📊 Mastering R in 30 Days

📝 Project Overview

This repository is a self-documented, end-to-end journey into the R programming language. In this journey I started from R fundamental to automated data pipelines. Rather than a 'challenge', this was a deep-dive into Mastering Data Logic, Verification along with Professional Visualization.

---

🎯 Key Technical Milestones

• Automated Data Pipelines: Developed workflows from live API ingestion ( WDI ) to automated PNG reporting.
• Database Integration: Implementation of SQL connectivity via RMySQL and DBI
• Logic Visuals: Created conceptual diagrams via draw.io to map out data structures and vector replication logic based on my understanding.

---

🌳 Environment & Resources

• Language: R (Version 4.5.2+)
• IDE: RStudio
• Core Packages: tidyverse, dplyr, ggplot2, WDI, treemapify, RMySQL, scales.
• Primary Learning Reference: R Programming Playlist by WSCube Tech.
• Technical Reference: Data Visualization with R (Rob Kabacoff).

---

🧱 Repository Structure

Days	Topics
Days 01-10:	Fundamentals (Syntax, Vectors, Matrices).
Days 11-20:	Data Manipulation (Dplyr, SQL connectivity).
Days 21-30:	Visualization & Pipeline Validation.

---

---

👁 Visual Highlights and Documentation

As a crucial part of this exploratory journey i have created few technical assets to visualize the concept better.

1. Cheatsheet: gives the conceptual logic for multiple datatype.
   

2. Vector Replication: provides the mapped logic of Vector Replication.
   

3. Trend Analysis: Automated Analysed Population Growth plot of Ireland(🇮🇪) over a Decade.
   

---

📈 Progress Tracker

Day	Topic	Status	Links
Day 01	Introduction, Installation & RStudio Basics	✅	Folder
Day 02	Variables, Data Types & Casting	✅	Folder
Day 03	Operators & If-Else Statements	✅	Folder
Day 04	Switch, Next, Break & For Loops	✅	Folder
Day 05	Repeat, While Loops & User Input	✅	Folder
Day 06	Custom & Built-In Functions	✅	Folder
Day 07	Vectors: Basics & Properties	✅	Folder
Day 08	Lists: Multi-type Data Structures	✅	Folder
Day 09	Vector Functions & Operations	✅	Folder
Day 10	Arrays: Multi-dimensional Data	✅	Folder
Day 11	Matrices: Creation and Manipulation	✅	Folder
Day 12	Data Frames: Tabular Data	✅	Folder
Day 13	Factors: Categorical Data	✅	Folder
Day 14	Revisting Topics and Cheatsheets	✅	Folder
Day 15	Importing Data: CSV Files	✅	Folder
Day 16	Data Manipulation: Dplyr Package Intro	✅	Folder
Day 17	Importing Data: Excel Files	✅	Folder
Day 18	Connecting R to MySQL Databases	✅	Folder
Day 19	Data Cleaning Practice (Dplyr)	✅	Folder
Day 20	Mid-Course Project: Data Import & Cleaning	✅	Folder
Day 21	Mid-Course Project: Analysis Summary	✅	Folder
Day 22	Data Visualization: Pie Charts	✅	Folder
Day 23	Data Visualization: Bar Charts	✅	Folder
Day 24	Data Visualization: Histograms	✅	Folder
Day 25	Data Visualization: Line Graphs	✅	Folder
Day 26	Data Visualization: Scatter Plots	✅	Folder
Day 27	Data Visualization: Boxplots	✅	Folder
Day 28	Data Visualization: Treemaps	✅	Folder
Day 29	Advance ggplot2 functions & Prep Final Project	✅	Folder
Day 30	Final Project: Conclusion and Validation	✅	Folder

Legend: ✅ Completed | ⏳ In Progress | 📅 Upcoming

---

📂 Folder Structure

To maintain a professional workflow, each day includes:

• script.R: Clean, commented code and practice exercises.
• Readme.md: For the notes taken on the respective day.
• data/: Source datasets for projects.(csv files included for datasets i have used)

---