Sometimes it is necessary to change the programming language or the tool you use to do your data analysis in. While R is a programming language created solely for the purpose of any kind of data analysis, Python is a general purpose language. This means there are a lot of circumstances in which it can be helpful to develop the data analysis process in R, but running it requires some of the general purpose advantages of python. For example when you want to access your algorithms via an API. But there are also different reasons why it can be helpful to rewrite your data analysis code in Python. This talk gives some examples of when it makes sense to do so and what to bear in mind when doing so.

Outline:

• When to rewrite your R code in Python?
• Discussion of strengths and weaknesses between R and python
• How to rewrite your R code in Python
• What are the pitfalls?
• Examples

Helena Schmidt

Helena Schmidt works as freelance data scientist. She has a PhD in gravitational physics. She is also a member of the hacking community and co-founder of the hackerspace Stratum0 in Braunschweig, Germany.

visit the speaker at: Github • Homepage