The project is organized as follows:
_config.yml # Configuration file for the Jekyll theme, used for customizing the website layout and settings
LICENSE # License information for the project
README.md # Project documentation, including an overview and instructions
requirements.txt # Python dependencies required to run the notebooks and scripts
_layouts/ # HTML layout templates for the website
default.html # Default layout template used across the site
arribo/ # Analysis of tourist arrivals to lodging establishments in Peru
arribo.ipynb # Analysis of monthly/yearly trends, domestic vs. international visitor patterns, seasonal visitation patterns, and predictive models
arribo.png # Snapshot image for visualization
rptaniomes_a.xls # Data file for monthly arrivals
rptaniomes_b.xls # Data file for monthly arrivals by national visitors
rptaniomes_c.xls # Data file for monthly arrivals by international visitors
rptaniomest_a.xls # Data file for regional arrivals
rptaniomest_b.xls # Data file for regional arrivals by national visitors
rptaniomest_c.xls # Data file for regional arrivals by international visitors
assets/ # Static assets for the project
css/ # Stylesheets for the website
style.scss # Main stylesheet for customizing the website's appearance
flujo_turista/ # Analysis of international tourist flows and economic impact
flujo_turista.ipynb # Analysis of foreign exchange earnings, tourist arrivals through entry points, migration patterns by country, and future forecasts
flujo_turista.png # Snapshot image for visualization
movimiento_general/ # Analysis of passenger movement at Peruvian airports
movimiento_general.ipynb # Comparison of passenger traffic across key airports, domestic vs. international patterns, and seasonal trends in air traffic
movimiento_general.png # Snapshot image for visualization
oferta_hotelera/ # Analysis of lodging infrastructure across Peru
oferta_hotelera.ipynb # Analysis of lodging establishments by region, room and bed-place capacity, and future infrastructure growth forecasts
pernoctaciones/ # Analysis of overnight stays in Peruvian lodging
pernoctaciones.ipynb # Analysis of overnight stays by domestic and international tourists, regional distributions, and seasonal occupancy patterns
pernoctaciones.png # Snapshot image for visualization
snapshot/ # Snapshot images used in the project
intro.jpg # Introductory image for the project
promperu.png # PromPeru logo used in the documentation
visitantes_a_sitios_turisticos/ # Analysis of visitor trends to specific tourist sites in Peru
visitantes_a_sitios_turisticos.ipynb # Analysis of visitor numbers to key cultural attractions, seasonal patterns, and long-term trends in site popularity
visitantes_a_sitios_turisticos.png # Snapshot image for visualization
Each notebook not only analyzes historical tourism data but also implements time series forecasting models to predict future trends, providing valuable insights for tourism planning and development in Peru.
MIT. See the LICENSE file for the copyright notice.
2018, October
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