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| Format: | Recurso digital |
| Language: | Spanish |
| Published: |
Zenodo
2025
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| Online Access: | https://doi.org/10.5281/zenodo.17586219 |
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| _version_ | 1866901637147131904 |
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| author | Pinedo, Lloy |
| author_facet | Pinedo, Lloy |
| contents | <p>The dataset compiles monthly historical information on tourist flows in Peru's main tourist destinations—Machu Picchu, Sacsayhuaman, Ollantaytambo, Moray, and the Ballestas Islands—during the period 2022–2024. The database integrates six groups of predictor variables: time (month and year), tourist flow (domestic and international visitors registered by MINCETUR), seasonality (low, medium, and high according to tourist activity), digital interest (Google Trends search indices weighted 80/20 between main name and variant), special events (0 = No, 1 = Yes), and climatic variables (average temperature and monthly precipitation reported by SENAMHI). Each record represents a monthly observation per destination, forming a temporal panel dataset suitable for supervised learning and time series prediction using machine learning techniques.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17586219 |
| institution | Zenodo |
| language | spa |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Tourist flow database in five destinations in Peru (2022-2024) Pinedo, Lloy <p>The dataset compiles monthly historical information on tourist flows in Peru's main tourist destinations—Machu Picchu, Sacsayhuaman, Ollantaytambo, Moray, and the Ballestas Islands—during the period 2022–2024. The database integrates six groups of predictor variables: time (month and year), tourist flow (domestic and international visitors registered by MINCETUR), seasonality (low, medium, and high according to tourist activity), digital interest (Google Trends search indices weighted 80/20 between main name and variant), special events (0 = No, 1 = Yes), and climatic variables (average temperature and monthly precipitation reported by SENAMHI). Each record represents a monthly observation per destination, forming a temporal panel dataset suitable for supervised learning and time series prediction using machine learning techniques.</p> |
| title | Tourist flow database in five destinations in Peru (2022-2024) |
| url | https://doi.org/10.5281/zenodo.17586219 |