engineering-nba-datalisted

**Goal**: Extract and process NBA statistical data efficiently using the nba_api library for data analysis, reporting, and application development. **IMPORTANT**: The nba_api library accesses stats.nba.com endpoints. All data requests return structured datasets that can be output as JSON, dictionaries, or pandas DataFrames. ## Workflow ### Phase 1: Setup and Installation - Install nba_api: `pip install nba_api` if not yet installed - Import required modules based on task: - `from nba_api.stats.endpoints import [endpoint_name]` for stats.nba.com data - `from nba_api.stats.static import players, teams` for static lookups - `from nba_api.stats.library.parameters import [parameter_classes]` for valid parameter values ### Phase 2: Data Retrieval **For Player/Team Lookups (No API Calls)**: - Use `players.find_players_by_full_name('player_name')` for player searches - Use `teams.find_teams_by_full_name('team_name')` for team searches - Both return dictionaries with `id`, `full_name`, and other metadata - No HTTP requests are sent; data is embedded in the package **For Stats Endpoints (API Calls)**: - Identify the correct endpoint from [table of contents](docs/table_of_contents.md) - Initialize endpoint with required parameters: `endpoint_class(param1=value1, param2=value2)` - Access datasets using dot notation: `response_object.dataset_name` - Retrieve data in desired format: - `.get_json()` for JSON string - `.get_dict()` for dictionary - `.get_data_frame()` fo