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Data Viz Blog

This is the repository for my data blog, visualizing and analyzing data from start to finish.

You can check out the blog here: datavizblog.herokuapp.com

About the App

The goal of this app is to share data visualizations on topics I find interesting.

Sometimes all the data is out there, but there isn't a decent visualization of exactly what you want. This happened to me a few times, so I decided I would just take the data and make what I want to see myself.

Making this app has also allowed me to practice using Python libraries for data manipulation and visualization. I talk about them a bit below in the Libraries section of the ReadMe.

A few ideas for the app layout were inspired by the open source project awesome-streamlit created and maintained by Mark Skov Madsen. You can access the app at awesome-streamlit.org and the repository at MarkSkovMadsen/awesome-streamlit.

Topics

I plan on writing about mutliple different topics over time, but at the beginning I'll be focusing on finance and stock market visualizations.

Posts

I'll try and maintain a list of the posts and specific repository folders here.

  • Dividend Growth Visualization - Folder
  • How Fear Determines the Market - Folder

Libraries

To create the app I used Streamlit. Streamlit is a Python library that allows for simple, elegant and rapid production of web apps that have anything to do with data. It was released in 2019 and they're always adding more to it, so I'm definitely excited to see how I can add to the blog through Streamlit.

To collect some of the finance related data, I used yfinance. yfinance is a Python library that allows you to get stock market data and history with a simple function call.

To read and process the data I used Pandas. Pandas is an extremely useful open source Python library used to read, manipulate and analyze data.

The graphs were created using Seaborn or Plotly. Seaborn is a Python library built ontop of Matplotlib used to create nice out-of-the-box charts for data visualization. Plotly is an Python graphing library that makes cool interactive charts.

Links to the Libraries

Contact & Feedback

If you enjoyed looking at the blog, have feedback on how I can improve it, a topic idea for a post or a post itself you'd like to share, I'd love to hear from you! The best way to reach me is via email or LinkedIn, both provided in my main profile page.

Feel free to submit a pull request if you have any suggestions you would like to try and fix or implement yourself.

If you're interested in any of the other projects I've worked on, check out my other repositiories on my GitHub or take a look at my Website (hosted with GitHub Pages from my 'Website repository'): elipropp.github.io/Website.

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The repo for my blog, visualizing and analyzing data in easy to read way

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