📊 wid: Update World Inequality Database (Nov 2024 release) #3569
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data-diff:= Dataset garden/cdc/latest/measles_cases
= Table measles_cases
~ Column cases (changed metadata, changed data)
- - date_accessed: '2025-03-03'
? ^ ^^
+ + date_accessed: '2025-02-18'
? ^ ^^
- - date_published: '2025-02-27'
? ^^
+ + date_published: '2025-02-06'
? ^^
~ Changed values: 1 / 41 (2.44%)
country year cases - cases +
United States 2025 164 93
~ Column outbreaks_n (changed metadata)
- - date_accessed: '2025-03-03'
? ^ ^^
+ + date_accessed: '2025-02-18'
? ^ ^^
- - date_published: '2025-02-27'
? ^^
+ + date_published: '2025-02-06'
? ^^
~ Column states_with_cases (changed metadata, changed data)
- - date_accessed: '2025-03-03'
? ^ ^^
+ + date_accessed: '2025-02-18'
? ^ ^^
- - date_published: '2025-02-27'
? ^^
+ + date_published: '2025-02-06'
? ^^
~ Changed values: 1 / 41 (2.44%)
country year states_with_cases - states_with_cases +
United States 2025 9 8
= Dataset garden/demography/2024-11-26/multiple_births
= Table multiple_births
~ Column multiple_rate (changed metadata)
- - description_short: Number of deliveries that are multiple deliveries (2 or more), per 1,000 deliveries.
? ^^^^ ------------
+ + description_short: The rate of deliveries that are multiple deliveries, per 1,000 deliveries.
? ^^ + +++
- - Column multiple_share
~ Column singleton_rate (changed metadata)
- - description_short: Number of deliveries that are single deliveries, per 1,000 deliveries.
? ^^^^
+ + description_short: The rate of deliveries that are single deliveries, per 1,000 deliveries.
? ^^ + +++
- - unit: deliveries per 1,000 deliveries
? ^^^^^
+ + unit: twin deliveries per total deliveries
? +++++ ^^^^^
- - Column singleton_share
- - Column triplets_plus_deliveries
- - Column triplets_plus_rate
- - Column triplets_plus_share
~ Column twin_deliveries (changed metadata)
- - description_key:
- - - |-
- - Twin births have risen dramatically since the 1980s. One reason is the use of reproductive technologies such as in vitro fertilization (IVF), which have made it possible for many more couples to conceive. During procedures like IVF, multiple eggs can be used at the same time to maximize the chances of a successful pregnancy, which can lead to twin births.
- - - |-
- - Another reason for the rise in twin births is that the (https://ourworldindata.org/grapher/period-average-age-of-mothers-birth-order). Older women are (https://doi.org/10.1111/j.1728-4457.2015.00088.x), even without using reproductive technologies.
- - - |-
- - In some countries, twin birth rates have dropped in recent decades, as reproductive technologies have shifted to using single-embryo transfers instead of multiple.
~ Column twinning_rate (changed metadata)
- - description_short: Number of twin deliveries, per 1,000 deliveries.
? ^^^^
+ + description_short: The rate of twin deliveries, per 1,000 deliveries.
? ^^ + +++
- - description_key:
- - - |-
- - Twin births have risen dramatically since the 1980s. One reason is the use of reproductive technologies such as in vitro fertilization (IVF), which have made it possible for many more couples to conceive. During procedures like IVF, multiple eggs can be used at the same time to maximize the chances of a successful pregnancy, which can lead to twin births.
- - - |-
- - Another reason for the rise in twin births is that the (https://ourworldindata.org/grapher/period-average-age-of-mothers-birth-order). Older women are (https://doi.org/10.1111/j.1728-4457.2015.00088.x), even without using reproductive technologies.
- - - |-
- - In some countries, twin birth rates have dropped in recent decades, as reproductive technologies have shifted to using single-embryo transfers instead of multiple.
- - Column twinning_share
~ Dataset garden/health/2025-02-20/measles_deaths_census_bureau
+ + Data on reported measles deaths in the United States, from the United States Census Bureau: [Part 2 - Vital Statistics and Health and Medical Care](https://www.census.gov/library/publications/1952/compendia/statab/73ed.html)
- - Data on reported measles deaths in the United States, from the United States Census Bureau.
- -
- - Sources for each year are as follows:
- -
- - * 1922-23: [US Census Bureau “Statistical Abstract of the United States: 1924"](https://www.census.gov/library/publications/1925/compendia/statab/47ed.html)
- -
- - * 1926: [US Census Bureau “Statistical Abstract of the United States: 1928”](https://www.census.gov/library/publications/1928/compendia/statab/50ed.html)
- -
- - * 1927: [US Census Bureau “Statistical Abstract of the United States: 1929”](https://www.census.gov/library/publications/1929/compendia/statab/50ed.html)
- -
- - * 1928: [US Census Bureau “Statistical Abstract of the United States: 1930”](https://www.census.gov/library/publications/1930/compendia/statab/52ed.html)
- -
- - * 1929: [US Census Bureau “Statistical Abstract of the United States: 1931”](https://www.census.gov/library/publications/1931/compendia/statab/53ed.html)
- -
- - * 1931: [US Census Bureau “Statistical Abstract of the United States: 1933”](https://www.census.gov/library/publications/1933/compendia/statab/55ed.html)
- -
- - * 1932: [US Census Bureau “Statistical Abstract of the United States: 1934”](https://www.census.gov/library/publications/1934/compendia/statab/56ed.html)
- -
- - * 1933: [US Census Bureau “Statistical Abstract of the United States: 1935”](https://www.census.gov/library/publications/1935/compendia/statab/57ed.html)
- -
- - * 1934: [US Census Bureau “Statistical Abstract of the United States: 1936”](https://www.census.gov/library/publications/1936/compendia/statab/58ed.html)
- -
- - * 1935: [US Census Bureau “Statistical Abstract of the United States: 1937”](https://www.census.gov/library/publications/1938/compendia/statab/59ed.html)
- -
- - * 1936: [US Census Bureau “Statistical Abstract of the United States: 1938”](https://www.census.gov/library/publications/1939/compendia/statab/60ed.html)
- -
- - * 1949: [US Census Bureau “Statistical Abstract of the United States: 1952”](https://www.census.gov/library/publications/1952/compendia/statab/73ed.html)
~ Table measles_deaths_census_bureau (changed metadata)
+ + Data on reported measles deaths in the United States, from the United States Census Bureau: [Part 2 - Vital Statistics and Health and Medical Care](https://www.census.gov/library/publications/1952/compendia/statab/73ed.html)
- - Data on reported measles deaths in the United States, from the United States Census Bureau.
- -
- - Sources for each year are as follows:
- -
- - * 1922-23: [US Census Bureau “Statistical Abstract of the United States: 1924"](https://www.census.gov/library/publications/1925/compendia/statab/47ed.html)
- -
- - * 1926: [US Census Bureau “Statistical Abstract of the United States: 1928”](https://www.census.gov/library/publications/1928/compendia/statab/50ed.html)
- -
- - * 1927: [US Census Bureau “Statistical Abstract of the United States: 1929”](https://www.census.gov/library/publications/1929/compendia/statab/50ed.html)
- -
- - * 1928: [US Census Bureau “Statistical Abstract of the United States: 1930”](https://www.census.gov/library/publications/1930/compendia/statab/52ed.html)
- -
- - * 1929: [US Census Bureau “Statistical Abstract of the United States: 1931”](https://www.census.gov/library/publications/1931/compendia/statab/53ed.html)
- -
- - * 1931: [US Census Bureau “Statistical Abstract of the United States: 1933”](https://www.census.gov/library/publications/1933/compendia/statab/55ed.html)
- -
- - * 1932: [US Census Bureau “Statistical Abstract of the United States: 1934”](https://www.census.gov/library/publications/1934/compendia/statab/56ed.html)
- -
- - * 1933: [US Census Bureau “Statistical Abstract of the United States: 1935”](https://www.census.gov/library/publications/1935/compendia/statab/57ed.html)
- -
- - * 1934: [US Census Bureau “Statistical Abstract of the United States: 1936”](https://www.census.gov/library/publications/1936/compendia/statab/58ed.html)
- -
- - * 1935: [US Census Bureau “Statistical Abstract of the United States: 1937”](https://www.census.gov/library/publications/1938/compendia/statab/59ed.html)
- -
- - * 1936: [US Census Bureau “Statistical Abstract of the United States: 1938”](https://www.census.gov/library/publications/1939/compendia/statab/60ed.html)
- -
- - * 1949: [US Census Bureau “Statistical Abstract of the United States: 1952”](https://www.census.gov/library/publications/1952/compendia/statab/73ed.html)
~ Dim country
- - Removed values: 12 / 1 (1200.00%)
year country
1926 United States
1928 United States
1931 United States
1935 United States
1936 United States
~ Dim year
- - Removed values: 12 / 1 (1200.00%)
country year
United States 1926
United States 1928
United States 1931
United States 1935
United States 1936
~ Column deaths (changed metadata, changed data)
+ + Data on reported measles deaths in the United States, from the United States Census Bureau: [Part 2 - Vital Statistics and Health and Medical Care](https://www.census.gov/library/publications/1952/compendia/statab/73ed.html)
- - Data on reported measles deaths in the United States, from the United States Census Bureau.
- -
- - Sources for each year are as follows:
- -
- - * 1922-23: [US Census Bureau “Statistical Abstract of the United States: 1924"](https://www.census.gov/library/publications/1925/compendia/statab/47ed.html)
- -
- - * 1926: [US Census Bureau “Statistical Abstract of the United States: 1928”](https://www.census.gov/library/publications/1928/compendia/statab/50ed.html)
- -
- - * 1927: [US Census Bureau “Statistical Abstract of the United States: 1929”](https://www.census.gov/library/publications/1929/compendia/statab/50ed.html)
- -
- - * 1928: [US Census Bureau “Statistical Abstract of the United States: 1930”](https://www.census.gov/library/publications/1930/compendia/statab/52ed.html)
- -
- - * 1929: [US Census Bureau “Statistical Abstract of the United States: 1931”](https://www.census.gov/library/publications/1931/compendia/statab/53ed.html)
- -
- - * 1931: [US Census Bureau “Statistical Abstract of the United States: 1933”](https://www.census.gov/library/publications/1933/compendia/statab/55ed.html)
- -
- - * 1932: [US Census Bureau “Statistical Abstract of the United States: 1934”](https://www.census.gov/library/publications/1934/compendia/statab/56ed.html)
- -
- - * 1933: [US Census Bureau “Statistical Abstract of the United States: 1935”](https://www.census.gov/library/publications/1935/compendia/statab/57ed.html)
- -
- - * 1934: [US Census Bureau “Statistical Abstract of the United States: 1936”](https://www.census.gov/library/publications/1936/compendia/statab/58ed.html)
- -
- - * 1935: [US Census Bureau “Statistical Abstract of the United States: 1937”](https://www.census.gov/library/publications/1938/compendia/statab/59ed.html)
- -
- - * 1936: [US Census Bureau “Statistical Abstract of the United States: 1938”](https://www.census.gov/library/publications/1939/compendia/statab/60ed.html)
- -
- - * 1949: [US Census Bureau “Statistical Abstract of the United States: 1952”](https://www.census.gov/library/publications/1952/compendia/statab/73ed.html)
- - citation_full: |-
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1924.
? ^ - -
+ + citation_full: US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States 1944-45.
? ^^^^^^^^^^^^^^ ++++
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1928.
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1929.
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1930.
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1931.
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1933.
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1934.
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1935.
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1936.
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1937.
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1938.
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1952.
- - Removed values: 12 / 1 (1200.00%)
country year deaths
United States 1926 8607
United States 1928 6146
United States 1931 3576
United States 1935 3907
United States 1936 1267
= Dataset garden/health/2025-02-20/measles_deaths_long_run
= Table measles_deaths_long_run
~ Dim country
- - Removed values: 12 / 81 (14.81%)
year country
1926 United States
1928 United States
1931 United States
1935 United States
1936 United States
~ Dim year
- - Removed values: 12 / 81 (14.81%)
country year
United States 1926
United States 1928
United States 1931
United States 1935
United States 1936
~ Column death_rate (changed metadata, changed data)
+ + Data on reported measles deaths in the United States, from the United States Census Bureau: [Part 2 - Vital Statistics and Health and Medical Care](https://www.census.gov/library/publications/1952/compendia/statab/73ed.html)
- - Data on reported measles deaths in the United States, from the United States Census Bureau.
- -
- - Sources for each year are as follows:
- -
- - * 1922-23: [US Census Bureau “Statistical Abstract of the United States: 1924"](https://www.census.gov/library/publications/1925/compendia/statab/47ed.html)
- -
- - * 1926: [US Census Bureau “Statistical Abstract of the United States: 1928”](https://www.census.gov/library/publications/1928/compendia/statab/50ed.html)
- -
- - * 1927: [US Census Bureau “Statistical Abstract of the United States: 1929”](https://www.census.gov/library/publications/1929/compendia/statab/50ed.html)
- -
- - * 1928: [US Census Bureau “Statistical Abstract of the United States: 1930”](https://www.census.gov/library/publications/1930/compendia/statab/52ed.html)
- -
- - * 1929: [US Census Bureau “Statistical Abstract of the United States: 1931”](https://www.census.gov/library/publications/1931/compendia/statab/53ed.html)
- -
- - * 1931: [US Census Bureau “Statistical Abstract of the United States: 1933”](https://www.census.gov/library/publications/1933/compendia/statab/55ed.html)
- -
- - * 1932: [US Census Bureau “Statistical Abstract of the United States: 1934”](https://www.census.gov/library/publications/1934/compendia/statab/56ed.html)
- -
- - * 1933: [US Census Bureau “Statistical Abstract of the United States: 1935”](https://www.census.gov/library/publications/1935/compendia/statab/57ed.html)
- -
- - * 1934: [US Census Bureau “Statistical Abstract of the United States: 1936”](https://www.census.gov/library/publications/1936/compendia/statab/58ed.html)
- -
- - * 1935: [US Census Bureau “Statistical Abstract of the United States: 1937”](https://www.census.gov/library/publications/1938/compendia/statab/59ed.html)
- -
- - * 1936: [US Census Bureau “Statistical Abstract of the United States: 1938”](https://www.census.gov/library/publications/1939/compendia/statab/60ed.html)
- -
- - * 1949: [US Census Bureau “Statistical Abstract of the United States: 1952”](https://www.census.gov/library/publications/1952/compendia/statab/73ed.html)
- - citation_full: |-
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1924.
? ^ - -
+ + citation_full: US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States 1944-45.
? ^^^^^^^^^^^^^^ ++++
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1928.
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1929.
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1930.
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1931.
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1933.
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1934.
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1935.
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1936.
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1937.
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1938.
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1952.
- - Removed values: 12 / 81 (14.81%)
country year death_rate
United States 1926 7.591684
United States 1928 5.26511
United States 1931 2.959507
United States 1935 3.139456
United States 1936 1.01099
~ Changed values: 1 / 81 (1.23%)
country year death_rate - death_rate +
United States 1921 3.632571 3.197118
~ Column deaths (changed metadata, changed data)
+ + Data on reported measles deaths in the United States, from the United States Census Bureau: [Part 2 - Vital Statistics and Health and Medical Care](https://www.census.gov/library/publications/1952/compendia/statab/73ed.html)
- - Data on reported measles deaths in the United States, from the United States Census Bureau.
- -
- - Sources for each year are as follows:
- -
- - * 1922-23: [US Census Bureau “Statistical Abstract of the United States: 1924"](https://www.census.gov/library/publications/1925/compendia/statab/47ed.html)
- -
- - * 1926: [US Census Bureau “Statistical Abstract of the United States: 1928”](https://www.census.gov/library/publications/1928/compendia/statab/50ed.html)
- -
- - * 1927: [US Census Bureau “Statistical Abstract of the United States: 1929”](https://www.census.gov/library/publications/1929/compendia/statab/50ed.html)
- -
- - * 1928: [US Census Bureau “Statistical Abstract of the United States: 1930”](https://www.census.gov/library/publications/1930/compendia/statab/52ed.html)
- -
- - * 1929: [US Census Bureau “Statistical Abstract of the United States: 1931”](https://www.census.gov/library/publications/1931/compendia/statab/53ed.html)
- -
- - * 1931: [US Census Bureau “Statistical Abstract of the United States: 1933”](https://www.census.gov/library/publications/1933/compendia/statab/55ed.html)
- -
- - * 1932: [US Census Bureau “Statistical Abstract of the United States: 1934”](https://www.census.gov/library/publications/1934/compendia/statab/56ed.html)
- -
- - * 1933: [US Census Bureau “Statistical Abstract of the United States: 1935”](https://www.census.gov/library/publications/1935/compendia/statab/57ed.html)
- -
- - * 1934: [US Census Bureau “Statistical Abstract of the United States: 1936”](https://www.census.gov/library/publications/1936/compendia/statab/58ed.html)
- -
- - * 1935: [US Census Bureau “Statistical Abstract of the United States: 1937”](https://www.census.gov/library/publications/1938/compendia/statab/59ed.html)
- -
- - * 1936: [US Census Bureau “Statistical Abstract of the United States: 1938”](https://www.census.gov/library/publications/1939/compendia/statab/60ed.html)
- -
- - * 1949: [US Census Bureau “Statistical Abstract of the United States: 1952”](https://www.census.gov/library/publications/1952/compendia/statab/73ed.html)
- - citation_full: |-
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1924.
? ^ - -
+ + citation_full: US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States 1944-45.
? ^^^^^^^^^^^^^^ ++++
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1928.
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1929.
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1930.
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1931.
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1933.
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1934.
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1935.
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1936.
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1937.
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1938.
- -
- - US Census Bureau. Part 2 - Vital Statistics, Statistical Abstract of the United States: 1952.
- - Removed values: 12 / 81 (14.81%)
country year deaths
United States 1926 8607
United States 1928 6146
United States 1931 3576
United States 1935 3907
United States 1936 1267
~ Changed values: 1 / 81 (1.23%)
country year deaths - deaths +
United States 1921 3829 3370
= Dataset garden/health/2025-02-20/measles_deaths_public_health_reports
= Table measles_deaths_public_health_reports
~ Column deaths (changed data)
~ Changed values: 1 / 8 (12.50%)
country year deaths - deaths +
United States 1921 3829 3370
~ Dataset garden/health/latest/measles_long_run
- - update_period_days: 7
+ + update_period_days: 730
? ++
= Table measles_long_run
~ Column case_rate (changed metadata, changed data)
- - description_short: |-
- - Reported number of measles cases in the United States per 100,000 people. Data for 2025 is incomplete and was last updated on 27 February 2025.
- - date_accessed: '2025-03-03'
? ^ ^^
+ + date_accessed: '2025-02-18'
? ^ ^^
- - date_published: '2025-02-27'
? ^^
+ + date_published: '2025-02-06'
? ^^
- - display:
- - entityAnnotationsMap: 'United States: Data for 2025 is incomplete'
- - presentation:
- - attribution: Public Health Reports (1919-1925); US Census Bureau (1945); Centers for Disease Control and Prevention (1994;
- - 2025)
~ Changed values: 1 / 92 (1.09%)
country year case_rate - case_rate +
United States 2025 0.047225 0.02678
~ Column case_rate_static (changed metadata)
- - date_accessed: '2025-03-03'
? ^ ^^
+ + date_accessed: '2025-02-18'
? ^ ^^
- - date_published: '2025-02-27'
? ^^
+ + date_published: '2025-02-06'
? ^^
~ Column cases (changed metadata, changed data)
- - title: Number of measles cases
- - description_short: Reported number of measles cases. Data for 2025 is incomplete and was last updated on 27 February 2025.
+ + title: Reported measles cases (updated weekly)
+ + description_short: Reported number of measles cases.
- - date_accessed: '2025-03-03'
? ^ ^^
+ + date_accessed: '2025-02-18'
? ^ ^^
- - date_published: '2025-02-27'
? ^^
+ + date_published: '2025-02-06'
? ^^
- - display:
- - entityAnnotationsMap: 'United States: Data for 2025 is incomplete'
- - attribution: Public Health Reports (1919-1925); US Census Bureau (1945); Centers for Disease Control and Prevention (1994;
- - 2025)
~ Changed values: 1 / 92 (1.09%)
country year cases - cases +
United States 2025 164 93
~ Column cases_static (changed metadata)
- - date_accessed: '2025-03-03'
? ^ ^^
+ + date_accessed: '2025-02-18'
? ^ ^^
- - date_published: '2025-02-27'
? ^^
+ + date_published: '2025-02-06'
? ^^
= Dataset garden/hmd/2024-12-03/hmd_country
= Table birth_rate_month
= Table birth_rate
= Table birth_rate_month_max
~ Column birth_rate_per_day_max (changed metadata)
- - name: Daily birth rate in the peak month
+ + name: Maximum birth rate, per day
= Dataset garden/met_office_hadley_centre/2025-01-21/near_surface_temperature
= Table near_surface_temperature
~ Column lower_limit (changed metadata, changed data)
- - description_from_producer: |-
- - The 1961-90 period is most often used as a baseline because it is the period recommended by the World Meteorological Organisation. In some cases other periods are used. For global average temperatures, an 1861-1890 period is sometimes used to show the warming since the "pre-industrial" period.
+ + - Temperature anomalies are given in degrees Celsius relative to the average temperature over the period 1961-1990.
+ + - Temperature anomalies are available for the Northern Hemisphere and the Southern Hemisphere.
+ + - The global mean is calculated by averaging anomalies for northern and southern hemispheres.
- - - |-
- - Temperature anomalies show how many degrees Celsius temperatures have changed compared to the 1861-1890 period. This baseline period is commonly used to highlight the changes in temperature since pre-industrial times, prior to major human impacts.
- - - |-
- - The data includes separate measurements for the Northern and Southern Hemispheres, which helps researchers analyze regional differences.
- - - The global temperature anomaly is the average of both hemisphere measurements.
- - display:
- - numDecimalPlaces: 1
- - processing_level: major
- - description_processing: |-
- - We switch from using 1961-1990 to using 1861-1890 as our baseline to better show how temperatures have changed since pre-industrial times. For each region, we calculate the mean temperature anomaly for 1961–1990 and for 1861–1890. The difference between these two means serves as the adjustment factor. This factor is applied uniformly to both the temperature anomalies and the confidence intervals to ensure that both the central values and the associated uncertainty bounds are correctly shifted relative to the new 1861–1890 baseline.
~ Changed values: 525 / 525 (100.00%)
region year lower_limit - lower_limit +
Global 1865 -0.162159 -0.524457
Northern hemisphere 1883 -0.205543 -0.586372
Northern hemisphere 1904 -0.343178 -0.724007
Northern hemisphere 1973 0.375642 -0.005188
Southern hemisphere 1951 0.011886 -0.33188
~ Column temperature_anomaly (changed metadata, changed data)
- - title: Global average temperature anomaly relative to 1861-1890
? ^ ^
+ + title: Global average temperature anomaly relative to 1961-1990
? ^ ^
- - description_short: Global average land-sea temperature anomaly relative to the 1861-1890 average temperature baseline.
- - description_from_producer: |-
- - The 1961-90 period is most often used as a baseline because it is the period recommended by the World Meteorological Organisation. In some cases other periods are used. For global average temperatures, an 1861-1890 period is sometimes used to show the warming since the "pre-industrial" period.
+ + - Temperature anomalies are given in degrees Celsius relative to the average temperature over the period 1961-1990.
+ + - Temperature anomalies are available for the Northern Hemisphere and the Southern Hemisphere.
+ + - The global mean is calculated by averaging anomalies for northern and southern hemispheres.
- - - |-
- - Temperature anomalies show how many degrees Celsius temperatures have changed compared to the 1861-1890 period. This baseline period is commonly used to highlight the changes in temperature since pre-industrial times, prior to major human impacts.
- - - |-
- - The data includes separate measurements for the Northern and Southern Hemispheres, which helps researchers analyze regional differences.
- - - The global temperature anomaly is the average of both hemisphere measurements.
- - display:
- - numDecimalPlaces: 1
- - processing_level: major
- - description_processing: |-
- - We switch from using 1961-1990 to using 1861-1890 as our baseline to better show how temperatures have changed since pre-industrial times. For each region, we calculate the mean temperature anomaly for 1961–1990 and for 1861–1890. The difference between these two means serves as the adjustment factor. This factor is applied uniformly to both the temperature anomalies and the confidence intervals to ensure that both the central values and the associated uncertainty bounds are correctly shifted relative to the new 1861–1890 baseline.
~ Changed values: 525 / 525 (100.00%)
region year temperature_anomaly - temperature_anomaly +
Global 1865 0.029816 -0.332481
Northern hemisphere 1883 -0.046234 -0.427063
Northern hemisphere 1904 -0.197443 -0.578273
Northern hemisphere 1973 0.402431 0.021601
Southern hemisphere 1951 0.167609 -0.176157
~ Column upper_limit (changed metadata, changed data)
- - description_from_producer: |-
- - The 1961-90 period is most often used as a baseline because it is the period recommended by the World Meteorological Organisation. In some cases other periods are used. For global average temperatures, an 1861-1890 period is sometimes used to show the warming since the "pre-industrial" period.
+ + - Temperature anomalies are given in degrees Celsius relative to the average temperature over the period 1961-1990.
+ + - Temperature anomalies are available for the Northern Hemisphere and the Southern Hemisphere.
+ + - The global mean is calculated by averaging anomalies for northern and southern hemispheres.
- - - |-
- - Temperature anomalies show how many degrees Celsius temperatures have changed compared to the 1861-1890 period. This baseline period is commonly used to highlight the changes in temperature since pre-industrial times, prior to major human impacts.
- - - |-
- - The data includes separate measurements for the Northern and Southern Hemispheres, which helps researchers analyze regional differences.
- - - The global temperature anomaly is the average of both hemisphere measurements.
- - display:
- - numDecimalPlaces: 1
- - processing_level: major
- - description_processing: |-
- - We switch from using 1961-1990 to using 1861-1890 as our baseline to better show how temperatures have changed since pre-industrial times. For each region, we calculate the mean temperature anomaly for 1961–1990 and for 1861–1890. The difference between these two means serves as the adjustment factor. This factor is applied uniformly to both the temperature anomalies and the confidence intervals to ensure that both the central values and the associated uncertainty bounds are correctly shifted relative to the new 1861–1890 baseline.
~ Changed values: 525 / 525 (100.00%)
region year upper_limit - upper_limit +
Global 1865 0.221792 -0.140506
Northern hemisphere 1883 0.113074 -0.267755
Northern hemisphere 1904 -0.051708 -0.432538
Northern hemisphere 1973 0.42922 0.04839
Southern hemisphere 1951 0.323332 -0.020434
2025-03-03 20:59:26 [error ] Traceback (most recent call last):
File "/home/owid/etl/etl/datadiff.py", line 446, 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 439, in func
differ.summary()
File "/home/owid/etl/etl/datadiff.py", line 265, in summary
self._diff_tables(self.ds_a, self.ds_b, table_name)
File "/home/owid/etl/etl/datadiff.py", line 248, in _diff_tables
out = _data_diff(
File "/home/owid/etl/etl/datadiff.py", line 597, in _data_diff
both = samp_a.merge(samp_b, on=dims, suffixes=(" -", " +"))
File "/home/owid/etl/lib/catalog/owid/catalog/tables.py", line 710, in merge
return merge(left=self, right=right, *args, **kwargs)
File "/home/owid/etl/lib/catalog/owid/catalog/tables.py", line 1435, in merge
tb[new_column].metadata = variables.combine_variables_metadata([left[column]], operation="merge", name=column)
File "/home/owid/etl/lib/catalog/owid/catalog/variables.py", line 555, in combine_variables_metadata
metadata.processing_level = combine_variables_processing_level(variables=variables_only)
File "/home/owid/etl/lib/catalog/owid/catalog/variables.py", line 499, in combine_variables_processing_level
assert len(unknown_processing_levels) == 0, f"Unknown processing levels: {unknown_processing_levels}"
AssertionError: Unknown processing levels: {'<% if sector == "Non-humanitarian aid" %>\nmajor\n<% else %>\nminor\n<%- endif -%>'}
= Dataset garden/poverty_inequality/2025-01-22/inequality_comparison
= Table inequality_comparison_analysis
~ Dim country
+ + New values: 4 / 744 (0.54%)
year ref_year reference_years excluded_years maximum_distances only_all_series pipwelfare pipreportinglevel country
1993 1993 1993-2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN Saint Lucia
1995 1993 1993-2019 Yes | Yes 5 | 5 Only countries in all sources income national Saint Lucia
2015 2019 1993-2019 Yes | Yes 5 | 5 Only countries in all sources income national Saint Lucia
2019 2019 1993-2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN Saint Lucia
~ Dim year
+ + New values: 4 / 744 (0.54%)
country ref_year reference_years excluded_years maximum_distances only_all_series pipwelfare pipreportinglevel year
Saint Lucia 1993 1993-2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN 1993
Saint Lucia 1993 1993-2019 Yes | Yes 5 | 5 Only countries in all sources income national 1995
Saint Lucia 2019 1993-2019 Yes | Yes 5 | 5 Only countries in all sources income national 2015
Saint Lucia 2019 1993-2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN 2019
~ Dim ref_year
+ + New values: 4 / 744 (0.54%)
country year reference_years excluded_years maximum_distances only_all_series pipwelfare pipreportinglevel ref_year
Saint Lucia 1993 1993-2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN 1993
Saint Lucia 1995 1993-2019 Yes | Yes 5 | 5 Only countries in all sources income national 1993
Saint Lucia 2015 1993-2019 Yes | Yes 5 | 5 Only countries in all sources income national 2019
Saint Lucia 2019 1993-2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN 2019
~ Dim reference_years
+ + New values: 4 / 744 (0.54%)
country year ref_year excluded_years maximum_distances only_all_series pipwelfare pipreportinglevel reference_years
Saint Lucia 1993 1993 Yes | Yes 5 | 5 Only countries in all sources NaN NaN 1993-2019
Saint Lucia 1995 1993 Yes | Yes 5 | 5 Only countries in all sources income national 1993-2019
Saint Lucia 2015 2019 Yes | Yes 5 | 5 Only countries in all sources income national 1993-2019
Saint Lucia 2019 2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN 1993-2019
~ Dim excluded_years
+ + New values: 4 / 744 (0.54%)
country year ref_year reference_years maximum_distances only_all_series pipwelfare pipreportinglevel excluded_years
Saint Lucia 1993 1993 1993-2019 5 | 5 Only countries in all sources NaN NaN Yes | Yes
Saint Lucia 1995 1993 1993-2019 5 | 5 Only countries in all sources income national Yes | Yes
Saint Lucia 2015 2019 1993-2019 5 | 5 Only countries in all sources income national Yes | Yes
Saint Lucia 2019 2019 1993-2019 5 | 5 Only countries in all sources NaN NaN Yes | Yes
~ Dim maximum_distances
+ + New values: 4 / 744 (0.54%)
country year ref_year reference_years excluded_years only_all_series pipwelfare pipreportinglevel maximum_distances
Saint Lucia 1993 1993 1993-2019 Yes | Yes Only countries in all sources NaN NaN 5 | 5
Saint Lucia 1995 1993 1993-2019 Yes | Yes Only countries in all sources income national 5 | 5
Saint Lucia 2015 2019 1993-2019 Yes | Yes Only countries in all sources income national 5 | 5
Saint Lucia 2019 2019 1993-2019 Yes | Yes Only countries in all sources NaN NaN 5 | 5
~ Dim only_all_series
+ + New values: 4 / 744 (0.54%)
country year ref_year reference_years excluded_years maximum_distances pipwelfare pipreportinglevel only_all_series
Saint Lucia 1993 1993 1993-2019 Yes | Yes 5 | 5 NaN NaN Only countries in all sources
Saint Lucia 1995 1993 1993-2019 Yes | Yes 5 | 5 income national Only countries in all sources
Saint Lucia 2015 2019 1993-2019 Yes | Yes 5 | 5 income national Only countries in all sources
Saint Lucia 2019 2019 1993-2019 Yes | Yes 5 | 5 NaN NaN Only countries in all sources
~ Dim pipwelfare
+ + New values: 4 / 744 (0.54%)
country year ref_year reference_years excluded_years maximum_distances only_all_series pipreportinglevel pipwelfare
Saint Lucia 1993 1993 1993-2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN
Saint Lucia 1995 1993 1993-2019 Yes | Yes 5 | 5 Only countries in all sources national income
Saint Lucia 2015 2019 1993-2019 Yes | Yes 5 | 5 Only countries in all sources national income
Saint Lucia 2019 2019 1993-2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN
~ Dim pipreportinglevel
+ + New values: 4 / 744 (0.54%)
country year ref_year reference_years excluded_years maximum_distances only_all_series pipwelfare pipreportinglevel
Saint Lucia 1993 1993 1993-2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN
Saint Lucia 1995 1993 1993-2019 Yes | Yes 5 | 5 Only countries in all sources income national
Saint Lucia 2015 2019 1993-2019 Yes | Yes 5 | 5 Only countries in all sources income national
Saint Lucia 2019 2019 1993-2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN
~ Column gini_pip_disposable_percapita (new data)
+ + New values: 4 / 744 (0.54%)
country year ref_year reference_years excluded_years maximum_distances only_all_series pipwelfare pipreportinglevel gini_pip_disposable_percapita
Saint Lucia 1993 1993 1993-2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN <NA>
Saint Lucia 1995 1993 1993-2019 Yes | Yes 5 | 5 Only countries in all sources income national 0.425844
Saint Lucia 2015 2019 1993-2019 Yes | Yes 5 | 5 Only countries in all sources income national 0.51223
Saint Lucia 2019 2019 1993-2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN <NA>
~ Column gini_wid_pretaxnational_peradult (changed metadata, new data, changed data)
- - Income is ‘pre-tax’ — measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.
? ^ ^
+ + Income is "pre-tax" — measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.
? ^ ^
- - date_accessed: '2024-07-04'
? ^ ^ ^^
+ + date_accessed: '2025-02-25'
? ^ ^ ^^
- - date_published: '2024'
? ^
+ + date_published: '2025'
? ^
+ + $schema: https://files.ourworldindata.org/schemas/grapher-schema.003.json
+ + attribution_short: World Inequality Database
+ + New values: 4 / 744 (0.54%)
country year ref_year reference_years excluded_years maximum_distances only_all_series pipwelfare pipreportinglevel gini_wid_pretaxnational_peradult
Saint Lucia 1993 1993 1993-2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN 0.685053
Saint Lucia 1995 1993 1993-2019 Yes | Yes 5 | 5 Only countries in all sources income national <NA>
Saint Lucia 2015 2019 1993-2019 Yes | Yes 5 | 5 Only countries in all sources income national <NA>
Saint Lucia 2019 2019 1993-2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN 0.593704
~ Changed values: 194 / 744 (26.08%)
country year ref_year reference_years excluded_years maximum_distances only_all_series pipwelfare pipreportinglevel gini_wid_pretaxnational_peradult - gini_wid_pretaxnational_peradult +
Barbados 1993 1993 1993-2019 Yes | Yes 5 | 5 All data points NaN NaN <NA> 0.685053
French Polynesia 1993 1993 1993-2019 Yes | Yes 5 | 5 All data points NaN NaN <NA> 0.460802
Kenya 1992 1993 1993-2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN 0.744092 0.618037
Monaco 2019 2019 1993-2019 Yes | Yes 5 | 5 All data points NaN NaN <NA> 0.479241
Yemen 1998 1993 1993-2019 Yes | Yes 5 | 5 All data points NaN NaN 0.662423 0.667707
~ Column p90p100share_pip_disposable_percapita (new data)
+ + New values: 4 / 744 (0.54%)
country year ref_year reference_years excluded_years maximum_distances only_all_series pipwelfare pipreportinglevel p90p100share_pip_disposable_percapita
Saint Lucia 1993 1993 1993-2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN <NA>
Saint Lucia 1995 1993 1993-2019 Yes | Yes 5 | 5 Only countries in all sources income national 32.480286
Saint Lucia 2015 2019 1993-2019 Yes | Yes 5 | 5 Only countries in all sources income national 38.583797
Saint Lucia 2019 2019 1993-2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN <NA>
~ Column p90p100share_wid_pretaxnational_peradult (changed metadata, new data, changed data)
- - Income is ‘pre-tax’ — measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.
? ^ ^
+ + Income is "pre-tax" — measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.
? ^ ^
- - date_accessed: '2024-07-04'
? ^ ^ ^^
+ + date_accessed: '2025-02-25'
? ^ ^ ^^
- - date_published: '2024'
? ^
+ + date_published: '2025'
? ^
+ + $schema: https://files.ourworldindata.org/schemas/grapher-schema.003.json
+ + attribution_short: World Inequality Database
+ + New values: 4 / 744 (0.54%)
country year ref_year reference_years excluded_years maximum_distances only_all_series pipwelfare pipreportinglevel p90p100share_wid_pretaxnational_peradult
Saint Lucia 1993 1993 1993-2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN 55.599998
Saint Lucia 1995 1993 1993-2019 Yes | Yes 5 | 5 Only countries in all sources income national <NA>
Saint Lucia 2015 2019 1993-2019 Yes | Yes 5 | 5 Only countries in all sources income national <NA>
Saint Lucia 2019 2019 1993-2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN 49.009998
~ Changed values: 234 / 744 (31.45%)
country year ref_year reference_years excluded_years maximum_distances only_all_series pipwelfare pipreportinglevel p90p100share_wid_pretaxnational_peradult - p90p100share_wid_pretaxnational_peradult +
Italy 1993 1993 1993-2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN 32.330002 32.190002
Moldova 2018 2019 1993-2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN 32.91 33.73
Spain 1993 1993 1993-2019 Yes | Yes 5 | 5 All data points NaN NaN 35.760002 34.630001
Turkey 2018 2019 1993-2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN 53.200001 53.530003
United Kingdom 1993 1993 1993-2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN 34.23 33.309998
~ Column p99p100share_wid_pretaxnational_peradult (changed metadata, new data, changed data)
- - Income is ‘pre-tax’ — measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.
? ^ ^
+ + Income is "pre-tax" — measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.
? ^ ^
- - date_accessed: '2024-07-04'
? ^ ^ ^^
+ + date_accessed: '2025-02-25'
? ^ ^ ^^
- - date_published: '2024'
? ^
+ + date_published: '2025'
? ^
+ + $schema: https://files.ourworldindata.org/schemas/grapher-schema.003.json
+ + attribution_short: World Inequality Database
+ + New values: 4 / 744 (0.54%)
country year ref_year reference_years excluded_years maximum_distances only_all_series pipwelfare pipreportinglevel p99p100share_wid_pretaxnational_peradult
Saint Lucia 1993 1993 1993-2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN 22.540001
Saint Lucia 1995 1993 1993-2019 Yes | Yes 5 | 5 Only countries in all sources income national <NA>
Saint Lucia 2015 2019 1993-2019 Yes | Yes 5 | 5 Only countries in all sources income national <NA>
Saint Lucia 2019 2019 1993-2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN 21.18
~ Changed values: 221 / 744 (29.70%)
country year ref_year reference_years excluded_years maximum_distances only_all_series pipwelfare pipreportinglevel p99p100share_wid_pretaxnational_peradult - p99p100share_wid_pretaxnational_peradult +
Ghana 2016 2019 1993-2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN 15.23 15.19
Moldova 2018 2019 1993-2019 Yes | Yes 5 | 5 All data points NaN NaN 9.27 10.19
Netherlands 2017 2019 1993-2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN 8.65 6.98
Spain 1993 1993 1993-2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN 11.150001 10.97
Turkey 2018 2019 1993-2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN 20.379999 20.57
~ Column palmaratio_pip_disposable_percapita (changed metadata, new data, changed data)
+ + {}
- - title: Palma ratio
- - description_short: |-
- - The Palma ratio is a measure of inequality that divides the share received by the richest 10% by the share of the poorest 40%. Higher values indicate higher inequality.
- - description_key:
- - - |-
- - Depending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the income of each household is attributed equally to each member of the household (including children).
- - - |-
- - Non-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.
- - origins:
- - - producer: World Bank Poverty and Inequality Platform
- - title: World Bank Poverty and Inequality Platform (PIP)
- - description: |-
- - The Poverty and Inequality Platform (PIP) is an interactive computational tool that offers users quick access to the World Bank’s estimates of poverty, inequality, and shared prosperity. PIP provides a comprehensive view of global, regional, and country-level trends for 170 economies around the world.
- - citation_full: |-
- - World Bank (2024). Poverty and Inequality Platform (version 20240627_2017 and 20240627_2011) [Data set]. World Bank Group. https://pip.worldbank.org/.
- - version_producer: 20240627_2017, 20240627_2011
- - url_main: https://pip.worldbank.org
- - date_accessed: '2024-10-07'
- - date_published: '2024-09-20'
- - license:
- - name: CC0
- - url: https://datacatalog.worldbank.org/search/dataset/0063646
- - unit: ''
- - short_unit: ''
- - display:
- - name: Palma ratio
- - numDecimalPlaces: 1
- - tolerance: 5
- - entityAnnotationsMap: 'Other high income countries (PIP): e.g. US, Western Europe, Australia, Japan, South Korea and Saudi
- - Arabia'
- - presentation:
- - title_public: Palma ratio
- - description_processing: |-
- - For most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.
- -
- - In most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.
- -
- - If you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Poverty Data Explorer](https://ourworldindata.org/explorers/poverty-explorer?Indicator=Share+in+poverty&Poverty+line=%2410+per+day&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our (https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.
+ + New values: 4 / 744 (0.54%)
country year ref_year reference_years excluded_years maximum_distances only_all_series pipwelfare pipreportinglevel palmaratio_pip_disposable_percapita
Saint Lucia 1993 1993 1993-2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN NaN
Saint Lucia 1995 1993 1993-2019 Yes | Yes 5 | 5 Only countries in all sources income national NaN
Saint Lucia 2015 2019 1993-2019 Yes | Yes 5 | 5 Only countries in all sources income national NaN
Saint Lucia 2019 2019 1993-2019 Yes | Yes 5 | 5 Only countries in all sources NaN NaN NaN
~ Changed values: 336 / 744 (45.16%)
country year ref_year reference_years excluded_years maximum_distances only_all_series pipwelfare pipreportinglevel palmaratio_pip_disposable_percapita - palmaratio_pip_disposable_percapita +
China 2019 2019 1993-2019 Yes | Yes 5 | 5 All data points consumption national 1.688926 NaN
Colombia 1992 1993 1993-2019 Yes | Yes 5 | 5 All data points income national 3.444536 NaN
Moldova 1997 1993 1993-2019 Yes | Yes 5 | 5 Only countries in all sources consumption national 1.5669 NaN
Spain 1993 1993 1993-2019 Yes | Yes 5 | 5 Only countries in all sources income national 1.41876
...diff too long, truncated...Automatically updated datasets matching weekly_wildfires|excess_mortality|covid|fluid|flunet|country_profile|garden/ihme_gbd/2019/gbd_risk are not included Edited: 2025-03-06 15:42:16 UTC |
✨ Changes for compatibility with pandas 3.0 --------- Co-authored-by: Joris Van den Bossche <[email protected]>
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https://github.com/owid/owid-issues/issues/1713