Dating time frames

We would like to extend warm thanks to Bill Venables (and David Smith) for granting permission to distribute this modified version of the notes in this way, and for being a supporter of R from way back. This should give some familiarity with the style of R sessions and more importantly some instant feedback on what actually happens.

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We recommend that all users upgrade to this version.

Highlights include: helps fill this gap, enabling you to carry out your entire data analysis workflow in Python without having to switch to a more domain specific language like R.

Combined with the excellent IPython toolkit and other libraries, the environment for doing data analysis in Python excels in performance, productivity, and the ability to collaborate.

does not implement significant modeling functionality outside of linear and panel regression; for this, look to statsmodels and scikit-learn.

More work is still needed to make Python a first class statistical modeling environment, but we are well on our way toward that goal.

is the perfect tool for bridging the gap between rapid iterations of ad-hoc analysis and production quality code.S system, which was developed at Bell Laboratories by John Chambers et al. The term “environment” is intended to characterize it as a fully planned and coherent system, rather than an incremental accretion of very specific and inflexible tools, as is frequently the case with other data analysis software.It provides a wide variety of statistical and graphical techniques (linear and nonlinear modelling, statistical tests, time series analysis, classification, clustering, ...). R is very much a vehicle for newly developing methods of interactive data analysis.This manual provides information on data types, programming elements, statistical modelling and graphics. It has developed rapidly, and has been extended by a large collection of , yet many people use R as a statistics system. See Graphics, which can be read at almost any time and need not wait until all the preceding sections have been digested. Many users will come to R mainly for its graphical facilities.