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InteractiveResource . 2024
License: CC BY
Data sources: ZENODO
ZENODO
InteractiveResource . 2024
License: CC BY
Data sources: Datacite
ZENODO
InteractiveResource . 2024
License: CC BY
Data sources: Datacite
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5th Brazilian Python Workshop for Biological Data: Exploring Matplotlib and Pandas Libraries

Authors: Mumbach, Leonardo; Funnicelli, Michelli; A.C. dos Santos, Renato;

5th Brazilian Python Workshop for Biological Data: Exploring Matplotlib and Pandas Libraries

Abstract

About the event Professionals in the Biological Sciences field work with an immense volume of data on a daily basis. Keeping data organized, analyzing it, and extracting relevant information is a complex task. Computational programming is an important tool to handle such challenges, providing a robust and elegant solution for various data analysis and organization problems. Therefore, in order to disseminate this knowledge, we offer the Brazilian Python Workshop for Biological Data, where, in addition to amazing lectures, we also provide hands-on introductory programming sessions using the Python language and many application examples so that you can enjoy the benefits of programming in biological data analysis! About the materialThis material corresponds to the practical activity of reviewing elements for the statistical analysis of the Brazilian Python Workshop for Biological Data 2022. Two distinct materials will be provided: one focusing on Matplotlib and the other on Pandas. The datasets utilized for these activities are attached in a file. Usage and AccessibilityThe resources provided here are aimed at facilitating the teaching of the Python programming language for biologists. All steps and commands are detailed, ensuring reproducibility and transparency AcknowledgmentsWe encourage users to cite this dataset and acknowledge the authors when utilizing these materials in publications or presentations.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average