# Boston Bus Equity Dataset

This dataset contains MBTA (Massachusetts Bay Transportation Authority) bus service data for Boston Bus Equity analysis.

## Dataset Subsets

### 1. arrival_departure
Bus arrival and departure times data (2020-2026).

**Schema:**
- `service_date` (date): Service date
- `route_id` (string): Bus route identifier
- `direction_id` (int): Direction (0=outbound, 1=inbound)
- `half_trip_id` (string): Half trip identifier
- `stop_id` (int): Bus stop identifier
- `time_point_id` (string): Time point identifier
- `time_point_order` (int): Order of time point on route
- `point_type` (string): Type of point
- `standard_type` (string): Standard type
- `scheduled` (datetime): Scheduled arrival/departure time
- `actual` (datetime): Actual arrival/departure time
- `scheduled_headway` (float): Scheduled headway in minutes
- `headway` (float): Actual headway in minutes
- `year` (int): Year derived from service_date
- `month` (int): Month derived from service_date

**Records:** ~161 million
**Size:** ~1.9 GB

### 2. ridership
Bus ridership data by trip, season, route, and stop (2016-2024).

**Schema:**
- `season` (string): Season and year (e.g., "Fall 2023")
- `route_id` (string): Bus route identifier
- `route_variant` (string): Route variant
- `direction_id` (int): Direction
- `trip_start_time` (time): Trip start time
- `day_type_id` (string): Day type ID
- `day_type_name` (string): Day type name (weekday, saturday, sunday)
- `stop_name` (string): Bus stop name
- `stop_id` (int): Bus stop identifier
- `stop_sequence` (int): Stop sequence on route
- `boardings` (float): Number of boardings
- `alightings` (float): Number of alightings
- `load_` (float): Passenger load
- `sample_size` (int): Sample size
- `year` (int): Year derived from season
- `season_name` (string): Season name (Fall, Spring, etc.)

**Records:** ~7.9 million
**Size:** ~50 MB

### 3. survey
MBTA 2024 System-Wide Passenger Survey data.

**Schema:**
- `aggregation_level` (string): Level of aggregation
- `service_mode` (string): Service mode (Bus, Rail, etc.)
- `reporting_group` (string): Reporting group
- `measure_group` (string): Measure group
- `measure` (string): Measure name
- `category` (string): Category
- `weighted_percent` (float): Weighted percentage
- `ObjectId` (int): Object identifier
- `year` (int): Survey year (2024)

**Records:** ~14,000
**Size:** ~244 KB

### 4. gtfs_stops
GTFS bus stop locations and information.

**Schema:**
- `stop_id` (int): Stop identifier
- `stop_code` (string): Stop code
- `stop_name` (string): Stop name
- `stop_lat` (float): Latitude
- `stop_lon` (float): Longitude
- `zone_id` (string): Fare zone
- `municipality` (string): Municipality name
- `on_street` (string): Street name
- `at_street` (string): Cross street
- `wheelchair_boarding` (int): Wheelchair accessibility
- `vehicle_type` (int): Vehicle type

**Records:** ~10,000
**Size:** ~550 KB

### 5. gtfs_routes
GTFS route information.

**Schema:**
- `route_id` (string): Route identifier
- `route_short_name` (string): Short route name
- `route_long_name` (string): Long route name
- `route_desc` (string): Route description
- `route_type` (int): Route type
- `route_color` (string): Route color (hex)
- `line_id` (string): Line identifier

**Records:** ~400
**Size:** ~25 KB

### 6. census (race, poverty_rates, per_capita_income)
Boston neighborhood demographic data from Census/ACS (2015-2019).

**Files:**
- `census_race.parquet` - Race/ethnicity by neighborhood
- `census_poverty_rates.parquet` - Poverty rates by neighborhood
- `census_per_capita_income.parquet` - Per capita income by neighborhood

**Records:** ~30 per file
**Size:** ~5-11 KB each

## Usage

```python
import pandas as pd

# Load arrival/departure data
df = pd.read_parquet("data/arrival_departure/arrival_departure.parquet")

# Load ridership data
ridership = pd.read_parquet("data/ridership/ridership.parquet")

# Load survey data
survey = pd.read_parquet("data/survey/survey.parquet")

# Load GTFS data
stops = pd.read_parquet("data/gtfs/gtfs_stops.parquet")
routes = pd.read_parquet("data/gtfs/gtfs_routes.parquet")

# Load census data
census_race = pd.read_parquet("data/census/census_race.parquet")
```

## Data Source

- MBTA Open Data Portal: https://mbta-massdot.opendata.arcgis.com/
- Boston Planning & Development Agency (BPDA)

## License

This dataset is derived from publicly available MBTA and City of Boston data.

## Citation

If you use this dataset, please cite:

```
@dataset{boston_bus_equity_2025,
  title={Boston Bus Equity Dataset},
  author={Boston Bus Equity Team},
  year={2025},
  publisher={HuggingFace},
  url={https://huggingface.co/datasets/LumenscopeAI/BostonBusEquity}
}
```