A RNN approach to predicting when a stay at home order was announced given case data
This folder was used to scrape the below sources and gather needed data
- shelterinplace.csv: scraped via "webscraping.ipynb" notebook, which pulls from NYTimes
- us-counties.csv: pulled from NYTimes github page, https://github.com/nytimes/covid-19-data
- city_count.csv: manually created to handle city/county discrepancies between above two files
- us_county_sociohealth_data.csv: pulled from github page: https://www.kaggle.com/johnjdavisiv/us-counties-covid19-weather-sociohealth-data
mergedata.ipynb: Combines the above four data sources into a final.csv for the RNN model
This is our primary model with the below architecture. It produces an RNN model that looks at the next 19 days to predict if today has a stay at home for a given county. This file also contains our model performance evaluation.
This model includes demographic information with the below architecture. Similar to the RNN_Model, it looks at the next 19 days to predict if today has a stay at home for a given county.
