R and Python Files for Data Science
- Radu Alin Păunescu
- Oct 5, 2022
- 2 min read
Updated: Feb 13, 2023
I would like to create a section for data science files. The website has different pages full of materials about R language and Python, but they are dispersed.
Take a look inside here:
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun.
Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible.
More materials about R and data science can be found below:
Take a look here:
Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this popular guide adds comprehensive examples in Python, provides practical guidance on applying statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what’s important and what’s not.
Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R or Python programming languages and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.
The book can be downloaded and accessed here:
This is an introduction to R and Latex.
This book is not introductory. It presumes some knowledge of basic statistical theory and practice. Readers are expected to know the essentials of statistical inference such as estimation, hypothesis testing and confidence intervals.
The document format “R Markdown” was first introduced in the knitr package (Xie 2015, 2022b) in early 2012.
The idea was to embed code chunks (of R or other languages) in Markdown documents.
Access the book here:
R Markdown cheats & results can be found here:
R markdown sources:
Curs R + Materiale | https://www.youtube.com/watch?v=_V8eKsto3Ug |
|---|---|
R vs Python: | https://www.datacamp.com/community/blog/when-to-use-python-or-r |
Curs R intro: | https://www.youtube.com/watch?v=_V8eKsto3Ug |
PCA in R: | https://www.datacamp.com/community/tutorials/pca-analysis-r |
Financial Analysis in R: | |
PowerPoint with R: | |
Top 10 R packages for data analytics: | |
Techincal Analysis with R (second edition): | |
Handling large data sets in R |
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