I am a Software Engineer and finding the relevance of a certain programming language seems to be pretty daunting with the ever-increasing pool of programming languages and their usage. This analysis tries to shed some light on the way we can perceive this data with the help of some other datasets as well. I am greatly indebted to jovian.ml for this course as well as the jovian package which has made version control a cake-walk almost. Setting up an adhoc online environment with Binder gives the flexibility of working on the fly with resource management as a server-sourced service available on a mouse-click. Rest of the packages used for this analyses are pandas, matplotlib and seaborn. The main data is sourced from https://www.kaggle.com/jaimevalero/developers-and-programming-languages
project_name = "usage-of-programming-languages"
!pip install jovian --upgrade -q !pip install pandas
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[jovian] Attempting to save notebook.. [jovian] Updating notebook "diysane/usage-of-programming-languages" on https://jovian.ml/ [jovian] Uploading notebook.. [jovian] Capturing environment.. [jovian] Committed successfully! https://jovian.ml/diysane/usage-of-programming-languages