Datasets:
Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
$schema: string
$id: string
title: string
description: string
type: string
additionalProperties: bool
required: list<item: string>
child 0, item: string
properties: struct<zcta5: struct<type: string, description: string>, state_fips: struct<type: string, descriptio (... 1463 chars omitted)
child 0, zcta5: struct<type: string, description: string>
child 0, type: string
child 1, description: string
child 1, state_fips: struct<type: string, description: string>
child 0, type: string
child 1, description: string
child 2, state_code: struct<type: string, description: string>
child 0, type: string
child 1, description: string
child 3, centroid_latitude_degrees: struct<type: string, description: string, units: string>
child 0, type: string
child 1, description: string
child 2, units: string
child 4, centroid_longitude_degrees: struct<type: string, description: string, units: string>
child 0, type: string
child 1, description: string
child 2, units: string
child 5, gdd_base_f: struct<type: string, description: string, units: string>
child 0, type: string
child 1, description: string
child 2, units: string
child 6, accumulation_start_date: struct<type: string, description: string, units: string>
child 0, type: string
child 1, description: string
child 2, units: string
child 7, observation_start_date: struct<type: list<item: string>, description: string, units:
...
tring, censusZctaCount: int64, zctaAndS (... 81 chars omitted)
child 0, schemaVersion: int64
child 1, source: string
child 2, sourceVintage: string
child 3, censusZctaCount: int64
child 4, zctaAndSupplementalCount: int64
child 5, supplementalZipCount: int64
child 6, retrieved_on: timestamp[s]
child 1, stateRelationship: struct<schemaVersion: int64, source: string, sourceVintage: string, assignmentMethod: string, covera (... 57 chars omitted)
child 0, schemaVersion: int64
child 1, source: string
child 2, sourceVintage: string
child 3, assignmentMethod: string
child 4, coverage: string
child 5, zctaCount: int64
child 6, retrieved_on: timestamp[s]
qa: struct<rows_sorted_by_zcta: bool, unique_zcta_count: int64, public_field_count: int64, stale_availab (... 56 chars omitted)
child 0, rows_sorted_by_zcta: bool
child 1, unique_zcta_count: int64
child 2, public_field_count: int64
child 3, stale_available_rows: int64
child 4, modeled_soil_temperature_included: bool
station_candidate_count: int64
freshness_max_lag_days: int64
version: timestamp[s]
distributions: list<item: struct<name: string, media_type: string>>
child 0, item: struct<name: string, media_type: string>
child 0, name: string
child 1, media_type: string
row_count: int64
source_year: int64
license: string
schema_version: int64
unavailable_row_count: int64
to
{'schema_version': Value('int64'), 'title': Value('string'), 'version': Value('timestamp[s]'), 'generated_at': Value('string'), 'source_year': Value('int64'), 'temporal_coverage': {'accumulation_start_date': Value('timestamp[s]'), 'minimum_observation_end_date': Value('timestamp[s]'), 'maximum_observation_end_date': Value('timestamp[s]')}, 'spatial_coverage': Value('string'), 'row_count': Value('int64'), 'available_row_count': Value('int64'), 'unavailable_row_count': Value('int64'), 'state_summary_row_count': Value('int64'), 'gdd_base_f': Value('int64'), 'station_candidate_count': Value('int64'), 'freshness_max_lag_days': Value('int64'), 'source_metadata': {'noaa': {'name': Value('string'), 'sourceYear': Value('int64'), 'observationFile': Value('string'), 'stationMetadata': Value('string')}, 'census': {'gazetteer': {'schemaVersion': Value('int64'), 'source': Value('string'), 'sourceVintage': Value('string'), 'censusZctaCount': Value('int64'), 'zctaAndSupplementalCount': Value('int64'), 'supplementalZipCount': Value('int64'), 'retrieved_on': Value('timestamp[s]')}, 'stateRelationship': {'schemaVersion': Value('int64'), 'source': Value('string'), 'sourceVintage': Value('string'), 'assignmentMethod': Value('string'), 'coverage': Value('string'), 'zctaCount': Value('int64'), 'retrieved_on': Value('timestamp[s]')}}}, 'license': Value('string'), 'citation': Value('string'), 'qa': {'rows_sorted_by_zcta': Value('bool'), 'unique_zcta_count': Value('int64'), 'public_field_count': Value('int64'), 'stale_available_rows': Value('int64'), 'modeled_soil_temperature_included': Value('bool')}, 'distributions': List({'name': Value('string'), 'media_type': Value('string')})}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
$schema: string
$id: string
title: string
description: string
type: string
additionalProperties: bool
required: list<item: string>
child 0, item: string
properties: struct<zcta5: struct<type: string, description: string>, state_fips: struct<type: string, descriptio (... 1463 chars omitted)
child 0, zcta5: struct<type: string, description: string>
child 0, type: string
child 1, description: string
child 1, state_fips: struct<type: string, description: string>
child 0, type: string
child 1, description: string
child 2, state_code: struct<type: string, description: string>
child 0, type: string
child 1, description: string
child 3, centroid_latitude_degrees: struct<type: string, description: string, units: string>
child 0, type: string
child 1, description: string
child 2, units: string
child 4, centroid_longitude_degrees: struct<type: string, description: string, units: string>
child 0, type: string
child 1, description: string
child 2, units: string
child 5, gdd_base_f: struct<type: string, description: string, units: string>
child 0, type: string
child 1, description: string
child 2, units: string
child 6, accumulation_start_date: struct<type: string, description: string, units: string>
child 0, type: string
child 1, description: string
child 2, units: string
child 7, observation_start_date: struct<type: list<item: string>, description: string, units:
...
tring, censusZctaCount: int64, zctaAndS (... 81 chars omitted)
child 0, schemaVersion: int64
child 1, source: string
child 2, sourceVintage: string
child 3, censusZctaCount: int64
child 4, zctaAndSupplementalCount: int64
child 5, supplementalZipCount: int64
child 6, retrieved_on: timestamp[s]
child 1, stateRelationship: struct<schemaVersion: int64, source: string, sourceVintage: string, assignmentMethod: string, covera (... 57 chars omitted)
child 0, schemaVersion: int64
child 1, source: string
child 2, sourceVintage: string
child 3, assignmentMethod: string
child 4, coverage: string
child 5, zctaCount: int64
child 6, retrieved_on: timestamp[s]
qa: struct<rows_sorted_by_zcta: bool, unique_zcta_count: int64, public_field_count: int64, stale_availab (... 56 chars omitted)
child 0, rows_sorted_by_zcta: bool
child 1, unique_zcta_count: int64
child 2, public_field_count: int64
child 3, stale_available_rows: int64
child 4, modeled_soil_temperature_included: bool
station_candidate_count: int64
freshness_max_lag_days: int64
version: timestamp[s]
distributions: list<item: struct<name: string, media_type: string>>
child 0, item: struct<name: string, media_type: string>
child 0, name: string
child 1, media_type: string
row_count: int64
source_year: int64
license: string
schema_version: int64
unavailable_row_count: int64
to
{'schema_version': Value('int64'), 'title': Value('string'), 'version': Value('timestamp[s]'), 'generated_at': Value('string'), 'source_year': Value('int64'), 'temporal_coverage': {'accumulation_start_date': Value('timestamp[s]'), 'minimum_observation_end_date': Value('timestamp[s]'), 'maximum_observation_end_date': Value('timestamp[s]')}, 'spatial_coverage': Value('string'), 'row_count': Value('int64'), 'available_row_count': Value('int64'), 'unavailable_row_count': Value('int64'), 'state_summary_row_count': Value('int64'), 'gdd_base_f': Value('int64'), 'station_candidate_count': Value('int64'), 'freshness_max_lag_days': Value('int64'), 'source_metadata': {'noaa': {'name': Value('string'), 'sourceYear': Value('int64'), 'observationFile': Value('string'), 'stationMetadata': Value('string')}, 'census': {'gazetteer': {'schemaVersion': Value('int64'), 'source': Value('string'), 'sourceVintage': Value('string'), 'censusZctaCount': Value('int64'), 'zctaAndSupplementalCount': Value('int64'), 'supplementalZipCount': Value('int64'), 'retrieved_on': Value('timestamp[s]')}, 'stateRelationship': {'schemaVersion': Value('int64'), 'source': Value('string'), 'sourceVintage': Value('string'), 'assignmentMethod': Value('string'), 'coverage': Value('string'), 'zctaCount': Value('int64'), 'retrieved_on': Value('timestamp[s]')}}}, 'license': Value('string'), 'citation': Value('string'), 'qa': {'rows_sorted_by_zcta': Value('bool'), 'unique_zcta_count': Value('int64'), 'public_field_count': Value('int64'), 'stale_available_rows': Value('int64'), 'modeled_soil_temperature_included': Value('bool')}, 'distributions': List({'name': Value('string'), 'media_type': Value('string')})}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
U.S. ZIP/ZCTA Growing Degree Days (base 50°F) — 2026-07-16 release
Cumulative growing degree days (base 50°F, accumulated from January 1) for 33,642 U.S. ZIP Code Tabulation Areas (ZCTAs), derived from NOAA GHCN-Daily station observations. Each ZCTA is mapped to its nearest weather stations (up to 8 candidates by Haversine distance, with a documented fallback chain), and daily GDD is computed from station min/max temperatures.
This is a frozen, immutable snapshot of the 2026-07-16 release, mirrored here for discovery and reuse. It will not be updated in place.
- Daily-updated data (canonical home): https://whentoapplypreemergent.com/datasets/gdd/
- This exact release (immutable record): https://whentoapplypreemergent.com/datasets/gdd/2026-07-16/
- Archived copy with DOI: https://doi.org/10.5281/zenodo.21465487
- Method and reproducibility: https://github.com/ke-pan/us-zip-gdd-dataset
Files
| File | Contents |
|---|---|
gdd50-zcta.csv / gdd50-zcta.parquet |
One row per ZCTA (33,642 rows): cumulative GDD, assigned station, distance, freshness, and availability fields |
state-summary.csv |
Per-state aggregates: ZCTA counts, min/median/mean/max GDD, latest observation date |
schema.json / state-summary-schema.json |
Frozen JSON Schema row contracts for the two tables |
sample.csv |
Small excerpt for quick inspection |
metadata.json, CITATION.cff, DATA-LICENSE.txt, checksums.sha256 |
Provenance, citation, license, and SHA-256 checksums |
Key columns in gdd50-zcta.csv: zcta5, state_code, centroid latitude/longitude, cumulative_gdd_f_degree_days, observation_end_date, station_id, station_distance_km, fallback_rank, freshness_status, data_available. Full column contracts are in schema.json.
Method (short)
- Download NOAA GHCN-Daily min/max temperature observations.
- Map each Census ZCTA centroid to its 8 nearest GHCN stations (Haversine); use the closest station with adequate data, falling back down the candidate list.
- Compute daily GDD as
max(0, (Tmax + Tmin)/2 − 50°F)and accumulate from January 1. - Publish with per-row freshness/availability flags and per-release SHA-256 checksums.
The full pipeline is documented in the reproducibility repository.
Limitations
- Values are modeled estimates interpolated from nearby stations, not ground measurements. Station distance and fallback rank are included per row so you can filter by proximity.
- ZCTAs are Census statistical areas, not USPS delivery boundaries.
- 20 of 33,642 ZCTAs are marked unavailable (
data_available = false, withunavailable_reason). - Base temperature is fixed at 50°F in this release.
License and citation
Data: CC BY 4.0 (see DATA-LICENSE.txt). Cite as:
PAN, KE (Offshoot Labs). WhenToApplyPreEmergent ZIP/ZCTA Growing Degree Days (base 50°F), version 2026-07-16. DOI: 10.5281/zenodo.21465487
Maintained by Offshoot Labs; it powers the lawn-care timing site WhenToApplyPreEmergent.com. Questions and corrections: open an issue on the reproducibility repository.
- Downloads last month
- 22