Programming for Corpus Linguistics with Python and Dataframes by Daniel Keller, Hardcover, 9781009486781 | Buy online at The Nile
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Programming for Corpus Linguistics with Python and Dataframes

Author: Daniel Keller   Series: Elements in Corpus Linguistics

Hardcover

This Element offers an introduction to programming for Corpus Linguists in the Python language using dataframes.

This Element offers intermediate or experienced programmers algorithms for Corpus Linguistic (CL) programming in the Python language using dataframes and provides core skills that can be applied to a range of CL research questions, as well as to original analyses not possible with existing corpus software.

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Summary

This Element offers an introduction to programming for Corpus Linguists in the Python language using dataframes.

This Element offers intermediate or experienced programmers algorithms for Corpus Linguistic (CL) programming in the Python language using dataframes and provides core skills that can be applied to a range of CL research questions, as well as to original analyses not possible with existing corpus software.

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Description

This Element offers intermediate or experienced programmers algorithms for Corpus Linguistic (CL) programming in the Python language using dataframes that provide a fast, efficient, intuitive set of methods for working with large, complex datasets such as corpora. This Element demonstrates principles of dataframe programming applied to CL analyses, as well as complete algorithms for creating concordances; producing lists of collocates, keywords, and lexical bundles; and performing key feature analysis. An additional algorithm for creating dataframe corpora is presented including methods for tokenizing, part-of-speech tagging, and lemmatizing using spaCy. This Element provides a set of core skills that can be applied to a range of CL research questions, as well as to original analyses not possible with existing corpus software.

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Product Details

Publisher
Cambridge University Press
Published
20th June 2024
Pages
114
ISBN
9781009486781

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