📊 one: Upload ODA data by sector #3305
Closed
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
|
Quick links (staging server):
Login: chart-diff: ✅No charts for review.data-diff:= Dataset garden/artificial_intelligence/2024-09-09/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 10 September 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 18 September 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 10 September 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 18 September 2024.
? ^
= Dataset garden/artificial_intelligence/2024-09-09/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 10 September 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 18 September 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 10 September 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 18 September 2024.
? ^
= Dataset garden/artificial_intelligence/2024-09-09/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 10 September 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 18 September 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 10 September 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 18 September 2024.
? ^
= Dataset garden/demography/2023-09-27/survivor_percentiles
~ Table survivor_percentiles (changed metadata)
+ + title: Human Mortality Database
+ + description: |-
+ + The Human Mortality Database (HMD) contains original calculations of death rates and life tables for national populations (countries or areas), as well as the input data used in constructing those tables. The input data consist of death counts from vital statistics, plus census counts, birth counts, and population estimates from various sources.
+ +
+ +
+ + # Scope and basic principles
+ +
+ + New data series to this collection. However, the database is limited by design to populations where death registration and census data are virtually complete, since this type of information is required for the uniform method used to reconstruct historical data series. As a result, the countries and areas included here are relatively wealthy and for the most part highly industrialized.
+ +
+ + The main goal of the Human Mortality Database is to document the longevity revolution of the modern era and to facilitate research into its causes and consequences. As much as possible, the authors of the database have followed four guiding principles: comparability, flexibility, accessibility, reproducibility.
+ +
+ +
+ + # Computing death rates and life tables
+ +
+ + Their process for computing mortality rates and life tables can be described in terms of six steps, corresponding to six data types that are available from the HMD. Here is an overview of the process:
+ +
+ + 1. Births. Annual counts of live births by sex are collected for each population over the longest possible time period. These counts are used mainly for making population estimates at younger ages.
+ + 2. Deaths. Death counts are collected at the finest level of detail available. If raw data are aggregated, uniform methods are used to estimate death counts by completed age (i.e., age-last-birthday at time of death), calendar year of death, and calendar year of birth.
+ + 3. Population size. Annual estimates of population size on January 1st are either obtained from another source or are derived from census data plus birth and death counts.
+ + 4. Exposure-to-risk. Estimates of the population exposed to the risk of death during some age-time interval are based on annual (January 1st) population estimates, with a small correction that reflects the timing of deaths within the interval.
+ + 5. Death rates. Death rates are always a ratio of the death count for a given age-time interval divided by an estimate of the exposure-to-risk in the same interval.
+ + 6. Life tables. To build a life table, probabilities of death are computed from death rates. These probabilities are used to construct life tables, which include life expectancies and other useful indicators of mortality and longevity.
+ +
+ +
+ + # Corrections to the data
+ +
+ + The data presented here have been corrected for gross errors (e.g., a processing error whereby 3,800 becomes 38,000 in a published statistical table would be obvious in most cases, and it would be corrected). However, the authors have not attempted to correct the data for systematic age misstatement (misreporting of age) or coverage errors (over- or under-enumeration of people or events).
+ +
+ + Some available studies assess the completeness of census coverage or death registration in the various countries, and more work is needed in this area. However, in developing the database thus far, the authors did not consider it feasible or desirable to attempt corrections of this sort, especially since it would be impossible to correct the data by a uniform method across all countries.
+ +
+ +
+ + # Age misreporting
+ +
+ + Populations are included here if there is a well-founded belief that the coverage of their census and vital registration systems is relatively high, and thus, that fruitful analyses by both specialists and non-specialists should be possible with these data. Nevertheless, there is evidence of both age heaping (overreporting ages ending in "0" or "5") and age exaggeration in these data.
+ +
+ + In general, the degree of age heaping in these data varies by the time period and population considered, but it is usually no burden to scientific analysis. In most cases, it is sufficient to analyze data in five-year age groups in order to avoid the false impressions created by this particular form of age misstatement.
+ +
+ + Age exaggeration, on the other hand, is a more insidious problem. The authors' approach is guided by the conventional wisdom that age reporting in death registration systems is typically more reliable than in census counts or official population estimates. For this reason, the authors derive population estimates at older ages from the death counts themselves, employing extinct cohort methods. Such methods eliminate some, but certainly not all, of the biases in old-age mortality estimates due to age exaggeration.
+ +
+ +
+ + # Uniform set of procedures
+ +
+ + A key goal of this project is to follow a uniform set of procedures for each population. This approach does not guarantee the cross-national comparability of the data. Rather, it ensures only that the authors have not introduced biases by the authors' own manipulations. The desire of the authors for uniformity had to face the challenge that raw data come in a variety of formats (for example, 1-year versus 5-year age groups). The authors' general approach to this problem is that the available raw data are used first to estimate two quantities: 1) the number of deaths by completed age, year of birth, and year of death; and 2) population estimates by single years of age on January 1 of each year. For each population, these calculations are performed separately by sex. From these two pieces of information, they compute death rates and life tables in a variety of age-time configurations.
+ +
+ + It is reasonable to ask whether a single procedure is the best method for treating the data from a variety of populations. Here, two points must be considered. First, the authors' uniform methodology is based on procedures that were developed separately, though following similar principles, for various countries and by different researchers. Earlier methods were synthesized by choosing what they considered the best among alternative procedures and by eliminating superficial inconsistencies. The second point is that a uniform procedure is possible only because the authors have not attempted to correct the data for reporting and coverage errors. Although some general principles could be followed, such problems would have to be addressed individually for each population.
+ +
+ + Although the authors adhere strictly to a uniform procedure, the data for each population also receive significant individualized attention. Each country or area is assigned to an individual researcher, who takes responsibility for assembling and checking the data for errors. In addition, the person assigned to each country/area checks the authors' data against other available sources. These procedures help to assure a high level of data quality, but assistance from database users in identifying problems is always appreciated!
= Dataset garden/demography/2023-10-04/gini_le
= Table gini_le
~ Dim location
+ + New values: 1626 / 212193 (0.77%)
year sex location
1776 female East Germany
1857 female East Germany
1898 male East Germany
1926 female East Germany
1985 female East Germany
~ Dim year
+ + New values: 1626 / 212193 (0.77%)
location sex year
East Germany female 1776
East Germany female 1857
East Germany male 1898
East Germany female 1926
East Germany female 1985
~ Dim sex
+ + New values: 1626 / 212193 (0.77%)
location year sex
East Germany 1776 female
East Germany 1857 female
East Germany 1898 male
East Germany 1926 female
East Germany 1985 female
~ Column life_expectancy_gini (new data)
+ + New values: 1626 / 212193 (0.77%)
location year sex life_expectancy_gini
East Germany 1776 female NaN
East Germany 1857 female NaN
East Germany 1898 male NaN
East Germany 1926 female NaN
East Germany 1985 female NaN
= Dataset garden/insee/2024-04-26/relative_poverty_france
= Table relative_poverty_france
~ Dim country
+ + New values: 1 / 34 (2.94%)
year spell country
1975 1 France
- - Removed values: 1 / 34 (2.94%)
year spell country
1975 <NA> France
~ Dim year
+ + New values: 1 / 34 (2.94%)
country spell year
France 1 1975
- - Removed values: 1 / 34 (2.94%)
country spell year
France <NA> 1975
~ Dim spell
+ + New values: 1 / 34 (2.94%)
country year spell
France 1975 1
- - Removed values: 1 / 34 (2.94%)
country year spell
France 1975 <NA>
~ Column headcount_ratio_40_median (new data, changed data)
+ + New values: 1 / 34 (2.94%)
country year spell headcount_ratio_40_median
France 1975 1 5.8
- - Removed values: 1 / 34 (2.94%)
country year spell headcount_ratio_40_median
France 1975 <NA> 5.8
~ Column headcount_ratio_50_median (new data, changed data)
+ + New values: 1 / 34 (2.94%)
country year spell headcount_ratio_50_median
France 1975 1 10.6
- - Removed values: 1 / 34 (2.94%)
country year spell headcount_ratio_50_median
France 1975 <NA> 10.6
~ Column headcount_ratio_60_median (new data, changed data)
+ + New values: 1 / 34 (2.94%)
country year spell headcount_ratio_60_median
France 1975 1 17.0
- - Removed values: 1 / 34 (2.94%)
country year spell headcount_ratio_60_median
France 1975 <NA> 17.0
~ Column headcount_ratio_70_median (new data, changed data)
+ + New values: 1 / 34 (2.94%)
country year spell headcount_ratio_70_median
France 1975 1 23.9
- - Removed values: 1 / 34 (2.94%)
country year spell headcount_ratio_70_median
France 1975 <NA> 23.9
= Dataset garden/wb/2024-03-27/world_bank_pip
= Table income_2017_decile5_avg
= Table income_consumption_2017_avg_shortfall_100
= Table consumption_2017_decile5_share
= Table income_consumption_2011_unsmoothed
= Table income_2017
= Table consumption_2017_avg_shortfall_100
= Table income_2017_decile1_share
= Table income_consumption_2017_headcount_215
= Table consumption_2017_decile8_share
= Table income_consumption_2017_headcount_365
= Table income_consumption_2017_headcount_ratio_365
= Table income_2017_avg_shortfall_4000
= Table consumption_2017_decile1_share
= Table income_consumption_2017_decile9_avg
= Table income_2017_total_shortfall_1000
= Table income_consumption_2017_mean
= Table income_consumption_2017_headcount_1000
= Table income_consumption_2017_poverty_gap_index_2000
= Table income_consumption_2017_poverty_gap_index_365
= Table consumption_2017_decile10_avg
= Table income_consumption_2017_bottom50_share
= Table income_2017_decile4_avg
= Table income_2017_p50_p10_ratio
= Table income_2017_headcount_ratio_4000
= Table income_2017_middle40_share
= Table income_2017_income_gap_ratio_685
= Table consumption_2017_decile3_thr
= Table income_2017_income_gap_ratio_1000
= Table consumption_2017_avg_shortfall_50_median
= Table consumption_2017_headcount_215
= Table consumption_2017_headcount_ratio_50_median
= Table income_2017_decile7_thr
= Table income_2017_decile4_share
= Table consumption_2017_decile3_share
= Table income_consumption_2017_decile2_thr
= Table income_2017_decile9_thr
= Table consumption_2017_palma_ratio
= Table income_consumption_2017_headcount_2000
= Table percentiles_income_consumption_2017
= Table income_consumption_2017_decile2_avg
= Table consumption_2017_poverty_gap_index_2000
= Table income_consumption_2017_headcount_50_median
= Table percentiles_income_consumption_2011
= Table income_2017_avg_shortfall_215
= Table consumption_2017_headcount_ratio_60_median
= Table income_consumption_2017_poverty_gap_index_40_median
= Table consumption_2017_decile3_avg
= Table consumption_2017_avg_shortfall_215
= Table income_consumption_2017_headcount_60_median
= Table income_consumption_2017_avg_shortfall_685
= Table consumption_2017_total_shortfall_40_median
= Table income_2017_headcount_ratio_50_median
= Table consumption_2017_decile6_avg
= Table consumption_2017_poverty_gap_index_3000
= Table income_2017_decile6_avg
= Table income_consumption_2017_headcount_4000
= Table consumption_2017_total_shortfall_3000
= Table income_consumption_2017_total_shortfall_685
= Table consumption_2017_poverty_gap_index_1000
= Table income_2017_decile5_thr
= Table consumption_2017_decile1_thr
= Table consumption_2017_headcount_ratio_685
= Table consumption_2017_income_gap_ratio_40_median
= Table income_consumption_2017_unsmoothed
= Table income_consumption_2017_headcount_ratio_2000
= Table income_consumption_2011_2017
= Table income_consumption_2017_total_shortfall_60_median
= Table income_2017_headcount_40_median
= Table income_2017_headcount_ratio_1000
= Table income_2017_total_shortfall_215
= Table income_2017_headcount_ratio_3000
= Table income_consumption_2017_avg_shortfall_1000
= Table income_consumption_2017_income_gap_ratio_365
= Table income_2017_decile6_share
= Table income_2017_income_gap_ratio_2000
= Table income_consumption_2017_income_gap_ratio_40_median
= Table consumption_2017_decile4_avg
= Table income_consumption_2017_headcount_ratio_100
= Table consumption_2017_income_gap_ratio_50_median
= Table consumption_2017_headcount_ratio_365
= Table income_consumption_2017_poverty_gap_index_50_median
= Table income_2017_income_gap_ratio_50_median
= Table income_consumption_2017_headcount_ratio_4000
= Table income_2017_poverty_gap_index_1000
= Table income_2017_avg_shortfall_40_median
= Table income_consumption_2017_polarization
= Table consumption_2017_income_gap_ratio_4000
= Table income_2017_income_gap_ratio_60_median
= Table income_2011_2017
= Table consumption_2017_poverty_gap_index_215
= Table consumption_2017_headcount_60_median
= Table income_2017_income_gap_ratio_3000
= Table income_consumption_2017_decile6_thr
= Table income_2017_headcount_ratio_60_median
= Table income_consumption_2017_avg_shortfall_50_median
= Table income_consumption_2017_headcount_685
= Table income_consumption_2017_poverty_gap_index_100
= Table income_2017_decile2_share
= Table income_consumption_2017_decile7_avg
= Table income_consumption_2017_s80_s20_ratio
= Table income_consumption_2017_decile1_avg
= Table income_consumption_2017_total_shortfall_215
= Table income_consumption_2017_headcount_ratio_215
= Table consumption_2017_headcount_365
= Table income_consumption_2017_income_gap_ratio_60_median
= Table income_2017_poverty_gap_index_40_median
= Table consumption_2017_income_gap_ratio_100
= Table consumption_2017_polarization
= Table income_consumption_2017
~ Column avg_shortfall_100 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column avg_shortfall_1000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column avg_shortfall_2000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column avg_shortfall_215 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column avg_shortfall_3000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column avg_shortfall_365 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column avg_shortfall_4000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column avg_shortfall_40_median (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column avg_shortfall_50_median (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column avg_shortfall_60_median (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column avg_shortfall_685 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column bottom50_share (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column decile10_avg (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column decile10_share (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column decile1_avg (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column decile1_share (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column decile1_thr (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column decile2_avg (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column decile2_share (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column decile2_thr (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column decile3_avg (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column decile3_share (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column decile3_thr (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column decile4_avg (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column decile4_share (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column decile4_thr (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column decile5_avg (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column decile5_share (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column decile5_thr (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column decile6_avg (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column decile6_share (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column decile6_thr (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column decile7_avg (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column decile7_share (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column decile7_thr (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column decile8_avg (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column decile8_share (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column decile8_thr (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column decile9_avg (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column decile9_share (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column decile9_thr (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column gini (changed metadata)
+ + originUrl: https://ourworldindata.org/economic-inequality
- - originUrl: https://ourworldindata.org/economic-inequality
+ + title: 'Income inequality: Gini coefficient'
+ + subtitle: |-
+ + The [Gini coefficient](#dod:gini) measures inequality on a scale from 0 to 1. Higher values indicate higher inequality. Depending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, (#dod:per-capita).
+ + note: |-
+ + Income and consumption estimates are available separately in this [Data Explorer](https://ourworldindata.org/explorers/pip-inequality-explorer).
+ + tab: map
+ + variantName: World Bank
+ + yAxis:
+ + min: 0
- - note: |-
- - Income and consumption estimates are available separately in this [Data Explorer](https://ourworldindata.org/explorers/pip-inequality-explorer).
- - subtitle: |-
- - The [Gini coefficient](#dod:gini) measures inequality on a scale from 0 to 1. Higher values indicate higher inequality. Depending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, (#dod:per-capita).
- - tab: map
- - title: 'Income inequality: Gini coefficient'
- - variantName: World Bank
- - yAxis:
- - min: 0
~ Column headcount_100 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_1000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_2000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_215 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
+ + title: Number of people living in extreme poverty
+ + subtitle: |-
+ + Extreme poverty is defined as living below the International Poverty Line of $2.15 per day. This data is adjusted for inflation and for differences in the cost of living between countries.
+ + note: |-
+ + This data is expressed in (#dod:int_dollar_abbreviation) at 2017 prices. Depending on the country and year, it relates to income measured after taxes and benefits, or to consumption, (#dod:per-capita).
+ + tab: map
+ + variantName: Line chart
+ + yAxis:
+ + min: 0
+ + binningStrategy: manual
- - binningStrategy: manual
- - note: |-
- - This data is expressed in (#dod:int_dollar_abbreviation) at 2017 prices. Depending on the country and year, it relates to income measured after taxes and benefits, or to consumption, (#dod:per-capita).
- - subtitle: |-
- - Extreme poverty is defined as living below the International Poverty Line of $2.15 per day. This data is adjusted for inflation and for differences in the cost of living between countries.
- - tab: map
- - title: Number of people living in extreme poverty
- - variantName: Line chart
- - yAxis:
- - min: 0
~ Column headcount_215_regions (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
+ + title: Total population living in extreme poverty by world region
+ + subtitle: |-
+ + Extreme poverty is defined as living below the International Poverty Line of $2.15 per day. This data is adjusted for inflation and for differences in the cost of living between countries.
- - originUrl: https://ourworldindata.org/poverty
- - addCountryMode: disabled
- - baseColorScheme: OwidCategoricalC
- - hideRelativeToggle: false
- - invertColorScheme: true
+ + type: StackedArea
+ + addCountryMode: disabled
+ + hideRelativeToggle: false
+ + baseColorScheme: OwidCategoricalC
+ + invertColorScheme: true
+ + yAxis:
+ + min: 0
- - subtitle: |-
- - Extreme poverty is defined as living below the International Poverty Line of $2.15 per day. This data is adjusted for inflation and for differences in the cost of living between countries.
- - title: Total population living in extreme poverty by world region
- - type: StackedArea
- - yAxis:
- - min: 0
~ Column headcount_3000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_365 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_4000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_40_median (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_50_median (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_60_median (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_685 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_above_100 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_above_1000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_above_2000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_above_215 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_above_3000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_above_365 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_above_4000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_above_685 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_between_1000_2000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_between_1000_3000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_between_100_215 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_between_2000_3000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_between_215_1000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_between_215_365 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_between_3000_4000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_between_365_685 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_between_685_1000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_ratio_100 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_ratio_1000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_ratio_2000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_ratio_215 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
+ + title: Share of population living in extreme poverty
+ + subtitle: |-
+ + Extreme poverty is defined as living below the International Poverty Line of $2.15 per day. This data is adjusted for inflation and for differences in the cost of living between countries.
+ + note: |-
+ + This data is expressed in (#dod:int_dollar_abbreviation) at 2017 prices. Depending on the country and year, it relates to income measured after taxes and benefits, or to consumption, (#dod:per-capita).
+ + tab: map
+ + variantName: Line chart
+ + yAxis:
+ + min: 0
- - note: |-
- - This data is expressed in (#dod:int_dollar_abbreviation) at 2017 prices. Depending on the country and year, it relates to income measured after taxes and benefits, or to consumption, (#dod:per-capita).
- - subtitle: |-
- - Extreme poverty is defined as living below the International Poverty Line of $2.15 per day. This data is adjusted for inflation and for differences in the cost of living between countries.
- - tab: map
- - title: Share of population living in extreme poverty
- - variantName: Line chart
- - yAxis:
- - min: 0
~ Column headcount_ratio_3000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
+ + title: 'Poverty: Share of population living on less than $30 a day'
+ + subtitle: This data is adjusted for inflation and for differences in the cost of living between countries.
+ + note: |-
+ + This data is expressed in (#dod:int_dollar_abbreviation) at 2017 prices. Depending on the country and year, it relates to income measured after taxes and benefits, or to consumption, (#dod:per-capita).
+ + tab: map
+ + variantName: Line chart
+ + yAxis:
+ + min: 0
- - note: |-
- - This data is expressed in (#dod:int_dollar_abbreviation) at 2017 prices. Depending on the country and year, it relates to income measured after taxes and benefits, or to consumption, (#dod:per-capita).
- - subtitle: This data is adjusted for inflation and for differences in the cost of living between countries.
- - tab: map
- - title: 'Poverty: Share of population living on less than $30 a day'
- - variantName: Line chart
- - yAxis:
- - min: 0
~ Column headcount_ratio_365 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
+ + title: 'Poverty: Share of population living on less than $3.65 a day'
+ + subtitle: |-
+ + The poverty line of $3.65 per day is set by the World Bank to be representative of the definitions of poverty adopted in lower-middle-income countries. This data is adjusted for inflation and for differences in the cost of living between countries.
+ + note: |-
+ + This data is expressed in (#dod:int_dollar_abbreviation) at 2017 prices. Depending on the country and year, it relates to income measured after taxes and benefits, or to consumption, (#dod:per-capita).
+ + tab: map
+ + variantName: Line chart
+ + yAxis:
+ + min: 0
- - note: |-
- - This data is expressed in (#dod:int_dollar_abbreviation) at 2017 prices. Depending on the country and year, it relates to income measured after taxes and benefits, or to consumption, (#dod:per-capita).
- - subtitle: |-
- - The poverty line of $3.65 per day is set by the World Bank to be representative of the definitions of poverty adopted in lower-middle-income countries. This data is adjusted for inflation and for differences in the cost of living between countries.
- - tab: map
- - title: 'Poverty: Share of population living on less than $3.65 a day'
- - variantName: Line chart
- - yAxis:
- - min: 0
~ Column headcount_ratio_4000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_ratio_40_median (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
+ + title: 'Relative poverty: Share of people below 40% of median income'
+ + subtitle: |-
+ + Relative poverty is measured in terms of a poverty line that rises and falls over time with average incomes – in this case set at 40% of median income.
+ + note: |-
+ + Depending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, (#dod:per-capita).
+ + hasMapTab: true
+ + tab: map
+ + yAxis:
+ + min: 0
- - hasMapTab: true
- - note: |-
- - Depending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, (#dod:per-capita).
- - subtitle: |-
- - Relative poverty is measured in terms of a poverty line that rises and falls over time with average incomes – in this case set at 40% of median income.
- - tab: map
- - title: 'Relative poverty: Share of people below 40% of median income'
- - yAxis:
- - min: 0
~ Column headcount_ratio_50_median (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
+ + title: 'Relative poverty: Share of people below 50% of median income'
+ + subtitle: |-
+ + Relative poverty is measured in terms of a poverty line that rises and falls over time with average incomes – in this case set at 50% of median income.
+ + note: |-
+ + Depending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, (#dod:per-capita).
+ + hasMapTab: true
+ + tab: map
+ + yAxis:
+ + min: 0
- - hasMapTab: true
- - note: |-
- - Depending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, (#dod:per-capita).
- - subtitle: |-
- - Relative poverty is measured in terms of a poverty line that rises and falls over time with average incomes – in this case set at 50% of median income.
- - tab: map
- - title: 'Relative poverty: Share of people below 50% of median income'
- - yAxis:
- - min: 0
~ Column headcount_ratio_60_median (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
+ + title: 'Relative poverty: Share of people below 60% of median income'
+ + subtitle: |-
+ + Relative poverty is measured in terms of a poverty line that rises and falls over time with average incomes — in this case set at 60% of median income.
+ + note: |-
+ + Depending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, (#dod:per-capita).
+ + hasMapTab: true
+ + tab: map
+ + yAxis:
+ + min: 0
- - hasMapTab: true
- - note: |-
- - Depending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, (#dod:per-capita).
- - subtitle: |-
- - Relative poverty is measured in terms of a poverty line that rises and falls over time with average incomes — in this case set at 60% of median income.
- - tab: map
- - title: 'Relative poverty: Share of people below 60% of median income'
- - yAxis:
- - min: 0
~ Column headcount_ratio_685 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
+ + title: 'Poverty: Share of population living on less than $6.85 a day'
+ + subtitle: |-
+ + The poverty line of $6.85 per day is set by the World Bank to be representative of the definitions of poverty adopted in upper-middle-income countries. This data is adjusted for inflation and for differences in the cost of living between countries.
+ + note: |-
+ + This data is expressed in (#dod:int_dollar_abbreviation) at 2017 prices. Depending on the country and year, it relates to income measured after taxes and benefits, or to consumption, (#dod:per-capita).
+ + tab: map
+ + variantName: Line chart
+ + yAxis:
+ + min: 0
- - note: |-
- - This data is expressed in (#dod:int_dollar_abbreviation) at 2017 prices. Depending on the country and year, it relates to income measured after taxes and benefits, or to consumption, (#dod:per-capita).
- - subtitle: |-
- - The poverty line of $6.85 per day is set by the World Bank to be representative of the definitions of poverty adopted in upper-middle-income countries. This data is adjusted for inflation and for differences in the cost of living between countries.
- - tab: map
- - title: 'Poverty: Share of population living on less than $6.85 a day'
- - variantName: Line chart
- - yAxis:
- - min: 0
~ Column headcount_ratio_above_100 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_ratio_above_1000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_ratio_above_2000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_ratio_above_215 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_ratio_above_3000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_ratio_above_365 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_ratio_above_4000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_ratio_above_685 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_ratio_between_1000_2000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_ratio_between_1000_3000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_ratio_between_100_215 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_ratio_between_2000_3000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_ratio_between_215_1000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_ratio_between_215_365 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_ratio_between_3000_4000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_ratio_between_365_685 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column headcount_ratio_between_685_1000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column income_gap_ratio_100 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column income_gap_ratio_1000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column income_gap_ratio_2000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column income_gap_ratio_215 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column income_gap_ratio_3000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column income_gap_ratio_365 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column income_gap_ratio_4000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column income_gap_ratio_40_median (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column income_gap_ratio_50_median (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column income_gap_ratio_60_median (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column income_gap_ratio_685 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column mean (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column median (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column middle40_share (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column mld (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column p50_p10_ratio (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column p90_p10_ratio (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column p90_p50_ratio (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column palma_ratio (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column polarization (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column poverty_gap_index_100 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column poverty_gap_index_1000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column poverty_gap_index_2000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column poverty_gap_index_215 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column poverty_gap_index_3000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column poverty_gap_index_365 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column poverty_gap_index_4000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column poverty_gap_index_40_median (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column poverty_gap_index_50_median (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column poverty_gap_index_60_median (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column poverty_gap_index_685 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column poverty_severity_100 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column poverty_severity_1000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column poverty_severity_2000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column poverty_severity_215 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column poverty_severity_3000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column poverty_severity_365 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column poverty_severity_4000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column poverty_severity_40_median (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column poverty_severity_50_median (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column poverty_severity_60_median (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column poverty_severity_685 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column reporting_level (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column s80_s20_ratio (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column surveys_past_decade (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column total_shortfall_100 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column total_shortfall_1000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column total_shortfall_2000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column total_shortfall_215 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column total_shortfall_3000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column total_shortfall_365 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column total_shortfall_4000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column total_shortfall_40_median (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column total_shortfall_50_median (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column total_shortfall_60_median (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column total_shortfall_685 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column watts_100 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column watts_1000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column watts_2000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column watts_215 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column watts_3000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column watts_365 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column watts_4000 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column watts_40_median (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column watts_50_median (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column watts_60_median (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column watts_685 (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
~ Column welfare_type (changed metadata)
+ + originUrl: https://ourworldindata.org/poverty
- - originUrl: https://ourworldindata.org/poverty
= Table income_consumption_2017_poverty_gap_index_215
= Table income_consumption_2017_income_gap_ratio_4000
= Table income_consumption_2017_avg_shortfall_4000
= Table income_consumption_2017_decile9_thr
= Table income_consumption_2017_p50_p10_ratio
= Table income_consumption_2017_avg_shortfall_215
= Table consumption_2017_decile4_share
= Table income_consumption_2017_decile1_share
= Table income_consumption_2017_p90_p50_ratio
= Table income_2017_decile8_avg
= Table income_2017_decile10_avg
= Table income_consumption_2017_decile8_thr
= Table income_2017_income_gap_ratio_4000
= Table income_2017_decile4_thr
= Table income_consumption_2017_poverty_gap_index_4000
= Table income_2017_income_gap_ratio_40_median
= Table income_2017_decile8_thr
= Table income_consumption_2017_avg_shortfall_3000
= Table income_2017_decile1_thr
= Table income_consumption_2017_middle40_share
= Table consumption_2017_total_shortfall_4000
= Table income_consumption_2017_total_shortfall_2000
= Table income_consumption_2017_headcount_40_median
=
...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: 2024-09-30 16:37:57 UTC |
paarriagadap
commented
Sep 18, 2024
pyproject.toml
Outdated
| @@ -64,13 +64,16 @@ cdsapi = "^0.7.0" | |||
| rioxarray = "^0.15.1" | |||
| html2text = "^2020.1.16" | |||
| pygithub = "^2.3.0" | |||
| pandas = "2.2.1" | |||
| pandas = "2.2.2" | |||
There was a problem hiding this comment.
@Marigold Hi! Is it fine if I update pandas and rapidfuzz? I need newer versions to run these oda-data and oda-reader functions
There was a problem hiding this comment.
Rapidfuzz is fine, but updating pandas is always tricky. Let me create a separate PR and make sure updating pandas doesn't change anything.
There was a problem hiding this comment.
@paarriagadap since the library is used only for creating the snapshot, it's fine if you don't include them in pyproject.toml (or keep them commented until we bump pandas version) and just install them with pip install oda_reader, run the snapshot once and then reinstall with poetry install. That should unblock you for the time being if you're in a hurry.
There was a problem hiding this comment.
Makes sense. Thanks @Marigold !
paarriagadap
force-pushed
the
oda-data-from-one
branch
from
bffd37a
to
16afe6e
Compare
paarriagadap
force-pushed
the
oda-data-from-one
branch
from
db5c108
to
b97985c
Compare
|
Hi @Marigold! I rebased this PR and it closed and... delete it? I don't quite understand what happened, maybe it's related to the pandas/uv update |
Hmm, that's weird. Let me know if you have details or if it happens again. I don't think it's related to the update, but one never knows... |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Main issue https://github.com/owid/owid-issues/issues/1620