Las Vegas Strip
Donated on 7/22/2017
This dataset includes quantitative and categorical features from online reviews from 21 hotels located in Las Vegas Strip, extracted from TripAdvisor (http://www.tripadvisor.com).
Dataset Characteristics
-
Subject Area
Business
Associated Tasks
Classification, Regression
Feature Type
Integer
# Instances
504
# Features
-
Dataset Information
Additional Information
All the 504 reviews were collected between January and August of 2015.
Has Missing Values?
No
Variables Table
| Variable Name | Role | Type | Description | Units | Missing Values |
|---|---|---|---|---|---|
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no |
0 to 10 of 20
Additional Variable Information
The dataset contains 504 records and 20 tuned features (as of “status = includedâ€, from Table 1 of the article mentioned below), 24 per hotel (two per each month, randomly selected), regarding the year of 2015. The CSV contains a header, with the names of the columns corresponding to the features marked as “status = includedâ€, from Table 1 of the aforementioned article.
Reviews
There are no reviews for this dataset yet.
pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset las_vegas_strip = fetch_ucirepo(id=397) # data (as pandas dataframes) X = las_vegas_strip.data.features y = las_vegas_strip.data.targets # metadata print(las_vegas_strip.metadata) # variable information print(las_vegas_strip.variables)
Moro,S., Rita,P., and Coelho,J.. (2017). Las Vegas Strip. UCI Machine Learning Repository. https://doi.org/10.24432/C5QG7W.
@misc{misc_las_vegas_strip_397,
author = {Moro,S., Rita,P., and Coelho,J.},
title = {{Las Vegas Strip}},
year = {2017},
howpublished = {UCI Machine Learning Repository},
note = {{DOI}: https://doi.org/10.24432/C5QG7W}
}Creators
S. Moro
P. Rita
J. Coelho
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.