Stack-Overflow-Analysis

This is a project designed to explore and visualize data from the Stack Exchange Data Explorer website, in an interactive RShiny applet. I also wrote a blog post about this project!

Table of Contents

• Motivation
• The Data
• The Code
• Demo of App!
• You Want To Contribute?

Motivation

From Wikipedia:

Stack Exchange is a network of question-and-answer websites on topics in diverse fields, each site covering a specific topic, where questions, answers, and users are subject to a reputation award process. The reputation system allows the sites to be self-moderating.

As a data scientist, I code often, and am learning new technologies constantly. Sometimes I get stuck and refer to StackOverflow to learn from the community. The Stack Exchange network has quickly become my most-consulted website for help with learning new technologies, theories, methodologies, and more. I became interested in learning more about the network and the areas of expertise contributed to by the community, and naturally wrote some code to analyze this data.

The Data

The datasets used in this analysis were downloaded from the Stack Exchange Data Explorer website using the following SQL query:

SELECT * FROM Posts;

and downloaded as CSV files. I downloaded datasets for a few Stack Exchange network websites I visit often, such as the Astronomy, Data Science, Academia, etc. networks. Note that these are static datasets that were last downloaded on Dec 7, 2022.

The Code

To view and explore the datasets, I created an app in R using the Shiny framework. If you want to run this app too, follow these instructions:

1. Clone this repo.
2. Have R and RStudio installed.
3. Click on the Stack-Overflow-Analysis.Rproj file. This should open RStudio with all files in this repository already loaded.
4. Run the file app.R. Enjoy!

Demo

You can change the selected dataset, and number of displayed data points, like so:

On the 'Time Series' tab, you can change the time range to view the overall trends for the selected dataset over a longer or shorter period of time.

You can also download plots for your own analysis using the 'Download plot' buttons below each plot! This saves the plots as a png image.

You Want To Contribute?

Excellent! Some ways you could contribute:

• download more datasets from Stack Exchange Data Explorer to use for this app
• create an issue for a feature you want to see
• create an issue for any type of analysis you want to see here
• etc!