Basic Pandas for beginners

Are you tired of struggling with basic Pandas examples that don't quite fit the bill? Unlock the true power of data manipulation with "Basic Pandas for Beginners," a comprehensive and practical e-book that will take your data analysis skills to the next level.

Written after months of dedicated practice with real-world, messy, and dirty data, this e-book is a treasure trove of knowledge derived from actual experience. The author has meticulously documented every method used, resulting in an invaluable resource for anyone eager to enhance their Pandas proficiency.

Why "Basic Pandas for Beginners" Stands Out:

1. Practical Approach to Real Pandas Examples: Unlike typical resources that offer basic, theoretical examples, this e-book immerses you in the world of practical data analysis. You will encounter real-life Pandas scenarios that reflect the challenges faced by data professionals every day.
2. Comprehensive Code Explanations: Have you ever followed a tutorial only to be left puzzled by unexplained code snippets? This e-book removes that frustration by providing clear and concise explanations for every piece of code presented. Understanding the "how" and "why" behind each operation will deepen your knowledge and instill confidence in your Pandas skills.
3. Implementation Insights: Data manipulation is an art that requires insight into the most effective implementation techniques. This e-book equips you with valuable insights into implementing Pandas methods, ensuring you grasp the best practices for every situation.
4. Learn Through Comparison: As you progress through "Basi Pandas for Beginners," you will discover comparisons between different methodologies. Understanding the strengths and weaknesses of various approaches will empower you to make informed decisions when handling diverse datasets.

What You'll Find Inside:

• INTRODUCTION
• INTRODUCTION TO PANDAS
• WHAT IS PANDAS?
• IMPORTING PANDAS
  • 1. Using Anaconda
  • 2. Using ‘pip’
• THE FIRST STEPS WITH PANDAS
  • 1. Loading CSV files
  • 2. Showing ‘head’ and ‘tail’
• THE FIRST STATISTICS
• FILTERING DATA
  • 1. “loc[]” and “iloc[]”
  • 2. The filter() method
  • 3. Other filtering methods
• PANDAS SERIES, AND PANDAS DATA FRAMES
  • 1. What are Pandas’ series and how to create them
  • 2. What are Pandas’ data frames and how to create them
• DEALING WITH “NaN” VALUES
• MELTING AND TRANSPOSING COLUMNS, MERGING DATA FRAMES
  • 1. Melting columns
  • 2. Transposing columns
  • 3. Merging data frames
• GROUPBY AND VALUE COUNTS
• ADVANCED MANIPULATION
  • 1. Renaming columns
  • 2. Generalizing string values
  • 3. Append values from a Pandas column to a list
  • 4. Filtering two data frames for a list
• PREPARING DATA FOR MACHINE LEARNING
  • 1. Add values in a new column based on a threshold
  • 2. One-hot encoding in Pandas
• News on Version 2.0