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In this paper we are concerned with the practical issues of working with data sets common to finance, statistics, and other related fields. pandas is a new library which aims to facilitate working with these data sets and to provide a set of fundamental building blocks for implementing statistical models. We will discuss specific design issues encountered in the course of developing pandas with relevant examples and some comparisons with the R language. We conclude by discussing possible future directions for statistical computing and data analysis using Python.
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Wes McKinney (Fri,) studied this question.
www.synapsesocial.com/papers/697e174d2ca05de6e2a4db60 — DOI: https://doi.org/10.25080/majora-92bf1922-00a
Wes McKinney
Proceedings of the Python in Science Conferences
Capital University
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