📊 antibiotics: adding aggregated antimicrobial use data by class #3629
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data-diff: ❌ Found differences~ Dataset garden/antibiotics/2024-11-12/antimicrobial_usage
- - update_period_days: 308
? ^^
+ + update_period_days: 365
? ^^
= Table class
~ Column ddd (changed metadata)
- - Defined daily doses of <% if routeofadministration == "O" %> orally administered <% elif routeofadministration == "P" %> parentearally administered <% elif routeofadministration == "R" %> rectally administered4 <% elif routeofadministration == "I" %> inhaled <% endif %> << antimicrobialclass>> - << atc4name.lower() >> used
? ^^
+ + Defined daily doses of <% if routeofadministration == "O" %> orally administered <% elif routeofadministration == "P" %> parentearally administered <% elif routeofadministration == "R" %> rectally administered4 <% elif routeofadministration == "I" %> inhaled <% endif %> << antimicrobialclass.lower()>> - << atc4name.lower() >> used
? ^^^^^^^^^^
- - description_short: Volume of antimicrobials used in a given year.
+ + description_short: Total (#dod:defined-daily-doses) of antimicrobials used in a given year.
+ + display:
+ + numDecimalPlaces: 0
~ Column did (changed metadata)
- - description_short: Volume of antimicrobials used per 1000 inhabitants per day.
+ + description_short: Total (#dod:defined-daily-doses) of antimicrobials used per 1000 inhabitants per day.
+ + display:
+ + numDecimalPlaces: 1
= Table aware
~ Column ddd (changed metadata)
- - Volume of AWaRe category: << awarelabel >> antibiotics used in a given year. <% if aware == "A" %> Access antibiotics have activity against a wide range of common pathogens and show lower resistance potential than antibiotics in the other groups. <% elif aware == "W" %> Watch antibiotic have higher resistance potential and include most of the highest priority agents among the Critically Important Antimicrobials for Human Medicine and/or antibiotics that are at relatively high risk of bacterial resistance. <% elif aware == "R" %> Reserve antibiotics should be reserved for treatment of confirmed or suspected infections due to multi-drug-resistant organisms. Reserve group antibiotics should be treated as “last resort” options. <% elif aware == "O" %> The use of the Not classified/Not recommended antibiotics is not evidence-based, nor recommended in high-quality international guidelines. WHO does not recommend the use of these antibiotics in clinical practice. <% endif %>
? ^^^^^^^^^
+ + Total (#dod:defined-daily-doses) of AWaRe category: << awarelabel >> antibiotics used in a given year. <% if aware == "A" %> Access antibiotics have activity against a wide range of common pathogens and show lower resistance potential than antibiotics in the other groups. <% elif aware == "W" %> Watch antibiotic have higher resistance potential and include most of the highest priority agents among the Critically Important Antimicrobials for Human Medicine and/or antibiotics that are at relatively high risk of bacterial resistance. <% elif aware == "R" %> Reserve antibiotics should be reserved for treatment of confirmed or suspected infections due to multi-drug-resistant organisms. Reserve group antibiotics should be treated as “last resort” options. <% elif aware == "O" %> The use of the Not classified/Not recommended antibiotics is not evidence-based, nor recommended in high-quality international guidelines. WHO does not recommend the use of these antibiotics in clinical practice. <% endif %>
? ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+ + display:
+ + numDecimalPlaces: 0
~ Column did (changed metadata)
- - Volume of AWaRe category: <<awarelabel>> used per 1000 inhabitants per day. <% if aware == "A" %> Access antibiotics have activity against a wide range of common pathogens and show lower resistance potential than antibiotics in the other groups. <% elif aware == "W" %> Watch antibiotic have higher resistance potential and include most of the highest priority agents among the Critically Important Antimicrobials for Human Medicine and/or antibiotics that are at relatively high risk of bacterial resistance. <% elif aware == "R" %> Reserve antibiotics should be reserved for treatment of confirmed or suspected infections due to multi-drug-resistant organisms. Reserve group antibiotics should be treated as “last resort” options. <% elif aware == "O" %> The use of the Not classified/Not recommended antibiotics is not evidence-based, nor recommended in high-quality international guidelines. WHO does not recommend the use of these antibiotics in clinical practice. <% endif %>
? ^^^^^^^^^
+ + Total (#dod:defined-daily-doses) of AWaRe category: <<awarelabel>> used per 1000 inhabitants per day. <% if aware == "A" %> Access antibiotics have activity against a wide range of common pathogens and show lower resistance potential than antibiotics in the other groups. <% elif aware == "W" %> Watch antibiotic have higher resistance potential and include most of the highest priority agents among the Critically Important Antimicrobials for Human Medicine and/or antibiotics that are at relatively high risk of bacterial resistance. <% elif aware == "R" %> Reserve antibiotics should be reserved for treatment of confirmed or suspected infections due to multi-drug-resistant organisms. Reserve group antibiotics should be treated as “last resort” options. <% elif aware == "O" %> The use of the Not classified/Not recommended antibiotics is not evidence-based, nor recommended in high-quality international guidelines. WHO does not recommend the use of these antibiotics in clinical practice. <% endif %>
? ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+ + display:
+ + numDecimalPlaces: 1
+ + Table class_aggregated
+ + Column ddd_anti_malarials
+ + Column ddd_antibacterials_and_antituberculosis
+ + Column ddd_antifungals
+ + Column ddd_antituberculosis
+ + Column ddd_antivirals
+ + Column did_anti_malarials
+ + Column did_antibacterials_and_antituberculosis
+ + Column did_antifungals
+ + Column did_antituberculosis
+ + Column did_antivirals
= Dataset garden/artificial_intelligence/2024-11-03/epoch_regressions
= Table epoch_regressions
~ Dim days_since_1949
+ + New values: 12 / 874 (1.37%)
system days_since_1949
1.5x/year 547
1.5x/year 22080
2.0x/year 22280
2.4x/year 27670
4.1x/year 27670
- - Removed values: 12 / 874 (1.37%)
system days_since_1949
1.5x/year between 1950–2010 547
1.5x/year between 1950–2010 22080
2.0x/year between 2010–2025 22280
2.4x/year between 2010–2025 27670
4.1x/year between 2010–2025 27670
~ Dim system
+ + New values: 12 / 874 (1.37%)
days_since_1949 system
547 1.5x/year
22080 1.5x/year
22280 2.0x/year
27670 2.4x/year
27670 4.1x/year
- - Removed values: 12 / 874 (1.37%)
days_since_1949 system
547 1.5x/year between 1950–2010
22080 1.5x/year between 1950–2010
22280 2.0x/year between 2010–2025
27670 2.4x/year between 2010–2025
27670 4.1x/year between 2010–2025
~ Column domain (new data)
+ + New values: 12 / 874 (1.37%)
days_since_1949 system domain
547 1.5x/year NaN
22080 1.5x/year NaN
22280 2.0x/year NaN
27670 2.4x/year NaN
27670 4.1x/year NaN
- - Removed values: 12 / 874 (1.37%)
days_since_1949 system domain
547 1.5x/year between 1950–2010 NaN
22080 1.5x/year between 1950–2010 NaN
22280 2.0x/year between 2010–2025 NaN
27670 2.4x/year between 2010–2025 NaN
27670 4.1x/year between 2010–2025 NaN
~ Column organization_categorization (new data)
+ + New values: 12 / 874 (1.37%)
days_since_1949 system organization_categorization
547 1.5x/year NaN
22080 1.5x/year NaN
22280 2.0x/year NaN
27670 2.4x/year NaN
27670 4.1x/year NaN
- - Removed values: 12 / 874 (1.37%)
days_since_1949 system organization_categorization
547 1.5x/year between 1950–2010 NaN
22080 1.5x/year between 1950–2010 NaN
22280 2.0x/year between 2010–2025 NaN
27670 2.4x/year between 2010–2025 NaN
27670 4.1x/year between 2010–2025 NaN
~ Column parameters (new data, changed data)
+ + New values: 12 / 874 (1.37%)
days_since_1949 system parameters
547 1.5x/year <NA>
22080 1.5x/year <NA>
22280 2.0x/year 577927.0625
27670 2.4x/year <NA>
27670 4.1x/year <NA>
- - Removed values: 12 / 874 (1.37%)
days_since_1949 system parameters
547 1.5x/year between 1950–2010 <NA>
22080 1.5x/year between 1950–2010 <NA>
22280 2.0x/year between 2010–2025 577927.0625
27670 2.4x/year between 2010–2025 <NA>
27670 4.1x/year between 2010–2025 <NA>
~ Column publication_date (new data)
+ + New values: 12 / 874 (1.37%)
days_since_1949 system publication_date
547 1.5x/year NaT
22080 1.5x/year NaT
22280 2.0x/year NaT
27670 2.4x/year NaT
27670 4.1x/year NaT
- - Removed values: 12 / 874 (1.37%)
days_since_1949 system publication_date
547 1.5x/year between 1950–2010 NaT
22080 1.5x/year between 1950–2010 NaT
22280 2.0x/year between 2010–2025 NaT
27670 2.4x/year between 2010–2025 NaT
27670 4.1x/year between 2010–2025 NaT
~ Column training_computation_petaflop (new data, changed data)
+ + New values: 12 / 874 (1.37%)
days_since_1949 system training_computation_petaflop
547 1.5x/year 0.0
22080 1.5x/year 0.246361
22280 2.0x/year <NA>
27670 2.4x/year <NA>
27670 4.1x/year 466953248.0
- - Removed values: 12 / 874 (1.37%)
days_since_1949 system training_computation_petaflop
547 1.5x/year between 1950–2010 0.0
22080 1.5x/year between 1950–2010 0.246361
22280 2.0x/year between 2010–2025 <NA>
27670 2.4x/year between 2010–2025 <NA>
27670 4.1x/year between 2010–2025 466952832.0
~ Column training_dataset_size__datapoints (new data, changed data)
+ + New values: 12 / 874 (1.37%)
days_since_1949 system training_dataset_size__datapoints
547 1.5x/year <NA>
22080 1.5x/year <NA>
22280 2.0x/year <NA>
27670 2.4x/year 60797116416.0
27670 4.1x/year <NA>
- - Removed values: 12 / 874 (1.37%)
days_since_1949 system training_dataset_size__datapoints
547 1.5x/year between 1950–2010 <NA>
22080 1.5x/year between 1950–2010 <NA>
22280 2.0x/year between 2010–2025 <NA>
27670 2.4x/year between 2010–2025 60797116416.0
27670 4.1x/year between 2010–2025 <NA>
= Dataset garden/health/latest/global_health_mpox
= Table global_health_mpox
~ Dim country
- - Removed values: 1 / 138 (0.72%)
date country
2024-11-10 Rwanda
~ Dim date
- - Removed values: 1 / 138 (0.72%)
country date
Rwanda 2024-11-10
~ Column reported_cases (changed data)
- - Removed values: 1 / 138 (0.72%)
country date reported_cases
Rwanda 2024-11-10 153
~ Column suspected_cases_cumulative (changed data)
- - Removed values: 1 / 138 (0.72%)
country date suspected_cases_cumulative
Rwanda 2024-11-10 4078
= Dataset garden/ophi/2024-10-28/multidimensional_poverty_index
= Table multidimensional_poverty_index
~ Column censored_headcount_ratio (changed metadata)
- - Multidimensional poverty is defined as being deprived in a range of health, education and living standards indicators. This is the share of the multidimensionally poor population deprived in the indicator _<<indicator.lower()>>_.<% if area == "Urban" %>
? - -
+ + Multidimensional poverty is defined as being deprived in a range of health, education and living standards indicators. This is the share of the multidimensionally poor population deprived in the indicator <<indicator.lower()>>.<% if area == "Urban" %>
- - Being in multidimensional poverty means that a person lives in a household deprived in a third or more of ten indicators, grouped into three dimensions of well-being: **health** (using two indicators: nutrition, child mortality), **education** (using two indicators: years of schooling, school attendance), and **living standards** (using six indicators: cooking fuel, sanitation, drinking water, electricity, housing, assets).
+ + Being _MPI poor_ means that a person lives in a household deprived in a third or more of ten indicators, grouped into three dimensions of well-being: **health** (using two indicators: nutrition, child mortality), **education** (using two indicators: years of schooling, school attendance), and **living standards** (using five indicators: cooking fuel, sanitation, drinking water, electricity, housing, assets).
- - This indicator is a current margin estimate (CME), meaning that it relies on the most recent survey data available for each country.
+ + This indicator is a current margin estimate (CME), based on the most recent survey data available for each country. Look for the harmonized over time (HOT) estimate to see trends over time.
- - This indicator is a harmonized over time (HOT) estimate. This harmonization seeks to make two or more MPI estimates comparable by aligning the indicator definitions in each survey.
+ + This indicator is a harmonized over time (HOT) estimate. This harmonization seeks to make two or more MPI estimates comparable by aligning the indicator definitions in each survey. Look for the current margin estimate (CME) to see the most recent survey data.
? +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+ + title_variant: <<area>>, <<flavor>>
- - title_variant: |-
- - <% if flavor == "Current margin estimate" %>
- - Most recent year
- - <% elif flavor == "Harmonized over time" %>
- - Harmonized over time
- - <%- endif -%><% if area == "Urban" %>
- - , Urban area
- - <% elif area == "Rural" %>
- - , Rural area
- - <% elif area == "Camp" %>
- - , Refugee camps
- - <%- endif -%>
~ Column headcount_ratio (changed metadata)
- - Being in multidimensional poverty means that a person lives in a household deprived in a third or more of ten indicators, grouped into three dimensions of well-being: **health** (using two indicators: nutrition, child mortality), **education** (using two indicators: years of schooling, school attendance), and **living standards** (using six indicators: cooking fuel, sanitation, drinking water, electricity, housing, assets).
+ + Being _MPI poor_ means that a person lives in a household deprived in a third or more of ten indicators, grouped into three dimensions of well-being: **health** (using two indicators: nutrition, child mortality), **education** (using two indicators: years of schooling, school attendance), and **living standards** (using five indicators: cooking fuel, sanitation, drinking water, electricity, housing, assets).
+ + <% if flavor == "Current margin estimate" %>
+ + This indicator is a current margin estimate (CME), based on the most recent survey data available for each country. Look for the harmonized over time (HOT) estimate to see trends over time.
- - <% set cme_link = "https://ourworldindata.org/grapher/share-multi-poverty" %> <% set hot_link = "https://ourworldindata.org/grapher/share-of-population-multidimensionally-poor-hot" %><% if flavor == "Current margin estimate" %>
- - This indicator is a current margin estimate (CME), meaning that it relies on the most recent survey data available for each country.<% if flavor == "Current margin estimate" and area == "National" %>
- - Look for the (<<hot_link>>) to see trends over time.
- - <% elif flavor == "Harmonized over time" and area == "National" %>
- - Look for the (<<cme_link>>) to see the most recent survey data.
- - <%- endif -%>
+ + This indicator is a harmonized over time (HOT) estimate. This harmonization seeks to make two or more MPI estimates comparable by aligning the indicator definitions in each survey. Look for the current margin estimate (CME) to see the most recent survey data.
- - This indicator is a harmonized over time (HOT) estimate. This harmonization seeks to make two or more MPI estimates comparable by aligning the indicator definitions in each survey.<% if flavor == "Current margin estimate" and area == "National" %>
- - Look for the (<<hot_link>>) to see trends over time.
- - <% elif flavor == "Harmonized over time" and area == "National" %>
- - Look for the (<<cme_link>>) to see the most recent survey data.
- - <%- endif -%>
+ + title_variant: <<area>>, <<flavor>>
- - title_variant: |-
- - <% if flavor == "Current margin estimate" %>
- - Most recent year
- - <% elif flavor == "Harmonized over time" %>
- - Harmonized over time
- - <%- endif -%><% if area == "Urban" %>
- - , Urban area
- - <% elif area == "Rural" %>
- - , Rural area
- - <% elif area == "Camp" %>
- - , Refugee camps
- - <%- endif -%>
~ Column intensity (changed metadata)
- - Being in multidimensional poverty means that a person lives in a household deprived in a third or more of ten indicators, grouped into three dimensions of well-being: **health** (using two indicators: nutrition, child mortality), **education** (using two indicators: years of schooling, school attendance), and **living standards** (using six indicators: cooking fuel, sanitation, drinking water, electricity, housing, assets).
+ + Being _MPI poor_ means that a person lives in a household deprived in a third or more of ten indicators, grouped into three dimensions of well-being: **health** (using two indicators: nutrition, child mortality), **education** (using two indicators: years of schooling, school attendance), and **living standards** (using five indicators: cooking fuel, sanitation, drinking water, electricity, housing, assets).
+ + <% if flavor == "Current margin estimate" %>
+ + This indicator is a current margin estimate (CME), based on the most recent survey data available for each country. Look for the harmonized over time (HOT) estimate to see trends over time.
- - <% set cme_link = "https://ourworldindata.org/grapher/intensity-of-multidimensional-poverty" %> <% set hot_link = "https://ourworldindata.org/grapher/intensity-of-multidimensional-poverty-hot" %><% if flavor == "Current margin estimate" %>
- - This indicator is a current margin estimate (CME), meaning that it relies on the most recent survey data available for each country.<% if flavor == "Current margin estimate" and area == "National" %>
- - Look for the (<<hot_link>>) to see trends over time.
- - <% elif flavor == "Harmonized over time" and area == "National" %>
- - Look for the (<<cme_link>>) to see the most recent survey data.
- - <%- endif -%>
+ + This indicator is a harmonized over time (HOT) estimate. This harmonization seeks to make two or more MPI estimates comparable by aligning the indicator definitions in each survey. Look for the current margin estimate (CME) to see the most recent survey data.
- - This indicator is a harmonized over time (HOT) estimate. This harmonization seeks to make two or more MPI estimates comparable by aligning the indicator definitions in each survey.<% if flavor == "Current margin estimate" and area == "National" %>
- - Look for the (<<hot_link>>) to see trends over time.
- - <% elif flavor == "Harmonized over time" and area == "National" %>
- - Look for the (<<cme_link>>) to see the most recent survey data.
- - <%- endif -%>
+ + title_variant: <<area>>, <<flavor>>
- - title_variant: |-
- - <% if flavor == "Current margin estimate" %>
- - Most recent year
- - <% elif flavor == "Harmonized over time" %>
- - Harmonized over time
- - <%- endif -%><% if area == "Urban" %>
- - , Urban area
- - <% elif area == "Rural" %>
- - , Rural area
- - <% elif area == "Camp" %>
- - , Refugee camps
- - <%- endif -%>
~ Column mpi (changed metadata)
- - The Multidimensional Poverty Index (MPI) is calculated by multiplying two values: the (https://ourworldindata.org/grapher/share-multi-poverty) and the (https://ourworldindata.org/grapher/intensity-of-multidimensional-poverty-national).
+ + The Multidimensional Poverty Index (MPI) is calculated by multiplying two values: the share of people who are multidimensionally poor and the intensity of their poverty.
- - Being in multidimensional poverty means that a person lives in a household deprived in a third or more of ten indicators, grouped into three dimensions of well-being: **health** (using two indicators: nutrition, child mortality), **education** (using two indicators: years of schooling, school attendance), and **living standards** (using six indicators: cooking fuel, sanitation, drinking water, electricity, housing, assets).
+ + Being _MPI poor_ means that a person lives in a household deprived in a third or more of ten indicators, grouped into three dimensions of well-being: **health** (using two indicators: nutrition, child mortality), **education** (using two indicators: years of schooling, school attendance), and **living standards** (using five indicators: cooking fuel, sanitation, drinking water, electricity, housing, assets).
+ + <% if flavor == "Current margin estimate" %>
+ + This indicator is a current margin estimate (CME), based on the most recent survey data available for each country. Look for the harmonized over time (HOT) estimate to see trends over time.
- - <% set cme_link = "https://ourworldindata.org/grapher/multidimensional-poverty-index-mpi" %> <% set hot_link = "https://ourworldindata.org/grapher/multidimensional-poverty-index-mpi-hot" %><% if flavor == "Current margin estimate" %>
- - This indicator is a current margin estimate (CME), meaning that it relies on the most recent survey data available for each country.<% if flavor == "Current margin estimate" and area == "National" %>
- - Look for the (<<hot_link>>) to see trends over time.
- - <% elif flavor == "Harmonized over time" and area == "National" %>
- - Look for the (<<cme_link>>) to see the most recent survey data.
- - <%- endif -%>
+ + This indicator is a harmonized over time (HOT) estimate. This harmonization seeks to make two or more MPI estimates comparable by aligning the indicator definitions in each survey. Look for the current margin estimate (CME) to see the most recent survey data.
- - This indicator is a harmonized over time (HOT) estimate. This harmonization seeks to make two or more MPI estimates comparable by aligning the indicator definitions in each survey.<% if flavor == "Current margin estimate" and area == "National" %>
- - Look for the (<<hot_link>>) to see trends over time.
- - <% elif flavor == "Harmonized over time" and area == "National" %>
- - Look for the (<<cme_link>>) to see the most recent survey data.
- - <%- endif -%>
+ + title_variant: <<area>>, <<flavor>>
- - title_variant: |-
- - <% if flavor == "Current margin estimate" %>
- - Most recent year
- - <% elif flavor == "Harmonized over time" %>
- - Harmonized over time
- - <%- endif -%><% if area == "Urban" %>
- - , Urban area
- - <% elif area == "Rural" %>
- - , Rural area
- - <% elif area == "Camp" %>
- - , Refugee camps
- - <%- endif -%>
~ Column severe (changed metadata)
- - Being in _severe_ multidimensional poverty means that a person lives in a household deprived in 50% or more of ten indicators, grouped into three dimensions of well-being: **health** (using two indicators: nutrition, child mortality), **education** (using two indicators: years of schooling, school attendance), and **living standards** (using six indicators: cooking fuel, sanitation, drinking water, electricity, housing, assets).
? ^^^
+ + Being in _severe_ multidimensional poverty means that a person lives in a household deprived in 50% or more of ten indicators, grouped into three dimensions of well-being: **health** (using two indicators: nutrition, child mortality), **education** (using two indicators: years of schooling, school attendance), and **living standards** (using five indicators: cooking fuel, sanitation, drinking water, electricity, housing, assets).
? ^^^^
- - This indicator is a current margin estimate (CME), meaning that it relies on the most recent survey data available for each country.
+ + This indicator is a current margin estimate (CME), based on the most recent survey data available for each country. Look for the harmonized over time (HOT) estimate to see trends over time.
- - This indicator is a harmonized over time (HOT) estimate. This harmonization seeks to make two or more MPI estimates comparable by aligning the indicator definitions in each survey.
+ + This indicator is a harmonized over time (HOT) estimate. This harmonization seeks to make two or more MPI estimates comparable by aligning the indicator definitions in each survey. Look for the current margin estimate (CME) to see the most recent survey data.
? +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+ + title_variant: <<area>>, <<flavor>>
- - title_variant: |-
- - <% if flavor == "Current margin estimate" %>
- - Most recent year
- - <% elif flavor == "Harmonized over time" %>
- - Harmonized over time
- - <%- endif -%><% if area == "Urban" %>
- - , Urban area
- - <% elif area == "Rural" %>
- - , Rural area
- - <% elif area == "Camp" %>
- - , Refugee camps
- - <%- endif -%>
~ Column uncensored_headcount_ratio (changed metadata)
- - Multidimensional poverty is defined as being deprived in a range of health, education and living standards indicators. This is the share of the population deprived in the indicator _<<indicator.lower()>>_.<% if area == "Urban" %>
? - -
+ + Multidimensional poverty is defined as being deprived in a range of health, education and living standards indicators. This is the share of the population deprived in the indicator <<indicator.lower()>>.<% if area == "Urban" %>
- - Being in multidimensional poverty means that a person lives in a household deprived in a third or more of ten indicators, grouped into three dimensions of well-being: **health** (using two indicators: nutrition, child mortality), **education** (using two indicators: years of schooling, school attendance), and **living standards** (using six indicators: cooking fuel, sanitation, drinking water, electricity, housing, assets).
+ + Being _MPI poor_ means that a person lives in a household deprived in a third or more of ten indicators, grouped into three dimensions of well-being: **health** (using two indicators: nutrition, child mortality), **education** (using two indicators: years of schooling, school attendance), and **living standards** (using five indicators: cooking fuel, sanitation, drinking water, electricity, housing, assets).
- - This indicator is a current margin estimate (CME), meaning that it relies on the most recent survey data available for each country.
+ + This indicator is a current margin estimate (CME), based on the most recent survey data available for each country. Look for the harmonized over time (HOT) estimate to see trends over time.
- - This indicator is a harmonized over time (HOT) estimate. This harmonization seeks to make two or more MPI estimates comparable by aligning the indicator definitions in each survey.
+ + This indicator is a harmonized over time (HOT) estimate. This harmonization seeks to make two or more MPI estimates comparable by aligning the indicator definitions in each survey. Look for the current margin estimate (CME) to see the most recent survey data.
? +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+ + title_variant: <<area>>, <<flavor>>
- - title_variant: |-
- - <% if flavor == "Current margin estimate" %>
- - Most recent year
- - <% elif flavor == "Harmonized over time" %>
- - Harmonized over time
- - <%- endif -%><% if area == "Urban" %>
- - , Urban area
- - <% elif area == "Rural" %>
- - , Rural area
- - <% elif area == "Camp" %>
- - , Refugee camps
- - <%- endif -%>
~ Column vulnerable (changed metadata)
- - Being _vulnerable_ to multidimensional poverty means that a person lives in a household deprived in 20-33.3% of ten indicators, grouped into three dimensions of well-being: **health** (using two indicators: nutrition, child mortality), **education** (using two indicators: years of schooling, school attendance), and **living standards** (using six indicators: cooking fuel, sanitation, drinking water, electricity, housing, assets).
? ^^^
+ + Being _vulnerable_ to multidimensional poverty means that a person lives in a household deprived in 20-33.3% of ten indicators, grouped into three dimensions of well-being: **health** (using two indicators: nutrition, child mortality), **education** (using two indicators: years of schooling, school attendance), and **living standards** (using five indicators: cooking fuel, sanitation, drinking water, electricity, housing, assets).
? ^^^^
- - This indicator is a current margin estimate (CME), meaning that it relies on the most recent survey data available for each country.
+ + This indicator is a current margin estimate (CME), based on the most recent survey data available for each country. Look for the harmonized over time (HOT) estimate to see trends over time.
- - This indicator is a harmonized over time (HOT) estimate. This harmonization seeks to make two or more MPI estimates comparable by aligning the indicator definitions in each survey.
+ + This indicator is a harmonized over time (HOT) estimate. This harmonization seeks to make two or more MPI estimates comparable by aligning the indicator definitions in each survey. Look for the current margin estimate (CME) to see the most recent survey data.
? +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+ + title_variant: <<area>>, <<flavor>>
- - title_variant: |-
- - <% if flavor == "Current margin estimate" %>
- - Most recent year
- - <% elif flavor == "Harmonized over time" %>
- - Harmonized over time
- - <%- endif -%><% if area == "Urban" %>
- - , Urban area
- - <% elif area == "Rural" %>
- - , Rural area
- - <% elif area == "Camp" %>
- - , Refugee camps
- - <%- endif -%>
= Dataset garden/who/2023-06-01/cholera
= Table cholera
~ Column cholera_case_fatality_rate (changed data)
~ Changed values: 2 / 2992 (0.07%)
country year cholera_case_fatality_rate - cholera_case_fatality_rate +
Somalia 2017 1.34 1.33
Africa 2017 1.79053 1.788862
~ Column cholera_deaths (changed data)
~ Changed values: 3 / 2992 (0.10%)
country year cholera_deaths - cholera_deaths +
Somalia 2017 1007 1004
World 2017 5650 5654
Africa 2017 3220 3217
= Dataset garden/who/2024-07-30/ghe
= Table ghe
~ Column daly_count (changed metadata)
- - <% if age_group == "ALLAges" %>
+ + <%- if age_group == "ALLAges" -%>
? + +
- - DALYs from << cause.lower() >> among <% if sex == "Both sexes" %>both sexes<% elif sex == "Male" %>males<% elif sex == "Female" %>females<% endif %>
+ + DALYs from << cause.lower() >> among <%- if sex == "Both sexes" %>both sexes<% elif sex == "Male" %>males<% elif sex == "Female" %>females<% endif -%>
? + +
- - <%- elif age_group == "Age-standardized" %>
+ + <%- elif age_group == "Age-standardized" -%>
? +
- - Age-standardized DALYs from << cause.lower() >> among <% if sex == "Both sexes" %>both sexes<% elif sex == "Male" %>males<% elif sex == "Female" %>females<% endif %>
+ + Age-standardized DALYs from << cause.lower() >> among <%- if sex == "Both sexes" %>both sexes<% elif sex == "Male" %>males<% elif sex == "Female" %>females<% endif -%>
? + +
- - <%- else %>
+ + <%- else -%>
? +
- - DALYs from << cause.lower() >> among <% if sex == "Both sexes" %>both sexes<% elif sex == "Male" %>males<% elif sex == "Female" %>females<% endif %> aged <% if age_group == "ALLAges" %>
+ + DALYs from << cause.lower() >> among <%- if sex == "Both sexes" %>both sexes<% elif sex == "Male" %>males<% elif sex == "Female" %>females<% endif -%> aged <%- if age_group == "ALLAges" -%>
? + + + +
- - <%- elif age_group == "age-standardized" %>
+ + <%- elif age_group == "age-standardized" -%>
? +
- - <%- elif age_group == "YEARS0-14" %>
+ + <%- elif age_group == "YEARS0-14" -%>
? +
- - <%- elif age_group == "YEARS0-4" %>
+ + <%- elif age_group == "YEARS0-4" -%>
? +
- - <%- elif age_group == "YEARS5-14" %>
+ + <%- elif age_group == "YEARS5-14" -%>
? +
- - <%- elif age_group == "YEARS15-19" %>
+ + <%- elif age_group == "YEARS15-19" -%>
? +
- - <%- elif age_group == "YEARS15-49" %>
+ + <%- elif age_group == "YEARS15-49" -%>
? +
- - <%- elif age_group == "YEARS20-24" %>
+ + <%- elif age_group == "YEARS20-24" -%>
? +
- - <%- elif age_group == "YEARS25-34" %>
+ + <%- elif age_group == "YEARS25-34" -%>
? +
- - <%- elif age_group == "YEARS35-44" %>
+ + <%- elif age_group == "YEARS35-44" -%>
? +
- - <%- elif age_group == "YEARS45-54" %>
+ + <%- elif age_group == "YEARS45-54" -%>
? +
- - <%- elif age_group == "YEARS50-69" %>
+ + <%- elif age_group == "YEARS50-69" -%>
? +
- - <%- elif age_group == "YEARS55-64" %>
+ + <%- elif age_group == "YEARS55-64" -%>
? +
- - <%- elif age_group == "YEARS65-74" %>
+ + <%- elif age_group == "YEARS65-74" -%>
? +
- - <%- elif age_group == "YEARS70+" %>
+ + <%- elif age_group == "YEARS70+" -%>
? +
- - <%- elif age_group == "YEARS75-84" %>
+ + <%- elif age_group == "YEARS75-84" -%>
? +
- - <%- elif age_group == "YEARS85PLUS" %>
+ + <%- elif age_group == "YEARS85PLUS" -%>
? +
- - <%- endif %>
+ + <%- endif -%>
? +
- - <%- endif %>
+ + <%- endif -%>
? +
- - <% if age_group == "ALLAges" %>
+ + <%- if age_group == "ALLAges" -%>
? + +
- - Estimated number of [DALYs](#dod:dalys) from << cause.lower() >> in <% if sex == "Both sexes" %>both sexes<% elif sex == "Male" %>males<% elif sex == "Female" %>females<% endif %>.
+ + Estimated number of [DALYs](#dod:dalys) from << cause.lower() >> in <%- if sex == "Both sexes" %>both sexes<% elif sex == "Male" %>males<% elif sex == "Female" %>females<% endif -%>.
? + +
- - <%- elif age_group == "Age-standardized" %>
+ + <%- elif age_group == "Age-standardized" -%>
? +
- - Estimated number of age-standardized [DALYs](#dod:dalys) from << cause.lower() >> in <% if sex == "Both sexes" %>both sexes<% elif sex == "Male" %>males<% elif sex == "Female" %>females<% endif %>.
? ^^^^^^^^^^
+ + Estimated number of age-standardized [DALYs](#dod:dalys) from << cause.lower() >> in <%- if sex == "Both sexes" %>both sexes<% elif sex == "Male" %>males<% elif sex == "Female" %>females<% endif -%>.
? ^^^^^^^^^^^ +
- - <%- else %>
+ + <%- else -%>
? +
- - Estimated number of [DALYs](#dod:dalys) from << cause.lower() >> among <% if sex == "Both sexes" %>both sexes<% elif sex == "Male" %>males<% elif sex == "Female" %>females<% endif %> aged <% if age_group == "ALLAges" %>
? ^^^^^^^^^^ ^^^^^^^^^^^^^
+ + Estimated number of [DALYs](#dod:dalys) from << cause.lower() >> among <%- if sex == "Both sexes" %>both sexes<% elif sex == "Male" %>males<% elif sex == "Female" %>females<% endif -%> aged <%- if age_group == "ALLAges" -%>
? ^^^^^^^^^^^ ^^^^^^^^^^^^^^^ +
- - <%- elif age_group == "age-standardized" %>
+ + <%- elif age_group == "age-standardized" -%>
? +
- - <%- elif age_group == "YEARS0-14" %>
+ + <%- elif age_group == "YEARS0-14" -%>
? +
- - <%- elif age_group == "YEARS0-4" %>
+ + <%- elif age_group == "YEARS0-4" -%>
? +
- - <%- elif age_group == "YEARS5-14" %>
+ + <%- elif age_group == "YEARS5-14" -%>
? +
- - <%- elif age_group == "YEARS15-19" %>
+ + <%- elif age_group == "YEARS15-19" -%>
? +
- - <%- elif age_group == "YEARS15-49" %>
+ + <%- elif age_group == "YEARS15-49" -%>
? +
- - <%- elif age_group == "YEARS20-24" %>
+ + <%- elif age_group == "YEARS20-24" -%>
? +
- - <%- elif age_group == "YEARS25-34" %>
+ + <%- elif age_group == "YEARS25-34" -%>
? +
- - <%- elif age_group == "YEARS35-44" %>
+ + <%- elif age_group == "YEARS35-44" -%>
? +
- - <%- elif age_group == "YEARS45-54" %>
+ + <%- elif age_group == "YEARS45-54" -%>
? +
- - <%- elif age_group == "YEARS50-69" %>
+ + <%- elif age_group == "YEARS50-69" -%>
? +
- - <%- elif age_group == "YEARS55-64" %>
+ + <%- elif age_group == "YEARS55-64" -%>
? +
- - <%- elif age_group == "YEARS65-74" %>
+ + <%- elif age_group == "YEARS65-74" -%>
? +
- - <%- elif age_group == "YEARS70+" %>
+ + <%- elif age_group == "YEARS70+" -%>
? +
- - <%- elif age_group == "YEARS75-84" %>
+ + <%- elif age_group == "YEARS75-84" -%>
? +
- - <%- elif age_group == "YEARS85PLUS" %>
+ + <%- elif age_group == "YEARS85PLUS" -%>
? +
- - <%- endif %>.
+ + <%- endif -%>.
? +
- - <%- endif %>
+ + <%- endif -%>
? +
- - <% if age == "Age-standardized" %>To allow for comparisons between countries and over time, this metric is (#dod:age_standardized).<% endif %>
+ + <%- if age == "Age-standardized" -%>To allow for comparisons between countries and over time, this metric is (#dod:age_standardized).<%- endif -%>
? + + + +
~ Column daly_rate100k (changed metadata)
- - <% if age_group == "ALLAges" %>
+ + <%- if age_group == "ALLAges" -%>
? + +
- - DALYs from << cause.lower() >>, among <% if sex == "Both sexes" %>both sexes<% elif sex == "Male" %>males<% elif sex == "Female" %>females<% endif %> per 100,000 people
+ + DALYs from << cause.lower() >>, among <%- if sex == "Both sexes" %>both sexes<% elif sex == "Male" %>males<% elif sex == "Female" %>females<% endif -%> per 100,000 people
? + +
- - <%- elif age_group == "Age-standardized" %>
+ + <%- elif age_group == "Age-standardized" -%>
? +
- - Age-standardized DALYs from << cause.lower() >> among <% if sex == "Both sexes" %>both sexes<% elif sex == "Male" %>males<% elif sex == "Female" %>females<% endif %>, per 100,000 people
+ + Age-standardized DALYs from << cause.lower() >> among <%- if sex == "Both sexes" %>both sexes<% elif sex == "Male" %>males<% elif sex == "Female" %>females<% endif -%>, per 100,000 people
? + +
- - <%- else %>
+ + <%- else -%>
? +
- - DALYs from << cause.lower() >> among <% if sex == "Both sexes" %>both sexes<% elif sex == "Male" %>males<% elif sex == "Female" %>females<% endif %> aged <% if age_group == "ALLAges" %>
+ + DALYs from << cause.lower() >> among <%- if sex == "Both sexes" %>both sexes<% elif sex == "Male" %>males<% elif sex == "Female" %>females<% endif -%> aged <%- if age_group == "ALLAges" -%>
? + + + +
- - <%- elif age_group == "age-standardized" %>
+ + <%- elif age_group == "age-standardized" -%>
? +
- - <%- elif age_group == "YEARS0-14" %>
+ + <%- elif age_group == "YEARS0-14" -%>
? +
- - <%- elif age_group == "YEARS0-4" %>
+ + <%- elif age_group == "YEARS0-4" -%>
? +
- - <%- elif age_group == "YEARS5-14" %>
+ + <%- elif age_group == "YEARS5-14" -%>
? +
- - <%- elif age_group == "YEARS15-19" %>
+ + <%- elif age_group == "YEARS15-19" -%>
? +
- - <%- elif age_group == "YEARS15-49" %>
+ + <%- elif age_group == "YEARS15-49" -%>
? +
- - <%- elif age_group == "YEARS20-24" %>
+ + <%- elif age_group == "YEARS20-24" -%>
? +
- - <%- elif age_group == "YEARS25-34" %>
+ + <%- elif age_group == "YEARS25-34" -%>
? +
- - <%- elif age_group == "YEARS35-44" %>
+ + <%- elif age_group == "YEARS35-44" -%>
? +
- - <%- elif age_group == "YEARS45-54" %>
+ + <%- elif age_group == "YEARS45-54" -%>
? +
- - <%- elif age_group == "YEARS50-69" %>
+ + <%- elif age_group == "YEARS50-69" -%>
? +
- - <%- elif age_group == "YEARS55-64" %>
+ + <%- elif age_group == "YEARS55-64" -%>
? +
- - <%- elif age_group == "YEARS65-74" %>
+ + <%- elif age_group == "YEARS65-74" -%>
? +
- - <%- elif age_group == "YEARS70+" %>
+ + <%- elif age_group == "YEARS70+" -%>
? +
- - <%- elif age_group == "YEARS75-84" %>
+ + <%- elif age_group == "YEARS75-84" -%>
? +
- - <%- elif age_group == "YEARS85PLUS" %>
+ + <%- elif age_group == "YEARS85PLUS" -%>
? +
- - <%- endif %>, per 100,000 people
+ + <%- endif -%>, per 100,000 people
? +
- - <%- endif %>
+ + <%- endif -%>
? +
- - <% if age_group == "ALLAges" %>
+ + <%- if age_group == "ALLAges" -%>
? + +
- - Estimated number of [DALYs](#dod:dalys) from << cause.lower() >> in <% if sex == "Both sexes" %>both sexes<% elif sex == "Male" %>males<% elif sex == "Female" %>females<% endif %>, per 100,000 people.
? ^^^^^^^^^^
+ + Estimated number of [DALYs](#dod:dalys) from << cause.lower() >> in <%- if sex == "Both sexes" %>both sexes<% elif sex == "Male" %>males<% elif sex == "Female" %>females<% endif -%>, per 100,000 people.
? ^^^^^^^^^^^ +
- - <%- elif age_group == "Age-standardized" %>
+ + <%- elif age_group == "Age-standardized" -%>
? +
- - Estimated number of age-standardized [DALYs](#dod:dalys) from << cause.lower() >> in <% if sex == "Both sexes" %>both sexes<% elif sex == "Male" %>males<% elif sex == "Female" %>females<% endif %>, per 100,000 people.
? ^^^^^^^^^^
+ + Estimated number of age-standardized [DALYs](#dod:dalys) from << cause.lower() >> in <%- if sex == "Both sexes" %>both sexes<% elif sex == "Male" %>males<% elif sex == "Female" %>females<% endif -%>, per 100,000 people.
? ^^^^^^^^^^^ +
- - <%- else %>
+ + <%- else -%>
? +
- - Estimated number of [DALYs](#dod:dalys) from << cause.lower() >> among <% if sex == "Both sexes" %>both sexes<% elif sex == "Male" %>males<% elif sex == "Female" %>females<% endif %> aged <% if age_group == "ALLAges" %>
? ^^^^^^^^^^ ^^^^^^^^^^^^^
+ + Estimated number of [DALYs](#dod:dalys) from << cause.lower() >> among <%- if sex == "Both sexes" %>both sexes<% elif sex == "Male" %>males<% elif sex == "Female" %>females<% endif -%> aged <%- if age_group == "ALLAges" -%>
? ^^^^^^^^^^^ ^^^^^^^^^^^^^^^ +
- - <%- elif age_group == "age-standardized" %>
+ + <%- elif age_group == "age-standardized" -%>
? +
- - <%- elif age_group == "YEARS0-14" %>
+ + <%- elif age_group == "YEARS0-14" -%>
? +
- - <%- elif age_group == "YEARS0-4" %>
+ + <%- elif age_group == "YEARS0-4" -%>
? +
- - <%- elif age_group == "YEARS5-14" %>
+ + <%- elif age_group == "YEARS5-14" -%>
? +
- - <%- elif age_group == "YEARS15-19" %>
+ + <%- elif age_group == "YEARS15-19" -%>
? +
- - <%- elif age_group == "YEARS15-49" %>
+ + <%- elif age_group == "YEARS15-49" -%>
? +
- - <%- elif age_group == "YEARS20-24" %>
+ + <%- elif age_group == "YEARS20-24" -%>
? +
- - <%- elif age_group == "YEARS25-34" %>
+ + <%- elif age_group == "YEARS25-34" -%>
? +
- - <%- elif age_group == "YEARS35-44" %>
+ + <%- elif age_group == "YEARS35-44" -%>
? +
- - <%- elif age_group == "YEARS45-54" %>
+ + <%- elif age_group == "YEARS45-54" -%>
? +
- - <%- elif age_group == "YEARS50-69" %>
+ + <%- elif age_group == "YEARS50-69" -%>
? +
- - <%- elif age_group == "YEARS55-64" %>
+ + <%- elif age_group == "YEARS55-64" -%>
? +
- - <%- elif age_group == "YEARS65-74" %>
+ + <%- elif age_group == "YEARS65-74" -%>
? +
- - <%- elif age_group == "YEARS70+" %>
+ + <%- elif age_group == "YEARS70+" -%>
? +
- - <%- elif age_group == "YEARS75-84" %>
+ + <%- elif age_group == "YEARS75-84" -%>
? +
- - <%- elif age_group == "YEARS85PLUS" %>
+ + <%- elif age_group == "YEARS85PLUS" -%>
? +
- - <%- endif %>, per 100,000 people.
+ + <%- endif -%>, per 100,000 people.
? +
- - <%- endif %>
+ + <%- endif -%>
? +
- - <% if age == "Age-standardized" %>To allow for comparisons between countries and over time, this metric is (#dod:age_standardized).<% endif %>
+ + <%- if age == "Age-standardized" -%>To allow for comparisons between countries and over time, this metric is (#dod:age_standardized).<%- endif -%>
? + + + +
~ Column death_count (changed metadata)
- - <% if age_group == "ALLAges" %>
+ + <%- if age_group == "ALLAges" -%>
? + +
- - Total deaths from << cause.lower() >> among <% if sex == "Both sexes" %>both sexes<% elif sex == "Male" %>males<% elif sex == "Female" %>females<% endif %>
+ + Total deaths from << cause.lower() >> among <%- if sex == "Both sexes" %>both sexes<% elif sex == "Male" %>males<% elif sex == "Female" %>females<% endif -%>
? + +
- - <%- elif age_group == "Age-standardized" %>
+ + <%- elif age_group == "Age-standardized" -%>
? +
- - Age-standardized deaths from << cause.lower() >> among <% if sex == "Both sexes" %>both sexes<% elif sex == "Male" %>males<% elif sex == "Female" %>females<% endif %>
+ + Age-standardized deaths from << cause.lower() >> among <%- if sex == "Both sexes" %>both sexes<% elif sex == "Male" %>males<% elif sex == "Female" %>females<% endif -%>
? + +
- - <%- else %>
+ + <%- else -%>
? +
- - Deaths from << cause.lower() >> among <% if sex == "Both sexes" %>both sexes<% elif sex == "Male" %>males<% elif sex == "Female" %>females<% endif %> aged <% if age_group == "ALLAges" %>
+ + Deaths from << cause.lower() >> among <%- if sex == "Both sexes" %>both sexes<% elif sex == "Male" %>males<% elif sex == "Female" %>females<% endif -%> aged <%- if age_group == "ALLAges" -%>
? + + + +
- - <%- elif age_group == "age-standardized" %>
+ + <%- elif age_group == "age-standardized" -%>
? +
- - <%- elif age_group == "YEARS0-14" %>
+ + <%- elif age_group == "YEARS0-14" -%>
? +
- - <%- elif age_group == "YEARS0-4" %>
+ + <%- elif age_group == "YEARS0-4" -%>
? +
- - <%- elif age_group == "YEARS5-14" %>
+ + <%- elif age_group == "YEARS5-14" -%>
? +
- - <%- elif age_group == "YEARS15-19" %>
+ + <%- elif age_group == "YEARS15-19" -%>
? +
- - <%- elif age_group == "YEARS15-49" %>
+ + <%- elif age_group == "YEARS15-49" -%>
? +
- - <%- elif age_group == "YEARS20-24" %>
+ + <%- elif age_group == "YEARS20-24" -%>
? +
- - <%- elif age_group == "YEARS25-34" %>
+ + <%- elif age_group == "YEARS25-34" -%>
? +
- - <%- elif age_group == "YEARS35-44" %>
+ + <%- elif age_group == "YEARS35-44" -%>
? +
- - <%- elif age_group == "YEARS45-54" %>
+ + <%- elif age_group == "YEARS45-54" -%>
? +
- - <%- elif age_group == "YEARS50-69" %>
+ + <%- elif age_group == "YEARS50-69" -%>
? +
- - <%- elif age_group == "YEARS55-64" %>
+ + <%- elif age_group == "YEARS55-64" -%>
? +
- - <%- elif age_group == "YEARS65-74" %>
+ + <%- elif age_group == "YEARS65-74" -%>
? +
- - <%- elif age_group == "YEARS70+" %>
+ + <%- elif age_group == "YEARS70+" -%>
? +
- - <%- elif age_group == "YEARS75-84" %>
+ + <%- elif age_group == "YEARS75-84" -%>
? +
- - <%- elif age_group == "YEARS85PLUS" %>
+ + <%- elif age_group == "YEARS85PLUS" -%>
? +
- - <%- endif %>
+ + <%- endif -%>
? +
- - <%- endif %>
+ + <%- endif
...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: 2024-11-29 16:42:58 UTC |
pabloarosado
approved these changes
Nov 28, 2024
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Looks good! Except for the way description processing is formatted. Keep in mind that it should be a string (not a list), otherwise it will not be rendered properly in grapher.
I also pointed out in the comments that, in principle, description processing should be about our processing, not about the processing of the data provider. But I understand that it makes sense to have that information there. So I leave it up to you. And feel free to disregard my minor suggestions.
etl/steps/data/garden/antibiotics/2024-11-12/antimicrobial_usage.py
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| "Antibacterials (ATC J01, A07AA, P01AB)": "Antibacterials (ATC J01, A07AA, P01AB, ATC J04A)", | ||
| }, | ||
| ) | ||
| assert len(tb["antimicrobialclass"].unique()) == 4 |
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Maybe it would be safer to assert the expected unique items in "antimicrobialclass" at the beginning of the function, and then rename them.
etl/steps/data/garden/antibiotics/2024-11-12/antimicrobial_usage.py
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| countries = tb_note["country"].unique() | ||
| countries_formatted = combine_countries(countries) | ||
| description_processing_string = f"- In {countries_formatted}: {note}\n" | ||
| tb_notes.loc[msk, "description_processing"] = description_processing_string |
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Interesting way to create description processing! In principle, that field should be dedicated to our own processing (i.e. things OWID has done to the data), not to how the data itself was processed. See that, on data pages, we say "Notes on our processing step for this indicator". I understand that these notes you are loading refer to the original processing by the data provider, right?
Maybe they should be elsewhere (key description points, if they are important?). But if you think they make more sense as description_processing, you can keep them this way.
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This is true, I guess they might more sense as description_key?
etl/steps/data/garden/antibiotics/2024-11-12/antimicrobial_usage.py
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etl/steps/data/garden/antibiotics/2024-11-12/antimicrobial_usage.py
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Having some issues nicely formatting the
description_processingany ideas of how to improve it would be v welcome!