R Vs Python Data Science Quiz

1. Type question here

I would like to run some exploratory analysis with just a few lines of code

I would like to easily integrate my analysis to an existing program or system

2. Maturity or flexibility

I don't care too much about the maturity of the analytical libraries, I prefer flexibility and innovation in my analysis

I care a lot the maturity, simplicity, and ease to use of the analytical libraries

3. How do you feel more comfortable

I feel more comfortable using a programming language that was designed to run statistical analysis

I feel more comfortable using a programming language that was designed to code with ease and speed

4. Same piece of functionality can be written in several ways... which way do you like the most?

I prefer the idea of getting statistical models that can be written with only a few lines of code

I prefer an easier coding and debugging of my statistical models

5. What type of coding do you like the most

I prefer a tool that allows me to easily run whatever analysis I need, even if that means more computing processing time until I get the results.

I prefer a tool that runs very efficiently and fast, even if that means investing more time coding.

6. In addition to the numerical analysis...

In addition to the numerical analysis, I care about the availability of advanced graphics that are ready and are simple to use.

In addition to the numerical analysis, I care about the capabilities to organize and maintain my code tidy, so I can easily find errors later

7. Which statement better defines your day to day activities?

I'm closer to statistics, research and data science

I'm closer to developing systems that integrate analysis or apply statistical techniques

8. Learning curve

I prefer to start as soon as possible the coding, even if that means less access to analytical resources

I prefer to have access to more analytical resources, even if that means investing more time learning how to code.

9. Every type of analysis available vs flexibility to develop my own analysis

The key is having enough flexibility for doing something novel that has never done before.

The key is that it has to be easy to use and it has to have access to all kind of statistical models.

10. Ecosystem

The analysis are mainly executed on a notebook/PC or a server

The analysis are mainly executed on a server as a part of some kind of a system or web application

11. What does your "programmers life" look like

I prefer to learn a multi-purpose programming language. I'm probably going to code some other things too that are not related to statistical analysis.

I prefer to learn a specialized statistical programming language, even if that means it is the only thing I can do with that programming language.

12. Purpose

I prefer an analytical tool that's mainly focused on user friendly data analysis, statistics and graphical models

I prefer an analytical tool that's mainly focused on gaining more productivity and code readability

13. Accessing to shared knowledge

I don't know if I'm going to need a specific library to run my analysis, but if I need it, I want the installation process to be as simple as possible

I'm used to installing code libraries and dealing with dependencies problems

14. Ease of Learning

I have basic coding experience and is not something that makes me afraid

I don't have coding experience and I need to start as quick as possible