📊 wid: Update World Inequality Database (Nov 2024 release) #3569
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data-diff:= Dataset garden/antibiotics/2024-11-15/testing_coverage
= Table testing_coverage
⚠ Error: Index must be unique.
= Dataset garden/artificial_intelligence/2023-06-14/ai_deepfakes
= Table ai_deepfakes
⚠ Error: Index must be unique.
⚠ Error: Index must be unique.
= Dataset garden/artificial_intelligence/2024-11-03/epoch_aggregates_domain
= Table epoch_aggregates_domain
~ Column cumulative_count (changed metadata)
- - Describes the specific area, application, or field in which an AI system is designed to operate. An AI system can operate in more than one domain, thus contributing to the count for multiple domains. The 2024 data is incomplete and was last updated 03 November 2024.
? ^^
+ + Describes the specific area, application, or field in which an AI system is designed to operate. An AI system can operate in more than one domain, thus contributing to the count for multiple domains. The 2024 data is incomplete and was last updated 6 November 2024.
? ^
~ Column yearly_count (changed metadata)
- - Describes the specific area, application, or field in which an AI system is designed to operate. An AI system can operate in more than one domain, thus contributing to the count for multiple domains. The 2024 data is incomplete and was last updated 03 November 2024.
? ^^
+ + Describes the specific area, application, or field in which an AI system is designed to operate. An AI system can operate in more than one domain, thus contributing to the count for multiple domains. The 2024 data is incomplete and was last updated 6 November 2024.
? ^
= Dataset garden/artificial_intelligence/2024-11-03/epoch_compute_intensive_countries
= Table epoch_compute_intensive_countries
~ Column cumulative_count (changed metadata)
- - Refers to the location of the primary organization with which the authors of a large-scale AI systems are affiliated. The 2024 data is incomplete and was last updated 03 November 2024.
? ^^
+ + Refers to the location of the primary organization with which the authors of a large-scale AI systems are affiliated. The 2024 data is incomplete and was last updated 6 November 2024.
? ^
~ Column yearly_count (changed metadata)
- - Refers to the location of the primary organization with which the authors of a large-scale AI systems are affiliated. The 2024 data is incomplete and was last updated 03 November 2024.
? ^^
+ + Refers to the location of the primary organization with which the authors of a large-scale AI systems are affiliated. The 2024 data is incomplete and was last updated 6 November 2024.
? ^
= Dataset garden/artificial_intelligence/2024-11-03/epoch_compute_intensive_domain
= Table epoch_compute_intensive_domain
~ Column cumulative_count (changed metadata)
- - Describes the specific area, application, or field in which a large-scale AI model is designed to operate. The 2024 data is incomplete and was last updated 03 November 2024.
? ^^
+ + Describes the specific area, application, or field in which a large-scale AI model is designed to operate. The 2024 data is incomplete and was last updated 6 November 2024.
? ^
~ Column yearly_count (changed metadata)
- - Describes the specific area, application, or field in which a large-scale AI model is designed to operate. The 2024 data is incomplete and was last updated 03 November 2024.
? ^^
+ + Describes the specific area, application, or field in which a large-scale AI model is designed to operate. The 2024 data is incomplete and was last updated 6 November 2024.
? ^
= Dataset garden/faostat/2024-03-14/faostat_fa
= Table faostat_fa
= Table faostat_fa_flat
2024-11-20 08:07:55 [warning ] DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` category=PerformanceWarning filename=/home/owid/etl/lib/catalog/owid/catalog/tables.py lineno=405
2024-11-20 08:08:59 [warning ] DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` category=PerformanceWarning filename=/home/owid/etl/lib/catalog/owid/catalog/tables.py lineno=405
2024-11-20 08:15:31 [warning ] DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` category=PerformanceWarning filename=/home/owid/etl/lib/catalog/owid/catalog/tables.py lineno=405
2024-11-20 08:15:59 [warning ] DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` category=PerformanceWarning filename=/home/owid/etl/lib/catalog/owid/catalog/tables.py lineno=405
= Dataset garden/lis/2024-06-13/luxembourg_income_study
= Table lis_percentiles_adults
= Table lis_percentiles
= Table luxembourg_income_study_adults
= Table luxembourg_income_study
⚠ Error: Index must be unique.
= Dataset garden/un/2022-07-11/un_wpp
= Table migration
= Table fertility
= Table demographic
= Table population
= Table un_wpp
= Table mortality
= Table population_granular
~ Column value (changed data)
~ Changed values: 1391 / 39815008 (0.00%)
location year metric sex age variant value - value +
Tokelau 2047 sex_ratio none 91 high <NA> inf
Tokelau 2046 sex_ratio none 91 low <NA> inf
Western Sahara 1967 sex_ratio none 95 medium <NA> inf
Falkland Islands 1957 sex_ratio none 89 medium <NA> inf
Tokelau 2033 sex_ratio none 78 medium <NA> inf
= Dataset garden/who/2023-11-01/who_statins
= Table who_statins
2024-11-20 08:30:48 [error ] Traceback (most recent call last):
File "/home/owid/etl/.venv/lib/python3.10/site-packages/requests/models.py", line 974, in json
return complexjson.loads(self.text, **kwargs)
File "/home/owid/etl/.venv/lib/python3.10/site-packages/simplejson/__init__.py", line 514, in loads
return _default_decoder.decode(s)
File "/home/owid/etl/.venv/lib/python3.10/site-packages/simplejson/decoder.py", line 386, in decode
obj, end = self.raw_decode(s)
File "/home/owid/etl/.venv/lib/python3.10/site-packages/simplejson/decoder.py", line 416, in raw_decode
return self.scan_once(s, idx=_w(s, idx).end())
simplejson.errors.JSONDecodeError: Expecting value: line 1 column 1 (char 0)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/owid/etl/etl/datadiff.py", line 429, in cli
lines = future.result()
File "/usr/lib/python3.10/concurrent/futures/_base.py", line 458, in result
return self.__get_result()
File "/usr/lib/python3.10/concurrent/futures/_base.py", line 403, in __get_result
raise self._exception
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
result = self.fn(*self.args, **self.kwargs)
File "/home/owid/etl/etl/datadiff.py", line 422, in func
differ.summary()
File "/home/owid/etl/etl/datadiff.py", line 260, in summary
self._diff_tables(self.ds_a, self.ds_b, table_name)
File "/home/owid/etl/etl/datadiff.py", line 122, in _diff_tables
table_a = future_a.result()
File "/usr/lib/python3.10/concurrent/futures/_base.py", line 458, in result
return self.__get_result()
File "/usr/lib/python3.10/concurrent/futures/_base.py", line 403, in __get_result
raise self._exception
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
result = self.fn(*self.args, **self.kwargs)
File "/home/owid/etl/.venv/lib/python3.10/site-packages/tenacity/__init__.py", line 336, in wrapped_f
return copy(f, *args, **kw)
File "/home/owid/etl/.venv/lib/python3.10/site-packages/tenacity/__init__.py", line 475, in __call__
do = self.iter(retry_state=retry_state)
File "/home/owid/etl/.venv/lib/python3.10/site-packages/tenacity/__init__.py", line 376, in iter
result = action(retry_state)
File "/home/owid/etl/.venv/lib/python3.10/site-packages/tenacity/__init__.py", line 398, in <lambda>
self._add_action_func(lambda rs: rs.outcome.result())
File "/usr/lib/python3.10/concurrent/futures/_base.py", line 451, in result
return self.__get_result()
File "/usr/lib/python3.10/concurrent/futures/_base.py", line 403, in __get_result
raise self._exception
File "/home/owid/etl/.venv/lib/python3.10/site-packages/tenacity/__init__.py", line 478, in __call__
result = fn(*args, **kwargs)
File "/home/owid/etl/etl/datadiff.py", line 843, in get_table_with_retry
return ds[table_name]
File "/home/owid/etl/etl/datadiff.py", line 284, in __getitem__
return tables.load()
File "/home/owid/etl/lib/catalog/owid/catalog/catalogs.py", line 312, in load
return self.iloc[0].load() # type: ignore
File "/home/owid/etl/lib/catalog/owid/catalog/catalogs.py", line 363, in load
return Table.read(uri)
File "/home/owid/etl/lib/catalog/owid/catalog/tables.py", line 179, in read
table = cls.read_feather(path, **kwargs)
File "/home/owid/etl/lib/catalog/owid/catalog/tables.py", line 365, in read_feather
cls._add_metadata(df, path, **kwargs)
File "/home/owid/etl/lib/catalog/owid/catalog/tables.py", line 337, in _add_metadata
metadata = cls._read_metadata(path)
File "/home/owid/etl/lib/catalog/owid/catalog/tables.py", line 399, in _read_metadata
return cast(Dict[str, Any], requests.get(metadata_path).json())
File "/home/owid/etl/.venv/lib/python3.10/site-packages/requests/models.py", line 978, in json
raise RequestsJSONDecodeError(e.msg, e.doc, e.pos)
requests.exceptions.JSONDecodeError: Expecting value: line 1 column 1 (char 0)
= Dataset garden/who/2024-09-09/flu_test
= Table flu_test
~ Dim country
- - Removed values: 10 / 72188 (0.01%)
date country
2024-11-04 Hong Kong
2024-11-04 Iran
2024-11-04 Japan
2024-11-04 Pakistan
2024-11-04 Sri Lanka
~ Dim date
- - Removed values: 10 / 72188 (0.01%)
country date
Hong Kong 2024-11-04
Iran 2024-11-04
Japan 2024-11-04
Pakistan 2024-11-04
Sri Lanka 2024-11-04
~ Column denomcombined (changed data)
- - Removed values: 10 / 72188 (0.01%)
country date denomcombined
Hong Kong 2024-11-04 6674
Iran 2024-11-04 1822
Japan 2024-11-04 5
Pakistan 2024-11-04 347
Sri Lanka 2024-11-04 76
~ Changed values: 21 / 72188 (0.03%)
country date denomcombined - denomcombined +
Japan 2024-07-01 31 30
Japan 2024-09-09 41 38
Japan 2024-09-30 49 44
Japan 2024-10-14 19 15
Sri Lanka 2024-10-28 57 56
~ Column pcnt_poscombined (changed data)
- - Removed values: 10 / 72188 (0.01%)
country date pcnt_poscombined
Hong Kong 2024-11-04 0.569374
Iran 2024-11-04 10.153677
Japan 2024-11-04 80.0
Pakistan 2024-11-04 6.051873
Sri Lanka 2024-11-04 9.210526
~ Changed values: 21 / 72188 (0.03%)
country date pcnt_poscombined - pcnt_poscombined +
Japan 2024-07-01 38.709679 40.000000
Japan 2024-09-09 65.853661 65.789474
Japan 2024-09-30 75.510201 75.000000
Japan 2024-10-14 73.684212 80.000000
Sri Lanka 2024-10-28 14.035088 12.500000
+ Dataset garden/wid/2024-11-19/world_inequality_database
+ + Table world_inequality_database
+ + Column p0p100_gini_pretax
+ + Column p0p100_gini_posttax_dis
+ + Column p0p100_gini_posttax_nat
+ + Column p0p100_gini_wealth
+ + Column palma_ratio_pretax
+ + Column s80_s20_ratio_pretax
+ + Column p90_p10_ratio_pretax
+ + Column p90_p50_ratio_pretax
+ + Column p50_p10_ratio_pretax
+ + Column palma_ratio_posttax_dis
+ + Column s80_s20_ratio_posttax_dis
+ + Column p90_p10_ratio_posttax_dis
+ + Column p90_p50_ratio_posttax_dis
+ + Column p50_p10_ratio_posttax_dis
+ + Column palma_ratio_posttax_nat
+ + Column s80_s20_ratio_posttax_nat
+ + Column p90_p10_ratio_posttax_nat
+ + Column p90_p50_ratio_posttax_nat
+ + Column p50_p10_ratio_posttax_nat
+ + Column palma_ratio_wealth
+ + Column s80_s20_ratio_wealth
+ + Column p90_p10_ratio_wealth
+ + Column p90_p50_ratio_wealth
+ + Column p50_p10_ratio_wealth
+ + Column p0p10_share_pretax
+ + Column p0p50_share_pretax
+ + Column p10p20_share_pretax
+ + Column p20p30_share_pretax
+ + Column p30p40_share_pretax
+ + Column p40p50_share_pretax
+ + Column p50p60_share_pretax
+ + Column p60p70_share_pretax
+ + Column p70p80_share_pretax
+ + Column p80p90_share_pretax
+ + Column p90p100_share_pretax
+ + Column p99_999p100_share_pretax
+ + Column p99_99p100_share_pretax
+ + Column p99_9p100_share_pretax
+ + Column p99p100_share_pretax
+ + Column p90p99_share_pretax
+ + Column p50p90_share_pretax
+ + Column p0p10_share_posttax_dis
+ + Column p0p50_share_posttax_dis
+ + Column p10p20_share_posttax_dis
+ + Column p20p30_share_posttax_dis
+ + Column p30p40_share_posttax_dis
+ + Column p40p50_share_posttax_dis
+ + Column p50p60_share_posttax_dis
+ + Column p60p70_share_posttax_dis
+ + Column p70p80_share_posttax_dis
+ + Column p80p90_share_posttax_dis
+ + Column p90p100_share_posttax_dis
+ + Column p99_999p100_share_posttax_dis
+ + Column p99_99p100_share_posttax_dis
+ + Column p99_9p100_share_posttax_dis
+ + Column p99p100_share_posttax_dis
+ + Column p90p99_share_posttax_dis
+ + Column p50p90_share_posttax_dis
+ + Column p0p10_share_posttax_nat
+ + Column p0p50_share_posttax_nat
+ + Column p10p20_share_posttax_nat
+ + Column p20p30_share_posttax_nat
+ + Column p30p40_share_posttax_nat
+ + Column p40p50_share_posttax_nat
+ + Column p50p60_share_posttax_nat
+ + Column p60p70_share_posttax_nat
+ + Column p70p80_share_posttax_nat
+ + Column p80p90_share_posttax_nat
+ + Column p90p100_share_posttax_nat
+ + Column p99_999p100_share_posttax_nat
+ + Column p99_99p100_share_posttax_nat
+ + Column p99_9p100_share_posttax_nat
+ + Column p99p100_share_posttax_nat
+ + Column p90p99_share_posttax_nat
+ + Column p50p90_share_posttax_nat
+ + Column p0p10_share_wealth
+ + Column p0p50_share_wealth
+ + Column p10p20_share_wealth
+ + Column p20p30_share_wealth
+ + Column p30p40_share_wealth
+ + Column p40p50_share_wealth
+ + Column p50p60_share_wealth
+ + Column p60p70_share_wealth
+ + Column p70p80_share_wealth
+ + Column p80p90_share_wealth
+ + Column p90p100_share_wealth
+ + Column p99_999p100_share_wealth
+ + Column p99_99p100_share_wealth
+ + Column p99_9p100_share_wealth
+ + Column p99p100_share_wealth
+ + Column p90p99_share_wealth
+ + Column p50p90_share_wealth
+ + Column p0p100_avg_pretax
+ + Column p0p10_avg_pretax
+ + Column p10p20_avg_pretax
+ + Column p20p30_avg_pretax
+ + Column p30p40_avg_pretax
+ + Column p40p50_avg_pretax
+ + Column p50p60_avg_pretax
+ + Column p60p70_avg_pretax
+ + Column p70p80_avg_pretax
+ + Column p80p90_avg_pretax
+ + Column p90p100_avg_pretax
+ + Column p99_999p100_avg_pretax
+ + Column p99_99p100_avg_pretax
+ + Column p99_9p100_avg_pretax
+ + Column p99p100_avg_pretax
+ + Column p0p100_avg_posttax_dis
+ + Column p0p10_avg_posttax_dis
+ + Column p10p20_avg_posttax_dis
+ + Column p20p30_avg_posttax_dis
+ + Column p30p40_avg_posttax_dis
+ + Column p40p50_avg_posttax_dis
+ + Column p50p60_avg_posttax_dis
+ + Column p60p70_avg_posttax_dis
+ + Column p70p80_avg_posttax_dis
+ + Column p80p90_avg_posttax_dis
+ + Column p90p100_avg_posttax_dis
+ + Column p99_999p100_avg_posttax_dis
+ + Column p99_99p100_avg_posttax_dis
+ + Column p99_9p100_avg_posttax_dis
+ + Column p99p100_avg_posttax_dis
+ + Column p0p100_avg_posttax_nat
+ + Column p0p10_avg_posttax_nat
+ + Column p10p20_avg_posttax_nat
+ + Column p20p30_avg_posttax_nat
+ + Column p30p40_avg_posttax_nat
+ + Column p40p50_avg_posttax_nat
+ + Column p50p60_avg_posttax_nat
+ + Column p60p70_avg_posttax_nat
+ + Column p70p80_avg_posttax_nat
+ + Column p80p90_avg_posttax_nat
+ + Column p90p100_avg_posttax_nat
+ + Column p99_999p100_avg_posttax_nat
+ + Column p99_99p100_avg_posttax_nat
+ + Column p99_9p100_avg_posttax_nat
+ + Column p99p100_avg_posttax_nat
+ + Column p0p100_avg_wealth
+ + Column p0p10_avg_wealth
+ + Column p10p20_avg_wealth
+ + Column p20p30_avg_wealth
+ + Column p30p40_avg_wealth
+ + Column p40p50_avg_wealth
+ + Column p50p60_avg_wealth
+ + Column p60p70_avg_wealth
+ + Column p70p80_avg_wealth
+ + Column p80p90_avg_wealth
+ + Column p90p100_avg_wealth
+ + Column p99_999p100_avg_wealth
+ + Column p99_99p100_avg_wealth
+ + Column p99_9p100_avg_wealth
+ + Column p99p100_avg_wealth
+ + Column p0p10_thr_pretax
+ + Column p10p20_thr_pretax
+ + Column p20p30_thr_pretax
+ + Column p30p40_thr_pretax
+ + Column p40p50_thr_pretax
+ + Column p50p60_thr_pretax
+ + Column p60p70_thr_pretax
+ + Column p70p80_thr_pretax
+ + Column p80p90_thr_pretax
+ + Column p90p100_thr_pretax
+ + Column p99_999p100_thr_pretax
+ + Column p99_99p100_thr_pretax
+ + Column p99_9p100_thr_pretax
+ + Column p99p100_thr_pretax
+ + Column p0p10_thr_posttax_dis
+ + Column p10p20_thr_posttax_dis
+ + Column p20p30_thr_posttax_dis
+ + Column p30p40_thr_posttax_dis
+ + Column p40p50_thr_posttax_dis
+ + Column p50p60_thr_posttax_dis
+ + Column p60p70_thr_posttax_dis
+ + Column p70p80_thr_posttax_dis
+ + Column p80p90_thr_posttax_dis
+ + Column p90p100_thr_posttax_dis
+ + Column p99_999p100_thr_posttax_dis
+ + Column p99_99p100_thr_posttax_dis
+ + Column p99_9p100_thr_posttax_dis
+ + Column p99p100_thr_posttax_dis
+ + Column p0p10_thr_posttax_nat
+ + Column p10p20_thr_posttax_nat
+ + Column p20p30_thr_posttax_nat
+ + Column p30p40_thr_posttax_nat
+ + Column p40p50_thr_posttax_nat
+ + Column p50p60_thr_posttax_nat
+ + Column p60p70_thr_posttax_nat
+ + Column p70p80_thr_posttax_nat
+ + Column p80p90_thr_posttax_nat
+ + Column p90p100_thr_posttax_nat
+ + Column p99_999p100_thr_posttax_nat
+ + Column p99_99p100_thr_posttax_nat
+ + Column p99_9p100_thr_posttax_nat
+ + Column p99p100_thr_posttax_nat
+ + Column p0p10_thr_wealth
+ + Column p10p20_thr_wealth
+ + Column p20p30_thr_wealth
+ + Column p30p40_thr_wealth
+ + Column p40p50_thr_wealth
+ + Column p50p60_thr_wealth
+ + Column p60p70_thr_wealth
+ + Column p70p80_thr_wealth
+ + Column p80p90_thr_wealth
+ + Column p90p100_thr_wealth
+ + Column p99_999p100_thr_wealth
+ + Column p99_99p100_thr_wealth
+ + Column p99_9p100_thr_wealth
+ + Column p99p100_thr_wealth
+ + Column median_pretax
+ + Column median_posttax_nat
+ + Column median_posttax_dis
+ + Column median_wealth
+ + Column p0p100_gini_pretax_extrapolated
+ + Column p0p100_gini_posttax_dis_extrapolated
+ + Column p0p100_gini_posttax_nat_extrapolated
+ + Column p0p100_gini_wealth_extrapolated
+ + Column palma_ratio_pretax_extrapolated
+ + Column s80_s20_ratio_pretax_extrapolated
+ + Column p90_p10_ratio_pretax_extrapolated
+ + Column p90_p50_ratio_pretax_extrapolated
+ + Column p50_p10_ratio_pretax_extrapolated
+ + Column palma_ratio_posttax_dis_extrapolated
+ + Column s80_s20_ratio_posttax_dis_extrapolated
+ + Column p90_p10_ratio_posttax_dis_extrapolated
+ + Column p90_p50_ratio_posttax_dis_extrapolated
+ + Column p50_p10_ratio_posttax_dis_extrapolated
+ + Column palma_ratio_posttax_nat_extrapolated
+ + Column s80_s20_ratio_posttax_nat_extrapolated
+ + Column p90_p10_ratio_posttax_nat_extrapolated
+ + Column p90_p50_ratio_posttax_nat_extrapolated
+ + Column p50_p10_ratio_posttax_nat_extrapolated
+ + Column palma_ratio_wealth_extrapolated
+ + Column s80_s20_ratio_wealth_extrapolated
+ + Column p90_p10_ratio_wealth_extrapolated
+ + Column p90_p50_ratio_wealth_extrapolated
+ + Column p50_p10_ratio_wealth_extrapolated
+ + Column p0p10_share_pretax_extrapolated
+ + Column p0p50_share_pretax_extrapolated
+ + Column p10p20_share_pretax_extrapolated
+ + Column p20p30_share_pretax_extrapolated
+ + Column p30p40_share_pretax_extrapolated
+ + Column p40p50_share_pretax_extrapolated
+ + Column p50p60_share_pretax_extrapolated
+ + Column p60p70_share_pretax_extrapolated
+ + Column p70p80_share_pretax_extrapolated
+ + Column p80p90_share_pretax_extrapolated
+ + Column p90p100_share_pretax_extrapolated
+ + Column p99_999p100_share_pretax_extrapolated
+ + Column p99_99p100_share_pretax_extrapolated
+ + Column p99_9p100_share_pretax_extrapolated
+ + Column p99p100_share_pretax_extrapolated
+ + Column p90p99_share_pretax_extrapolated
+ + Column p50p90_share_pretax_extrapolated
+ + Column p0p10_share_posttax_dis_extrapolated
+ + Column p0p50_share_posttax_dis_extrapolated
+ + Column p10p20_share_posttax_dis_extrapolated
+ + Column p20p30_share_posttax_dis_extrapolated
+ + Column p30p40_share_posttax_dis_extrapolated
+ + Column p40p50_share_posttax_dis_extrapolated
+ + Column p50p60_share_posttax_dis_extrapolated
+ + Column p60p70_share_posttax_dis_extrapolated
+ + Column p70p80_share_posttax_dis_extrapolated
+ + Column p80p90_share_posttax_dis_extrapolated
+ + Column p90p100_share_posttax_dis_extrapolated
+ + Column p99_999p100_share_posttax_dis_extrapolated
+ + Column p99_99p100_share_posttax_dis_extrapolated
+ + Column p99_9p100_share_posttax_dis_extrapolated
+ + Column p99p100_share_posttax_dis_extrapolated
+ + Column p90p99_share_posttax_dis_extrapolated
+ + Column p50p90_share_posttax_dis_extrapolated
+ + Column p0p10_share_posttax_nat_extrapolated
+ + Column p0p50_share_posttax_nat_extrapolated
+ + Column p10p20_share_posttax_nat_extrapolated
+ + Column p20p30_share_posttax_nat_extrapolated
+ + Column p30p40_share_posttax_nat_extrapolated
+ + Column p40p50_share_posttax_nat_extrapolated
+ + Column p50p60_share_posttax_nat_extrapolated
+ + Column p60p70_share_posttax_nat_extrapolated
+ + Column p70p80_share_posttax_nat_extrapolated
+ + Column p80p90_share_posttax_nat_extrapolated
+ + Column p90p100_share_posttax_nat_extrapolated
+ + Column p99_999p100_share_posttax_nat_extrapolated
+ + Column p99_99p100_share_posttax_nat_extrapolated
+ + Column p99_9p100_share_posttax_nat_extrapolated
+ + Column p99p100_share_posttax_nat_extrapolated
+ + Column p90p99_share_posttax_nat_extrapolated
+ + Column p50p90_share_posttax_nat_extrapolated
+ + Column p0p10_share_wealth_extrapolated
+ + Column p0p50_share_wealth_extrapolated
+ + Column p10p20_share_wealth_extrapolated
+ + Column p20p30_share_wealth_extrapolated
+ + Column p30p40_share_wealth_extrapolated
+ + Column p40p50_share_wealth_extrapolated
+ + Column p50p60_share_wealth_extrapolated
+ + Column p60p70_share_wealth_extrapolated
+ + Column p70p80_share_wealth_extrapolated
+ + Column p80p90_share_wealth_extrapolated
+ + Column p90p100_share_wealth_extrapolated
+ + Column p99_999p100_share_wealth_extrapolated
+ + Column p99_99p100_share_wealth_extrapolated
+ + Column p99_9p100_share_wealth_extrapolated
+ + Column p99p100_share_wealth_extrapolated
+ + Column p90p99_share_wealth_extrapolated
+ + Column p50p90_share_wealth_extrapolated
+ + Column p0p100_avg_pretax_extrapolated
+ + Column p0p10_avg_pretax_extrapolated
+ + Column p10p20_avg_pretax_extrapolated
+ + Column p20p30_avg_pretax_extrapolated
+ + Column p30p40_avg_pretax_extrapolated
+ + Column p40p50_avg_pretax_extrapolated
+ + Column p50p60_avg_pretax_extrapolated
+ + Column p60p70_avg_pretax_extrapolated
+ + Column p70p80_avg_pretax_extrapolated
+ + Column p80p90_avg_pretax_extrapolated
+ + Column p90p100_avg_pretax_extrapolated
+ + Column p99_999p100_avg_pretax_extrapolated
+ + Column p99_99p100_avg_pretax_extrapolated
+ + Column p99_9p100_avg_pretax_extrapolated
+ + Column p99p100_avg_pretax_extrapolated
+ + Column p0p100_avg_posttax_dis_extrapolated
+ + Column p0p10_avg_posttax_dis_extrapolated
+ + Column p10p20_avg_posttax_dis_extrapolated
+ + Column p20p30_avg_posttax_dis_extrapolated
+ + Column p30p40_avg_posttax_dis_extrapolated
+ + Column p40p50_avg_posttax_dis_extrapolated
+ + Column p50p60_avg_posttax_dis_extrapolated
+ + Column p60p70_avg_posttax_dis_extrapolated
+ + Column p70p80_avg_posttax_dis_extrapolated
+ + Column p80p90_avg_posttax_dis_extrapolated
+ + Column p90p100_avg_posttax_dis_extrapolated
+ + Column p99_999p100_avg_posttax_dis_extrapolated
+ + Column p99_99p100_avg_posttax_dis_extrapolated
+ + Column p99_9p100_avg_posttax_dis_extrapolated
+ + Column p99p100_avg_posttax_dis_extrapolated
+ + Column p0p100_avg_posttax_nat_extrapolated
+ + Column p0p10_avg_posttax_nat_extrapolated
+ + Column p10p20_avg_posttax_nat_extrapolated
+ + Column p20p30_avg_posttax_nat_extrapolated
+ + Column p30p40_avg_posttax_nat_extrapolated
+ + Column p40p50_avg_posttax_nat_extrapolated
+ + Column p50p60_avg_posttax_nat_extrapolated
+ + Column p60p70_avg_posttax_nat_extrapolated
+ + Column p70p80_avg_posttax_nat_extrapolated
+ + Column p80p90_avg_posttax_nat_extrapolated
+ + Column p90p100_avg_posttax_nat_extrapolated
+ + Column p99_999p100_avg_posttax_nat_extrapolated
+ + Column p99_99p100_avg_posttax_nat_extrapolated
+ + Column p99_9p100_avg_posttax_nat_extrapolated
+ + Column p99p100_avg_posttax_nat_extrapolated
+ + Column p0p100_avg_wealth_extrapolated
+ + Column p0p10_avg_wealth_extrapolated
+ + Column p10p20_avg_wealth_extrapolated
+ + Column p20p30_avg_wealth_extrapolated
+ + Column p30p40_avg_wealth_extrapolated
+ + Column p40p50_avg_wealth_extrapolated
+ + Column p50p60_avg_wealth_extrapolated
+ + Column p60p70_avg_wealth_extrapolated
+ + Column p70p80_avg_wealth_extrapolated
+ + Column p80p90_avg_wealth_extrapolated
+ + Column p90p100_avg_wealth_extrapolated
+ + Column p99_999p100_avg_wealth_extrapolated
+ + Column p99_99p100_avg_wealth_extrapolated
+ + Column p99_9p100_avg_wealth_extrapolated
+ + Column p99p100_avg_wealth_extrapolated
+ + Column p0p10_thr_pretax_extrapolated
+ + Column p10p20_thr_pretax_extrapolated
+ + Column p20p30_thr_pretax_extrapolated
+ + Column p30p40_thr_pretax_extrapolated
+ + Column p40p50_thr_pretax_extrapolated
+ + Column p50p60_thr_pretax_extrapolated
+ + Column p60p70_thr_pretax_extrapolated
+ + Column p70p80_thr_pretax_extrapolated
+ + Column p80p90_thr_pretax_extrapolated
+ + Column p90p100_thr_pretax_extrapolated
+ + Column p99_999p100_thr_pretax_extrapolated
+ + Column p99_99p100_thr_pretax_extrapolated
+ + Column p99_9p100_thr_pretax_extrapolated
+ + Column p99p100_thr_pretax_extrapolated
+ + Column p0p10_thr_posttax_dis_extrapolated
+ + Column p10p20_thr_posttax_dis_extrapolated
+ + Column p20p30_thr_posttax_dis_extrapolated
+ + Column p30p40_thr_posttax_dis_extrapolated
+ + Column p40p50_thr_posttax_dis_extrapolated
+ + Column p50p60_thr_posttax_dis_extrapolated
+ + Column p60p70_thr_posttax_dis_extrapolated
+ + Column p70p80_thr_posttax_dis_extrapolated
+ + Column p80p90_thr_posttax_dis_extrapolated
+ + Column p90p100_thr_posttax_dis_extrapolated
+ + Column p99_999p100_thr_posttax_dis_extrapolated
+ + Column p99_99p100_thr_posttax_dis_extrapolated
+ + Column p99_9p100_thr_posttax_dis_extrapolated
+ + Column p99p100_thr_posttax_dis_extrapolated
+ + Column p0p10_thr_posttax_nat_extrapolated
+ + Column p10p20_thr_posttax_nat_extrapolated
+ + Column p20p30_thr_posttax_nat_extrapolated
+ + Column p30p40_thr_posttax_nat_extrapolated
+ + Column p40p50_thr_posttax_nat_extrapolated
+ + Column p50p60_thr_posttax_nat_extrapolated
+ + Column p60p70_thr_posttax_nat_extrapolated
+ + Column p70p80_thr_posttax_nat_extrapolated
+ + Column p80p90_thr_posttax_nat_extrapolated
+ + Column p90p100_thr_posttax_nat_extrapolated
+ + Column p99_999p100_thr_posttax_nat_extrapolated
+ + Column p99_99p100_thr_posttax_nat_extrapolated
+ + Column p99_9p100_thr_posttax_nat_extrapolated
+ + Column p99p100_thr_posttax_nat_extrapolated
+ + Column p0p10_thr_wealth_extrapolated
+ + Column p10p20_thr_wealth_extrapolated
+ + Column p20p30_thr_wealth_extrapolated
+ + Column p30p40_thr_wealth_extrapolated
+ + Column p40p50_thr_wealth_extrapolated
+ + Column p50p60_thr_wealth_extrapolated
+ + Column p60p70_thr_wealth_extrapolated
+ + Column p70p80_thr_wealth_extrapolated
+ + Column p80p90_thr_wealth_extrapolated
+ + Column p90p100_thr_wealth_extrapolated
+ + Column p99_999p100_thr_wealth_extrapolated
+ + Column p99_99p100_thr_wealth_extrapolated
+ + Column p99_9p100_thr_wealth_extrapolated
+ + Column p99p100_thr_wealth_extrapolated
+ + Column median_pretax_extrapolated
+ + Column median_posttax_nat_extrapolated
+ + Column median_posttax_dis_extrapolated
+ + Column median_wealth_extrapolated
+ + Column headcount_ratio_40_median_pretax
+ + Column headcount_ratio_50_median_pretax
+ + Column headcount_ratio_60_median_pretax
+ + Column headcount_ratio_40_median_pretax_extrapolated
+ + Column headcount_ratio_50_median_pretax_extrapolated
+ + Column headcount_ratio_60_median_pretax_extrapolated
+ + Column headcount_ratio_40_median_posttax_nat
+ + Column headcount_ratio_50_median_posttax_nat
+ + Column headcount_ratio_60_median_posttax_nat
+ + Column headcount_ratio_40_median_posttax_nat_extrapolated
+ + Column headcount_ratio_50_median_posttax_nat_extrapolated
+ + Column headcount_ratio_60_median_posttax_nat_extrapolated
+ + Column headcount_ratio_40_median_posttax_dis
+ + Column headcount_ratio_50_median_posttax_dis
+ + Column headcount_ratio_60_median_posttax_dis
+ + Column headcount_ratio_40_median_posttax_dis_extrapolated
+ + Column headcount_ratio_50_median_posttax_dis_extrapolated
+ + Column headcount_ratio_60_median_posttax_dis_extrapolated
+ + Column headcount_ratio_40_median_wealth
+ + Column headcount_ratio_50_median_wealth
+ + Column headcount_ratio_60_median_wealth
+ + Column headcount_ratio_40_median_wealth_extrapolated
+ + Column headcount_ratio_50_median_wealth_extrapolated
+ + Column headcount_ratio_60_median_wealth_extrapolated
+ + Table world_inequality_database_distribution
+ + Column thr
+ + Column avg
+ + Column share
+ + Column thr_extrapolated
+ + Column avg_extrapolated
+ + Column share_extrapolated
+ + Table world_inequality_database_fiscal
+ + Column p99p100_share_fiscal992i
+ + Column p99p100_share_fiscal992j
+ + Column p99p100_share_fiscal992t
= Dataset garden/worldbank_wdi/2022-05-26/wdi
= Table wdi
~ Column omm_goods_exp_share_gdp (changed data)
~ Changed values: 1 / 14400 (0.01%)
country year omm_goods_exp_share_gdp - omm_goods_exp_share_gdp +
Guyana 1977 57.650002 57.639999
~ Column omm_merch_exp_share_gdp (changed data)
~ Changed values: 1 / 14400 (0.01%)
country year omm_merch_exp_share_gdp - omm_merch_exp_share_gdp +
Kiribati 1995 12.43 12.42
~ Column omm_net_savings_percap (changed data)
~ Changed values: 5 / 14400 (0.03%)
country year omm_net_savings_percap - omm_net_savings_percap +
Albania 2008 311.76001 311.750000
Congo 2007 -328.380005 -328.369995
Indonesia 2019 592.23999 592.250000
Israel 1970 243.539993 243.529999
Panama 1995 694.280029 694.270020
= Dataset garden/worldbank_wdi/2024-05-20/wdi
= Table wdi
~ Column omm_goods_exp_share_gdp (changed data)
~ Changed values: 4 / 14570 (0.03%)
country year omm_goods_exp_share_gdp - omm_goods_exp_share_gdp +
Eswatini 2019 44.349998 44.360001
Guyana 1977 57.650002 57.639999
Singapore 2006 188.800003 188.789993
Switzerland 2007 42.73 42.720001
⚠ Found errors, create an issue please
Legend: +New ~Modified -Removed =Identical Details
Hint: Run this locally with etl diff REMOTE data/ --include yourdataset --verbose --snippetAutomatically updated datasets matching weekly_wildfires|excess_mortality|covid|fluid|flunet|country_profile|garden/ihme_gbd/2019/gbd_risk are not included Edited: 2024-11-26 09:36:03 UTC |
✨ Changes for compatibility with pandas 3.0 --------- Co-authored-by: Joris Van den Bossche <jorisvandenbossche@gmail.com>
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https://github.com/owid/owid-issues/issues/1713