandas offers its users two choices to select a single column of data and that is with either brackets or dot notation. In this article, I suggest using the brackets and not dot notation for the following ten reasons.
I also have a video from the Dunder Data YouTube channel where I demonstrate this entire process. I believe this is a post that is better viewed as a demonstration, so if you have the time see the video below.
A major pain point for beginners is writing too many lines of code in a single cell. When you are learning, you need to get feedback on every single line of code that you write and verify that it is in fact correct. Only once you have verified the...
In this article, I will discuss the overall approach I took to writing Pandas Cookbook along with highlights of each chapter.
I have a new book titled Master Data Analysis with Python that is far superior to Pandas Cookbook. It contains over 300 exercises and projects to reinforce all the material and will receive continuous updates indefinitely. If you are interested in Pandas Cookbook, I would strongly suggest to purchase Master...
In this post, I will offer my review of the book, Python for Data Analysis (2nd edition) by Wes McKinney. My name is Ted Petrou and I am an expert at pandas and author of the recently released Pandas Cookbook. I thoroughly read through PDA and created a very long, review that is available on github. This post provides some of the highlights from that full review.
I read this book as if I was the only technical reviewer and I was...
This is the fourth and final part of the series “Selecting Subsets of Data in Pandas”. Pandas offers a wide variety of options for subset selection, which necessitates multiple articles. This series is broken down into the following topics.
If you want to be trusted to make decisions using pandas and scikit-learn, you must become an...