Datasets:

variantwise
/

indian-cars-variants

Error code:   StreamingRowsError
Exception:    ValueError
Message:      Expected object or value
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 281, in _generate_tables
                  examples = [ujson_loads(line) for line in batch.splitlines()]
                              ~~~~~~~~~~~^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 20, in ujson_loads
                  return pd.io.json.ujson_loads(*args, **kwargs)
                         ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
              ValueError: Expected object or value

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The data behind variantwise.com: every car model, trim, engine and variant on sale in India, with prices and a controlled feature vocabulary, plus the state road tax tables that power on-road price breakdowns. Exported from the same build that renders the site. A mirror copy like this one is current as of its release date, stamped in each file's dataAsOf; the always-current files live at variantwise.com/data.

Data as of: see the dataAsOf field inside each file. New releases are cut as the catalogue changes; the live files are always at variantwise.com/data.

Files

File	What it holds
`data/catalogue.json`	Every model with its engines, trims (full feature set) and variants with prices
`data/catalogue.csv`	One flat row per variant, for spreadsheets
`data/road-tax.json`	Road tax tables for 25 Indian states and 95 cities, each rate with its source, confidence and verification date

Licence: CC BY 4.0

Free to use, share and build on, including commercially, with attribution: credit VariantWise and link to https://variantwise.com.

A working credit line: "Data: VariantWise, variantwise.com".

Full licence: https://creativecommons.org/licenses/by/4.0/

How the data is made

Every price and specification traces to a source. When sources disagree, the manufacturer's own site wins, always.
Road tax rates are transcribed from state acts, gazettes and notifications, and each carries the instrument it came from, a confidence grade and the date it was verified. Scope is an individual buyer's first private car.
Where a figure could not be verified it is absent rather than guessed. An absent state or field is a fact about what is known, not an oversight.
Imagery is excluded: the photographs are the manufacturers' property.

The full method: https://variantwise.com/methodology

Reading the data

Prices follow each market's priceStyle. For India that is lakh: a price of 14.49 means Rs 14.49 lakh (Rs 14,49,000), ex-showroom.
variant ids are unique only within their model. Always pair a variant id with its model id.
Trim features use a controlled vocabulary: graded values like "led-projector" or "panoramic" rather than yes/no flags, so a field can say what a car actually has.

An example of what it can answer

The same car costs lakhs more on the road depending on the state that registers it. The computed finding, refreshed with every data update: https://variantwise.com/data/findings/on-road-spread

Corrections

Spotted an error, or built something with this? Tell us: info@variantwise.com

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