• Python 3
Reading time
  • Approximately 74 days
What you will learn
  • Algorithm and Data Structure
  • Blaine Bateman
  • 3 months, 3 weeks ago
Packages you will be introduced to
  • pandas
  • matplotlib

Learn the fundamentals of data science with Python by analyzing real datasets and solving problems using pandas

Key Features

  • Learn how to apply data retrieval, transformation, visualization, and modeling techniques using pandas
  • Become highly efficient in unlocking deeper insights from your data, including databases, web data, and more
  • Build your experience and confidence with hands-on exercises and activities

Book Description

The Pandas Workshop will teach you how to be more productive with data and generate real business insights to inform your decision-making. You will be guided through real-world data science problems and shown how to apply key techniques in the context of realistic examples and exercises. Engaging activities will then challenge you to apply your new skills in a way that prepares you for real data science projects.

You'll see how experienced data scientists tackle a wide range of problems using data analysis with pandas. Unlike other Python books, which focus on theory and spend too long on dry, technical explanations, this workshop is designed to quickly get you to write clean code and build your understanding through hands-on practice. As you work through this Python pandas book, you'll tackle various real-world scenarios, such as using an air quality dataset to understand the pattern of nitrogen dioxide emissions in a city, as well as analyzing transportation data to improve bus transportation services.

By the end of this data analytics book, you'll have the knowledge, skills, and confidence you need to solve your own challenging data science problems with pandas.

What you will learn

  • Access and load data from different sources using pandas
  • Work with a range of data types and structures to understand your data
  • Perform data transformation to prepare it for analysis
  • Use Matplotlib for data visualization to create a variety of plots
  • Create data models to find relationships and test hypotheses
  • Manipulate time-series data to perform date-time calculations
  • Optimize your code to ensure more efficient business data analysis

Who this book is for

This data analysis book is for anyone with prior experience working with the Python programming language who wants to learn the fundamentals of data analysis with pandas. Previous knowledge of pandas is not necessary.

Table of Contents

  1. An Introduction to pandas
  2. Working with Data Structures
  3. Data I/O
  4. pandas Data Types
  5. Data Selection – DataFrames
  6. Data Selection – Series
  7. Data Exploration and Transformation
  8. Data Visualization
  9. Data Modeling – Preprocessing
  10. Data Modeling – Modeling Basics
  11. Data Modeling – Regression Modeling
  12. Using Time in pandas
  13. Exploring Time Series
  14. Applying pandas Data Processing for Case Studies
The author Blaine Bateman has the following credentials.

  • Python Software Foundation Donor Honor Roll, a major contributor to the language or its community
  • Works/Worked at Autonet AB
  • Works/Worked at Springboard
  • Works/Worked at McKinsey
  • Works/Worked at Haave, LLC
  • Works/Worked at Coursera
  • Works/Worked at Laird Technologies
  • Works/Worked at Centurion Wireless Technologies
  • Works/Worked at Ionics Sievers