getting started with pandas pandas will be the primary library of interest throughout much of the rest of the book it contains high-level data structures and manipulation tools designed to make data analysis fast and easy in python pandas is built on top of numpy and makes it easy to use in numpy-centric applications as bit of backgroundi started building pandas in early during my tenure at aqra quantitative investment management firm at the timei had distinct set of requirements that were not well-addressed by any single tool at my disposaldata structures with labeled axes supporting automatic or explicit data alignment this prevents common errors resulting from misaligned data and working with differently-indexed data coming from different sources integrated time series functionality the same data structures handle both time series data and non-time series data arithmetic operations and reductions (like summing across an axiswould pass on the metadata (axis labelsflexible handling of missing data merge and other relational operations found in popular database databases (sqlbasedfor examplei wanted to be able to do all of these things in one placepreferably in language wellsuited to general purpose software development python was good candidate language for thisbut at that time there was not an integrated set of data structures and tools providing this functionality over the last four yearspandas has matured into quite large library capable of solving much broader set of data handling problems than ever anticipatedbut it has expanded in its scope without compromising the simplicity and ease-of-use that desired from the very beginning hope that after reading this bookyou will find it to be just as much of an indispensable tool as do throughout the rest of the booki use the following import conventions for pandas www it-ebooks info