DATA11001 Introduction to Data Science project

Welcome to the "Google Trends And COVID: Predictions and Correlation" project. This project aims to provide insights into how Google search trends can be used to make predictions and analyze the correlation between online search behavior and COVID-19 cases. The project was created as an assignment for DATA11001 Introduction to Data Science by Yaqoub Baisili, Haseeb Shaikh and Jakub Grad.

The repository contains all the code, notebooks, and data related to the project.

The files:

1. data:

   1. owid-covid-data.csv: Official COVID data from Our Word in Data
   2. google_trends: folder containing the data for all the google trends keywords used
   3. pytrends_data: folder containing old google trends daily data for the pytrends notebook
   4. cleaned_data: folder contained all the data after being preprocessed and other intermediary outputs

2. final project.ipynb: This notebook contains the whole process, from the start reading all the files, preporcessing, find the keywords that best correlates to COVID, to fitting the model and testing its accuracy.

3. pytrends.ipynb: Old notebook containing exploratory data analysis on how daily google trends data correlates to covid data before we switched to weekly data and 2 week spans.