index.qmd

---
title: "Welcome"
---

Welcome to pydatavolley, where data analysis meets volleyball. This book is a curated collection of skills designed for the volleyball analyst eager to transcend the conventional boundaries of data exploration.

In the following pages, we will delve into various topics that not only harness the power of Python but also explore the realm of [R](https://posit.co/download/rstudio-desktop/). Each chapter and section of this website is crafted to seamlessly integrate both languages, providing a comprehensive and versatile approach to data analysis in the context of volleyball. We will focus on using [pandas](https://pandas.pydata.org/) in Python. [Tidyverse](https://www.tidyverse.org/) in R. If you would like a more Tidyverse approach in Python, consider using [siuba](https://github.com/machow/siuba/) which replicates the use of dplyr into Python.

## Sources {#Sources}
Parts of this webpage you'll find in the Openvolleys offical snippit book: https://snippets.openvolley.org/

## Acknowledgements {#Acknowledgements}

[Openvolley](https://openvolley.github.io/) team and their support for my addition to pydatavolley and this page!