Cainiao-AI/LaDe-D

LaDe is a public last-mile delivery dataset containing millions of parcels from industry. The dataset has three distinctive characteristics: (1) Large scale – it involves 21,000 couriers handling 10,677,000 parcels over six months. (2) Comprehensive information – it provides raw parcel details such as location and time requirements, as well as task event information that records the courier's location and time at task acceptance and completion. (3) Diversity – the dataset includes pick‑up and delivery data from multiple cities, each exhibiting unique spatio‑temporal patterns.

Updated 6/22/2023

hugging_face

Description

Dataset Overview

Dataset Name: LaDe

License: Apache-2.0

Tags:

Spatial-Temporal
Graph
Logistic
Last-mile Delivery

Size Category: 10M < n < 100M

Dataset Features

Feature Name	Data Type
order_id	int64
region_id	int64
city	string
courier_id	int64
lng	float64
lat	float64
aoi_id	int64
aoi_type	int64
accept_time	string
accept_gps_time	string
accept_gps_lng	float64
accept_gps_lat	float64
delivery_time	string
delivery_gps_time	string
delivery_gps_lng	float64
delivery_gps_lat	float64
ds	int64

Dataset Splits

Split Name	Bytes	Sample Count
delivery_jl	5,568,309	31,415
delivery_cq	168,574,531	931,351
delivery_yt	36,796,326	206,431
delivery_sh	267,095,520	1,483,864
delivery_hz	335,088,000	1,861,600

Download Information

Download Size: 290,229,555 bytes
Dataset Size: 813,122,686 bytes

Dataset Description

LaDe is a public last‑mile delivery dataset containing millions of parcels from industry. The dataset has the following characteristics:

Large Scale: It involves 10,677k parcels and 21k couriers, covering six months of real‑world operation.
Comprehensive Information: It provides raw parcel details such as location and time requirements, as well as task event information that records the courier's location and time at task acceptance and completion.
Diversity: The dataset contains data from various scenarios, such as parcel pick‑up and delivery across multiple cities, each with its own unique spatio‑temporal patterns.

Dataset Usage

When using this dataset for research, please cite the relevant paper: {xxx}

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Topics

Last‑Mile Delivery

Logistics Data Analysis

Source

Organization: hugging_face

Created: Unknown

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