I'm going to use this data to calculate an indicator for migration within and between subregions for Simons upcoming article - but I anticipate that these subregions are useful for other indicators as well.
chart-diff: ✅
No charts for review.
data-diff: ❌ Found differences
```diff
= Dataset garden/regions/2023-01-01/regions
= Table regions
~ Dim code
+ + New values: 22 / 334 (6.59%)
code
UNSD_CAM
UNSD_NAF
UNSD_POL
UNSD_SAF
UNSD_WAS
~ Column aliases (new data)
+ + New values: 22 / 334 (6.59%)
code aliases
UNSD_CAM NaN
UNSD_NAF NaN
UNSD_POL NaN
UNSD_SAF NaN
UNSD_WAS NaN
~ Column cow_code (new data)
+ + New values: 22 / 334 (6.59%)
code cow_code
UNSD_CAM
UNSD_NAF
UNSD_POL
UNSD_SAF
UNSD_WAS
~ Column cow_letter (new data)
+ + New values: 22 / 334 (6.59%)
code cow_letter
UNSD_CAM NaN
UNSD_NAF NaN
UNSD_POL NaN
UNSD_SAF NaN
UNSD_WAS NaN
~ Column defined_by (new data)
+ + New values: 22 / 334 (6.59%)
code defined_by
UNSD_CAM unsd
UNSD_NAF unsd
UNSD_POL unsd
UNSD_SAF unsd
UNSD_WAS unsd
~ Column end_year (new data)
+ + New values: 22 / 334 (6.59%)
code end_year
UNSD_CAM
UNSD_NAF
UNSD_POL
UNSD_SAF
UNSD_WAS
~ Column imf_code (new data)
+ + New values: 22 / 334 (6.59%)
code imf_code
UNSD_CAM
UNSD_NAF
UNSD_POL
UNSD_SAF
UNSD_WAS
~ Column is_historical (new data)
+ + New values: 22 / 334 (6.59%)
code is_historical
UNSD_CAM False
UNSD_NAF False
UNSD_POL False
UNSD_SAF False
UNSD_WAS False
~ Column iso_alpha2 (new data)
+ + New values: 22 / 334 (6.59%)
code iso_alpha2
UNSD_CAM NaN
UNSD_NAF NaN
UNSD_POL NaN
UNSD_SAF NaN
UNSD_WAS NaN
~ Column iso_alpha3 (new data)
+ + New values: 22 / 334 (6.59%)
code iso_alpha3
UNSD_CAM NaN
UNSD_NAF NaN
UNSD_POL NaN
UNSD_SAF NaN
UNSD_WAS NaN
~ Column kansas_code (new data)
+ + New values: 22 / 334 (6.59%)
code kansas_code
UNSD_CAM NaN
UNSD_NAF NaN
UNSD_POL NaN
UNSD_SAF NaN
UNSD_WAS NaN
~ Column legacy_country_id (new data)
+ + New values: 22 / 334 (6.59%)
code legacy_country_id
UNSD_CAM
UNSD_NAF
UNSD_POL
UNSD_SAF
UNSD_WAS
~ Column legacy_entity_id (new data)
+ + New values: 22 / 334 (6.59%)
code legacy_entity_id
UNSD_CAM
UNSD_NAF
UNSD_POL
UNSD_SAF
UNSD_WAS
~ Column marc_code (new data)
+ + New values: 22 / 334 (6.59%)
code marc_code
UNSD_CAM NaN
UNSD_NAF NaN
UNSD_POL NaN
UNSD_SAF NaN
UNSD_WAS NaN
~ Column members (new data)
+ + New values: 22 / 334 (6.59%)
code members
UNSD_CAM ["BLZ", "CRI", "SLV", "GTM", "HND", "MEX", "NIC", "PAN"]
UNSD_NAF ["DZA", "EGY", "LBY", "MAR", "SDN", "TUN", "ESH"]
UNSD_POL ["ASM", "COK", "PYF", "NIU", "PCN", "WSM", "TKL", "TON", "TUV", "WLF"]
UNSD_SAF ["BWA", "LSO", "NAM", "ZAF", "SWZ"]
UNSD_WAS ["ARM", "AZE", "BHR", "CYP", "GEO", "IRQ", "ISR", "JOR", "KWT", "LBN", "OMN", "QAT", "SAU", "SYR", "TUR", "ARE", "YEM"]
~ Column name (new data)
+ + New values: 22 / 334 (6.59%)
code name
UNSD_CAM Central America (UNSD)
UNSD_NAF Northern Africa (UNSD)
UNSD_POL Polynesia (UNSD)
UNSD_SAF Southern Africa (UNSD)
UNSD_WAS Western Asia (UNSD)
~ Column ncd_code (new data)
+ + New values: 22 / 334 (6.59%)
code ncd_code
UNSD_CAM NaN
UNSD_NAF NaN
UNSD_POL NaN
UNSD_SAF NaN
UNSD_WAS NaN
~ Column penn_code (new data)
+ + New values: 22 / 334 (6.59%)
code penn_code
UNSD_CAM NaN
UNSD_NAF NaN
UNSD_POL NaN
UNSD_SAF NaN
UNSD_WAS NaN
~ Column region_type (new data)
+ + New values: 22 / 334 (6.59%)
code region_type
UNSD_CAM aggregate
UNSD_NAF aggregate
UNSD_POL aggregate
UNSD_SAF aggregate
UNSD_WAS aggregate
~ Column related (new data)
+ + New values: 22 / 334 (6.59%)
code related
UNSD_CAM NaN
UNSD_NAF NaN
UNSD_POL NaN
UNSD_SAF NaN
UNSD_WAS NaN
~ Column short_name (new data, changed data)
+ + New values: 22 / 334 (6.59%)
code short_name
UNSD_CAM Central America (UNSD)
UNSD_NAF Northern Africa (UNSD)
UNSD_POL Polynesia (UNSD)
UNSD_SAF Southern Africa (UNSD)
UNSD_WAS Western Asia (UNSD)
~ Changed values: 2 / 334 (0.60%)
code short_name - short_name +
BIH Bosnia and Herzegovina Bosnia and Herz.
TCA Turks and Caicos Islands Turks and Caicos
~ Column successors (new data)
+ + New values: 22 / 334 (6.59%)
code successors
UNSD_CAM NaN
UNSD_NAF NaN
UNSD_POL NaN
UNSD_SAF NaN
UNSD_WAS NaN
~ Column unctad_code (new data)
+ + New values: 22 / 334 (6.59%)
code unctad_code
UNSD_CAM NaN
UNSD_NAF NaN
UNSD_POL NaN
UNSD_SAF NaN
UNSD_WAS NaN
~ Column wikidata_code (new data)
+ + New values: 22 / 334 (6.59%)
code wikidata_code
UNSD_CAM NaN
UNSD_NAF NaN
UNSD_POL NaN
UNSD_SAF NaN
UNSD_WAS NaN
Legend: +New ~Modified -Removed =Identical Details
Hint: Run this locally with etl diff REMOTE data/ --include yourdataset --verbose --snippet
```
Automatically updated datasets matching _weekly_wildfires|excess_mortality|covid|fluid|flunet|country_profile|garden/ihme_gbd/2019/gbd_risk_ are not included
Adds the geographic sub-regions by the UN Statistics to our regions data set.
I'm going to use this data to calculate an indicator for migration within and between subregions for Simons upcoming article - but I anticipate that these subregions are useful for other indicators as well.
Reference to the discussion in Slack.