deletions | additions       diff --git a/Introduction.tex b/Introduction.tex  index 0f758bf..b189419 100644  --- a/Introduction.tex  +++ b/Introduction.tex 
...
GADGET is used to investigate a wide range of astrophysical problems due to the ease with which it can be extended.   Unfortunately this also leads to fractionation of the data storage format as each research group modifies the output to suit their needs.  This state of affairs has historically forced significant duplication of effort, with individual research groups separately developing their own unique analysis scripts to perform similar operations.  While adoption of the platform-independent Hierarchical Data Format (HDF5) for data storage helps mitigate some of these issues, being able to load a dataset into memory is only the first step in performing useful, insight-generating analysis.  While use of the HDF5 data model provides a solid starting point, being able to read in a dataset is only the first step in performing useful, insight-generating analysis. Python is quickly becoming the language of choice for astronomers, and the analysis capabilities provided by the nascent pandas library will only strengthen that trend in the future. Pandas is a thoroughly documented, open-source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for python with a strong community of developers. With this in mind, we present a pandas-based framework for analyzing GADGET-HDF5 files: the GADGET dataframe library, or GADFLY. This project is in no way expected to be a replacement for the far more feature-complete yt or pynbody projects. Rather, we focus instead on implementing the minimum functionality necessary to interface between simulation data in the GADGET HDF5 format, and the pandas data analysis library.