datasets

Kasipa datasets

kasipa/ai_software_selloff_credit_risk_context.csv

• Nasdaq Composite (FRED): https://fred.stlouisfed.org/series/NASDAQCOM
• Baa minus 10Y spread (FRED): https://fred.stlouisfed.org/series/BAA10Y
• ICE BofA US High Yield OAS (FRED): https://fred.stlouisfed.org/series/BAMLH0A0HYM2
• Post context: https://old.reddit.com/r/news/comments/1r4lflq/ailed_software_selloff_may_pose_risk_for_15/

kasipa/us_health_agency_trust_signals_2024_2026.csv

• Primary report (AP): https://apnews.com/article/rfk-jr-kennedy-cdc-covid-health-trust-7ef5f0e2c6f91ce6d908cb58f9e2fcb2
• Poll references cited in report: KFF, Gallup, Annenberg Public Policy Center
• Post context: https://old.reddit.com/r/news/comments/1r4p039/trust_in_us_health_agencies_is_eroding_under_rfk/

kasipa/kff_federal_health_agency_confidence_jan2026.csv

• Primary source (full wave topline): https://files.kff.org/attachment/topline-kff-health-tracking-poll-jan-2026.pdf
• Context explainer: https://www.kff.org/health-information-trust/trust-in-cdc-and-views-of-federal-childhood-vaccine-schedule-changes/
• This file includes the full “confidence in federal health agencies responsibilities” question battery reported for Jan 2026.

kasipa/heineken_headcount_revenue_productivity_2015_2026.csv

• Revenue series source: https://www.macrotrends.net/stocks/charts/HEINY/heineken/revenue
• Employee count source: https://www.macrotrends.net/stocks/charts/HEINY/heineken/number-of-employees
• Post context: https://old.reddit.com/r/technology/comments/1r4p4hr/heineken_to_slash_up_to_6000_jobs_in_ai/
• Notes: historical rows use annual reported values (2015–2024). 2026 row is an event/scenario marker reflecting the announced "up to 6,000 jobs" cut.

kasipa/ai_selloff_credit_stress_windows_2023_2026.csv

• Base market/credit series:
  • Nasdaq Composite (FRED): https://fred.stlouisfed.org/series/NASDAQCOM
  • Baa minus 10Y spread (FRED): https://fred.stlouisfed.org/series/BAA10Y
  • ICE BofA US High Yield OAS (FRED): https://fred.stlouisfed.org/series/BAMLH0A0HYM2
• Post context: https://old.reddit.com/r/news/comments/1r4lflq/ailed_software_selloff_may_pose_risk_for_15/
• Notes: derived 21-trading-day windows from daily data. Includes Nasdaq 21d return and simultaneous credit spread changes to classify risk-off vs mixed vs risk-on periods.

kasipa/ai_credit_regime_share_by_quarter_2023_2026.csv

• Derived from: kasipa/ai_selloff_credit_stress_windows_2023_2026.csv
• Post context: https://old.reddit.com/r/news/comments/1r4lflq/ailed_software_selloff_may_pose_risk_for_15/
• Notes: quarterly share (%) of windows classified as Risk-off stress, Risk-on relief, and Mixed/neutral.

kasipa/china_imports_from_africa_2023.csv

• Primary data source: TrendEconomy data explorer (annual trade by country, HS)
  • Page: https://trendeconomy.com/data/h2/China/TOTAL
  • Backend endpoint used for extraction: https://trendeconomy.com/te.rest.web/json/key_family
• Build parameters used:
  • reporter = China
  • trade_flow = Import
  • indicator = Trade Value (TV)
  • commodity = TOTAL
  • time_period = 2023
• Notes: filtered to African partner countries from the returned partner-country rows.

kasipa/china_imports_from_africa_2023_with_country_tariff_proxy.csv

• Base trade dataset: kasipa/china_imports_from_africa_2023.csv
• Tariff proxy source: World Bank indicator API
  • Indicator: TM.TAX.MRCH.WM.AR.ZS (Tariff rate, applied, weighted mean, all products, %)
  • API docs root: https://api.worldbank.org/
  • Example endpoint format: https://api.worldbank.org/v2/country/{ISO3}/indicator/TM.TAX.MRCH.WM.AR.ZS?format=json
• Notes:
  • Adds latest available country-level tariff value/year per country.
  • This is a country-level proxy and not a China bilateral HS-line tariff schedule.

kasipa/china_zero_tariff_opportunity_2023.csv

• Built from: kasipa/china_imports_africa_tariff_quadrant.csv
• Upstream raw/indicator sources used in parent dataset:
  • China import values by African partner (TrendEconomy):
    • Page: https://trendeconomy.com/data/h2/China/TOTAL
    • Backend endpoint: https://trendeconomy.com/te.rest.web/json/key_family
  • Tariff proxy (World Bank):
    • Indicator: TM.TAX.MRCH.WM.AR.ZS
    • API root: https://api.worldbank.org/
  • Export dependency proxy (World Bank):
    • Indicator: NE.EXP.GNFS.CD
    • API root: https://api.worldbank.org/
• Post context:
  • https://old.reddit.com/r/Economics/comments/1r549cv/china_to_implement_zero_tariffs_on_imports_from/
• Notes:
  • Adds derived fields for opportunity framing:
    • estimated_tariff_cost_usd_billion
    • estimated_tariff_cost_usd
    • opportunity_score

kasipa/global_ewaste_monitor_2024_country_2022.csv

• Primary source report:
  • Global E-waste Monitor 2024 (UNITAR/ITU), Annex 2 country table
  • PDF: https://ewastemonitor.info/wp-content/uploads/2024/12/GEM_2024_EN_11_NOV-web.pdf
  • Landing page: https://ewastemonitor.info/the-global-e-waste-monitor-2024/
• Additional joined source:
  • World Bank GDP per capita (current US$), indicator NY.GDP.PCAP.CD
  • API root: https://api.worldbank.org/
• Notes:
  • Extracted from Annex 2 Table A2.4 (country-level key e-waste statistics, reference year 2022).
  • Includes: generated total (million kg), generated per-capita (kg), documented formally collected/recycled (million kg, when available), region, plus gdp_per_capita_usd and gdp_per_capita_year.

kasipa/atus_a8_2024_waking_hours_selected_characteristics.csv

• Primary source:
  • U.S. Bureau of Labor Statistics (BLS), American Time Use Survey (ATUS)
  • Table A-8: Waking hours spent alone or with others, by selected characteristics, 2024 annual averages
  • PDF: https://www.bls.gov/tus/tables/a8-2024.pdf
  • Tables index: https://www.bls.gov/tus/tables.htm
• Notes:
  • Manually transcribed from the A-8 table values in the source PDF.
  • Contains selected rows for age, sex, race/ethnicity, employment status, household-children status, marital status, day type, and education.

kasipa/china_imports_all_african_countries_2023_double_checked.csv

• Base import source:
  • TrendEconomy China imports (reporter=China, trade_flow=Import, indicator=TV, commodity=TOTAL, time_period=2023)
  • Page: https://trendeconomy.com/data/h2/China/TOTAL
  • Backend endpoint used: https://trendeconomy.com/te.rest.web/json/key_family
• Tariff context source (proxy):
  • World Bank indicator TM.TAX.MRCH.WM.AR.ZS (country applied weighted mean tariff, all products)
  • API root: https://api.worldbank.org/
• Notes:
  • Covers all 54 African Union member states with ISO3.
  • Import values are China imports from each country in 2023; countries with no observed value in source are set to 0.
  • Tariff column is a country-level proxy and not a China bilateral tariff schedule by partner/product line.

kasipa/us_debt_spiral_projection_2025_2036.csv

• Primary context thread: https://old.reddit.com/r/Economics/comments/1r5tmu0/a_us_debt_spiral_could_start_soon_as_the_interest/
• Base source article: https://fortune.com/2026/02/14/us-debt-spiral-interest-rate-treasury-bond-yields-economic-growth-gdp/
• Macro source series (FRED):
  • Debt-to-GDP proxy: https://fred.stlouisfed.org/series/GFDEGDQ188S
  • Nominal GDP index: https://fred.stlouisfed.org/series/GDPC1
  • 10Y Treasury proxy: https://fred.stlouisfed.org/series/DGS10
• Notes:
  • Contains mixed historical rows (2000–2026 quarterly aggregates) and anchor projections from the article (debt-to-GDP and nominal growth/interest-rate assumptions).
  • Historical values are pulled as-is from FRED series CSV endpoints; projection points are manually aligned to article projections for charting context.

kasipa/pertussis_dtp1_dtp3_coverage_1980_2024.csv

• Source endpoints (Our World in Data grapher, WHO/UNICEF 2025 and UN WPP 2024 variants):
  • DTP1 coverage: https://ourworldindata.org/grapher/vaccination-coverage-who-unicef.csv?antigen=dtpcv1&metric=coverage
  • DTP3 coverage: https://ourworldindata.org/grapher/vaccination-coverage-who-unicef.csv?antigen=dtpcv3&metric=coverage
• Purpose: compare first-dose and third-dose pertussis vaccine coverage over time.
• Post context to anchor the chart narrative: https://www.abc.net.au/news/2026-02-16/whooping-cough-cases-at-record-high-level-in-australia/106332954
• Notes: includes global/WHO-region and selected-country rows, plus dtp3_minus_dtp1_pct_gap to show completion gap.

kasipa/taklamakan_climate_monthly_2000_2025.csv

• Primary source: NASA POWER MERRA-2 Monthly Point Data API
  • Endpoint: https://power.larc.nasa.gov/api/temporal/monthly/point
• Parameters used: T2M (2m temperature), PRECTOTCORR (precipitation), EVPTRNS (evapotranspiration)
• Point location used: Taklamakan Desert center (40.5°N, 84.9°E)
• Window: 2000–2025
• Notes: includes seasonal tagging (Wet (Jul-Sep) vs Dry (Oct-Jun)) for a climate-regime comparison tied to restoration timing discussion in the Taklamakan restoration literature.

kasipa/taklamakan_climate_seasonal_annual_2000_2025.csv

• Derived from: kasipa/taklamakan_climate_monthly_2000_2025.csv
• Source API call example:
  • https://power.larc.nasa.gov/api/temporal/monthly/point?parameters=T2M,PRECTOT,EVPTRNS&community=AG&longitude=84.9&latitude=40.5&start=2000&end=2025&format=JSON
• Derived fields:
  • wet_season_precip_mm_per_day: mean monthly precip in Jul-Sep
  • dry_season_precip_mm_per_day: mean monthly precip in Oct-Jun
  • wet_minus_dry_precip_mm_per_day: seasonal contrast (wet-dry) for regime strength
• Angle: track whether the wet-season advantage has strengthened as a practical framing clue for afforestation feasibility.

kasipa/japan_growth_trade_fx_1990_2025.csv

• Core sources (World Bank API, indicator endpoint):
  • GDP growth (annual %): https://api.worldbank.org/v2/country/JPN;USA/indicator/NY.GDP.MKTP.KD.ZG?format=json
  • Exports of goods and services (current US$): https://api.worldbank.org/v2/country/JPN;USA/indicator/NE.EXP.GNFS.CD?format=json
  • Official exchange rate (JPY per US$): https://api.worldbank.org/v2/country/JPN/indicator/PA.NUS.FCRF?format=json
• Country set: Japan (JPN) and United States (USA)
• Window: 1990–2025
• Notes: derived exports YoY growth for both Japan and U.S., plus JPY-per-USD to test the “Japan weak-growth + soft yen + export cooling” narrative from a macro lens.
• Posted context candidate: https://old.reddit.com/r/Economics/comments/1r6afvv/japans_economy_barely_grows_in_the_last_quarter/

kasipa/china_new_home_prices_70cities_jan2026_snapshot.csv

• Primary monthly aggregate source (NBS series mirror):
  • TradingEconomics China housing index page: https://tradingeconomics.com/china/housing-index
• Official release summary source (tier-level January MoM moves):
  • SCIO/Xinhua summary: http://english.scio.gov.cn/pressroom/2026-02/13/content_118333097.html
  • China.org mirror: http://www.china.org.cn/2026-02/13/content_118333030.shtml
• City-level January YoY examples + breadth signal source references:
  • TradingEconomics news text block on the same indicator page (Guangzhou, Shenzhen, Chongqing, Tianjin, Beijing, Shanghai)
  • Reuters report URL (for 62/70 vs 58/70 breadth context): https://www.reuters.com/world/asia-pacific/chinas-new-home-prices-extend-decline-january-2026-02-13/
• Notes:
  • This is a compact snapshot dataset for fast visualization, not a full official 70-city January table export.
  • Includes national aggregate, selected major-city YoY points, tier-level January MoM, and a market-breadth count.

kasipa/china_new_home_prices_2025_only.csv

• Primary monthly aggregate source (NBS series mirror):
  • TradingEconomics China housing index page: https://tradingeconomics.com/china/housing-index
• City-level Dec 2025 YoY examples:
  • TradingEconomics indicator news text on the same page (Guangzhou, Shenzhen, Tianjin, Chongqing, Beijing, Shanghai)
• Market breadth context (Dec 2025):
  • Reuters report URL (58 of 70 cities declining): https://www.reuters.com/world/asia-pacific/chinas-new-home-prices-extend-decline-january-2026-02-13/
• Notes:
  • Strictly 2025 values only (December snapshot).
  • Compact dataset intended for quick Kasipa charting.

kasipa/china_new_home_prices_nbs_dec2025_selected_cities.csv

• Official NBS source (primary):
  • National Bureau of Statistics of China, Press Release (English):
  • https://www.stats.gov.cn/english/PressRelease/202601/t20260119_1962346.html
• Extraction basis:
  • Table I: "Sales Price Indices of Newly Constructed Commercial Residential Buildings in 70 Large and Medium-Sized Cities"
• Notes:
  • Uses official NBS index values for Dec 2025 (Last Month=100 and Same Month Last Year=100) for selected cities.
  • Includes derived percent changes (mom_change_percent, yoy_change_percent) computed as index minus 100.

kasipa/china_new_home_prices_nbs_dec2025_all_70_cities.csv

• Official NBS source (primary):
  • National Bureau of Statistics of China, Press Release (English):
  • https://www.stats.gov.cn/english/PressRelease/202601/t20260119_1962346.html
• Extraction basis:
  • Table I: "Sales Price Indices of Newly Constructed Commercial Residential Buildings in 70 Large and Medium-Sized Cities"
• Notes:
  • Full 70-city Dec 2025 coverage from official NBS table values.
  • Columns include NBS indices (mom_index_last_month_100, yoy_index_same_month_last_year_100, avg_index_jan_dec_last_year_100) and derived percentage-point deltas vs 100 (mom_change_percent, yoy_change_percent).
  • Includes one extra aggregate row: China (simple average across 70 cities) computed directly from NBS Table I city indices (unweighted mean; clearly labeled as derived, not an official NBS weighted national headline index).

kasipa/china_new_home_prices_nbs_dec2025_all_70_cities_with_population_2020_census.csv

• Base housing source:
  • NBS Table I (same as file above): https://www.stats.gov.cn/english/PressRelease/202601/t20260119_1962346.html
• Population source (2020 census basis):
  • China Seventh National Census city-level urban aggregates as compiled on CityPopulation (explicitly citing NBS census web tables): https://www.citypopulation.de/en/china/cities/
• Notes:
  • Adds population_2020_census to the 70-city housing rows.
  • 4 cities currently have blank population due absence in the cited urban-aggregate table cutoff: Anqing, Beihai, Sanya, Dali.

kasipa/cost_wmt_tgt_indexed_1y_daily.csv

• Price history source (Stooq CSV endpoints):
  • Costco (COST): https://stooq.com/q/d/l/?s=cost.us&i=d
  • Walmart (WMT): https://stooq.com/q/d/l/?s=wmt.us&i=d
  • Target (TGT): https://stooq.com/q/d/l/?s=tgt.us&i=d
• Context thread:
  • https://old.reddit.com/r/Economics/comments/1r7bmug/costco_defied_trumps_dei_directive_as_target_and/
• Notes:
  • Daily intersection of trading dates across all three tickers.
  • Includes raw close (*_close_usd) and normalized series (*_indexed_100) using the first date in the 1-year window as base=100.

kasipa/cost_wmt_tgt_indexed_1y_summary.csv

• Derived from: kasipa/cost_wmt_tgt_indexed_1y_daily.csv
• Notes:
  • Compact per-ticker return summary over the same normalized window (indexed_return_pct).

kasipa/prediction_markets_cross_platform_top_markets_snapshot.csv

• Platform API sources:
  • Polymarket Gamma API: https://gamma-api.polymarket.com/markets?closed=false&limit=500
  • Manifold Markets API: https://api.manifold.markets/v0/markets?limit=1000
• Context thread:
  • https://old.reddit.com/r/worldnews/comments/1r71uvi/new_zealand_declares_prediction_markets_are/
• Notes:
  • Snapshot file (single pull timestamp) with top markets by sampled volume from each platform.
  • Includes standardized columns: volume_usd, liquidity_usd, resolution state, and market URL.

kasipa/prediction_markets_cross_platform_activity_summary_snapshot.csv

• Derived from: kasipa/prediction_markets_cross_platform_top_markets_snapshot.csv (same snapshot run)
• Notes:
  • Platform-level aggregate sample metrics (sample_total_volume_usd, sample_total_liquidity_usd, median volume, markets sampled).

kasipa/us_import_price_vs_cpi_monthly_2018_2026.csv

• Primary source (FRED combined CSV endpoint):
  • https://fred.stlouisfed.org/graph/fredgraph.csv?id=IR14200,CPIAUCSL
• Underlying series pages:
  • U.S. Import Price Index: All Commodities (IR14200): https://fred.stlouisfed.org/series/IR14200
  • CPI for All Urban Consumers: All Items (CPIAUCSL): https://fred.stlouisfed.org/series/CPIAUCSL
• Notes:
  • Monthly rows filtered to 2018-01-01 onward where both series are present.
  • Includes derived fields:
    • import_price_yoy_pct
    • cpi_yoy_pct
    • gap_import_minus_cpi_yoy_pp

kasipa/us_customs_duties_vs_imports_quarterly_1990_2026.csv

• Primary source (FRED combined CSV endpoint):
  • https://fred.stlouisfed.org/graph/fredgraph.csv?id=B235RC1Q027SBEA,IMPGS
• Underlying series pages:
  • Federal government current tax receipts: customs duties (B235RC1Q027SBEA): https://fred.stlouisfed.org/series/B235RC1Q027SBEA
  • Imports of goods and services (IMPGS): https://fred.stlouisfed.org/series/IMPGS
• Context thread:
  • https://old.reddit.com/r/news/comments/1r9xrq7/supreme_court_strikes_down_most_of_trumps_tariffs/
• Notes:
  • Quarterly rows filtered to 1990-01-01 onward where both series are present.
  • Includes derived fields:
    • customs_duties_to_imports_pct
    • customs_duties_yoy_pct
    • imports_yoy_pct
    • duty_intensity_yoy_change_pp

kasipa/tesla_recalls_ota_share_by_model_year_2020_2026.csv

• Primary source (NHTSA recalls API):
  • Endpoint template: https://api.nhtsa.gov/recalls/recallsByVehicle?make=TESLA&model={MODEL}&modelYear={YEAR}
  • Example: https://api.nhtsa.gov/recalls/recallsByVehicle?make=TESLA&model=MODEL%20Y&modelYear=2025
• Context thread:
  • https://old.reddit.com/r/technology/comments/1ra7jkz/youtuber_mkbhd_says_tesla_stopped_talking_to_me/
• Notes:
  • Covers Tesla models MODEL Y, MODEL 3, MODEL S, MODEL X, and CYBERTRUCK for model years 2020–2026.
  • Includes derived fields:
    • ota_recall_count
    • ota_share_pct
  • Some model-year combinations are not valid in NHTSA API and return HTTP 400; those rows are retained with zero counts and a query_error value for transparency.