Table descriptions

The descriptions shown on this page.

meta_tables, page 1 of 2
nameTEXT	titleTEXT	descriptionTEXT
zones	Taxi zones	One row per TLC taxi zone: borough, service zone, the zone name the 2021 model used, map centroid and yearly pickups/drop-offs.
zone_hourly	Zone x weekday x hour	Trips and trip-duration statistics per zone, ISO weekday (1 = Monday, 0 = all days) and hour (24 = all day), for pickups (pickup time) and drop-offs (drop-off time).
zone_vendor	Zone x vendor	Yearly trips per zone and vendor, the data behind the 2021 vendor choropleths.
routes	Zone-to-zone routes	Every pickup zone to drop-off zone pair seen in 2019 with trips, median and mean minutes, distance, fare and speed.
route_hourly	Route x hour	Hourly trips and median minutes for zone pairs with at least 1,000 trips in 2019.
borough_flows	Borough flows	Trips between boroughs (the 2021 'route' feature), with median minutes.
daily	Daily series	One row per day of 2019: trips, duration statistics, NOAA Central Park weather, permitted events and collisions (summed over boroughs).
daily_borough	Daily x borough	Pickups, median minutes, permitted events and collisions per day and borough.
weekday_hour_vendor	Weekday x hour x vendor	Mean and median trip minutes per ISO weekday, pickup hour and vendor (0 = both), as in the 2021 vendor line charts.
weather	NOAA weather	Daily Central Park weather after the notebook's cleaning: TAVG = (TMAX + TMIN) / 2, gaps filled with 0, WT04 dropped.
events_daily	Permitted events	Permitted events starting each day per borough (NYC Open Data bkfu-528j, current version).
collisions_hourly	Collisions	NYPD motor-vehicle collisions per borough, day and hour (2021 BigQuery export).
cleaning_funnel	Cleaning funnel	Rows left after every cleaning rule, revived pipeline next to the counts printed by the 2021 notebook.
model_folds	Cross-validation folds	R^2 and RMSE per fold: the 2021 notebook, the 2021 coefficients scored on the revived folds, and the 2026 refit.
model_path	Regularisation path	Mean 10-fold R^2, RMSE and number of non-zero coefficients for several regParam values at the notebook's elasticNetParam = 0.8.
model_coefficients	Model coefficients	All 579 regression coefficients in VectorAssembler order: 2021 fold 1 next to the 2026 refit.
model_zone_index	Zone name index	Spark StringIndexer order of pickup and drop-off zone names (most trips first), rebuilt from the revived data.
evidence_meta	Evidence metadata	Key-value summaries (JSON) of the regression, hold-out, effects and data-quality analyses: sample sizes, references, splits and self-checks.
ols_coefficients	OLS coefficients with robust SEs	Unpenalised OLS counterpart of the 2021 model on all 2019 model rows: estimates with classical, HC3 and day-clustered standard errors and 95% intervals. One reference level per block is omitted.
holdout_models	Hold-out models	The models compared on the temporal (Nov-Dec) and in-period (Jan-Oct fold 0) hold-outs.
holdout_daily	Hold-out errors per day	Per test day and model: trips and sums of errors, squared errors, absolute errors, y and y squared. The website bootstraps whole days from these.
residual_hist2d	Residuals vs fitted (2D histogram)	Trips per 1-minute fitted bin and 2-minute residual bin, for the 2021 coefficients and the OLS fit.
residual_bins	Residuals by fitted value	Mean and 10th/50th/90th percentile residual per 1-minute fitted bin (bins with at least 200 trips).
residual_qq	Residual quantiles (QQ)	Residual quantiles against the normal quantiles with the same mean and standard deviation.
residual_groups	Residual spread by group	Trips, mean residual, residual SD and MAE per pickup borough, pickup hour and borough x hour.