Michelin Star Data Set Dashboard
This comprehensive web application provides an interactive visualization of Michelin-starred restaurants data. The dashboard offers insights into restaurant distributions, awards, cuisines, and facilities across various cities.
Live Application: Michelin Star Restaurant Guide Dashboard
GitHub Repository: michelin-star-restaurant-guide-dashboard
Features
City Selection
Users can select a specific city from a dropdown menu, which filters the data displayed in all visualizations.
Award Filter
A multi-select dropdown allows users to filter restaurants by Michelin recognition levels:
- 3 Stars
- 2 Stars
- 1 Star
- Bib Gourmand
- Selected Restaurants
Theme Toggle
The dashboard includes a light/dark mode toggle for user preference and improved readability in different lighting conditions.
Interactive Visualizations
Facility-Award Correlation Heatmap
This heatmap displays the correlation between restaurant facilities/services and Michelin awards for the selected city. It helps identify which amenities are most associated with higher Michelin ratings. The correlation is calculated using Point-biserial correlation, which measures the relationship between a binary variable (presence or absence of a facility) and a continuous variable (encoded Michelin award level). This method allows for quantifying the strength and direction of the association between each facility and the Michelin rating.
Top 5 Cuisines Table
A data table showcasing the five most prevalent cuisines in the selected city, along with their respective counts.
Award Distribution Map
An interactive scatter map plots the locations of Michelin-recognized restaurants in the chosen city. Each point is color-coded based on the award level, providing a geographical overview of restaurant distribution.
Awards by City Bar Chart
This bar chart illustrates the distribution of Michelin awards within the selected city, offering a quick comparison of the number of restaurants at each recognition level.
Technical Implementation
The dashboard is built using the following technologies:
- Dash: A Python framework for building analytical web applications
- Plotly: For creating interactive visualizations
- Pandas: For data manipulation and analysis
- NumPy: For numerical computations
- Bootstrap: For responsive layout and styling
- SciPy: For calculating Point-biserial correlation between facilities and awards
- Scikit-learn: For one-hot encoding of facilities data using MultiLabelBinarizer
Key files in the project structure:
app.py: Main application file containing the Dash layout and callbackssrc/data_cleaning.py: Functions for data preprocessingsrc/facility_award_correlation.py: Correlation analysis between facilities and awardssrc/figures.py: Functions to generate various visualizations
Data Source
The dashboard utilizes the “michelin_by_Jerry_Ng.csv” dataset, which contains detailed information about Michelin-recognized restaurants worldwide.
Light and Dark Mode
The application supports both light and dark modes for enhanced user experience.
Light Mode
In light mode, the dashboard uses a white background and the “carto-voyager” map style for the scatter map.
Dark Mode
When switched to dark mode, the dashboard applies a dark background (#111111) and uses the “carto-darkmatter” map style for the scatter map.
Conclusion
This Michelin Star Data Set Dashboard provides a user-friendly interface for exploring and analyzing Michelin-recognized restaurants across different cities. Its interactive features and visualizations offer valuable insights into the distribution of awards, popular cuisines, and the relationship between restaurant amenities and Michelin ratings.
welcome to the community.