Planning Planned Parenthood

Algorithm for selecting a new MA Planned Parenthood location!

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Planning Planned Parenthood

Space in the budget? Don't know where to put your next publicly funded health clinic? You've come to the right place.

Project Description

Planning Planned Parenthood is an webpage that takes in user input on criteria they value most when selecting a Massachusetts County to place a Planned Parenthood. Our algorithmic weights each criteria based on the user's ranking, and then produces the county that had the largest weighted sum value after assigning rank weights to each criteria.

Table Number!

15

Inspiration

We wanted to find and use data in a way that would impact the healthcare industry on a local level. Anika teaches 9th grade health classes in the Boston Public School System through Peer Health Exchange. While the class covers many topics, it seems that the teenagers always have the most questions about sex and relationships. While she is a trained educator, it would be great if there were more nearby resources that Anika could point them to when she doesn't know the answer. So we started looking for data about clinics and publicly funded health centers in Massachusetts. Our focus grew from Boston and teens to Massachusetts and its lack of Planned Parenthoods when we found a dataset detailing the need for publicly funded contraceptive services and supplies in all of the different counties across Massachusetts. We were also astonished to find that in the entire state of Massachusetts, with a population of almost 7 million people, there are only 4 Planned Parenthood locations. By comparison, Connecticut, a much smaller state (which we are both from) has a population of 3.5 million people, and 16 Planned Parenthood locations.

What's Next for PPP

It would be awesome if we could reach out to Planned Parenthood to possibly use some of their data about the subject. Because it would work best as an internal tool for them it would be okay to use their private datasets. This would mean that further refining of the algorithm would also have to be done. Another possible tweak would be to connect the data to some kind of Maps API. This way, we could visualize the counties and actually see the need for publicly funded clinics in the state. This would also allow the output data to be presented to the user in a more intuitive way.

How'd we do it?

  1. After obtaining multiple publicly available datasets, we imported all files into Python and used pandas dataframes to drop unneccessary data, as well as calculate new proportions that we use in our algorithm.
  2. The aggregated dataframes were then exported as a csv file to access in JavaScript.
  3. We built a webpage using HTML, CSS, and JavaScript, as well as some Bootstrap code.
  4. One of the largest functionalities we built was the form that allows the user to drag-and-drop their valued criteria. We had to use a lot of chained functions in order to mutate the HTML when the user pressed 'Submit'.
  5. Finally, we styled our website, and added some fun accessories, such as making a logo on Illustrator, and making our landing page look nicer.

Team Members

Caterina Wang and Anika Rabenhorst

Setup for your own computer!

  1. Clone this repository to your local machine. E.g., in your terminal / command prompt CD to where you want this the folder for this activity to be. Then run git clone <YOUR_REPO_URL>
  2. CD or open a terminal / command prompt window into the cloned folder.
  3. Start a simple python webserver. E.g., python -m http.server, python3 -m http.server, or py -m http.server. If you are using python 2 you will need to use python -m SimpleHTTPServer instead, but please switch to python 3.
  4. Wait for the output: Serving HTTP on 0.0.0.0 port 8000 (http://0.0.0.0:8000/).
  5. Now open your web browser (Firefox or Chrome) and navigate to the URL: http://localhost:8000
  6. Also: Update the file paths in the PPDataCleaning.py file so that it can correctly access the datasets.
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