Sureet Sarau Portfolio

Covid Data Analysis and Visualization

Data Analysis

Overview

About the project

As a project for my Data-Oriented Programming class, I, along with 2 peers, worked to gather data from 2 API's and 1 website. With that data, we created tables, conducted various calculations, and visualized data through multiple graphs. Data was based off of the CDC's tracking of weekly national and Michigan covid cases, weekly initial unemployment claims nationally and in Michigan based off data from the US Department of Labor, and weekly national and Michigan travel numbers based off data from the Transportation Bureau. Data from March 2020 to March 2021 was collected. We used Python to gather data, run calculations, visualize data, and implement tables into SQL. These tables were used for calculations for graph visualizations.

Date Started

March 22, 2021

Date Completed

April 26, 2021

My Responsibilities

Gather national and state-wide unemployment claim data by week
Create and join unemployment tables into single SQL database
Run calculations from all 3 data sources for visualizations
Export calculations into CSV file

Tools Used

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Importing data to Python

To collect weekly unemployment claim data from the Department of Labor, I parsed through an HTML file and scrapped the data. I used python, and the python library BeautifulSoup, to create code to collect this data. The data was stored into 2 dictionaries - one for national and one for state-wide data.

SQL Database of tables from each sources

Creating SQL Tables

Afterwards, I created code to construct and fill tables in our SQL database for my team to also have access to my data and vice versa.

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Running Calculations

Once we had finished data collection, I used data from SQL tables to run calculations in python. I ran calculations like weekly percent changes and cumulative totals - 10 calculations total. Afterwards, I created and imported this data to a CSV file

Visualizations

Based off the calculations, we created various graphs to visualize this data and trend changes in unemployment and travel throughout the lockdown. We used python to visualize the data. Some of the visualizations can be seen below