Dataset: Uber Travel Movement Data [2 Billion+ Trips]

About this Dataset

Uber Travel Movement Data [2 Billion+ Trips]

Uber Movement provides anonymized data from over two billion trips to help urban planning around the world.

About this Dataset

Objectives

Over the past six and a half years, Uber has learned a lot about the future of urban mobility and what it means for cities and the people who live in them. Uber has gotten consistent feedback from cities they partner with that access to their aggregated data will inform decisions about how to adapt existing infrastructure and invest in future solutions to make our cities more efficient. Uber hopes Uber Movement can play a role in helping cities grow in a way that works for everyone.

Background

https://d3i4yxtzktqr9n.cloudfront.net/web-movement/static/pdfs/Movement-TravelTimesMethodology-76002ded22.pdf

Tables

Travel Times Bogota

@kaggle.ishandutta_uber_travel_movement_data_2_billion_trips.travel_times_bogota

627.36 KB
496 rows
10 columns


CREATE TABLE travel_times_bogota (
  "origin_movement_id" BIGINT,
  "origin_display_name" VARCHAR,
  "origin_geometry" VARCHAR,
  "destination_movement_id" BIGINT,
  "destination_display_name" VARCHAR,
  "destination_geometry" VARCHAR,
  "date_range" VARCHAR,
  "mean_travel_time_seconds" BIGINT,
  "range_lower_bound_travel_time_seconds" BIGINT,
  "range_upper_bound_travel_time_seconds" BIGINT
);

Travel Times Boston

@kaggle.ishandutta_uber_travel_movement_data_2_billion_trips.travel_times_boston

266.86 KB
700 rows
10 columns


CREATE TABLE travel_times_boston (
  "origin_movement_id" BIGINT,
  "origin_display_name" VARCHAR,
  "origin_geometry" VARCHAR,
  "destination_movement_id" BIGINT,
  "destination_display_name" VARCHAR,
  "destination_geometry" VARCHAR,
  "date_range" VARCHAR,
  "mean_travel_time_seconds" BIGINT,
  "range_lower_bound_travel_time_seconds" BIGINT,
  "range_upper_bound_travel_time_seconds" BIGINT
);

Travel Times Johannesburg And Pretoria

@kaggle.ishandutta_uber_travel_movement_data_2_billion_trips.travel_times_johannesburg_and_pretoria

17.56 KB
226 rows
8 columns


CREATE TABLE travel_times_johannesburg_and_pretoria (
  "origin_movement_id" BIGINT,
  "origin_display_name" VARCHAR,
  "destination_movement_id" BIGINT,
  "destination_display_name" VARCHAR,
  "date_range" VARCHAR,
  "mean_travel_time_seconds" BIGINT,
  "range_lower_bound_travel_time_seconds" BIGINT,
  "range_upper_bound_travel_time_seconds" BIGINT
);

Travel Times Manila

@kaggle.ishandutta_uber_travel_movement_data_2_billion_trips.travel_times_manila

74.74 KB
477 rows
10 columns


CREATE TABLE travel_times_manila (
  "origin_movement_id" BIGINT,
  "origin_display_name" VARCHAR,
  "origin_geometry" VARCHAR,
  "destination_movement_id" BIGINT,
  "destination_display_name" VARCHAR,
  "destination_geometry" VARCHAR,
  "date_range" VARCHAR,
  "mean_travel_time_seconds" BIGINT,
  "range_lower_bound_travel_time_seconds" BIGINT,
  "range_upper_bound_travel_time_seconds" BIGINT
);

Travel Times Paris

@kaggle.ishandutta_uber_travel_movement_data_2_billion_trips.travel_times_paris

80.04 KB
2227 rows
8 columns


CREATE TABLE travel_times_paris (
  "origin_movement_id" BIGINT,
  "origin_display_name" VARCHAR,
  "destination_movement_id" BIGINT,
  "destination_display_name" VARCHAR,
  "date_range" VARCHAR,
  "mean_travel_time_seconds" BIGINT,
  "range_lower_bound_travel_time_seconds" BIGINT,
  "range_upper_bound_travel_time_seconds" BIGINT
);

Travel Times Sydney

@kaggle.ishandutta_uber_travel_movement_data_2_billion_trips.travel_times_sydney

178.41 KB
871 rows
10 columns


CREATE TABLE travel_times_sydney (
  "origin_movement_id" BIGINT,
  "origin_display_name" VARCHAR,
  "origin_geometry" VARCHAR,
  "destination_movement_id" BIGINT,
  "destination_display_name" VARCHAR,
  "destination_geometry" VARCHAR,
  "date_range" VARCHAR,
  "mean_travel_time_seconds" BIGINT,
  "range_lower_bound_travel_time_seconds" BIGINT,
  "range_upper_bound_travel_time_seconds" BIGINT
);

Travel Times Washington Dc

@kaggle.ishandutta_uber_travel_movement_data_2_billion_trips.travel_times_washington_dc

1.31 MB
550 rows
10 columns


CREATE TABLE travel_times_washington_dc (
  "origin_movement_id" BIGINT,
  "origin_display_name" VARCHAR,
  "origin_geometry" VARCHAR,
  "destination_movement_id" BIGINT,
  "destination_display_name" VARCHAR,
  "destination_geometry" VARCHAR,
  "date_range" VARCHAR,
  "mean_travel_time_seconds" BIGINT,
  "range_lower_bound_travel_time_seconds" BIGINT,
  "range_upper_bound_travel_time_seconds" BIGINT
);