https://github.com/erictleung/tutorial-tidyverse
:milky_way: Presentation on the tidyverse in R to clean and manipulate data
https://github.com/erictleung/tutorial-tidyverse
data-cleaning data-manipulation data-science manipulate-data presentation programming r tidyverse tutorial
Last synced: 3 months ago
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:milky_way: Presentation on the tidyverse in R to clean and manipulate data
- Host: GitHub
- URL: https://github.com/erictleung/tutorial-tidyverse
- Owner: erictleung
- Created: 2017-01-20T01:38:26.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2017-04-07T15:19:20.000Z (about 8 years ago)
- Last Synced: 2025-03-19T08:39:42.669Z (3 months ago)
- Topics: data-cleaning, data-manipulation, data-science, manipulate-data, presentation, programming, r, tidyverse, tutorial
- Language: HTML
- Homepage: https://erictleung.com/tutorial-tidyverse/
- Size: 2.95 MB
- Stars: 5
- Watchers: 2
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# tutorial-tidyverse
Presentation on the tidyverse in R to clean and manipulate data
**Table of Contents**
- [Prerequisites](#prerequisites)
- [About Data](#about-data)
- [Compile Presentation](#compile-presentation)
- [Packages within `tidyverse`](#packages-within-tidyverse)
- [Repository Structure](#repository-structure)
- [License](#license)
## Prerequisites
- `R`
- `rmarkdown` (to compile presentation)
- `tidyverse`
## About Data
Data is a modified version found on [@laderast][ted]'s workshop on exploratory
data analysis, [ShinyEDA][shinyeda].
[ted]: https://github.com/laderast
[shinyeda]: https://github.com/laderast/shinyEDA
## Compile Presentation
```shell
make
```
## Packages within `tidyverse`
- `broom` (convert statistical objects to tidy data)
- `dplyr` (easily tidy data)
- `forcats` (work with categorical variables)
- `ggplot2` (create elegant data visualizations)
- `haven` (import and export SPSS, Stata, and SAS)
- `httr` (work with URLs and HTTP)
- `hms` (pretty time of day)
- `jsonlite` (robust JSON parser)
- `lubridate` (deal with dates easier)
- `magrittr` (pipe character)
- `modelr` (modeling functions)
- `purrr` (functional programming)
- `readr` (read tabular data)
- `readxl` (read Excel data)
- `stringr` (manipulate strings)
- `tibble` (simple data frames)
- `rvest` (web scrapping tools)
- `tidyr` (easily tidy data)
- `xml2` (parse XML files)
## Repository Structure
```
.
├── data
│ └── all_data.xlsx
├── images
│ ├── cover.png
│ ├── data-science-communicate.png
│ ├── data-science-explore.png
│ ├── data-science.png
│ ├── data-science-wrangle.png
│ ├── datasetA.png
│ ├── datasetB.png
│ ├── rstudio-hex-purrr.png
│ ├── tidy-data.png
│ └── tidy-logos.png
├── Makefile
├── R
│ ├── broom.R
│ └── purrr.R
├── README.md
├── tidyverse.html
├── tidyverse.Rmd
└── tutorial-tidyverse.Rproj
3 directories, 18 files
```
## License
This work is licensed under a Creative Commons Attribution 4.0 International License.