- Alex
- Chuanqi
- Qinrui
- Tianshu
- Tianyu
This package contains all the necessary tools to process, H1-B application data from US Department of Labor statistics, generate visualizations based on the statistics and their trends, and run a predictor on application certification likelihood based on user-determined parameters.
The datasets were directly downloaded from the US Department of Labor's webpage on Performance Data. We have preprocessed the data, unifying the attribute names for all the years' datasets and removing extraneous attributes.
The Flask-Vue app consists of a home page with several links to views of dynamic visualizations of the statistics drawn from the data sets. All visualizations are dynamic charts created with D3.js.
The predictor is a gradient-boosted decision tree using the LightGBM framework.
Download the .zip package.
Or git clone https://github.com/budd713/datadreamteam.git
after we open our project as public.
-
The preprocessed datasets can be accessed in cloud storage by the links provided below (there should be 5). Please download them and place them in PROJECT_ROOT/data.:
https://abuddenbaum3.blob.core.windows.net/h1b/h1b_data_2017_new.csv https://abuddenbaum3.blob.core.windows.net/h1b/h1b_data_2018_new.csv https://abuddenbaum3.blob.core.windows.net/h1b/h1b_data_2019_new.csv https://abuddenbaum3.blob.core.windows.net/h1b/h1b_data_2020_new.csv https://abuddenbaum3.blob.core.windows.net/h1b/h1b_data_2021_new.csv
- Be sure to have NodeJs v14.17.x installed (or npm v6.14.x).
- Run
npm install
in the root directory of front-end PROJECT_ROOT/project/frontend.
Be sure to have python v3.8.x with flask-restful v0.3.9 and pandas installed.
- if not, download python3 from its official website
- then run
pip install -v flask==2.0.2
pip install -v flask-restful==0.3.9
pip install -v pandas==2.3
pip install -v numpy==1.21.2
pip install -v lightgbm==3.2.1
Run python app.py
in the root directory of back-end PROJECT_ROOT/flaskProject to launch the back-end service and wait for a few minutes (it may depend on your machine) to read and preprocess the data.
Run npm run serve
in the root directory of front-end PROJECT_ROOT/frontend to launch the frontend project.
Enter localhost:8080
in your browser to explore and enjoy our project!