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I work with CSV files containing 10-minute data of temperatures of some years of a station, and I usually perform some calculations: mean, average, correlations between two stations, correlations in different seasons, correlations day/night, ...

I program this calculations by using plain Python or Microsoft Excel VBA, by using loops and simple calculations. It's not very hard to code, but I wonder if there is a Python library or any other programming environment which helps me to save time and lines of code.

I've heard about ScyPy and R, and I would be very grateful if you could share any experience with these tools.

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Both Python and R are excellent choices for this type of work.

If you are already using Python, then the easiest option might be to start using Numerical Python (NumPy). The tutorial provides a basic introduction. For further pointers, see the top answer to numpy: learning resources.

If you are interested in learning R, the following thread provides lots of pointers: Books for learning the R language.

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    $\begingroup$ Check out the Pandas library if you go with Python. $\endgroup$ – Drew Jun 10 '12 at 21:13
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If you wind up using R, check out the FDA package. It will help you turn those repeat observations into functional data (i.e. smooth curves), opening up a variety of interesting modes of analysis.

http://cran.r-project.org/web/packages/fda/index.html

http://en.wikipedia.org/wiki/Functional_data_analysis

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