PyHelpers: An open-source toolkit for facilitating Python users' data manipulation tasks

Qian Fu

doi:10.5281/zenodo.4017438

PyHelpers: An open-source toolkit for facilitating Python users' data manipulation tasks

Research output: Non-textual form › Software

Abstract

PyHelpers is an open-source Python package designed to streamline data (pre-)processing and manipulation tasks. It accommodates a wide range of functions and classes grounded in practical applications, making common data operations more accessible and efficient. This toolkit is particularly useful for Python learners, researchers and data scientists seeking to enhance their workflows.

The package supports handling various data types, such as geographical and textual data, allowing for flexibility for diverse data processing needs. It also simplifies data input and output operations by offering functionalities for managing many different file-like objects. In addition, PyHelpers facilitates communication with relational databases, such as PostgreSQL and Microsoft SQL Server. This capability greatly smooths data integration with database systems through efficient data storage and retrieval.

With its comprehensive suite of practical tools, PyHelpers simplifies complex data processing tasks and boosts productivity. It is ready to serve as an essential resource for effective data manipulation, management and analysis for anyone working with data in Python.

Original language	English
Publisher	Zenodo
Media of output	Online
DOIs	https://doi.org/10.5281/zenodo.4017438
Publication status	Published - 2020

Keywords

Python
Utilities
Data preprocessing
Data manipulation

Access to Document

10.5281/zenodo.4017438Licence: Other (please provide link to licence statement

4 Conference contribution
3 Article
2 Software
1 Other report
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- 1 Paper

Development of an Integrated Computing Platform for Measuring, Predicting, and Analyzing the Profile-Specific Fixity of Railway Tracks
Fu, Q., Easton, J. & Burrow, M., Jun 2024, In: Transportation Research Record. 2678, 6, p. 1-13 13 p.
Research output: Contribution to journal › Article › peer-review

Open Access
File
102 Downloads (Pure)
Understanding User Experience with Smart Home Products
Yu, Y., Fu, Q., Zhang, D. & Gu, Q., 21 Oct 2024, (E-pub ahead of print) In: Journal of Computer Information Systems.
Research output: Contribution to journal › Article › peer-review

Open Access
File
25 Downloads (Pure)
What are Smart Home Product Users Commenting on? A Case Study of Robotic Vacuums
Yu, Y., Fu, Q., Zhang, D. & Gu, Q., 27 Jun 2024, Next Generation Data Science: Second Southwest Data Science Conference, SDSC 2023, Waco, TX, USA, March 24–25, 2023, Revised Selected Papers. Han, H. & Baker, E. (eds.). 1 ed. Springer, p. 34-45 11 p. (Communications in Computer and Information Science).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Data Study Group Network Final Report: Bristol City Council (Get Bristol moving: tackling air pollution in Bristol city centre)
Mougan, C. (Contributor), Fu, Q., Kolath, J., Tong, H., Dixit, S., Geffert, L., Shin, H., Rabuh, A. A., Robinson, C. & Gale, E. (Contributor), 29 Apr 2020, Zenodo. 23 p.
Research output: Book/Report › Other report

Open Access
PyDriosm: an open-source tool for downloading, reading and PostgreSQL-based I/O of OpenStreetMap data
Fu, Q., 2020
Research output: Non-textual form › Software

Open Access
PyRCS: An open-source tool for collecting railway codes used in different UK rail industry systems
Fu, Q., 2020
Research output: Non-textual form › Software

Open Access
A data model for heat-related rail buckling: implications for operations, maintenance and long-term adaptation
Jaroszweski, D., Fu, Q. & Easton, J., 1 Aug 2019, (Accepted/In press) Proceedings of the 12th World Congress on Railway Research. 6 p.
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Open Access
File

3 Finished

Forecasting resilience of railway network under propagating uncertainty
Fu, Q. (Principal Investigator) & Mills, S. (Co-Investigator)
SCIENCE & TECHNOLOGY FACILITIES COUNCIL
1/04/24 → 31/12/24
Project: Research Councils
Avanti PTI
Fu, Q. (Co-Investigator), Mills, S. (Principal Investigator), Plummer, P. (Co-Investigator) & Easton, J. (Co-Investigator)
First Trenitalia West Coast Rail Ltd
13/03/23 → 31/07/23
Project: Industry
Post-Doctoral Enrichment Award
Styles, I. (Principal Investigator), Chu, M. (Co-Investigator), Chua, W. W. L. (Co-Investigator) & Fu, Q. (Co-Investigator)
Alan Turing Institute
1/03/22 → 31/10/22
Project: Research

Cite this

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abstract = "PyHelpers is an open-source Python package designed to streamline data (pre-)processing and manipulation tasks. It accommodates a wide range of functions and classes grounded in practical applications, making common data operations more accessible and efficient. This toolkit is particularly useful for Python learners, researchers and data scientists seeking to enhance their workflows.The package supports handling various data types, such as geographical and textual data, allowing for flexibility for diverse data processing needs. It also simplifies data input and output operations by offering functionalities for managing many different file-like objects. In addition, PyHelpers facilitates communication with relational databases, such as PostgreSQL and Microsoft SQL Server. This capability greatly smooths data integration with database systems through efficient data storage and retrieval.With its comprehensive suite of practical tools, PyHelpers simplifies complex data processing tasks and boosts productivity. It is ready to serve as an essential resource for effective data manipulation, management and analysis for anyone working with data in Python.",

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AB - PyHelpers is an open-source Python package designed to streamline data (pre-)processing and manipulation tasks. It accommodates a wide range of functions and classes grounded in practical applications, making common data operations more accessible and efficient. This toolkit is particularly useful for Python learners, researchers and data scientists seeking to enhance their workflows.The package supports handling various data types, such as geographical and textual data, allowing for flexibility for diverse data processing needs. It also simplifies data input and output operations by offering functionalities for managing many different file-like objects. In addition, PyHelpers facilitates communication with relational databases, such as PostgreSQL and Microsoft SQL Server. This capability greatly smooths data integration with database systems through efficient data storage and retrieval.With its comprehensive suite of practical tools, PyHelpers simplifies complex data processing tasks and boosts productivity. It is ready to serve as an essential resource for effective data manipulation, management and analysis for anyone working with data in Python.

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PyHelpers: An open-source toolkit for facilitating Python users' data manipulation tasks

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Cite this