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https://github.com/atxtechbro/tearsheet-generator

Retrieves JSON response from REST API the 2021 'Inc. 5000' dataset of the fastest growing proivate companies in the USA. Enter your industry and/or metro area to retrieve a "tearsheet" to use in order to make sure you are applying to these rapidly growing companies in your industry.
https://github.com/atxtechbro/tearsheet-generator

Last synced: 2 months ago
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Retrieves JSON response from REST API the 2021 'Inc. 5000' dataset of the fastest growing proivate companies in the USA. Enter your industry and/or metro area to retrieve a "tearsheet" to use in order to make sure you are applying to these rapidly growing companies in your industry.

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# Tearsheet-Generator

Retrieves JSON response from REST API the 2021 'Inc. 5000' dataset of the fastest growing proivate companies in the USA. Enter your industry and/or metro area to retrieve a "tearsheet" to use in order to make sure you are applying to these rapidly growing companies in your industry.



When I was working in the staffing and recruiting industry, "Tearsheets" is a name I heard thrown around all the time. I never got a firm definition of 'tearsheet' but my impression is that is was the type of document where you would quicklyu jot down some hot leads on a piece of scrap paper while researching and then literally 'tear the sheet' off the binder and run over to your desk to make phone calls to prospective clients who have a higher than likely chance of responding positively compared to a random name picked out of a phone book.



This project takes inspiration from that concept and applies a less manual, more automated approach by taking advtage of open source technologies freely available to the public such as Python, the inc. 5000 REST API JSON - formatted reponse, the requests library and the pandas library (like excel for Python).



I put this project out with the scope of the job seeker in mind. I am in fact trying to find full time employment at the moment and noticed when a bunch of posts came out today talking about the Inc 5000 list on LinkedIn posts.



5000 companies is a lot. Consider the Dow (30), the S&P (500) or the Russel (2000) these are all publically traded companies with quarterly published earning reports. They are the household names millions of Americans instantly recognize. Due to that, these large companies enjoy a well-known brand presence consequently an attractive image in the minds of job-seekers.



However 44% of economic activity is generated by small businesses. These firms may not be on the radar of job seekers, not least because they may not even be aware of the smaller yet exponentially growing firms. The problem this project is trying to solve is to inform jobseekers of the small and medium sized companies in their industry and/or location by providing them with a tearsheet containing roughly 20 companies.



I know from my experience when running it myself for "Software" & "Chicago" I was looking at a list of 20 companies and I had only ever heard of 3 of them. So I will certainly click on the websites that are also provided and most likely fill out at least a dozen applications, all of which I am local for (advantage) and there are less candidates applying for because lack of employer name recogition (advantage). 



I encourage feedback and also encourage exploration of the dataset. This project could eaisily be forked in order to just collect the 5,000 company list in the form of a dataframe. In order to do that, simply use the 'df' variable and run the script in a python session. This saves the developer the time expense of hunting for the endpoint connecting to api.



I hope this actually gets used by either the jobseekers, the data explorers, or some other user I haven't predicted. That is the joy of open source. Please enjoy!