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Female Representation

Phoenix Rising: Mihee Park, Shae Stringer-Jones, Maria Valdes, Kelly Fry

Content

  • This repository contains an interactive dashboard that explores various aspects of female participation in the workforce, internationally and within the United States.
  • International wage gap trends are explored with Leaflet, leadership trends in US elected positions are visualizated with Tableau, and machine learning is used to predict when the representation gap will close. Machine Learning is also used to interactively estimate salary based on user input.
  • This repository contains the notebooks utlilized in the ETL and cleaning process, raw data, cleaned JSON files, code for the Flask Server, saved ML models, and HTML files for the website used during the presentation.

Tools/Languages Utilized

  • Back-end: Python, Pandas, API, Jupyter notebook, Flask, PostgreSQL, Machine Learning, Graphviz, Joblib, Pickle
  • Front-end: HTML, CSS, Javascript，Tableau, Leaflet, Heroku

Note about Gender

  • The members of this group recognize that the scope of this project excludes groups of people with gender identities outside of male and female. We fully believe that those groups deserve equal representation and advocate that data collection methodology be inclusive of non-binary gender identities.