Begin mastering the fundamentals of data analysis in Python by getting introduced to the pandas library.
Intro to Pandas provides an introduction to the components of the two primary pandas objects, the DataFrame and Series, and how to select subsets of data from them.
There are nearly 50 exercises available to help practice the material taught from the lectures. Detailed video and text solutions for each of the exercises are available so that you can see exactly how Ted thinks through the exercises to arrive at a solution.
All of the material and exercises are written in Jupyter Notebooks, which you will be able to download. This allows you to read the notes, run the code, and write solutions to the exercises all in a single place. Additionally, the full contents of the course are available as a pdf document giving you access to the material from anywhere.
This course targets those who have an interest in becoming experts and completely mastering the pandas library for data analysis in a professional environment. This course does not cover all of the pandas library, just a small and fundamental portion of it. If you are looking for a brief introduction of the entire pandas library, this course is not it. It takes many dozens of hours, lots of practice, and rigorous understanding to be successful using pandas for data analysis.
This course is taught by expert instructor Ted Petrou, author of the highly-rated book Pandas Cookbook. Ted has taught over 1,000 hours of live in-person data science courses that use the pandas library. Pandas is a difficult library to use effectively and is often taught incorrectly with poor practices. Ted is extremely adept at using pandas and is known for developing best practices on how to use the library.
This course assumes no previous pandas experience. The only prerequisite knowledge is to understand the fundamentals of Python.
If you'd like to continue learning pandas for data analysis, purchase Master Data Analysis with Python.
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