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bee_colony_dashboard_r's Introduction

๐Ÿ Bee Colony Dashboard

Providing apiarists with valuable insights into bee colony health

dashboard-gif

Welcome

Thank you for showing interest in the Bee Colony Dashboard! To view the dashboard please click here.

This README was created to provide you with more information about this project. Use the links below to jump to a section or scroll down.

What are we doing?

The problem

During the winter of 2006-2007, some beekeepers in America began to report unusually high losses of 30-90 percent of their hives. Bees are one of the most essential components of modern agriculture as a wide variety of flowering plants, including apples and blueberries, require managed pollinators such as bees to ensure continued production. Colony loss has declined since then but is still a concern as bees are vital to the natural ecosystem and our food systems.

The solution

Easy access to data on declining colony health is therefore necessary to maintaining natural ecosystems and food systems. In particular our dashboard will allow users to visualize and explore the number of colonies, the loss trend, and colony stressors over time in different localities of the United States through a time series plot, a stacked bar chart, and a geographic map.

In the time series plot, the number of colonies of a single state as it varies over a specified period of time is visualized, and by hovering over a point, the user can get an exact value of the number of colonies at a certain quarter of the year. The user can control the state and time period by choosing options through three different dropdown menus.

In the stacked bar chart, the percentage of colonies being affected by different types of colony stressors in a single state, as it varies over a specified period of time is visualized. By hovering over a segment of the bar chart, the user can obtain the exact percentage of colonies being affected by a certain stressor type at a certain quarter of the year. Using the same dropdown menus as the time series plot, the user can control the state and time period that is visualized.

In the geographic map of the United States of America, the user is be able to adjust the time period (measured by quarters of a year) that they are looking at by using a dropdown menu. By hovering over a state, the user can obtain the colony loss percentage, measured as the number of lost colonies divided by the maximum number of colonies in that time period.

Please refer to our proposal for more information.

Who are we?

The founders of the Bee Colony Dashboard, Daniel King, Manju Neervaram Abhinandana Kumar, Qingqing Song, and Tianwei Wang, are Masters of Data Science students at the University of British Columbia.

Get involved

If you find a bug or have thought of a way in which our project can improve please refer to our contributing guidelines. We welcome and recognize all contributions! In addition, if you join us in this project we ask that you follow our code of conduct.

License

Bee_Colony_Dashboard_R was created by Daniel King, Manju Neervaram Abhinandana Kumar, Qingqing Song, and Tianwei Wang. It is licensed under the terms of the MIT license.

Run the app locally

If you cannot open the app online for some reason, you can also run our app using Docker by running the following commands from the command line after cloning the repo:

cd Bee_Colony_Dashboard_R
docker-compose up

Finally, open the app in the following URL: http://localhost:8050/

Note that it may take about 10 minutes to build the app locally.

Thank you

Thank you again for showing interest in our project! We hope that you found what you were looking for. Feel free to give us suggestions on how we can improve or any other thoughts on the project.

bee_colony_dashboard_r's People

Contributors

danfke avatar davidwang11 avatar manju-abhinandana avatar scarlqq avatar

Forkers

davidwang11

bee_colony_dashboard_r's Issues

Finish your interactive Dash app with R and ggplotly

rubric={accuracy:10, quality:5, viz:15}

Put together all the code your team members created for IA2 in an DashR in the UBC-MDS repo you created for milestone3.
The goal is to implement most of your milestone 2 dashboard, so that you can compare dashboard development in Python and R. But if the app it is not 100% identical we are still going to consider it correct.
The main reason to deviate from your milestone 2 dashboard is if your TA has given you feedback that you want to implement.
Update your README with a link to the deployed R dashboard and a new image/gif of the R dashboard in action.
Note that TAs will be grading your app on Heroku in a full-screen window.
Again, the app should be easily usable, so focus on the most important things first. include the link to your deployed dashboard clearly visible near the top of your README or in the ABOUT section of the repo.

Deployment on Heroku

rubric={accuracy:5}

Deploy your app on Heroku and include the link to your deployed dashboard clearly visible near the top of your README.
Make sure to take away debug=True when you are deploying to Heroku, there should not be a blue debug button on the page your target audience will visit!
Remember to follow all the tips for Heroku deployment in IA2 and other common issues that can be read in the GitHub issues of the course

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