Data Analysis with Pandas and Python

4.6 (10758)
Learning paid
20.5 hours course
Course by Udemy
What will you learn?
Perform a multitude of data operations in Python's popular "pandas" library including grouping, pivoting, joining and more!
Learn hundreds of methods and attributes across numerous pandas objects
Possess a strong understanding of manipulating 1D, 2D, and 3D data sets
Resolve common issues in broken or incomplete data sets
About the course

Student Testimonials:

  • The instructor knows the material, and has detailed explanation on every topic he discusses. Has clarity too, and warns students of potential pitfalls. He has a very logical explanation, and it is easy to follow him. I highly recommend this class, and would look into taking a new class from him. - Diana
  • This is excellent, and I cannot complement the instructor enough. Extremely clear, relevant, and high quality - with helpful practical tips and advice. Would recommend this to anyone wanting to learn pandas. Lessons are well constructed. I'm actually surprised at how well done this is. I don't give many 5 stars, but this has earned it so far. - Michael
  • This course is very thorough, clear, and well thought out. This is the best Udemy course I have taken thus far. (This is my third course.) The instruction is excellent! - James

Welcome to the most comprehensive Pandas course available on Udemy! An excellent choice for both beginners and experts looking to expand their knowledge on one of the most popular Python libraries in the world!

Data Analysis with Pandas and Python offers 19+ hours of in-depth video tutorials on the most powerful data analysis toolkit available today. Lessons include:

  • installing
  • sorting
  • filtering
  • grouping
  • aggregating
  • de-duplicating
  • pivoting
  • munging
  • deleting
  • merging
  • visualizing

and more!

Why learn pandas?

If you've spent time in a spreadsheet software like Microsoft Excel, Apple Numbers, or Google Sheets and are eager to take your data analysis skills to the next level, this course is for you! 

Data Analysis with Pandas and Python introduces you to the popular Pandas library built on top of the Python programming language. 

Pandas is a powerhouse tool that allows you to do anything and everything with colossal data sets analyzing, organizing, sorting, filtering, pivoting, aggregating, munging, cleaning, calculating, and more! 

I call it "Excel on steroids"!

Over the course of more than 19 hours, I'll take you step-by-step through Pandas, from installation to visualization! We'll cover hundreds of different methods, attributes, features, and functionalities packed away inside this awesome library. We'll dive into tons of different datasets, short and long, broken and pristine, to demonstrate the incredible versatility and efficiency of this package.

Data Analysis with Pandas and Python is bundled with dozens of datasets for you to use. Dive right in and follow along with my lessons to see how easy it is to get started with pandas!

Whether you're a new data analyst or have spent years (*cough* too long *cough*) in Excel, Data Analysis with pandas and Python offers you an incredible introduction to one of the most powerful data toolkits available today!

Installation and Setup
Download, install, and configure the Anaconda distribution to set up Python and pandas on your Mac or Windows computer!
Introduction to the Course
  • Introduces Python, pandas, Anaconda, Jupyter Notebook, and the course prerequisites
  • Explores sample Jupyter Notebooks to showcase the power of pandas for data analysis
  • The attachment with the working files for this course is attached to this lesson. 
  • Download and unpack the file in the directory of your choice.
Completed Course Files
Mac OS - Download the Anaconda Distribution
The next batch of lessons focuses on the installation and configuration process for pandas on a Mac machine. In this lesson, we download the Anaconda distribution from the Continuum Analytics. If you're new to Python, choose the 3.5 version of the distribution.
Mac OS - Install Anaconda Distribution
In this lesson, we install the Anaconda distribution on a Mac OS machine from the executable package we downloaded. The process installs Python and over 100 of the most popular libraries for data science in a central directory on your computer.
Mac OS - Access the Terminal
The Terminal is an application for communicating with your Mac with text-based commands. In this lesson, you'll learn two ways to access the Terminal on a Mac OS machine.
Mac OS - Update Anaconda Libraries
We need to install and update some Python libraries to ensure a smooth process with Jupyter Notebooks and pandas. In this lesson, we use the Terminal to complete the update process.
Mac OS - Unpack Course Materials + The Startdown and Shutdown Process
This course is bundled with a collection of .csv and .xlsx files for you to use. I strongly recommend following along with my tutorials by practicing the syntax on your end. In this lesson, I'll explain the startup and shutdown process for a Jupyter Notebook session. Follow this process every time you come back to the course.
Windows - Download the Anaconda Distribution
The Windows operating system comes in 32-bit and 64-bit versions. In this lesson, we'll access the Control Panel to determine what category your computer falls into and then download the proper version of the Anaconda distribution on the Continuum Analytics website.
Windows - Install Anaconda Distribution
Run the Anaconda installer package on a Windows computer. The executable installs Python, pandas, Jupyter Notebook and over 100 popular libraries for data analysis.
Windows - Access the Command Prompt and Update Anaconda Libraries
Access the Command Prompt on a Windows machine. The prompt (also known as the command line) is used to interact with the computer with text-based commands. We'll use it to download additional Python libraries for the course and update all installed Anaconda libraries.
Windows - Unpack Course Materials + The Startdown and Shutdown Process
This course is bundled with .csv and .xlsx files. The primary .zip file is attached to the first lesson of this course. In this lesson, we'll unpack the course materials and learn the startup and shutdown process for a Jupyter Notebook. Follow this process as you proceed throughout the course.
  • Basic / intermediate experience with Microsoft Excel or another spreadsheet software (common functions, vlookups, Pivot Tables etc)
  • Basic experience with the Python programming language
  • Strong knowledge of data types (strings, integers, floating points, booleans) etc
Boris Paskhaver
Boris Paskhaver
Software Engineer | Consultant | Author
Udemy courses are suited to professional development. The platform is organized in such a way that it is experts themselves that decide the topic and when the course will start. All supporting documents are made available to you for lifetime access. On this platform, you can find a course on about any subject, and that is no exaggeration – from a tutorial on how to ride a motorcycle, to managing the financial markets. The language and the course format are established by the teacher. This is why it is important to read the information about the course carefully before parting with any money.
Comments (10758)
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