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The dataset generation failed because of a cast error
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 6 new columns ({'platform', 'high_usd_per_hour', 'median_usd_per_hour', 'low_usd_per_hour', 'tier', 'region'}) and 4 missing columns ({'item', 'category', 'value', 'attribute'}).

This happened while the csv dataset builder was generating data using

hf://datasets/zimzum1984/website-project-cost-benchmarks/hourly_rates.csv (at revision e7fbcb4aa699c67b1a7845ddb8a098930bc90180), ['hf://datasets/zimzum1984/website-project-cost-benchmarks@e7fbcb4aa699c67b1a7845ddb8a098930bc90180/cost_benchmarks_flat.csv', 'hf://datasets/zimzum1984/website-project-cost-benchmarks@e7fbcb4aa699c67b1a7845ddb8a098930bc90180/hourly_rates.csv']

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 "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1837, in _prepare_split_single
                  writer.write_table(table)
                  ~~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 765, in write_table
                  self._write_table(pa_table, writer_batch_size=writer_batch_size)
                  ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              platform: string
              region: string
              tier: string
              low_usd_per_hour: int64
              median_usd_per_hour: int64
              high_usd_per_hour: int64
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1010
              to
              {'category': Value('string'), 'item': Value('string'), 'attribute': Value('string'), 'value': Value('string')}
              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 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1683, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1839, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
                  ...<4 lines>...
                  )
              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 6 new columns ({'platform', 'high_usd_per_hour', 'median_usd_per_hour', 'low_usd_per_hour', 'tier', 'region'}) and 4 missing columns ({'item', 'category', 'value', 'attribute'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/zimzum1984/website-project-cost-benchmarks/hourly_rates.csv (at revision e7fbcb4aa699c67b1a7845ddb8a098930bc90180), ['hf://datasets/zimzum1984/website-project-cost-benchmarks@e7fbcb4aa699c67b1a7845ddb8a098930bc90180/cost_benchmarks_flat.csv', 'hf://datasets/zimzum1984/website-project-cost-benchmarks@e7fbcb4aa699c67b1a7845ddb8a098930bc90180/hourly_rates.csv']
              
              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.

category
string
item
string
attribute
string
value
string
base_project_types
landing_page
base_price_usd
300
base_project_types
landing_page
base_weeks
1
base_project_types
landing_page
base_complexity
8
base_project_types
landing_page
default_platform
wordpress
base_project_types
presentation
base_price_usd
500
base_project_types
presentation
base_weeks
2
base_project_types
presentation
base_complexity
12
base_project_types
presentation
default_platform
wordpress
base_project_types
portfolio
base_price_usd
450
base_project_types
portfolio
base_weeks
2
base_project_types
portfolio
base_complexity
15
base_project_types
portfolio
default_platform
wordpress
base_project_types
blog
base_price_usd
600
base_project_types
blog
base_weeks
3
base_project_types
blog
base_complexity
18
base_project_types
blog
default_platform
wordpress
base_project_types
ecommerce
base_price_usd
1500
base_project_types
ecommerce
base_weeks
5
base_project_types
ecommerce
base_complexity
35
base_project_types
ecommerce
default_platform
shopify
base_project_types
marketplace
base_price_usd
5000
base_project_types
marketplace
base_weeks
12
base_project_types
marketplace
base_complexity
60
base_project_types
marketplace
default_platform
magento
base_project_types
web_app
base_price_usd
4000
base_project_types
web_app
base_weeks
8
base_project_types
web_app
base_complexity
45
base_project_types
web_app
default_platform
custom
platform_multipliers
wordpress
price
1
platform_multipliers
wordpress
complexity_modifier
0
platform_multipliers
wordpress
timeline
1
platform_multipliers
wordpress
hosting_monthly_usd
15
platform_multipliers
wordpress
saas_fee_usd
0
platform_multipliers
shopify
price
0.85
platform_multipliers
shopify
complexity_modifier
-5
platform_multipliers
shopify
timeline
0.8
platform_multipliers
shopify
hosting_monthly_usd
0
platform_multipliers
shopify
saas_fee_usd
39
platform_multipliers
woocommerce
price
1.1
platform_multipliers
woocommerce
complexity_modifier
5
platform_multipliers
woocommerce
timeline
1.1
platform_multipliers
woocommerce
hosting_monthly_usd
25
platform_multipliers
woocommerce
saas_fee_usd
0
platform_multipliers
magento
price
2
platform_multipliers
magento
complexity_modifier
15
platform_multipliers
magento
timeline
1.8
platform_multipliers
magento
hosting_monthly_usd
80
platform_multipliers
magento
saas_fee_usd
0
platform_multipliers
custom
price
2.5
platform_multipliers
custom
complexity_modifier
20
platform_multipliers
custom
timeline
2
platform_multipliers
custom
hosting_monthly_usd
40
platform_multipliers
custom
saas_fee_usd
0
geographic_multipliers
south_asia
price
0.35
geographic_multipliers
south_asia
hourly_rate_usd
15|45
geographic_multipliers
eastern_europe
price
0.55
geographic_multipliers
eastern_europe
hourly_rate_usd
25|50
geographic_multipliers
western_europe
price
1
geographic_multipliers
western_europe
hourly_rate_usd
60|100
geographic_multipliers
uk
price
1.15
geographic_multipliers
uk
hourly_rate_gbp
55|90
geographic_multipliers
australia
price
1.3
geographic_multipliers
australia
hourly_rate_aud
90|150
geographic_multipliers
us
price
1.45
geographic_multipliers
us
hourly_rate_usd
80|150
pricing_tier_multipliers
freelancer
global
1
pricing_tier_multipliers
freelancer
hourly_reference_usd
65
pricing_tier_multipliers
freelancer
service_markup
1
pricing_tier_multipliers
agency
global
2.2
pricing_tier_multipliers
agency
hourly_reference_usd
120
pricing_tier_multipliers
agency
service_markup
1.5
urgency_multipliers
relaxed
price
0.95
urgency_multipliers
relaxed
timeline
1.3
urgency_multipliers
relaxed
risk_add
-5
urgency_multipliers
normal
price
1
urgency_multipliers
normal
timeline
1
urgency_multipliers
normal
risk_add
0
urgency_multipliers
tight
price
1.25
urgency_multipliers
tight
timeline
0.75
urgency_multipliers
tight
risk_add
8
urgency_multipliers
rush
price
1.65
urgency_multipliers
rush
timeline
0.5
urgency_multipliers
rush
risk_add
18
client_type_multipliers
startup
price
1
client_type_multipliers
startup
timeline
0.9
client_type_multipliers
startup
risk_add
3
client_type_multipliers
small_business
price
1.05
client_type_multipliers
small_business
timeline
1
client_type_multipliers
small_business
risk_add
0
client_type_multipliers
mid_market
price
1.15
client_type_multipliers
mid_market
timeline
1.2
client_type_multipliers
mid_market
risk_add
4
client_type_multipliers
enterprise
price
1.35
client_type_multipliers
enterprise
timeline
1.5
client_type_multipliers
enterprise
risk_add
8
project_origin_multipliers
new_build
price
1
project_origin_multipliers
new_build
timeline
1
project_origin_multipliers
new_build
complexity_add
0
project_origin_multipliers
new_build
risk_add
0
project_origin_multipliers
redesign
price
1.15
End of preview.

Website & App Project Cost Benchmarks 2026

Website & app project cost benchmarks - calibrated on 600+ project quotes and public rate benchmarks. CC-BY 4.0. Source and methodology: https://projectcostestimator.com

This is the dataset behind Project Cost Estimator, an independent website cost estimator. The canonical machine-readable source is the live endpoint https://projectcostestimator.com/api/cost-data (no auth, CORS open). The files here are a published snapshot of that endpoint plus two CSV views derived from it.

Files

File Contents
cost-data.json Raw snapshot of the live API response (Schema.org Dataset JSON-LD wrapper, all data under the data key)
hourly_rates.csv Tidy table of web developer hourly rates: one row per platform x region x tier
cost_benchmarks_flat.csv Mechanical flatten of the whole data object: category, item, attribute, value

What is in the data

All monetary values are USD unless the key says otherwise (hourly_rate_gbp, hourly_rate_aud).

hourly_rates.csv columns

Column Meaning
platform One of 12: wordpress, shopify, shopify_plus, woocommerce, magento2, magento1, prestashop, bigcommerce, wix, squarespace, webflow, custom
region One of 6: eastern_europe, western_europe, uk, us, australia, south_asia
tier freelancer or agency
low_usd_per_hour Low end of the observed rate band
median_usd_per_hour Median observed rate
high_usd_per_hour High end of the observed rate band

Rate sources: Clutch (Apr 2026), Talmatic Global Snapshot, Arc.dev, Upwork medians, TechReviewer, plus other public rate benchmarks. See https://projectcostestimator.com/rate-database for the sourced, human-readable version.

cost-data.json fields (under data)

Key Meaning
base_project_types Per project type (landing_page, presentation, portfolio, blog, ecommerce, marketplace, web_app): base_price_usd, base_weeks, base_complexity (0-100 score), default_platform
platform_multipliers Per platform (wordpress, shopify, woocommerce, magento, custom): price and timeline multipliers vs the WordPress baseline, complexity_modifier, hosting_monthly_usd, saas_fee_usd
geographic_multipliers Per market (south_asia, eastern_europe, western_europe, uk, australia, us): price multiplier vs Western Europe baseline and a typical hourly rate band (hourly_rate_usd, hourly_rate_gbp or hourly_rate_aud as `low
pricing_tier_multipliers freelancer vs agency: global price multiplier, hourly_reference_usd, service_markup
urgency_multipliers relaxed, normal, tight, rush: price, timeline, risk_add (percentage points added to the risk score)
client_type_multipliers startup, small_business, mid_market, enterprise: price, timeline, risk_add
project_origin_multipliers new_build, redesign, migration: price, timeline, complexity_add, risk_add
safety_buffer Contingency fractions: default, by_complexity (low, medium, high), by_origin
compound_multiplier_cap Cap applied to the product of all multipliers (8)
median_project_cost_usd Median delivered project cost, freelancer vs agency, for 12 project or platform archetypes
platform_subscription_fees_monthly_usd Published monthly plan fees for Shopify, Wix, Squarespace, Webflow
methodology calibration_sample (600+ quotes), markets_covered (6), accuracy_band, the 9 engine names
hourly_rate_database The nested source of hourly_rates.csv: rates[platform][region][tier] = {low, median, high} in USD per hour

cost_benchmarks_flat.csv columns

Mechanical flatten of every leaf value in data. category is the top-level key, item the second-level key, attribute the remaining dotted path. Scalar lists are joined with | (for example a rate band 25|50 means low 25, high 50).

Methodology in one paragraph

Base prices per project type are calibrated against 600+ real project quotes across 6 geographic markets, then adjusted by platform, geography, provider tier, urgency, client type and project origin multipliers, with a compound multiplier cap and a complexity-based safety buffer. Stated accuracy band: +/-18%. Full write-up: https://projectcostestimator.com/methodology

License

Creative Commons Attribution 4.0 International (CC BY 4.0). Free to use, share and adapt, including commercially, with attribution to projectcostestimator.com. Full text in LICENSE.

Cite as

Project Cost Estimator Website Cost Dataset 2026, projectcostestimator.com/api/cost-data

@misc{projectcostestimator2026,
  title  = {Website \& App Project Cost Benchmarks 2026},
  author = {{Project Cost Estimator}},
  year   = {2026},
  url    = {https://projectcostestimator.com/api/cost-data},
  note   = {CC BY 4.0. Methodology: https://projectcostestimator.com/methodology}
}

Freshness

The live endpoint is the source of truth; this snapshot is refreshed when the upstream data changes (dateModified inside cost-data.json tells you the upstream revision date).

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