BuddyMove Data Set
Donated on 6/30/2018
User interest information extracted from user reviews published in holidayiq.com about various types of point of interests in South India
Dataset Characteristics
Multivariate, Text
Subject Area
Other
Associated Tasks
Classification, Clustering
Feature Type
Real
# Instances
249
# Features
-
Dataset Information
Additional Information
This dataset was populated from destination reviews published by 249 reviewers of holidayiq.com till October 2014. Reviews falling in 6 categories among destinations across South India were considered and the count of reviews in each category for every reviewer (traveler) is captured.
Has Missing Values?
No
Variables Table
| Variable Name | Role | Type | Description | Units | Missing Values |
|---|---|---|---|---|---|
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no |
0 to 7 of 7
Additional Variable Information
Attribute 1 : Unique user id Attribute 2 : Number of reviews on stadiums, sports complex, etc. Attribute 3 : Number of reviews on religious institutions Attribute 4 : Number of reviews on beach, lake, river, etc. Attribute 5 : Number of reviews on theatres, exhibitions, etc. Attribute 6 : Number of reviews on malls, shopping places, etc. Attribute 7 : Number of reviews on parks, picnic spots, etc.
Dataset Files
| File | Size |
|---|---|
| buddymove_holidayiq.csv | 7.4 KB |
Reviews
There are no reviews for this dataset yet.
pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset buddymove_data_set = fetch_ucirepo(id=476) # data (as pandas dataframes) X = buddymove_data_set.data.features y = buddymove_data_set.data.targets # metadata print(buddymove_data_set.metadata) # variable information print(buddymove_data_set.variables)
Renjith, S. (2014). BuddyMove Data Set [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5N316.
Creators
Shini Renjith
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.