https://github.com/parvatijay2901/data-analytics-on-stackoverflow-questions
EC498: Mini Project II
https://github.com/parvatijay2901/data-analytics-on-stackoverflow-questions
Last synced: over 1 year ago
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EC498: Mini Project II
- Host: GitHub
- URL: https://github.com/parvatijay2901/data-analytics-on-stackoverflow-questions
- Owner: parvatijay2901
- Created: 2021-11-26T08:26:37.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2021-12-22T09:37:32.000Z (over 4 years ago)
- Last Synced: 2023-11-10T03:01:09.868Z (over 2 years ago)
- Language: Jupyter Notebook
- Size: 4 MB
- Stars: 0
- Watchers: 1
- Forks: 1
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Data-Analytics-on-Stackoverflow-questions
Stackoverflow is the most popular Q&A website for programmers as it provides useful information to many million programmers across the globe with its database of questions and answers. This provides techies a good opportunity to explore the trends and gather insights from data.
Data Analytics refers to the process of examining available datasets to draw conclusions about the information they contain. This enables us to take raw data and discover patterns to extract valuable insights from it. Thus, we performed descriptive data analytics on Stackoverflow to discover useful information, analyse trends and draw conclusions.
We aimed to collect data using Web Scraping instead of using survey data which is already available. Success of any data analysis depends heavily on the quality of data. We then performed the analysis and interpreted results by creating visualizations and interpretations.
Additionally, we have provided the user with a freedom to do the analysis on any domain and have provided various options for them to do the analysis:
## Web-scraping:

## Analytics:



## References:
- [Web Scraping using python tutorial](https://automatetheboringstuff.com/2e/chapter12/)
- [Request-HTML method](https://docs.python-requests.org/projects/requests-html/en/latest/)
- [seaborn:Statistical data visualization](https://seaborn.pydata.org/)