Hi DQ Community
This question is more towards the teachers, content writers, mentors, moderators and similar working at and behind DQ and also professionals.
But any thoughts, suggestions, anecdotes are welcome!
Had this question since I came across Matplotlib library. I understand anything new takes it time to be learned and understood.
May be because I used other data-visualization tools (not as main work, but basis requirements in projects assigned) at my previous work-place, I find Matplotlib overwhelming.
I came across these articles (and similar comparisons in Quora and other platforms):
https://www.stoltzmaniac.com/tool-selection-python-tableau-r/
I make one chart, go on to learn the other type and voila my slate for previous is pristinely clean. Everything goes blank.
I would like to understand if the companies and industries definitely prefer to have single and streamlined package learning that is if I want to be a Data Scientist then I need to know Python with R with Plotly with Matplotlib and so on.
Is it okay, to build a profile for DS that has a mix and combination of tools and techniques for the purpose they were intended to?
As in, will I diminish my chances to find work if I can learn the ETL and cleansing process in Python ( and R - I haven’t yet started anything on R) and go for strong DV tools like Tableau/ QlikView and so on, mix and match them together to achieve complete results.
As of now, I have replicated the data visualization part for one “GP-Employee Exit Survey” under DS track. Following is a link for the same. I am still learning and adding so the graphs would look very primitive
link for tableau project: https://public.tableau.com/profile/ruchi.sharma#!/vizhome/ExitSurveyDETETAFE/ExitSurvey
Thanks and Regards