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PyData Berlin 2014
Python has been taking over R and SPSS in the last couple of years. Python has many tools to offer like NumPy and scikit-learn that make any data scientist happy but pandas has been the main reason for many analysts to switch. It is fast, flexible, simple to learn, well documented, has a substantial community and has been accepted in many businesses as an every day tool. One reason why people still prefer R is the ggplotmodule. It offers a non-verbose yet flexible way to visualise information. In this session we will show you that a proper workflow with ipython-notebook/pandas still allows the use of this library ggplot. With this workflow you have the best of both worlds with no compromises. At the end of this session you have been show how to load data, aggregate data and analyse data with pandas and how to then visualise it with ggplot.