Brain Canada Management System

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Inspiration

While working in a lab developing bio-mechatronic systems for rehabilitation of Musculoskeletal Disorders (MSDs) I noticed similar difficulties in terms of logistics that Brain Canada did. We felt like a solution in python (specifically pandas library) would be a good start for the app. We both are familiar with front end and web but wanted to tackle python and more backend languages/frameworks so this was perfect.

What it does

Our code first imports the excel sheets (the samples provided by Brain Canada were used). The user inputs the name of the applicant they want to match with the reviewers, the code sorts all eligible reviewers in a list based on comparing similarities using the Levenshtein.distance method on all 3 columns (application type, area of research or keywords) and outputs the top 3 most similar reviewers to that applicant (when more than 1 have the same similarity score the choices are random to eliminate bias)

How we built it

We build it using python more specifically pandas and Levenshtein libraries on replit to make collaboration a little easier. We had to manipulate dataframes using append methods and even made our own functions that sort the reviewers and combine 3 similarity scores after comparing 3 columns of excel with string values.

Challenges we ran into

We had a lot of trouble with manipulating the data without a database, we went through multiple manual implementations before using pandas dataframe object.

What we learned

We are really proud of learning all about manipulating dataframes, python in the backend, importing/exporting excel sheets and even sorting algorithms!

What's next for Brain Canada Management System

We intend to make a login page where the reviewer can login and check which applicants are assigned to them. This python code would be the backend and the front-end a simple login page.

Built With

• beginner
• levenshtein
• pandas
• python