Python Book 4 - Python Data Science Essentials for Rookies: Pandas and NumPy

Table of Contents

1. Introduction

1.1 What is Data Science?

1.2 Why Python for Data Science?

1.3 Installing Python and Required Packages

1.4 Setting Up the Working Environment

2. Getting Started with NumPy

2.1 What is NumPy?

2.2 Creating and Manipulating NumPy Arrays

2.3 Performing Basic Operations and Calculations

2.4 Indexing, Slicing, and Reshaping Arrays

2.5 Applying Functions and Aggregations

2.6 Project: Analyzing Weather Data with NumPy

3. Getting Started with Pandas

3.1 What is Pandas?

3.2 Creating and Manipulating Pandas Series and DataFrames

3.3 Reading and Writing Data from Different Sources

3.4 Handling Missing and Duplicate Data

3.5 Sorting, Filtering, and Grouping Data

3.6 Merging, Joining, and Concatenating Data

3.7 Project: Exploring Movie Ratings Data with Pandas

4. Data Visualization with Matplotlib and Seaborn

4.1 What is Data Visualization?

4.2 Introduction to Matplotlib and Seaborn

4.3 Creating and Customizing Different Types of Plots

4.4 Adding Titles, Labels, Legends, and Annotations

4.5 Saving and Showing Plots

4.6 Project: Visualizing COVID-19 Data with Matplotlib and Seaborn 5. Conclusion

5.1 Summary of the Main Concepts and Skills

5.2 Further Resources and Learning Paths

5.3 Feedback and Contact Information