Picturing Plots with Python

remember learning C and C++ back when I was pursuing my engineering. I also remember learning JAVA when I joined my first job back in 2017. And I definitely remember, finding both of them a little overwhelming for my coding appetite.

With Python, not only did coding become more fun and enjoyable, I also found myself more curious and eager to learn new things to do with it. I had taken up a few courses a few months back and completed a few certifications on Data Visualization & Analysis with Python out of interest. And this quarantine I decided to play around and get comfortable experimenting with a COVID-19 data subset I found online.

I was able to download a file that contained COVID-19 statistics for each state in the US for a period of 19 days. The folder had a set of files, one for each day, recording the numbers state-wise.

Tasks I performed using Python:

1. I first collected the name of each of these 19 files, and then captured the content from each of these files into a Pandas DataFrame.
2. I performed Data Wrangling on the dataset. In other words, I cleaned the dataset and re-organised it into a desirable format and layout.
3. I made use of Folium to plot and mark each of the states on a map with an icon, clicking which displays the name of the state and the total count of cases. I color-coded them based on a threshold value.
4. Lastly, I plotted a few bar and scatter plots to display the data visually for ease of interpretation.

Here are a few snapshots from my mini-project.

Note:

• The data depicted may not be 100% accurate since values might have gotten tweaked as a result of data cleaning and deletion of missing or unknown values.
• The data available captures an estimate of values from 12th April 2020 for a period of 19 days, and may not give a full, accurate coverage of the progress of COVID-19.
• This mini-project was created with the intention of getting myself more comfortable and familiarized with Data Analysis and Visualization with Python.