This first (short) topic is a bit different from the other topics. Here we will look at the python data analytics library pandas and use it to reproduce the analysis of a simple data set.
Top X pandas commands
Pandas is a huge library and it is not practical to give a detailed description of its capabilities in a single session. So I'm going to focus on some of the operations that I find most useful.
This practical will use a case study from NIST Engineering Statistics Handbook, analysing the effects of machining factors on the strength of ceramics to demonstrate visualisation using pandas.
