Who Cited It

Data Structures for Statistical Computing in Python

2010 · Proceedings of the Python in Science Conferences · 11,654 citations · 4 from inside this corpus

Wes McKinney low

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.

Data Structures for Statistical Computing in Python (2010)Data Structures for Statistic…The R Project in Statistical Computing (2001)The R Project in Statistical …Array programming with NumPy (2020)Array programming with NumPyArray programming with NumPy (2020)Array programming with NumPyDefinitions, methods, and applications in interpretable machine learning (2019)Definitions, methods, and app…Pingouin: statistics in Python (2018)Pingouin: statistics in Python
5 of 5 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.
this paper works it cites works citing it node size = global citations · hover for the full title

Citation edge evidence

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What this paper cites, inside the corpus

PaperYearCited
The R Project in Statistical Computing20012,682

What cites it, inside the corpus

PaperYearCited
Array programming with NumPy202023,533
Array programming with NumPy202018,812
Definitions, methods, and applications in interpretable machine learning20192,161
Pingouin: statistics in Python20181,913

Links

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Topics

Computational Physics and Python ApplicationsComputer Science

Is this record sound?

complete

Nothing in this record contradicts itself and no field we check is missing.

  • supports1 author record(s) attached.
  • supports2 reference(s) recorded.
  • neutralThe DOI carries no year to check against.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:40+00:00.

sha256 7e3d99a592f7f61f…