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Aaron Kyle Dennis
Social development practitioner. Trying to understand our world.
Public
Social Analysis
Edited
May 29, 2023
1
Social Analysis
Review & Compilation: Public Gender Surveys(Re-)Structuring IFC PS1Project Safeguards Data Structure (NEPAL) | CensusProject Safeguards Data Structure (NEPAL) | MonitoringProject Safeguards Data Structure (NEPAL) | ConsultationProject Safeguards Data Structure (NEPAL) | Impact AssessmentProject Safeguards Data Structure (NEPAL) | Land ValuationProject Safeguards Data Structure (NEPAL) | GRMProject Safeguards Data Structure (NEPAL) | ConceptWorld Bank Gender Data Portal | AssetsAccessing IMF Spatial Data | Climate ChangeAngola Exploration | UNDRR Geospatial DataPlotting Bhutan's Agriculture StatisticsICIMOD | Bhutan Geospatial Data
World Bank Gender Stats
World Bank | PIP - Shared ProsperityBhutan | Agriculture Statistics 2021Asian Development Outlook (ADO) | Per Capita GDP Growth in Asia and the PacificAsian Development Outlook (ADO) | Inflation Rate in Asia and the PacificMassGIS Data: Property Tax ParcelsNepal | District Socio-Economic ProfilesWorld Bank API - Meet Vega LiteUN Sustainable Development Goals APISri Lanka | Sources of Geospatial Data on Administrative DivisionsBhutan | Sources of Geospatial Data on Administrative DivisionsNepal | Sources of Geospatial Data on Administrative DivisionsGlobal Mining-Induced Displacement and Resettlement EventsIndonesian Data - Baseline SurveyGujarat, IndiaRussian Law - Indigenous PeoplesFPIC LiteratureIndigenous Peoples LiteratureIndonesian Law - SafeguardsIndian Law - SafeguardsKabupaten Kepulauan Tanimbar
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csv_archive = FileAttachment("Gender_Stats_CSV.zip").zip()
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// This function removes the BOM character at teh beginning of our dataset
// courtesy of @fil
// See https://en.wikipedia.org/wiki/Byte_order_mark
function stripBOM(text) {
return text.charCodeAt(0) === 0xfeff ? text.slice(1) : text;
}
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gender_stats_DB = DuckDBClient.of({
gender_stats_data,
gender_stats_country,
gender_stats_series,
gender_stats_series_country,
// Note: We're re-building the full database, but we won't build these next two tables into our next queries
gender_stats_series_time,
gender_stats_series_footnote})
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d3.group(Gender_Stats, d => d.Topic, d => d["Country Name"])
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