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  3. Getting Started with Pandas
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Getting Started with Pandas

This Pandas course prepares teaches the fundamentals of data analysis. It shows how to load data, inspect it, deal with missing values, use statistical summaries, plot, pivot and more. This course contains 18 hours of materials, taught by Matt Harrison, a Python and Pandas expert and author.

Matt Harrison
Matt Harrison
Data Science | core | 5 minutes | Apr 30 | 12:42 PM GMT

Overview

3.3KSTUDENTS*
97%RECOMMEND*

This course includes:

  • 9+ hours of on-demand video
  • 5 modules
  • Core level
  • Direct access/chat with the instructor
  • 100% self-paced online
  • Many downloadable resources
  • Shareable certificate of completion
This Pandas course teaches us the fundamentals of data analysis. It shows how to load data, inspect it, deal with missing values, use statistical summaries, plot, pivot and more. This course contains 18 hours of materials, taught by Matt Harrison, a Python and Pandas expert and author. Following this course students will be able to leverage their skills with pandas to perform powerful data analysis, create plots, clean data, and prepare data for machine learning. Pandas is a powerful library, but it can be confusing. Fill in the knowledge gaps and understand how Pandas works under the covers. You will come out of this class grokking the syntax, and the best practices for creating beautiful Pandas code. We will also show how to use Jupyter and install additional packages.  

Skills You Will Gain

Jupyter
Pandas

Learning Outcomes (At the end of this program you will be able to)

  • Getting Started – Installation, Jupyter, and Example
    • Understanding Jupyter and editors
    • Installing libraries
    • Overview of functionality of Pandas
  • Series objects
    • Basic operations
    • Aggregation methods
    • Index manipulation
    • String manipulation
  • DataFrame objects
    • Slicing data
    • Cleaning data
    • Boolean arrays and filtering
    • Plotting
  • Grouping
    • Grouping with a column
    • Grouping with multiple columns, functions, and dates
    • Pivoting and stacking
  • Time series
    • Shifting data
    • Window operations
    • Date grouping
    • Dealing with missing data
    • Plotting
  • Tips and Tricks
    • Apply tricks
    • Debugging
    • Testing
    • Seaborn plotting

Prerequisites

  • Basic computer knowledge is assumed
  • Prior programming experience with Python is strongly preferred

Who Should Attend

  • New Python developers looking to quickly develop and keen understanding of the power of Pandas
  • Individuals who are familiar with data science and need to understand Pandas

Instructors

Frequently Asked Questions

How much do the courses at Starweaver cost?

We offer flexible payment options to make learning accessible for everyone. With our Pay-As-You-Go plan, you can pay for each course individually. Alternatively, our Subscription-Based plan provides you with unlimited access to all courses for a monthly or yearly fee.

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Yes, we do offer a certification upon completion of our course to showcase your newly acquired skills and expertise.

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Yes, we do offer a 100% refund guarantee for our courses within a specified time frame. If you are not satisfied with the course, contact our customer support team to request a refund with your order details. Some restrictions may apply.

*Where courses have been offered multiple times, the “# Students” includes all students who have enrolled. The “%Recommended” shown is also based on this data.
Matt Harrison

Matt Harrison

Matt is a seasoned Python and Data Science expert with over a decade of experience, known for his passion for making complex programming and data analysis concepts accessible and engaging. A Stanford University graduate with a background in Computer Science, Matt has applied his skills across a wide range of domains—from building predictive models that classify job postings to developing scalable systems using AWS and Docker.

Matt’s expertise spans machine learning, natural language processing, web application development, and beyond. He has a proven track record of translating technical depth into impactful educational experiences. As an instructor, he has designed and delivered high-impact courses such as Python for Finance and Essentials of Stats with Python, enabling learners to grasp both the theoretical foundations and practical applications of programming and data science.

A strong advocate for critical thinking and problem-solving, Matt creates inclusive learning environments where students from all backgrounds can thrive. His dedication to education extends to the global stage, where he regularly speaks at conferences like PyCon and SciPy and contributes to leading platforms including O’Reilly Media and Pluralsight.

With a teaching philosophy grounded in authenticity and real-world relevance, Matt is committed to empowering the next generation of data scientists and programmers—bridging the gap between theory and application, and inspiring learners to unlock the full potential of Python and data science.

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