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Building-a-Beginner-Analytics-Dashboard-Python-SQL-CSV

This project is a beginner-friendly end-to-end data pipeline that demonstrates how to load data from a CSV file, clean it, store it in a SQL database, and build a simple analytics dashboard in streamlit using Python .

It is designed as an introductory project for anyone learning data engineering, data analytics, or Python-based ETL pipelines.

📁 Project Structure

📦 Beginner_Data_Pipeline_Python_SQL_CSV_file

┣ 📄 README.md

┣ 📄 pipeline.py

┣ 📄 dashboard.py

┣ 📄 sales_data.xlsx

Data Architechture Diagram

Beginner_Pi

🚀 Features

  • Import data from a CSV file

  • Clean and preprocess the dataset using Pandas

  • Store cleaned data into a SQLite database

  • Use SQL queries to aggregate and analyze the data

  • Create a simple analytics dashboard (tables + charts) in Streamlit (Web based visualization platform)

  • Beginner-friendly, fully documented Python code

🛠 Technologies Used

  • Python 3.x

  • Pandas

  • SQLite3

  • SQLAlchemy

  • Altair (statistical visualization library)

📊 Example Insights Generated

  • The first five products

  • Total Revenue

  • Revenue by Region

  • Top-performing products

  • Daily Sales Trend by products

▶️ How to Run the Project

  1. Clone the Repository git clone https://github.com/Kindoli/Building-a-Beginner-Analytics-Dashboard-Python-SQL-CSV-.git cd Building-a-Beginner-Analytics-Dashboard-Python-SQL-CSV-

  2. Run the Pipeline python pipeline.py

This will:

  • Load the CSV

  • Clean the data

  • Insert it into the SQL database (sales.db)

  1. Run the Dashboard Script python dashboard.py

This will generate charts and summary tables.

Streamlit Dashboard snapshot

dasbboard_image

📂 Sample Code Snippet

df = pd.read_excel("sales_data.xlsx")

df_clean = df.dropna()

df_clean.to_sql("Sales_data", conn, if_exists="replace", index=False)

📘 Learning Objectives

This project helps beginners learn:

  • Reading CSV files in Python

  • Basic data cleaning

  • SQL operations using Python

  • Building a simple analytics dashboard using Streamlit

  • Structuring a real-world mini data pipeline

🤝 Contributing

Pull requests are welcome! Feel free to submit improvements or additional analytics steps.