Merge pull request #1 from com-480-data-visualization/ms1

Milestone 1

Author: gruvw

.gitignore

@@ -0,0 +1,21 @@
+### VisualStudioCode ###
+.vscode/*
+!.vscode/settings.json
+!.vscode/tasks.json
+!.vscode/launch.json
+!.vscode/extensions.json
+!.vscode/*.code-snippets
+
+# Local History for Visual Studio Code
+.history/
+
+# Built Visual Studio Code Extensions
+*.vsix
+
+### VisualStudioCode Patch ###
+# Ignore all local history of files
+.history
+.ionide
+
+.DS_Store
+data/*

README.md

@@ -1,62 +1,24 @@
 # HoopViz 🏀
 
-Project of Data Visualization (COM-480) - 2026
+HoopViz is an **interactive**, **web based**, **data visualization** project designed to turn decades of dry **NBA statistics** into a **dynamic**, **interactive** and **visual** story.
+While most basketball statistics sites feel like looking at a tax return, we want our project to mirror the fast-paced and playful energy of the game itself.
 
-**Live demo: <https://com-480-data-visualization.github.io/Hoopviz/>**
+By using multiple seasons of data, we are building a "time-traveling" experience where users can slide through history to see how the league has evolved over the years with interesting transitions.
+
+**Live demo: <https://com-480-data-visualization.github.io/HoopViz/>**
+
+Project of Data Visualization (EPFL COM-480) - 2026
 
 | Student's name | SCIPER |
 | -------------- | ------ |
 | Lucas Jung | 324724 |
-| | |
-| | |
-
-[Milestone 1](#milestone-1) • [Milestone 2](#milestone-2) • [Milestone 3](#milestone-3)
-
-## Milestone 1 (20th March, 5pm)
-
-**10% of the final grade**
-
-This is a preliminary milestone to let you set up goals for your final project and assess the feasibility of your ideas.
-Please, fill the following sections about your project.
-
-*(max. 2000 characters per section)*
-
-### Dataset
-
-> Find a dataset (or multiple) that you will explore. Assess the quality of the data it contains and how much preprocessing / data-cleaning it will require before tackling visualization. We recommend using a standard dataset as this course is not about scraping nor data processing.
->
-> Hint: some good pointers for finding quality publicly available datasets ([Google dataset search](https://datasetsearch.research.google.com/), [Kaggle](https://www.kaggle.com/datasets), [OpenSwissData](https://opendata.swiss/en/), [SNAP](https://snap.stanford.edu/data/) and [FiveThirtyEight](https://data.fivethirtyeight.com/)).
-
-### Problematic
-
-> Frame the general topic of your visualization and the main axis that you want to develop.
-> - What am I trying to show with my visualization?
-> - Think of an overview for the project, your motivation, and the target audience.
-
-### Exploratory Data Analysis
-
-> Pre-processing of the data set you chose
-> - Show some basic statistics and get insights about the data
-
-### Related work
-
-
-> - What others have already done with the data?
-> - Why is your approach original?
-> - What source of inspiration do you take? Visualizations that you found on other websites or magazines (might be unrelated to your data).
-> - In case you are using a dataset that you have already explored in another context (ML or ADA course, semester project...), you are required to share the report of that work to outline the differences with the submission for this class.
-
-## Milestone 2 (17th April, 5pm)
-
-**10% of the final grade**
-
-
-## Milestone 3 (29th May, 5pm)
-
-**80% of the final grade**
+| Anasse El Boudiri | 374212 |
+| Sam Lee | 375535 |
 
+## Deliverables
 
-## Late policy
+- [Milestone 1](./deliverables/MS1.md)
+- [Milestone 2](./deliverables/MS2.md)
+- [Milestone 3](./deliverables/MS3.md)
 
-- < 24h: 80% of the grade for the milestone
-- < 48h: 70% of the grade for the milestone
+**Note**: Each deliverable comes with its associated GitHub release of the repository.

data/README.md

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+# NBA Data
+
+This folder contains the datasets that we will be using for our project. We have 3 main datasets:
+
+- nba_awards/ : Details about the awards given to players and teams in the NBA (MVP, ROY, DPOY, etc.) : https://www.kaggle.com/api/v1/datasets/download/sumitrodatta/nba-aba-baa-stats
+
+- nba_database/ : Contains player and team statistics for every NBA game from 1947 to the present. It is historical and comprehensive, updated daily. It provides a solid foundation for exploring basketball history, player performance, and team dynamics : https://www.kaggle.com/api/v1/datasets/download/eoinamoore/historical-nba-data-and-player-box-scores
+
+- nba_play_by_play_shot_data/ : A large-scale play-by-play and shot-detail dataset covering both NBA and WNBA games, collected from multiple public sources (e.g., official league APIs and stats sites). It provides every in-game event—from period starts, jump balls, fouls, turnovers, rebounds, and field-goal attempts through free throws—along with detailed shot metadata (shot location, distance, result, assisting player, etc.) : https://www.kaggle.com/api/v1/datasets/download/brains14482/nba-playbyplay-and-shotdetails-data-19962021