Dataset research report
Hormuz Shipping Crisis research report
A reproducible data report with schema notes, generated chart evidence, suggested follow-up questions, and export-ready Helix queries.
Executive Summary
Synthetic Hormuz shipping crisis dataset with vessel transits, energy throughput, prices, attacks, insurance premiums, and reroute impacts.
Research Context
Daily tracking from Jan-May 2026: pre-war Hormuz traffic (~105 transits/day), the Feb 28 closure after US-Israel strikes, carrier Cape reroutes, insurance spikes, and selective reopening for approved flags.
Data Profile
Chart Evidence
These views are generated from the dataset profile. Each chart is paired with a Helix query so it can be opened, adjusted, and exported.
Daily ship transits through Hormuz
Pre-war baseline ~105/day; transits collapsed to near-zero after the Feb 28 closure.
Open and export this chartBrent crude vs transit disruption
Scatter view: prices climbed as strait traffic fell during the crisis.
Open and export this chartPre-war vs crisis averages
Grouped bars comparing mean daily transits, oil flow, and war-risk insurance.
Open and export this chartOil & LNG throughput
Energy flows through the strait — both collapsed as carriers rerouted via the Cape.
Open and export this chartWar risk insurance & diesel prices
Insurance premiums spiked while US Gulf Coast diesel rose with crude.
Open and export this chartCumulative vessel attacks
Running attack count climbed through March-April as transit remained minimal.
Open and export this chartAttack types during the crisis
Horizontal bar of non-zero attack_type counts across war_crisis days.
Open and export this chartCape reroute penalty & stranded vessels
Extra transit days jumped to ~14 while hundreds of vessels remained stranded in the Gulf.
Open and export this chartFollow-Up Queries
- line chart of daily ship transits with annotation at strait closure
- scatter Brent crude vs transit pct of pre-war colored by period_type
- grouped bar comparing pre_war vs war_crisis averages for transits oil and war risk insurance
- stacked area chart of oil and LNG throughput over time
- dual axis line chart of war risk insurance pct and diesel price
- area chart of cumulative vessels attacked over the timeline
- horizontal bar chart of attack types during war_crisis
- bar and line chart of cape reroute extra days vs vessels stranded in the Gulf
Preview Rows
| # | datetext | period_typetext | days_since_closureinteger | daily_ship_transitsinteger | monthly_vessel_countinteger | monthly_count_is_exactboolean | transit_pct_of_prewar_avgfloat | oil_throughput_mbpdfloat |
|---|---|---|---|---|---|---|---|---|
| 1 | 2026-01-01 | pre_war | 0 | 103 | 3000 | False | 100 | 19.7 |
| 2 | 2026-01-02 | pre_war | 0 | 108 | 3000 | False | 100 | 19.5 |
| 3 | 2026-01-03 | pre_war | 0 | 108 | 3000 | False | 100 | 19.7 |
| 4 | 2026-01-04 | pre_war | 0 | 108 | 3000 | False | 100 | 19.8 |
| 5 | 2026-01-05 | pre_war | 0 | 98 | 3000 | False | 100 | 19.9 |
| 6 | 2026-01-06 | pre_war | 0 | 98 | 3000 | False | 100 | 20.5 |
Data Dictionary
- date date Observation date
- period_type categorical pre_war or war_crisis
- daily_ship_transits int Vessels transiting the strait per day
- transit_pct_of_prewar_avg float Transit volume as % of pre-war baseline
- oil_throughput_mbpd float Oil throughput (million barrels per day)
- lng_throughput_bcfd float LNG throughput (billion cubic feet per day)
- brent_crude_usd_bbl float Brent crude spot price USD/bbl
- vessels_attacked_cumulative int Running total of attacked vessels
- vessels_stranded_in_gulf int Vessels stranded in the Persian Gulf
- war_risk_insurance_pct float War risk insurance premium %
- cape_reroute_extra_days int Extra transit days via Cape reroute
- key_event text Notable daily event annotation
Method And Limits
- Load the catalog entry and preview rows from the processed dataset file.
- Infer numeric, categorical, time, and location fields from real columns.
- Generate a small set of defensive Plotly chart specifications from that profile.
- Expose each chart idea as a query link so the report can be rerun or exported in Helix.
This report is intentionally reproducible. It uses the local catalog metadata and generated chart specifications rather than claiming external conclusions beyond the dataset.