Exploratory Data Analysis in SQL 🚀

Welcome to the Exploratory Data Analysis (EDA) in SQL repository! 🎯 This project showcases essential SQL skills and techniques learned through DataCamp's Exploratory Data Analysis in SQL course. 📚

Project Overview 📌

This repository demonstrates key concepts, methodologies, and practical applications of exploratory data analysis using PostgreSQL. You'll find structured SQL scripts, comprehensive documentation, and examples of real-world analyses. 🔍

Repository Structure 🗂️

Exploratory-Data-Analysis-in-SQL/
├── LICENSE
├── README.md
├── certificate/
│   └── README.md
├── data/
│   ├── README.md
│   └── erdiagram.png
│   ├── ev311.csv
│   ├── fortune.csv
│   ├── sql_eda_dbcreate.sql.txt
│   └── stackexchange.csv
├── docs/
│   ├── README.md
│   ├── data-types-and-casting.md
│   ├── date-truncation-and-time-series.md
│   ├── eda-overview.md
│   ├── generate-series-and-binning.md
│   ├── grouping-and-aggregation.md
│   ├── outlier-handling-and-percentiles.md
│   ├── summary-functions.md
│   ├── text-cleaning-and-standardization.md
│   ├── time-difference-and-lag.md
├── sql/
│   ├── 01_Database_Structure_and_Schema_Exploration.sql
│   ├── 02_Numeric_Summary_and_Distributions.sql
│   ├── 03_Text_and_Categorical_Analysis.sql
│   ├── 04_Event_Timing_and_Duration.sql
│   └── README.md
└── visuals/
    ├── README.md
    └── Data-distribution-example.png

Key SQL Topics 🌟

1. Database Structure 🗃️

• Understanding tables, primary keys, foreign keys, and constraints.
• Essential commands for database exploration: information_schema queries.

2. Numeric Data Analysis 📊

• Aggregation and summary statistics: AVG, MIN, MAX, SUM.
• Variance, standard deviation, correlation, and binning techniques.

3. Text Data Analysis 📝

• Character types (char, varchar, text), case conversion (UPPER, LOWER).
• Splitting, trimming, and concatenating text data.

4. Date and Time Analysis 📅

• Handling dates, timestamps, and intervals.
• Aggregation by date/time, date_trunc, extract, and generating date/time series.

Practical Examples 💡

• SQL scripts in the /sql directory illustrate typical EDA tasks such as:

  • Summarizing data distributions and identifying outliers.
  • Cleaning text fields for consistent analysis.
  • Aggregating data by time intervals to identify trends and patterns.

Certification 🎓

Find the course certificate in the /certificate directory, confirming successful completion of DataCamp's Exploratory Data Analysis in SQL.

Documentation 📖

Detailed markdown files in /docs provide clear explanations and examples for each SQL concept, making the repository a valuable reference:

• Data types and casting
• Summary functions
• Grouping and aggregation
• Text cleaning and formatting
• Time differences and lagging
• Series generation and binning
• Outlier handling and percentiles
• Date truncation and time-series analysis

Data & Visuals 📈

• ER diagrams and relevant images are stored in the /data directory.
• Visual examples of data distributions and analyses are in the /visuals directory.

License 📜

This project is licensed under the MIT License. See the LICENSE file for details.