Baselight

Uber Travel Movement Data [2 Billion+ Trips]

Uber Movement provides anonymized data from over two billion trips.

@kaggle.ishandutta_uber_travel_movement_data_2_billion_trips

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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

Data retrieved from Uber Movement, (c) 2017 Uber Technologies, Inc.,https://movement.uber.com

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
  • 642.41 kB
  • 496 rows
  • 10 columns
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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  -- Mean Travel Time (Seconds),
  "range_lower_bound_travel_time_seconds" BIGINT  -- Range - Lower Bound Travel Time (Seconds),
  "range_upper_bound_travel_time_seconds" BIGINT  -- Range - Upper Bound Travel Time (Seconds)
);

Travel Times Boston

@kaggle.ishandutta_uber_travel_movement_data_2_billion_trips.travel_times_boston
  • 273.26 kB
  • 700 rows
  • 10 columns
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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  -- Mean Travel Time (Seconds),
  "range_lower_bound_travel_time_seconds" BIGINT  -- Range - Lower Bound Travel Time (Seconds),
  "range_upper_bound_travel_time_seconds" BIGINT  -- Range - Upper Bound Travel Time (Seconds)
);

Travel Times Johannesburg And Pretoria

@kaggle.ishandutta_uber_travel_movement_data_2_billion_trips.travel_times_johannesburg_and_pretoria
  • 17.98 kB
  • 226 rows
  • 8 columns
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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  -- Mean Travel Time (Seconds),
  "range_lower_bound_travel_time_seconds" BIGINT  -- Range - Lower Bound Travel Time (Seconds),
  "range_upper_bound_travel_time_seconds" BIGINT  -- Range - Upper Bound Travel Time (Seconds)
);

Travel Times Manila

@kaggle.ishandutta_uber_travel_movement_data_2_billion_trips.travel_times_manila
  • 76.53 kB
  • 477 rows
  • 10 columns
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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  -- Mean Travel Time (Seconds),
  "range_lower_bound_travel_time_seconds" BIGINT  -- Range - Lower Bound Travel Time (Seconds),
  "range_upper_bound_travel_time_seconds" BIGINT  -- Range - Upper Bound Travel Time (Seconds)
);

Travel Times Paris

@kaggle.ishandutta_uber_travel_movement_data_2_billion_trips.travel_times_paris
  • 81.96 kB
  • 2,227 rows
  • 8 columns
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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  -- Mean Travel Time (Seconds),
  "range_lower_bound_travel_time_seconds" BIGINT  -- Range - Lower Bound Travel Time (Seconds),
  "range_upper_bound_travel_time_seconds" BIGINT  -- Range - Upper Bound Travel Time (Seconds)
);

Travel Times Sydney

@kaggle.ishandutta_uber_travel_movement_data_2_billion_trips.travel_times_sydney
  • 182.69 kB
  • 871 rows
  • 10 columns
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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  -- Mean Travel Time (Seconds),
  "range_lower_bound_travel_time_seconds" BIGINT  -- Range - Lower Bound Travel Time (Seconds),
  "range_upper_bound_travel_time_seconds" BIGINT  -- Range - Upper Bound Travel Time (Seconds)
);

Travel Times Washington Dc

@kaggle.ishandutta_uber_travel_movement_data_2_billion_trips.travel_times_washington_dc
  • 1.38 MB
  • 550 rows
  • 10 columns
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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  -- Mean Travel Time (Seconds),
  "range_lower_bound_travel_time_seconds" BIGINT  -- Range - Lower Bound Travel Time (Seconds),
  "range_upper_bound_travel_time_seconds" BIGINT  -- Range - Upper Bound Travel Time (Seconds)
);

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