The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
Error code: DatasetGenerationCastError
Exception: DatasetGenerationCastError
Message: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 12 new columns ({'lot_size', 'street_address', 'bedrooms', 'city', 'price_usd', 'state', 'listing_date', 'latitude', 'square_feet', 'year_built', 'bathrooms', 'longitude'}) and 2 missing columns ({'url', 'property_id'}).
This happened while the csv dataset builder was generating data using
hf://datasets/datahiveai/Zillow-Panoramic-Property-Dataset/properties.csv (at revision 37fa4909d5c28615fdbacf85a0c53ce230c2cb5a)
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1871, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 643, in write_table
pa_table = table_cast(pa_table, self._schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2293, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2241, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
id: int64
street_address: string
latitude: double
longitude: double
city: string
state: string
square_feet: double
bedrooms: int64
bathrooms: double
year_built: int64
lot_size: int64
price_usd: int64
listing_date: string
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1768
to
{'id': Value(dtype='int64', id=None), 'property_id': Value(dtype='int64', id=None), 'url': Value(dtype='string', id=None)}
because column names don't match
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1436, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1053, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 925, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1001, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1742, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1873, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 12 new columns ({'lot_size', 'street_address', 'bedrooms', 'city', 'price_usd', 'state', 'listing_date', 'latitude', 'square_feet', 'year_built', 'bathrooms', 'longitude'}) and 2 missing columns ({'url', 'property_id'}).
This happened while the csv dataset builder was generating data using
hf://datasets/datahiveai/Zillow-Panoramic-Property-Dataset/properties.csv (at revision 37fa4909d5c28615fdbacf85a0c53ce230c2cb5a)
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
id
int64 | property_id
int64 | url
string |
|---|---|---|
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This is a sample dataset. To access the full version or request any custom dataset tailored to your needs, contact DataHive at contact@datahive.ai.
This free trial dataset contains high-resolution Zillow panoramic image data extracted from 500 residential properties across the United States. Each property is paired with structured metadata - including geolocation, square footage, pricing, and listing details - and is associated with multiple 360° interior panoramas. These images provide rich spatial and visual context, making the dataset highly suitable for AI development, spatial scene understanding, and real estate analytics. Unlike cubemap-based datasets, where each panorama is split into directional tiles, this dataset uses a single equirectangular image per panorama, capturing the full 360° field of view from a single interior location. This format ensures compatibility with standard vision and XR frameworks and supports straightforward use in both supervised and generative modeling tasks. The free trial version includes:
- 500 residential properties
- 13,500+ equirectangular panoramas
- Between 1 and 109 panoramas per property
- Structured metadata and imagery are stored in two relational tables: PROPERTIES and PANORAMAS
All panorama images are hosted externally and accessible via stable public URLs. The full dataset contains over 1.35 million panoramic images and continues to expand.
Uses
- Train models for room segmentation, furniture classification, or layout prediction using dense panoramic input. Use multi-view panoramic image sets to synthesize full interior spaces, perform scene completion, or infer depth.
- Combine structured property data (e.g., square footage, bedrooms, price) with high-resolution interior panoramas to uncover deeper insights into real estate trends. This dataset supports use cases like modeling how visual features impact pricing, predicting home condition, clustering by interior style, and analyzing design preferences across markets or buyer segments.
- Use room-scale panoramic imagery to develop and evaluate systems for spatial reasoning, path planning, and autonomous navigation. The dataset supports robotics simulation, scene understanding, and virtual pretraining with realistic visual input from diverse indoor environments.
Dataset Structure
The dataset is delivered as a plain CSV file containing metadata and direct image URLs. Images are hosted on a scalable cloud infrastructure and can be accessed via script or browser.
Source Data
Zillow panoramic image data extracted from residential properties across the United States
Dataset Card Contact
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