Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/bhushan148/restaurant-data-analysis-insights

🍴 Analyzed a restaurant dataset for business insights. 🔍 Cleaned & transformed data using Python, SQL, and MySQL. 📊 Visualized trends with Matplotlib, Seaborn, Plotly & Folium. 📈 Tasks included cuisine analysis, city trends, price range, and service insights. 📍 Focused on improving restaurant operations.
https://github.com/bhushan148/restaurant-data-analysis-insights

Last synced: about 2 months ago
JSON representation

🍴 Analyzed a restaurant dataset for business insights. 🔍 Cleaned & transformed data using Python, SQL, and MySQL. 📊 Visualized trends with Matplotlib, Seaborn, Plotly & Folium. 📈 Tasks included cuisine analysis, city trends, price range, and service insights. 📍 Focused on improving restaurant operations.

Awesome Lists containing this project

README 

        
# Restaurant Data Analysis Internship - Project Report



**Connect with me on [LinkedIn](https://www.linkedin.com/in/bhushan-gawali-97b645233/)**



---



## Project Overview



This project involves analyzing a **restaurant dataset** to uncover key trends and actionable insights that can optimize restaurant operations. The analysis is performed using **Python**, **SQL**, and various **data visualization** tools including **Matplotlib**, **Seaborn**, **Plotly**, and **Folium**. The dataset includes critical information about restaurants, including their locations, cuisines, price ranges, ratings, and service availability (e.g., online delivery and table booking).



---



## Key Tasks and Tools Used



### 1. **Data Cleaning and Storage in MySQL**

- Cleaned and standardized the dataset to ensure consistency.

- Stored the cleaned data in a **MySQL database** for better management and accessibility.



### 2. **Insights Extraction**

- Extracted valuable insights using **SQL** queries and **Python** libraries such as **Pandas** and **NumPy**.



### 3. **Data Visualization**

- Utilized various tools for data visualization:

  - **Matplotlib**, **Seaborn**, and **Plotly** for general visualizations.

  - **Folium** for mapping restaurant locations and providing geographic insights.



### 4. **Actionable Insights**

- Provided **data-driven recommendations** for improving restaurant operations and optimizing business strategies.



---



## Internship Tasks and Insights Extraction



### **Level 1 Tasks**:  

- **🍽 Top Cuisines**: Identified the most popular cuisines based on the dataset.  

- **🌆 City Analysis**: Analyzed restaurant distributions by city.  

- **💲 Price Range Distribution**: Examined how restaurants are distributed across different price ranges.  

- **📦 Online Delivery**: Investigated the availability of online delivery services in restaurants.



### **Level 2 Tasks**:  

- **🍕 Cuisine Combination**: Analyzed common cuisine combinations across restaurants.  

- **🗺 Geographic Analysis**: Mapped restaurant locations and analyzed trends across different areas.  

- **🍴 Restaurant Chains**: Identified restaurant chains based on names and analyzed their performance.



### **Level 3 Tasks**:  

- **🗳 Votes Analysis**: Analyzed customer votes and their correlation with restaurant ratings.  

- **💲 Price Range vs. Online Delivery & Table Booking**: Investigated how the price range affects the availability of online delivery and table booking.



---



## Data Cleaning and Transformation Process



### **1. Data Cleaning:**

- **Standardized Column Names**: Ensured uniformity across column names for better readability.

- **Handling Missing Values**: Addressed missing data through imputation or removal.

- **Data Type Correction**: Corrected data types of columns for accurate calculations.

- **Currency Conversion**: Standardized currency to ensure consistency across all restaurants.

- **Final Data Quality Check**: Conducted a thorough data quality check to ensure a clean dataset.



### **2. Data Transformation:**

- **Database Connection**: Established a connection with MySQL and stored the cleaned data.

- **Table Creation**: Created necessary tables in MySQL and ensured data was successfully inserted.



---



## Deliverables and Documentation



- **[Dataset Link](https://github.com/Bhushan148/Restaurant-Data-Analysis-Insights/blob/main/project-docs-and-assets/Dataset%20.csv)**: Direct link to the restaurant dataset used for analysis.  

- **[Jupyter Notebook Documentation (PDF)](https://github.com/Bhushan148/Restaurant-Data-Analysis-Insights/blob/main/project-docs-and-assets/Cognifyz%20Technologies%20Task%20final%20Document.pdf)**: Downloadable PDF containing all analysis steps and code from the Jupyter Notebook.  

- **[Internship Task Documentation (PDF)](https://github.com/Bhushan148/Restaurant-Data-Analysis-Insights/blob/main/project-docs-and-assets/Data%20Analysis%20Internship%20Task%20.pdf)**: Detailed documentation outlining all the internship tasks completed and their corresponding solutions.



---



## 📔 Interactive Notebook on Google Colab



You can access the interactive version of the notebook on Google Colab:  

[Restaurant Data Analysis Notebook](https://colab.research.google.com/drive/YOUR_NOTEBOOK_ID)



This notebook contains the complete code, visualizations, and analysis steps for the project.



---



## Thank You for Visiting My Repository! 🚀



I appreciate you taking the time to explore my project. Please feel free to reach out if you have any questions, suggestions, or feedback. I'm always open to learning and improving.



**Stay tuned for more exciting projects!**



---



**Bhushan Gawali | Data Analyst**