Coffee Break Pandas

74 Pandas Puzzles to Build Your Pandas Data Science Superpower

Coffee Break Pandas Book

Data is the new oil -- whoever develops the skills to harvest this largely untapped asset class will increase their value in the 21st-century marketplace.

  • Computers and sensors create ever-growing data sets that become increasingly relevant in every part of our lives.
  • Smartphones collect billions of GPS traces that reveal valuable information towards new mobility solutions and truly smart cities.
  • Smartwatches track the heart rates of millions of people to detect health problems and prevent unnecessary deaths.
  • Intelligent cars collect myriads of sample data points that increase traffic efficiency, prevent millions of car accidents, and save humanity hundreds of millions of hours in traffic jams.

Data truly is a modern-world asset. And data processing now plays a key part in organizing modern society.

During the first years of the computer, hardware capacities were limited and expensive. Processing vast amounts of data was impossible during the first few decades.

Fortunately, Moore's Law -- the number of transistors on a microchip doubles roughly every two years -- lead to an exponential cost reduction for computing power.

Hardware became more powerful and much cheaper by orders of magnitudes.

Today, it is financially viable to store, process, and analyze hundreds of terabytes of data.

Big corporations such as Amazon, Google, and Facebook are avidly collecting data to get to know their users even better and increase their revenues.

By reading this book, you'll learn the powerful skill of analyzing and processing data with Python's Pandas framework.

60-Days 100% Money-Back Guarantee (& Keep Book)!

If you don’t think that the book is worth your time, you’ll get 100% of your money back for as long as 60(!) days after the purchase! Just like that. And you keep the book for free.

Table of Contents

145 pages of value-packed Pandas puzzles to boost your data science skills and general code understanding.

1 Introduction

-  Data Is The New Oil
-  What is Pandas?
-  Why Learning Pandas

2 A Case for Puzzle-based Learning

-  Overcome the Knowledge Gap
-  Embrace the Eureka Moment
-  Divide and Conquer
-  Improve From Immediate Feedback
-  Measure Your Skills
-  Individualized Learning
-  Small is Beautiful
-  Active Beats Passive Learning
-  Make Code a First-class Citizen
-  What You See is All There is

3 The Elo Rating for Python

-  How to Use This Book
-  How to Test and Train Your Skills?

4 Pandas Code Puzzles Elo 1500-1600

-  Create a Series From a Scalar Value
-  Create a Series From a List of Data
-  Create Series with Custom Index Values
-  Create a Series From a Dictionary
-  The Dimension of a Series
-  The Size of a Series
-  Checking Series for NaN-Values
-  Integer Location Index
-  Location Index
-  Methods of Series: all() and any()
-  The Methods min() and max()
-  Update Values in a Series
-  Index Operators I
-  Index Operators II
-  Filtering Series
-  Method Chaining
-  The axis Argument
-  Working with Multiple Series
-  Create a DataFrame from a List of Lists
-  Create a DataFrame from a Dictionary of Lists
-  List of Dict to DataFrame
-  Create a DataFrame from a List of Tuples
-  Create a DataFrame from Series
-  Create a DataFrame from a CSV File

5 Pandas Code Puzzles Elo 1600-1700

-  DataFrame Head
-  DataFrame Tail
-  Slices of DataFrames I
-  Slices of DataFrames II
-  Slicing
-  DataFrame vs. Series
-  Modifying Column Labels
-  Sorting a DataFrame by Column
-  Replacing Values
-  Renaming Columns
-  Column Datatypes
-  Integer Location Index: Multiple Values
-  Count Non-NaN Values
-  Drop NaN-Values
-  Adding Columns I
-  Adding Columns II
-  Boolean Indexing I
-  Drop NaN-Values II
-  Drop Columns
-  Drop Selected Values
-  Sort In-Place
-  Reverse Column Order
-  Reverse Row Order
-  Reset the Index
-  Reference Confusion
-  Select Values From a List
-  Boolean Indexing II
-  Aggregation
-  DataFrame Concatenation I
-  DataFrame Concatenation II
-  Inner Merge
-  Right Merge
-  Outer Merge

6 Pandas Code Puzzles Elo 1700-1800

-  Fun With NaN
-  DataFrame Information
-  DataFrame Statistics
-  DataFrame Memory Usage
-  Numpy Arrays
-  Regexing Column Labels
-  Replacing NaN-Values
-  Dummy Values
-  Method Chaining II
-  Length vs. Count
-  Modifying Values
-  Value Clusters
-  Exploding Values
-  Comparison: equals() vs. ==
-  Merged DataFrames Value Sources

7 Pandas Code Puzzles Elo 1800+

-  Index iloc and Lambdas
-  Pivot Tables

8 Final Remarks

-  Your Skill Level
-  Where to Go From Here?

Who This Book Is For?

  • You're an aspiring coder and seek ways to advance your coding skills.
  • You want to learn Pandas to be more productive in your job and your data science projects.
  • You enjoy solving code puzzles and you want to improve your brain capacity and problem-solving capabilities.

Who This Book Is NOT For?

If you don't enjoy solving code puzzles and you don't want to invest 10-20h learning Pandas, this book is not for you.

About the Authors

Dr. Christian MayerFounder Finxter.com, Computer Scientist, Blogger, and Freelancer

I just finished working as a doctoral computer science researcher on distributed systems in Germany. As a researcher, I have taught many students in computer science, graph theory, and distributed systems. 

My passions are writing, reading, and coding. But my #1 passion is to serve aspiring coders through Finxter and help them to boost their skills. 

I practice what I preach teaching only tricks I learned from building my own freelance developer business online.

Lukas RiegerFinxter COO & Instagram Influencer (60k subs), DevOp Engineer, Computer Scientist

After my apprenticeship as a practical coder, I studied software engineering at University of Stuttgart where I worked together with Christian in distributed graph processing research. For the last years, I have been working as a developer and Cloud Operations Engineer.

I discovered my passion for teaching computer science as a coding tutor. With this book, I want to share with you my love for Python -- because of its clarity, flexibility, and vast range of libraries!

Do You Want to Master the Hottest Data Science Library in Python?

What's the only difference between you and the person earning double your income? ... Skills!

Start developing your new high-income skill "Python Pandas". You'll love it! ❤

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Coffee Break Pandas Book

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