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Data Structures for Statistical Computing in Python

Wes McKinney · Proceedings of the Python in Science Conferences · 2010

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Author / responsible party
Wes McKinney
Publisher
Proceedings of the Python in Science Conferences
Year
2010
Language
English

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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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APA 7

McKinney, W. (2010). Data Structures for Statistical Computing in Python. https://doi.org/10.25080/majora-92bf1922-00a

MLA

McKinney, Wes. "Data Structures for Statistical Computing in Python." 2010. https://doi.org/10.25080/majora-92bf1922-00a.

Chicago

McKinney, Wes. 2010. "Data Structures for Statistical Computing in Python.". https://doi.org/10.25080/majora-92bf1922-00a.

Harvard

McKinney, W. 2010, Data Structures for Statistical Computing in Python, Proceedings of the Python in Science Conferences, available at: https://doi.org/10.25080/majora-92bf1922-00a [Accessed 6 Aug. 2026].

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Title
Data Structures for Statistical Computing in Python
Author / contributors
Wes McKinney
Publisher
Proceedings of the Python in Science Conferences
Publication year
2010
Language
English

Subjects

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Python (programming language); Computer science; Data science; Data exploration; Statistical analysis; Data structure; Computational statistics; Theoretical computer science; Data mining; Software engineering; Programming language; Machine learning
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