Publication | Open Access
Data Structures for Statistical Computing in Python
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2010
Year
Data RepresentationEngineeringFinancial DataBusiness IntelligenceAlgorithmic LibraryStructured DataBusiness AnalyticsData StructuresR LanguageData ScienceData MiningManagementStatistical ComputingData IntegrationStatisticsSpecific Design IssuesKnowledge DiscoveryComputer ScienceFinancePractical IssuesData SetData AnalyticsStatistical DatabaseFinancial EngineeringData Modeling
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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