Intro to Pandas

Get an introduction to the components of the two primary pandas objects, the DataFrame and Series, and how to select subsets of data from them. You'll also get access to a challenging certification exam to validate your knowledge gained.

Begin Intro to Pandas Now!

Get access to the free Intro to Pandas course and the challenging certification exam

What you'll learn

DataFrame and Series

The DataFrame and Series are the two primary containers of data in pandas. It is essential that you understand their components - the index, columns, and values.

Selecting Subsets of Data

One of the most common and unfortunately confusing tasks involves selecting a subset of data from your DataFrame. You'll learn best practices to do any kind of subset selection.

Certification Exam

Over 100 exercises are available with detailed solutions to help you reinforce the knowledge gained from the lectures. At the end of the course, you'll take a challenging certification exam to prove your understanding.

Course Description

 

Intro to Pandas targets those who want to completely master doing data analysis with pandas. This course 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 over 100 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 150-page 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 assumes no previous pandas experience. The only prerequisite knowledge is to understand the fundamentals of Python.

This course is the first part from Master Data Analysis with Python. If you wish to continue this learning path, visit the next course, Essential Pandas Commands

Who this course is for:
  • A desire to completely master data analysis in Python using pandas
  • A desire to have a very deep introduction to subset selection of a DataFrame or Series
  • Interested in pandas best practices for effectiveness and efficiency
  • A desire to use pandas in a professional environment

About the Instructor

This course is taught by Ted Petrou, an expert at Python, data exploration and machine learning. He is the author of multiple highly rated texts including:

Ted has taught hundreds of students Python and data science during in-person classroom settings. He sees first hand exactly where students struggle and continually upgrades his material to minimize these struggles by providing a simple and direct path forward.

Ted is one of the foremost authorities on using the pandas library to do data analysis. His blog posts have totaled well over 1 million views. He is also a prolific contributor on Stack Overflow having answered over 400 questions. He is an enthusiastic instructor and dedicates his time to helping students at their desk during exercises to ensure understanding.

Ted demonstrates his deep fluency in Python by developing open source Python libraries and is the creator of dexplo, a suite of data science packages that include bar_chart_race, dexplot, jupyter_to_medium, and dataframe_image.

Ted holds a Master's degree in Statistics from Rice University.

Testimonials

What you get

  • 14 Jupyter Notebooks - one for each chapter
  • 150 page PDF of all of the material
  • 5 hours of video detailing exactly how to run each command and solve each exercise
  • Challenging certification exam to validate your knowledge gained

Requirements

  • Students must feel comfortable with the basics of Python.

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