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I do a fair bit of data analysis using Python. I find that I often end up repeating the same analysis for different input variables (e.g., looking at GDP and then seeing if the answer changes under GPI) or maybe using a different aggregation technique (e.g., mean vs median).

I was thinking about putting together a python framework to help apply various variations to an analysis but was wondering if there is an existing python library accomplishes this.

  • Try googling “monte carlo simulation python”. Lots of hits. – Eric Shain May 18 at 20:51
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As in other programming languages, one usually accomplishes such a thing in Python by writing a loop or function. For example, if you have an analysis that involves taking the mean of something with numpy.mean, you can replace np.mean with f and wrap the analysis code in a new function that has f as a parameter.

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The general term for what you are looking for is Monte Carlo simulations. Although I don't have any personal experience with it, there is a Monte Carlo feature in the Pandas library. In addition, I found pyhmc, pyMC and pyMC3 (which looks like the most up to date).

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