get_event_price_chart

Reads only.

Use this for one event's daily price and inventory series, per book. Use get_event_section_series instead for one section in 5 minute or hourly steps, and get_event_analytics_history for signal columns over time. Daily price + inventory time series for one event, ordered snapshot_date ASC, the backtesting primitive for price. Each row is one day's rollup of intraday snapshots: median/p25/p75_price are the day's mean of those snapshots, lowest_price and lowest_aip_price (all-in, buyer-pays) are the day's LOW, listings/tickets carry the day's min and max (no closing value is kept), percent_remaining is the day's mean, snapshot_count says how many samples back the day. days_missing lists calendar days inside the returned span with no rollup: real absences (gaps in the history), NEVER interpolate across them. The answer also carries event_name, local_date, venue_name and sub_category_id, what the series is OF, so a chart legend reads a name and never an id. Daily rollups are full depth on every plan, so plan_capped is always false here. Returns rows:[] when the event has no price history. Use with get_event_analytics_history to backtest a signal against subsequent price. A rendered chart image of the series is included by default; pass render:false for data only. source selects the comparison source: without it (or with vs) you get this daily-rollup shape; tp, tm, tmr, gt or sg answers the shared per-source series envelope instead ({source, meta:{coverageStart, lastMeasuredAt, granularity, mapped}, series:[{date, floor, median, p25, p75, listings, tickets}]}). mapped:false means the event has no link to that source (an empty series with mapped:true means linked but no data). Envelope responses are data-only (no rendered image), raw values unrescaled; range does not apply to them. Each code carries its own price basis, so never blend two: tm is a primary book (face-value levels), tmr its resale book, vs and tp resale, and gt and sg resale quoted ALL-IN, the buyer's final number and not a base that fees are added to. gt and sg are the two that fill p25/p75, because they read every listing; sg listings is not comparable to another source's count, because sg splits one seller block into several listings, so compare tickets. tm points are exact states at their own times, so their dates are full timestamps: each day keeps its highest-availability state and its last, each with the prices of that same moment. A plan limit is never missing data: a reading the account's plan does not include is refused with a plan_required error (entitled false, required_tier the plan that unlocks it, a one line message), and a column or field the plan strips from an answer is named in a top level withheld list with the same three fields. null, an empty list and available false mean the data does not exist.

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