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Data Analysis with Python

Published by O'Reilly Media, Inc.

Beginner to intermediate content levelBeginner to intermediate

Empowering data-driven insights and proactive decision-making

Course outcomes

  • Understand the basics of Python programming for data manipulation and analysis
  • Learn how to clean, transform, and prepare data for analysis using the pandas library
  • Explore using Matplotlib and Seaborn to create compelling visual narratives
  • Explore using Plotly to design dynamic and interactive charts
  • Understand techniques for visually exploring complex datasets to uncover hidden patterns and relationships

Course description

In today's data-driven world, the ability to clearly and effectively visualize complex datasets is indispensable for making informed decisions and conveying insights.

Join expert Dr. Chester Ismay to delve into Python's rich ecosystem of libraries such as pandas, Matplotlib, Seaborn, and Plotly and explore in-depth how to transform raw data into compelling data summaries and visual narratives. You’ll learn how to use Python's visualization tools to create dynamic plots and informative charts that communicate data insights with clarity and impact. Through a series of hands-on exercises and real-world case studies, you'll learn the principles of good visualization design, explore techniques for presenting complex data relationships, and understand how to tailor visualizations for different audiences. In a few hours, you’ll be equipped with the knowledge to leverage Python's data wrangling and visualization capabilities for impactful data storytelling.

What you’ll learn and how you can apply it

  • Use Python's data wrangling tools to clean and prepare data, making it ready for analysis and visualization
  • Design and implement a variety of charts and plots that effectively communicate your data's story
  • Conduct thorough explorations of your datasets, identifying key trends, patterns, and outliers
  • Leverage your analytical and visualization skills to support informed decision-making related to organizational/business goals

This live event is for you because...

  • You're an analyst or data enthusiast who’s looking to enhance your data analysis and visualization skills.
  • You want to improve reporting by producing more engaging and insightful reports for your team, management, or clients.
  • You're a professional interested in leveraging data more effectively in your role.
  • You aspire to tell better data stories and transform complex data findings into clear, compelling narratives.

Prerequisites

  • Familiarity with introductory Python
  • Basic knowledge of working with Jupyter environments

Recommended preparation:

Recommended follow-up:

Schedule

The time frames are only estimates and may vary according to how the class is progressing.

Foundations of data analysis with Python (15 minutes)

  • Presentation: Overview of data analysis and the Python ecosystem
  • Group discussion: What aspect of data analysis are you most interested in?
  • Hands-on exercise: Set up the Python environment
  • Q&A

Data wrangling with pandas (45 minutes)

  • Presentation: Introduction to pandas for data analysis; cleaning and preparing data with pandas
  • Hands-on exercises: Load and inspect data with pandas; explore data transformation and aggregation
  • Q&A
  • Break

Data visualization basics with Matplotlib and Seaborn (60 minutes)

  • Presentation: Fundamentals of data visualization with Matplotlib; enhancing visualizations with Seaborn
  • Hands-on exercises: Create basic plots with Matplotlib; explore advanced data visualization techniques with Seaborn
  • Q&A
  • Break

Advanced data visualization with Plotly (60 minutes)

  • Presentation: Interactive data visualizations with Plotly; customizing Plotly visualizations for different audiences
  • Hands-on exercises: Build interactive charts and dashboards with Plotly; create a dynamic data report
  • Q&A
  • Break

Real-world data analysis project (60 minutes)

  • Presentation: Applying your skills—from data to insights; storytelling with data—presenting your findings
  • Hands-on exercises: Work on a real-world data analysis project; finalize and present your project
  • Q&A

Your Instructor

  • Chester Ismay

    Dr. Chester Ismay is an experienced data science educator and consultant. Chester enjoys helping others get into data science, figuring out how to best practice and improve their skills. He is co-author of "Statistical Inference via Data Science: A ModernDive into R and the Tidyverse" available at https://moderndive.com/v2/ He likes leading education and data science teams to improve best practices based on data from the learning sciences. Throughout his career, he has worked in academia, as a corporate trainer, at tech bootcamps, and as an independent consultant in the fields of education, insurance, and sports analytics.

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Skill covered

Python