JobPulse Insights
Unveiling Hidden Job Listing Metrics with Data Magic
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💡 Why did I execute this project ?
Potential Job seekers have the following questions....
Which industry is dominating recruitment ?
Which State/city would be best for career ?
Where should I study based on my career aspirations ?
{ Myself as a student, I wanted data that I could rely on and take decisions based on facts. So I took matters into my own hands. 👐}
Steps followed for the project 🚀
LinkedIn already has a good enough dataset, however they do not let users explore statistics related to the posting.
Developed a web scraping script which will extract data from LinkedIn and store it into a pandas data frame.
(The input is taken from user: Job Role)Next data was cleaned and transformed and prepared for consumption.
Finally used seaborna and matplotlib to create some beautiful visualizations.
Analyze the linkedin html code --> script using beautiful soup --> pandas to extract data
Analyze Requirements
Analyze Requirements
First step is analyze what exactly needs to be scraped.
Script, Web Scrape
Script, Web Scrape
Next developed a scrpit that will go into the webpage and pickup all data points necessary.
Scrape summary
Scrape summary
This image shows the summary of the scrape, 250 records were retrieved in 0.8 minutes
Data generated is then visualized using seaborn, matplotlib
(Data Extracted for Data Science jobs on 21st August 2023, USA)
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