PANDOR
Donated on 10/1/2018
PANDOR is a novel and publicly available dataset for online recommendation provided by Purch (http://www.purch.com/).
Dataset Characteristics
Multivariate
Subject Area
Other
Associated Tasks
Recommendation
Feature Type
Categorical
# Instances
48000000
# Features
-
Dataset Information
Additional Information
source, offerId, pageViewId, offerViewId, utcDate, keywords, wasClicked, offerViewCountPerPageView, clickCountPerPageView, userId, productLemmas, productFeatures, url, pageLemmas, pageFeatures # Events: 48,602,664 # Users: 5,894,431 # Offers: 14,716 # Clicks: 337,511 # OffersShown: 48,754,927 # Max offers shown to 1 user: 2,029 # Max clicks done by 1 user: 119 Average # Offers Shown to 1 user: 8.271 Average # Clicks done by 1 user: 0.057 Average # Clicks done by 1 user (if user did at least 1 click): 1.350616661464461 # Events where user did at least 1 click: 4,544,848 # Events which have at least 1 page text words: 1,212,170 # Events which have at least 1 product Text words: 450,050 # Events which have at least 1 keyword: 4,492,544 page text vocabulary size: 9,111 product text vocabulary size: 6,016 keyword vocabulary size: 543 Out of 9,847 offers, 2,701 offers have at least 1 text word (27.4%) Out of 7,092 pages, 1,990 pages have at least 1 text word (28.1%)
Has Missing Values?
No
Dataset Files
| File | Size |
|---|---|
| fullData.anonymous.tar.bz2 | 4.6 GB |
Reviews
There are no reviews for this dataset yet.
pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset pandor = fetch_ucirepo(id=460) # data (as pandas dataframes) X = pandor.data.features y = pandor.data.targets # metadata print(pandor.metadata) # variable information print(pandor.variables)
Amini, M., Laclau, C., & Sidana, S. (2018). PANDOR [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5Q025.
Creators
Massih-Reza Amini
Charlotte Laclau
Sumit Sidana
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.