Stack-Overflow

Findings from Stack Overflow 2018

1. Installation
2. Project Motivation
3. File Descriptions
4. Results
5. Licensing, Authors, and Acknowledgements

Installation:

There should be no necessary libraries to run the code here beyond the Anaconda distribution of Python. The code should run with no issues using Python versions 3.*.

Project Motivation:

For this project, I was interested in using Stack Overflow data from 2018 to better understand:

• Why is Stack Overflow a success? How does people give back to the community?
• How many languages are discussed in Stack Overflow?
• What methods does people follow for learning new programming technology without taking courses?

These factors give a fair idea about different aspects of Stack Overflow's success.

File description:

There are 2 Jupyter notebooks used in this project. The Stackoverflow.ipynb file is main file used to answer the above questions. GThe Extra-analysis.ipynb file contains extra visualizations carried to better understand the data set.

Results:

The main findings of this project can be found here.

Licensing, Authors, and Acknowledgement

Must give credit to Stack Overflow for the data. You can find the Licensing for the data and other descriptive information at the Kaggle link available here. Otherwise, feel free to use the code here as you would like!