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I agree. Within the data science community I often see the question of "R versus Python" and it always makes me think of the Old El Paso commercial: ¿por qué no

I agree. Within the data science community I often see the question of "R versus Python" and it always makes me think of the Old El Paso commercial: ¿por qué no los dos? I know choosing the right tools for the task can have serious long-term implications on the project, team, or organization level, but individually I get the impression that people worry too much about which language is best when, in reality, many of them are perfectly suitable and appropriate.

glogla 8y ago
For us, the answer to "R vs Python" is "Spark" since eventually you get to dara sizes where just R and Python don't really work.
- mastazi 8y ago
  > where just R and Python don't really work. From the Spark website: "Write applications quickly in Java, Scala, Python, R, and SQL".
  - glogla 8y ago
    Thats not really how it works. You can write spark code in all those languages, but it's still spark code, running on spark execution engine. When you do stuff, it's on spark dataframes, not on R or Python dataframes. There's limited interaction with pandas but that's about it - you don't get R statistical algoritms for example.
    - mastazi 8y ago
      (I just realised that my previous comment may have come out as rude, I'm sorry for that. I was typing in a hurry and it came out a bit dry). Yes I agree with your points, what I was trying to convey in my comment is that, since Spark is not a programming language, I think that comparing it to Python or R is a bit of an apples to oranges comparison. The other point that I was trying to make is that both of those languages could be described as first-class citizens within the Spark ecosystem.