Suitability of Google Symptoms Trends data to analyze COVID pandemic: A geo-spatial case study

Packages required:

How to use :

SAITS_imputation_forecasting_granger.ipynb : This file can be used for imputation using SAITS and forecasting using NBEATS and TCN for regions of high quality and low quality data.
Clustering.ipynb : Clustering of correlated symptoms is done here for all regions
EDA.ipynb : Primary Exploratory Data Analysis and Recursive feature elimination is done here
CDC.ipynb : CDC data collection, resampling to weekly data and analysis is done here
EDA module : Contains helper functions for EDA.ipynb, CDC.ipynb and Clustering.ipynb

Name		Name	Last commit message	Last commit date
Latest commit History 45 Commits
EDAModule		EDAModule
datasets		datasets
CDC.ipynb		CDC.ipynb
Clustering.ipynb		Clustering.ipynb
EDA.ipynb		EDA.ipynb
GOOGLE_Symptom_Trends.tar.gz		GOOGLE_Symptom_Trends.tar.gz
LICENSE		LICENSE
README.md		README.md
SAITS_imputation_forecasting_granger.ipynb		SAITS_imputation_forecasting_granger.ipynb

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