Vacation Destination Check
with SAS Visual Analytics
Project Background
This project involved analyzing up-to-date global weather data. As a result, I have successfully developed a user-friendly web application that provides personalized holiday destination recommendations tailored to your preferred weather conditions in SAS Visual Analytics.
Objective
The objective of this project was to analyze current global weather data and develop a user-friendly web application using SAS Visual Analytics.
Question
How can we leverage up-to-date global weather data to offer personalized holiday destination recommendations?
Data
- kaggle.com
- dwd.de
Skills
- extracting text files and converting them to CSV format using Python
- filtering and cleaning data using SAS Studio
- creating visually appealing dashboards for data analysis and presentation purposes
Tools
- Excel
- Python
- SAS Visual Analytics
- SAS Studio
How does the Web-App look like?
The developed web application features a user-friendly interface with clear instructions located at the top, a comprehensive set of applicable filters on the left-hand side, and a central world map displaying average temperature and precipitation levels as the core visualization.
How do the filters look like?
Now, let’s explore the available filters. Within the web application, you have the flexibility to select your desired travel month, specify the minimum and maximum temperature ranges, indicate your preferred wind speed, and set a maximum limit for precipitation at your holiday destination. As you adjust these filters, the map will automatically update to display only the countries that meet your specific criteria, ensuring a tailored selection for your perfect holiday.
Get more weather details!
By simply double-clicking on a country of interest, you can access a wealth of detailed information about that specific location within the web application. This feature provides users with an opportunity to delve deeper into comprehensive details such as the region, sub region all the temperature details as well as data on pressure and wind speed.
Limitations
Limitations: It should be noted that the datasets used for this project donot include data for all countries, and the reliance on a single weather station per country may introduce limitations in terms of representing the overall weather conditions accurately for each location.