Recommended Chapter Flow

The book is organized into the following learning sequence:

1. Project Setup
   Set up an RStudio Project, organize folders, and understand reproducible workflows.

2. Tidyverse Basics
   Learn core tidyverse functions for reading, selecting, filtering, mutating, and summarizing data.

3. Joining Data
   Practice combining datasets using keys and joins, with examples from the Titanic dataset.

4. Data Cleaning
   Work with raw files, column names, missing values, reshaping, and structured cleaning steps.

5. Strings and Regular Expressions
   Use stringr, separate(), str_extract(), and regex patterns to clean and parse text data.

6. Data Visualization
   Create clear visual summaries using ggplot2, including line plots, bar charts, and grouped visualizations.

7. Exploratory Data Analysis
   Build an organized EDA workflow using summaries, plots, missing-value checks, and data validation.

8. Communicating Results
   Use storyboards, dashboards, and reporting structure to communicate data insights clearly.

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