Your browser is not supported. Please download another browser to be able to use all of the Maven features.

Self-Paced Course

Data Analysis with Python & Pandas

Master the basics of NumPy and Pandas for data analysis, and learn how to explore, transform, aggregate, join and visualize dataframes.

Course Hours22 hours
Skills Learned
Data Prep
Data Analysis
Data Visualization
Course Level

Course Description

This is a hands-on, project-based course designed to help you learn two of the most popular Python packages for data analysis: NumPy and Pandas.

We'll start with a NumPy primer to introduce arrays and array properties, practice common operations like indexing, slicing, filtering and sorting, and explore important concepts like vectorization and broadcasting.

From there we'll dive into Pandas, and focus on the essential tools and methods to explore, analyze, aggregate and transform series and dataframes. You'll practice plotting dataframes with charts and graphs, manipulating time-series data, importing and exporting various file types, and combining dataframes using common join methods.

Throughout the course you'll play the role of Data Analyst for Maven Mega Mart, a large, multinational corporation that operates a chain of retail and grocery stores. Using the Python skills you learn throughout the course, you'll work with members of the Maven Mega Mart team to analyze products, pricing, transactions, and more.

If you're a data scientist, BI analyst or data engineer looking to add Pandas to your Python skill set, this is the course for you.



  • 13.5 hours on-demand video (22.0 CPE credits)

  • 48 homework assignments (plus 2 course projects)

  • 8 quizzes

  • 2 skills assessments (1 benchmark, 1 final)



  • Analysts or BI professionals looking to learn NumPy & Pandas
  • Aspiring data scientists who want to build core Python skills
  • Anyone interested in learning one of the most popular open source programming languages in the world


  • Jupyter Notebooks (free download, we'll walk through the install)
  • No advance preparation is required (basic familiarity with programming is a plus, but not a prerequisite)


  • Identify NumPy array properties and syntax, including array creation, indexing & slicing, operations, aggregation, vectorization, and broadcasting

  • Identify basic properties and data types for Pandas Series and DataFrames

  • Identify and interpret Pandas syntax for exploring Series and DataFrames, including indexing, accessing, sorting, and filtering

  • Identify and interpret Pandas syntax for manipulating Pandas Series and DataFrames, including handling missing values, applying custom functions, and dropping & creating columns

  • Identify and interpret examples of optimizing memory use in Pandas DataFrames, including type conversion and downcasting

  • Identify and interpret Pandas syntax for aggregating DataFrames, including grouping columns, accessing multi-index DataFrames, aggregating groups, and pivoting & unpivoting

  • Identify and interpret basic data visualization methods using Pandas, including customizing chart formatting, changing chart types, and saving charts as images

  • Identify and interpret Pandas syntax for working with time series data, including the datetime data type, formatting & parting, time deltas, shifting, resampling, and aggregating

  • Identify the proper syntax and functions for reading, processing, and writing data from different sources, including flat files, SQL databases, and other formats

  • Identify and interpret Pandas syntax for combining multiple DataFrames, including appending data to add rows and using several join methods to add related columns


  • CPE Credits: 22.0

  • Field of Study: Information Technology

  • Delivery Method: QAS Self Study

Maven Analytics LLC is registered with the National Association of State Boards of Accountancy (NASBA) as a sponsor of continuing professional education on the National Registry of CPE Sponsors. State boards of accountancy have the final authority on the acceptance of individual courses for CPE credit. Complaints regarding registered sponsors may be submitted to the National Registry of CPE Sponsors through its website: www.nasbaregistry.org.

For more information regarding administrative policies such as complaints or refunds, please contact us at admin@mavenanalytics.io or (857) 256-1765.

*Last Updated: July 21, 2022

Start learning for FREE, no credit card required!

Every subscription includes access to the following course materials

  • Interactive Project files
  • Downloadable e-books
  • Graded quizzes and assessments
  • 1-on-1 Expert support
  • 100% satisfaction guarantee
  • Verified credentials & accredited badges
Sign Up Today

Ready to become a

data rockstar?

Start learning for free, no credit card required!

Sign Up for Free