Published September 27, 2024 | Version v2
Lesson Open

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

  • 1. ROR icon Universidade do Vale do Rio dos Sinos
  • 2. ROR icon Universidade Estadual Paulista (Unesp)
  • 3. University of São Paulo (USP) - Campus Luiz de Queiroz - Laboratório de Biologia Computacional, Evolutiva e de Sistemas, Centro de Energia Nuclear na Agricultura
  • 4. University of Georgia - The Wallace Lab, Center for Applied Genetic Technologies

Contributors

  • 1. Federal University of Pará Francisco Mauro Salzano Molecular Biology Laboratory, Institute of Biological Sciences.

Description

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 material
This 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 Accessibility
The 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

Acknowledgments
We encourage users to cite this dataset and acknowledge the authors when utilizing these materials in publications or presentations.

Files

Day2_Pandas&Matplotlib_2022_EN.ipynb

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