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  • Hospitality and Tourism
  • Beautiful Soup
  • Dash by Plotly
  • Folium
  • Matplotlib
  • NumPy
  • Pandas
  • Plotly
  • Requests
  • Scikit-learn
  • Seaborn
  • TensorFlow

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  1. Disciplines

๐Ÿจ Hospitality and Tourism

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Hospitality and Tourism

Beautiful Soup

  • Description: A library for pulling data out of HTML and XML files.

  • Use Case: Scraping websites for information on hotels, attractions, and reviews, which is essential for market analysis and customer sentiment analysis in hospitality and tourism.

  • Documentation:

  • GitHub Repository:

Dash by Plotly

  • Description: A Python framework for building analytical web applications.

  • Use Case: Creating interactive, web-based dashboards for visualizing tourism data, such as visitor statistics, booking rates, and customer preferences.

  • Documentation:

  • GitHub Repository:

Folium

  • Description: A library that makes it easy to visualize data thatโ€™s been manipulated in Python on an interactive leaflet map.

  • Use Case: Mapping tourist attractions, routes, and accommodation options, providing interactive maps for websites and apps.

  • Documentation:

  • GitHub Repository:

Matplotlib

  • Description: A plotting library for creating static, animated, and interactive visualizations in Python.

  • Use Case: Generating charts and graphs for tourism studies, such as visitor flow analysis, seasonal trends, and revenue forecasts.

NumPy

  • Description: The fundamental package for scientific computing with Python.

  • Use Case: Handling numerical data for statistical analysis in tourism research, financial forecasting, and operational optimization.

Pandas

  • Description: Data analysis and manipulation library.

  • Use Case: Managing and analyzing tourism-related data sets, such as booking records, customer feedback, and occupancy rates.

Plotly

  • Description: An interactive graphing library.

  • Use Case: Creating dynamic and interactive visualizations for hospitality and tourism data, enhancing reports and presentations with engaging visuals.

Requests

  • Description: A simple HTTP library for Python.

  • Use Case: Automating the retrieval of data from APIs related to weather, local events, or transportation schedules, which can inform hospitality services and tourism offerings.

Scikit-learn

  • Description: Machine learning in Python.

  • Use Case: Predictive modeling for customer behavior, demand forecasting, and personalization of hospitality services.

Seaborn

  • Description: A Python data visualization library based on Matplotlib.

  • Use Case: Creating attractive statistical graphics for hospitality and tourism research, offering insights into customer demographics, satisfaction scores, and market trends.

TensorFlow

  • Description: An end-to-end open-source platform for machine learning.

  • Use Case: Developing AI models for enhancing customer experiences in tourism, such as personalized travel recommendations, chatbots for customer service, and image recognition for interactive guides.


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Documentation:

GitHub Repository:

Documentation:

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GitHub Repository:

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GitHub Repository:

Documentation:

GitHub Repository:

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GitHub Repository:

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GitHub Repository:

Beautiful Soup Documentation
Beautiful Soup GitHub
Dash Documentation
Dash GitHub
Folium Documentation
Folium GitHub
Matplotlib Documentation
Matplotlib GitHub
NumPy Documentation
NumPy GitHub
Pandas Documentation
Pandas GitHub
Plotly Documentation
Plotly GitHub
Requests Documentation
Requests GitHub
Scikit-learn Documentation
Scikit-learn GitHub
Seaborn Documentation
Seaborn GitHub
TensorFlow Documentation
TensorFlow GitHub