Datasets:

brien18
/

global-emigration-dataset

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 ({'field_name', 'dataset', 'unit', 'example_value', 'description', 'data_type'}) and 8 missing columns ({'country', 'city', 'rent_1br_periphery_eur', 'monthly_cost_single_eur', 'rent_1br_center_eur', 'currency', 'monthly_cost_family_eur', 'tier'}).

This happened while the csv dataset builder was generating data using

hf://datasets/brien18/global-emigration-dataset/data-dictionary.csv (at revision 1564e58a05aa5a5ca092ec8c4fa4bb4ba0218e1c), ['hf://datasets/brien18/global-emigration-dataset@1564e58a05aa5a5ca092ec8c4fa4bb4ba0218e1c/cost-of-living-global-2026.csv', 'hf://datasets/brien18/global-emigration-dataset@1564e58a05aa5a5ca092ec8c4fa4bb4ba0218e1c/data-dictionary.csv', 'hf://datasets/brien18/global-emigration-dataset@1564e58a05aa5a5ca092ec8c4fa4bb4ba0218e1c/digital-nomad-visas-2026.csv', 'hf://datasets/brien18/global-emigration-dataset@1564e58a05aa5a5ca092ec8c4fa4bb4ba0218e1c/easiest-countries-2026.csv', 'hf://datasets/brien18/global-emigration-dataset@1564e58a05aa5a5ca092ec8c4fa4bb4ba0218e1c/immigration-pathways-by-category-2026.csv', 'hf://datasets/brien18/global-emigration-dataset@1564e58a05aa5a5ca092ec8c4fa4bb4ba0218e1c/quality-of-life-global-2026.csv', 'hf://datasets/brien18/global-emigration-dataset@1564e58a05aa5a5ca092ec8c4fa4bb4ba0218e1c/salary-by-profession-global-2026.csv', 'hf://datasets/brien18/global-emigration-dataset@1564e58a05aa5a5ca092ec8c4fa4bb4ba0218e1c/visa-processing-times-2026.csv', 'hf://datasets/brien18/global-emigration-dataset@1564e58a05aa5a5ca092ec8c4fa4bb4ba0218e1c/visa-thresholds-global-2026.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
              dataset: string
              field_name: string
              data_type: string
              description: string
              unit: string
              example_value: string
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 986
              to
              {'country': Value('string'), 'tier': Value('int64'), 'currency': Value('string'), 'city': Value('string'), 'monthly_cost_single_eur': Value('int64'), 'monthly_cost_family_eur': Value('int64'), 'rent_1br_center_eur': Value('int64'), 'rent_1br_periphery_eur': Value('int64')}
              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 ({'field_name', 'dataset', 'unit', 'example_value', 'description', 'data_type'}) and 8 missing columns ({'country', 'city', 'rent_1br_periphery_eur', 'monthly_cost_single_eur', 'rent_1br_center_eur', 'currency', 'monthly_cost_family_eur', 'tier'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/brien18/global-emigration-dataset/data-dictionary.csv (at revision 1564e58a05aa5a5ca092ec8c4fa4bb4ba0218e1c), ['hf://datasets/brien18/global-emigration-dataset@1564e58a05aa5a5ca092ec8c4fa4bb4ba0218e1c/cost-of-living-global-2026.csv', 'hf://datasets/brien18/global-emigration-dataset@1564e58a05aa5a5ca092ec8c4fa4bb4ba0218e1c/data-dictionary.csv', 'hf://datasets/brien18/global-emigration-dataset@1564e58a05aa5a5ca092ec8c4fa4bb4ba0218e1c/digital-nomad-visas-2026.csv', 'hf://datasets/brien18/global-emigration-dataset@1564e58a05aa5a5ca092ec8c4fa4bb4ba0218e1c/easiest-countries-2026.csv', 'hf://datasets/brien18/global-emigration-dataset@1564e58a05aa5a5ca092ec8c4fa4bb4ba0218e1c/immigration-pathways-by-category-2026.csv', 'hf://datasets/brien18/global-emigration-dataset@1564e58a05aa5a5ca092ec8c4fa4bb4ba0218e1c/quality-of-life-global-2026.csv', 'hf://datasets/brien18/global-emigration-dataset@1564e58a05aa5a5ca092ec8c4fa4bb4ba0218e1c/salary-by-profession-global-2026.csv', 'hf://datasets/brien18/global-emigration-dataset@1564e58a05aa5a5ca092ec8c4fa4bb4ba0218e1c/visa-processing-times-2026.csv', 'hf://datasets/brien18/global-emigration-dataset@1564e58a05aa5a5ca092ec8c4fa4bb4ba0218e1c/visa-thresholds-global-2026.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.

country string	tier int64	currency string	city string	monthly_cost_single_eur int64	monthly_cost_family_eur int64	rent_1br_center_eur int64	rent_1br_periphery_eur int64
Canada	1	CAD	Toronto	2,590	4,850	1,551	1,346
Canada	1	CAD	Vancouver	2,690	5,050	1,781	1,488
Canada	1	CAD	Montreal	2,000	3,850	1,181	886
Australia	1	AUD	Sydney	3,140	5,650	2,072	1,447
Australia	1	AUD	Melbourne	2,503	4,800	1,475	1,096
Australia	1	AUD	Brisbane	2,448	4,550	1,565	1,130
Germany	1	EUR	Berlin	2,200	4,100	1,232	850
Germany	1	EUR	Munich	2,536	4,650	1,467	1,080
Germany	1	EUR	Hamburg	2,090	3,950	1,085	780
Portugal	1	EUR	Lisbon	2,180	3,800	1,429	1,001
Portugal	1	EUR	Porto	1,750	3,200	1,043	750
Portugal	1	EUR	Faro	1,500	2,800	850	650
United Kingdom	1	GBP	London	3,977	6,800	2,734	2,029
United Kingdom	1	GBP	Manchester	2,340	4,200	1,287	936
United Kingdom	1	GBP	Edinburgh	2,340	4,250	1,287	936
Netherlands	1	EUR	Amsterdam	3,133	5,400	2,030	1,500
Netherlands	1	EUR	Rotterdam	2,350	4,200	1,447	1,100
Netherlands	1	EUR	The Hague	2,480	4,350	1,600	1,150
New Zealand	2	NZD	Auckland	2,200	4,100	1,485	1,045
New Zealand	2	NZD	Wellington	2,090	3,900	1,375	990
New Zealand	2	NZD	Christchurch	1,870	3,550	1,100	825
Spain	2	EUR	Madrid	2,250	3,900	1,400	950
Spain	2	EUR	Barcelona	2,350	4,050	1,450	1,000
Spain	2	EUR	Valencia	1,700	3,100	1,025	720
UAE	2	AED	Dubai	3,093	5,600	2,143	1,322
UAE	2	AED	Abu Dhabi	2,325	4,400	1,375	950
UAE	2	AED	Sharjah	1,650	3,200	825	575
Ireland	2	EUR	Dublin	3,043	5,400	2,500	1,900
Ireland	2	EUR	Cork	2,595	4,600	2,000	1,500
Ireland	2	EUR	Galway	2,514	4,400	1,850	1,400
Sweden	2	SEK	Stockholm	2,578	4,650	1,403	910
Sweden	2	SEK	Gothenburg	1,938	3,700	1,056	748
Sweden	2	SEK	Malmö	1,707	3,350	880	660
Switzerland	2	CHF	Zurich	4,070	7,200	2,430	1,854
Switzerland	2	CHF	Geneva	3,780	6,700	2,200	1,680
Switzerland	2	CHF	Basel	3,400	6,100	1,890	1,470
Thailand	3	THB	Bangkok	1,170	2,400	574	283
Thailand	3	THB	Chiang Mai	858	1,750	364	208
Thailand	3	THB	Phuket	1,144	2,250	520	312
Mexico	3	MXN	Mexico City	1,150	2,300	690	460
Mexico	3	MXN	Guadalajara	880	1,850	460	300
Mexico	3	MXN	Playa del Carmen	1,200	2,350	644	414
Japan	3	JPY	Tokyo	1,930	3,800	1,123	621
Japan	3	JPY	Osaka	1,500	3,050	793	488
Japan	3	JPY	Fukuoka	1,250	2,600	610	366
Estonia	3	EUR	Tallinn	1,594	3,000	695	500
Estonia	3	EUR	Tartu	1,383	2,650	600	420
Estonia	3	EUR	Pärnu	1,200	2,350	480	350
Singapore	3	SGD	Singapore	3,426	6,200	2,438	1,808
Costa Rica	3	USD	San José	1,290	2,500	644	460
Costa Rica	3	USD	Tamarindo	1,750	3,200	1,334	920
Costa Rica	3	USD	Puerto Viejo	1,150	2,200	552	368
Malaysia	3	MYR	Kuala Lumpur	1,100	2,200	580	370
Malaysia	3	MYR	Penang	850	1,750	393	258
Malaysia	3	MYR	Johor Bahru	920	1,850	428	300
Panama	3	USD	Panama City	1,520	2,900	920	598
Panama	3	USD	David	1,050	2,050	552	368
Panama	3	USD	Boquete	1,200	2,250	694	460
Austria	3	EUR	Vienna	2,100	3,900	1,100	780
Austria	3	EUR	Graz	1,805	3,400	750	550
Austria	3	EUR	Salzburg	2,186	4,000	1,150	850
Chile	3	CLP	Santiago	1,300	2,600	650	430
Chile	3	CLP	Valparaíso	1,050	2,150	460	320
Chile	3	CLP	Concepción	990	2,000	400	280
Czech Republic	3	CZK	Prague	1,881	3,500	1,028	855
Czech Republic	3	CZK	Brno	1,500	2,900	720	560
Czech Republic	3	CZK	Ostrava	1,250	2,500	520	400
Denmark	3	DKK	Copenhagen	2,929	5,200	1,772	1,198
Denmark	3	DKK	Aarhus	2,285	4,200	1,340	938
Denmark	3	DKK	Odense	2,110	3,900	1,140	804
South Korea	3	KRW	Seoul	1,764	3,500	858	553
South Korea	3	KRW	Busan	1,380	2,800	621	414
South Korea	3	KRW	Incheon	1,400	2,850	635	428
Uruguay	3	UYU	Montevideo	1,380	2,700	600	425
Uruguay	3	UYU	Punta del Este	1,750	3,300	920	644
Uruguay	3	UYU	Colonia	1,100	2,200	460	322
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End of preview.

Global Emigration Intelligence Dataset (2026)

Open data from WhereToEmigrate.io — a visa-intelligence engine tracking 2,500+ visa and residency pathways across 190+ countries, each linked to an official government source.

Files

File	Contents
`easiest-countries-2026.csv`	Countries ranked by accessible visa pathways (open to all, no job offer, no investment)
`digital-nomad-visas-2026.csv`	Every tracked digital-nomad visa: income thresholds, PR routes
`visa-processing-times-2026.csv`	Published processing times per pathway
`immigration-pathways-by-category-2026.csv`	Open pathways by category
`visa-thresholds-global-2026.csv`	Minimum income/savings thresholds by programme
`cost-of-living-global-2026.csv`	Cost-of-living context by country
`salary-by-profession-global-2026.csv`	Salary context by profession
`quality-of-life-global-2026.csv`	Quality-of-life indices
`data-dictionary.csv`	Column definitions

Methodology

Figures are computed from the WhereToEmigrate pathway database (snapshot: July 2026). Collection and verification methodology: https://wheretoemigrate.io/methodology — values are directional; always verify with the official government source linked per pathway before acting.

License & citation

CC BY 4.0 — free to use, share and adapt with attribution:

Source: WhereToEmigrate — Emigration Research

Updates

Refreshed quarterly. Latest version + more studies: https://wheretoemigrate.io/research/datasets

Downloads last month: 46

Total file size:

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