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Features

ZipLoc4 (requires GOOGLE API KEY + OPENWEATHER API KEY, both available for free)

CLICK HERE TO DOWNLOAD: https://github.com/thndrthf/ZipLoc/releases/download/Weather/ZipLoc4.zip

  • Functionality: Generate a snapshot of weather and air quality data based on selected locations, such as cities, zip codes, or notable landmarks.
  • Usage: Run ZipLoc4 to collect current temperature and AQI information tailored to your areas of interest.
  • Whatever locations you enter will return a separate weather/AQI text file with a timestamp. These files will be automatically read into the viewer applications.

LocView10 (requires GOOGLE API KEY only)

CLICK HERE TO DOWNLOAD: https://github.com/thndrthf/ZipLoc/releases/download/Weather/LocView10.zip

  • Functionality: Create detailed temperature data visualizations and maps with pins marking the selected locations.
  • Usage: Execute LocView10 to produce comprehensive graphical outputs, making it easier to understand and analyze temperature variations across different areas.
  • Automatically reads in data generated by ZipLoc4, to generate a new graph simply generate new data. It will graph whatever you stuff into it, so if you pick Brooklyn NYC and San Diego CA for example it will give you a comparative graph with those data points.

LocViewFinalAQI (no api key)

CLICK HERE TO DOWNLOAD: https://github.com/thndrthf/ZipLoc/releases/download/Weather/LocViewFINALaqi.zip

  • Functionality: Generate an in-depth graphical output of AQI pollutant levels, providing a clear view of air quality variations.
  • Usage: Run LocViewFinalAQI after collecting your data to visualize the specific pollutant levels, aiding in environmental analysis.
  • Automatically reads in the data and returns a graph from whatever data points you gathered with ZipLoc4.

LocView4 (Optional) (no api key)

CLICK HERE TO DOWNLOAD: https://github.com/thndrthf/ZipLoc/releases/download/Weather/LocView4.zip

  • Functionality: This optional module creates beautiful graphical outputs that are aesthetically pleasing and suitable for presentation, and publication - less functional and more visually stunning - maps the temp plot points with pollutant info.
  • Usage: While not essential, using LocView4 enhances the visual appeal of your AQI data, making it worthy of publication or display. It gives a polished impression with a variety of data points on one graphical output that is just nice to look at.
  • Automatically reads and plots data from ZipLoc4. Give it a try.

Requirements

  • No additional software or Python installation is required to run the executable.
  • The application is fully self-contained with all necessary dependencies packaged.

-No Installation Required-

  1. Clone the repository or download the ZipLoc folder.
  2. Run the appropriate scripts as described above to collect and visualize your data.
  3. Scripts output in the parent folder above the applications, to keep the folder uncluttered, but structure it however you want. I believe they run from a subfolder but this software surprises me what it will do - including accepting slight misspelling, accepting coordinates, zipcodes and even just airport codes even, try it out - "EMPIRE STATE BUILDING" for example works.

Usage

To use ZipLoc effectively, follow the workflow:

  1. Run ZipLoc4 to gather weather and AQI data.
  2. Execute LocView10 to visualize temperature data on a map.
  3. Use LocViewFinalAQI to produce pollutant level graphs.
  4. Optionally, run LocView4 for enhanced graphical outputs.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

Special thanks to contributors and users for their feedback and support in improving the functionality and usability of ZipLoc.

Full Changelog: https://github.com/thndrthf/ZipLoc/commits/Weather

About

A streamlined application for accessing and visualizing air quality and weather data. ZipLoc allows users to generate snapshots of AQI and temperature readings for specific locations. With mapping capabilities and graphical outputs, it simplifies the analysis of environmental data.

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