R & Python

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Investigating data samples with R

R is a free software environment for statistics that has been available since 1995 under the GNU General Public License. We use R primarily in order to investigate samples of larger data pools quickly and flexibly in the framework of a preliminary or analysis project, and to offer data-driven consulting. With the help of regression and cluster analyses, for example, models can be created to analyze correlations between variables and to produce forecasts. Libraries like ggplot2 enable clear and simple data visualization. R benefits from a large community and many extensions. The CRAN Repository offers over 7,000 packages that round off the environment.

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Integrating analyses flexibly with Python

Whereas R is explicitly designed for statisticians, Python – a general-purpose programming language – is currently experiencing an upsurge in the field of data science. On the one hand, this is due to the growing maturity of data analysis packages like NumPy and matplotlib. On the other hand, Python offers greater flexible integration potential. Data analyses and statistical code can be combined more conveniently with web applications, or interact with databases.

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