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 Harris

Matt Harrison
Published: Apr 2020
Core
Data Science
8 hours 15 minutes
Getting Started with Pandas

Course Overview

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

Course Includes

3.3K
STUDENTS*
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

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

Curriculum

Explore the comprehensive, hands-on curriculum designed to build your expertise step by step.

Meet Your Expert Instructors

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