Python Matplotlib vs Tableau

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):

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 :stuck_out_tongue:

link for tableau project:!/vizhome/ExitSurveyDETETAFE/ExitSurvey

Thanks and Regards


I think it varies a lot from company to company. As an example, at Dataquest our data team has a mix of Python and R specialists. We primarily work in SQL as our data lives in databases and then use WYSIWYG data visualization tools built into our SQL platform (Mode Analytics) to visualize them. If we want to do some more complex analysis/visualization, then the analyst uses their personal preference of Python or R. We don’t really use anything like Tableau.

My understanding is that Tableau is not really an appropriate tool for ETL and data cleaning, so you’re going to need to use one or more of Python/SQL/R for these tasks anyway. What you then do with the data depends on what your specific skills are, and what the company you’re at supports.

It might be useful for you to spend some time researching the sort of entry-level jobs you are aiming for, to understand the typical toolset they use. This can help you more appropriately choose what tools you spend time learning so you use your time wisely.


Hey @joshdq

Thank you for the detailed response.

I am currently not employed and hence confused as to what to learn, in what depth and how to leverage my prior knowledge (I did courses on Oracle DB, PL/SQL, Java etc.) and have experience on Oracle Hyperion applications (although it didn’t include coding for my role).

I am following the entire track of Data-Science at DQ right now.

I agree on ETL in SQL, or Python is immensely powerful as compared to Tableau. But for couple of GP projects, I ditched matplotlib, and instead used Tableau public to make the same plots. This is what bugs me, if that was a good thing to do or it shows my laziness!

I am going through the DQ blogs about portfolio and profile building in between completing courses as well.

Thanks again. Will reach out in case of further doubts under this category.


I think one of the best things you can do is start looking at job listings. Keep in mind that entry level roles can be called data analyst, business analyst etc. Look at the skills that they are listing, and use that to inform what you learn.

The job market can vary a lot from location to location (and within locations, industries) so by looking at actual job ads you are able to educate yourself on how to use your learning time effectively.


I have the opposite problem: I really enjoy using seaborn/matplotlib/plotly and I am lazy to learn Tableau or Power BI, but I see these tools in the job requirements along with Python, so I don’t really understand why do I need a data viz tool if I can program everything myself.

(P.s. I currently work as a Software Developer (Python, Groovy), so coding for me is easier than learning to use some tool…but I am not sure how marketable I can be in the Data Analytics job market without these tools…)

1 Like

What is your data viz tools at DQ?

Data viz tools are more rapid in production.