TDS-Project1

Git hub users analysis repo

• How data was scrapped

  1. Created a user token for using rest api in github

  2. Used chatgpt to generate python code.

  3. Used google collab to run python note book

  4. The only change which had to be done in python code was replacement of user token

  5. Ran the program which generated the top 100 users in bangalore as csv (this gave only 5-6 users)

  6. So step5 raised a doubt and ran the users script with Bengaluru (this gave 20 users).. So overall step 5 + Step 5.5 = 25 users

  7. Ran the second program which used the top100userscsv as input

  8. Both the output as well as the programs have been checked in to this repo.

• Interesting/Surprising facts

  1. Python is grouped individually as juniper note book and python (but overall had 450 references) making it most popular in github (please refer the pivot generated from repository-chart.xls)

  2. Next in list were javascript and java respectively

  3. Almost 30% of repo data had blanks in language which can affect the overall analysis

• Recommendation

  1. As per the trend for python and scripting languages(java script and html) there can be useful references available in github for reuse.

  2. For overall development quickly chatgpt really helps.