https://github.com/sinhasomya100/task-7

Get Basic Sales Summary from a Tiny SQLite Database using Python
https://github.com/sinhasomya100/task-7

jupiter-notebook matplotlib pandas python3 sqlite3

Last synced: 3 months ago
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Get Basic Sales Summary from a Tiny SQLite Database using Python

• Host: GitHub
• URL: https://github.com/sinhasomya100/task-7
• Owner: sinhasomya100
• Created: 2025-04-20T06:08:50.000Z (9 months ago)
• Default Branch: main
• Last Pushed: 2025-04-20T06:51:13.000Z (9 months ago)
• Last Synced: 2025-04-23T11:42:56.550Z (9 months ago)
• Topics: jupiter-notebook, matplotlib, pandas, python3, sqlite3
• Language: Jupyter Notebook
• Homepage:
• Size: 1.18 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# 📦 Task-7 – Get Basic Sales Summary from a Tiny SQLite Database using Python

---

## 📊 Sales Data Analysis with Python & SQLite

This project demonstrates how to use **Python**, **SQLite**, **SQL queries**, and **Matplotlib** to analyze and visualize sales data directly from a database.

---

| File Name                              | Description                                         |

|---------------------------------------|-----------------------------------------------------|

| `TASK 7 DA [1]`                       | Internship task description for Task 8        |

| `Task_7_Sales_Analysis_ipynb.ipynb`   | Jupiter Notebook file on google collab        |

| `TASK 7th.pdf`                        | Step by Step Summary with ouputs           |

| `Interview Q/A`                       | Interview Q/A |

| `README.md`                           | Overview and documentation of the project    |

| `png2pdf.pdf`                         |Summary of Task 7 using Canva  | 

---

## 📁 Project Overview

- Created a **SQLite database** with a `sales` table  

- Inserted **sample sales data** (products, quantity, price)  

- Ran SQL queries inside Python to get:

  - ✅ Total quantity sold

  - ✅ Total revenue

  - ✅ Revenue by product

- Visualized results using **Matplotlib bar chart**

- Displayed summary in a neat table using **pandas**

---

## 📦 Technologies Used

- Python 3.x  

- SQLite (with `sqlite3` module)  

- SQL (`GROUP BY`, `SUM`)  

- pandas  

- matplotlib  

---

## 📑 Steps Performed in the Notebook

-- Connected to SQLite database using Python

![image](https://github.com/user-attachments/assets/ca49fdd3-a008-4d3a-8dd0-38b606fa51ee)

![image](https://github.com/user-attachments/assets/59070d3e-d821-433f-a912-78e8adbd404f)

![image](https://github.com/user-attachments/assets/03d54d52-5b5c-45c0-8b95-7175987a446a)

---

  

--Executed SQL query to fetch product-wise total quantity and revenue

![image](https://github.com/user-attachments/assets/70b302db-720c-4f11-b836-9e05cdbe1960)

![image](https://github.com/user-attachments/assets/d566523a-05d0-488b-9f91-77b861f29f91)

---

  

--Loaded SQL result into pandas

--Plotted a charts using matplotlib

![image](https://github.com/user-attachments/assets/75882d00-1419-40a6-9904-ff14fde3d499)

![image](https://github.com/user-attachments/assets/b71e3080-a23a-43e3-867e-effe0f662789)

--Summary table

![image](https://github.com/user-attachments/assets/2370c12e-e36c-4162-8366-2372a4688958)

---

💡 What I Learnt

-Connecting Python with SQLite databases

-Writing and running SQL queries inside Python

-Performing aggregation with GROUP BY

-Using pandas for tabular data handling

---

📬 Contact

If you have any questions, feel free to reach out:

https://www.linkedin.com/posts/activity-7321762537123782656-d6jB?utm_source=share&utm_medium=member_desktop&rcm=ACoAADazOB0BRuax1fAhu4L7QyodlFZtYz-UgyU