Stock keeping units
Donated on 4/9/2019
The dataset is provided by the “Trialto Latvia LTDâ€, the third-party logistics operator. Each observation stands for a distinct type of item for sale.
Dataset Characteristics
Multivariate
Subject Area
Business
Associated Tasks
Clustering
Feature Type
Integer, Real
# Instances
2279
# Features
9
Dataset Information
Additional Information
The dataset is originally provided by the “Trialto Latvia LTDâ€, the third-party logistics operator. The dataset consists 2279 observations with 7 features. Selected features include only numerical data and comprise a lot of information beyond that utilized by a classical ABC analysis. 3All the features have an undeniable impact on the inventory management and constitute two core groups: handling-related and turnover-related. Such features as expire date, pallet weight, pallet height and number of units per pallet determine the speed and subtlety of handling. On the other hand,total outbound and number of outbound orders indicate how tradable a particular product is. The total outbound and the number of outbound orders is represented as different attributes despite the fact of sharing some mutual information. It is done on purpose, since both the demand size and the demand frequency are important for the research. It is also worth to note that the feature “number of outbound orders†is calculated based on arisen demand from 2017-02-06 to 2018-02-13 (537,791 orders in total).
Has Missing Values?
Yes
Variable Information
1) Unit price - unit price in euro 2) Expire date - shelf-life 3) Total outbound - number of pallets sold from 2017-02-06 to 2018-02-13 4) Number of outbound orders - how many times a product was ordered from 2017-02-06 to 2018-02-13 5) Pallet weight - how much a fully-loaded pallet weights (kg) 6) Pallet height - height of a fully-loaded pallet (cm) 7) Units per pallet
Dataset Files
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pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset stock_keeping_units = fetch_ucirepo(id=531) # data (as pandas dataframes) X = stock_keeping_units.data.features y = stock_keeping_units.data.targets # metadata print(stock_keeping_units.metadata) # variable information print(stock_keeping_units.variables)
Stock keeping units [Dataset]. (2019). UCI Machine Learning Repository. https://doi.org/10.24432/C5CG7S.
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.