Data Structures for Statistical Computing in Python
Структуры данных для статистических вычислений в Python
2010-01-01
SCID: 54.1/8fdgb3cn
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comparison with Rdata structures for statistical computingfinance and statistics datasetspandastime series data
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Abstract (AI)
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.
Key Findings
1
Comparisons with the R language are provided to contextualize pandas' design and functionality.
2
The authors outline possible future directions for statistical computing and data analysis using Python.
3
The paper discusses specific design issues encountered during pandas development, illustrated with relevant examples.
4
pandas is a new Python library designed to facilitate working with data sets common to finance, statistics, and related fields.
5
pandas provides fundamental building blocks intended for implementing statistical models in Python.
Research Object
pandas library for data structures for statistical computing in Python
Research Subject
Design and practical use of data structures and building blocks for working with datasets common to finance and statistics, including implementation issues, examples, and comparisons with R
Publication Details
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2010-01-01
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