https://github.com/dslc-io/tidytuesdayR
Extract weekly TidyTuesday Data/Readme
https://github.com/dslc-io/tidytuesdayR
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Extract weekly TidyTuesday Data/Readme
- Host: GitHub
- URL: https://github.com/dslc-io/tidytuesdayR
- Owner: dslc-io
- License: other
- Created: 2019-02-12T00:12:45.000Z (about 6 years ago)
- Default Branch: main
- Last Pushed: 2024-09-17T11:00:37.000Z (7 months ago)
- Last Synced: 2024-09-18T03:37:13.311Z (7 months ago)
- Language: HTML
- Homepage: https://dslc-io.github.io/tidytuesdayR/
- Size: 5.16 MB
- Stars: 77
- Watchers: 3
- Forks: 15
- Open Issues: 2
-
Metadata Files:
- Readme: README.Rmd
- Changelog: NEWS.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
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README
---
output: github_document
---```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```# tidytuesdayR
[](https://CRAN.R-project.org/package=tidytuesdayR)
[](https://github.com/dslc-io/tidytuesdayR/actions)
[](https://app.codecov.io/github/dslc-io/tidytuesdayR?branch=main)
[](https://cran.r-project.org/package=tidytuesdayR)
[](https://opensource.org/licenses/MIT)
[](https://github.com/dslc-io/tidytuesdayR/actions/workflows/R-CMD-check.yaml)tidytuesdayR makes it easy to participate in the weekly [`#TidyTuesday`](https://tidytues.day/) project by providing functions to quickly import data posted to the [Tidy Tuesday repository](https://github.com/rfordatascience/tidytuesday).
## Installation
This package is (usually) available on CRAN via:
``` r
install.packages("tidytuesdayR")
```To get the latest in-development features, install the development version from GitHub:
``` r
#install.packages("pak")
pak::pak("dslc-io/tidytuesdayR")
```## Usage
There are currently two methods to access the data from the respository.
### Load the Data!
The simplest way is to use the `tt_load()` function. This
function has accepts two types of inputs to determine which data to
grab. It can be a date as a string in the YYYY-MM-DD format like below.``` r
library(tidytuesdayR)
tt_data <- tt_load("2019-01-15")
```Or the function can accept the year as the first argument, and which
week of the year as the second.``` r
tt_data <- tt_load(2019, week=3)
````tt_load()` naively downloads *all* the data that is available and
stores them in the resulting `tt_data` object. To access the data, use
the `$` or `[[` notation and the name of the dataset.``` r
tt_data$agencies
tt_data[["agencies"]]
```To view the readme, either print the `tt_data` object or use the `readme()`
function. When you print the `tt_data` object, you also get the available
datasets names printed in the console.``` r
readme(tt_data)
print(tt_data)
``````
## Available Datasets:
## agencies
## launches
##
```### TidyTemplate
As part of the goal of making participating in #TidyTuesday easier, {tidytuesdayR} now also provides a template!
To use it, just use the `use_tidytemplate()` function!By default, the template will assume to be using the most recent TidyTuesday.
However, you can pass a date object or character string in YYYY-MM-DD format
defining a different date you want to use. If you don't recall the exact date,
no worries, you can use the `tt_available()` function to figure out which date
and get the date to use!```r
## this weeks TidyTuesday!
tidytuesdayR::use_tidytemplate()## TidyTuesday from Week 42 of 2019
tidytuesdayR::use_tidytemplate(refdate = "2019-10-15")
```Additionally, by default the template will create the new file in your working
directory, using the "YYYY_MM_DD" format per good practices.
However, if you are so inclined, you can rename it to whatever you wish.```r
tidytuesdayR::use_tidytemplate(name = "My Super Great TidyTuesday.Rmd")
```## Contributing
Please note that the ‘tidytuesdayR’ project is released with a
[Contributor Code of Conduct](CODE_OF_CONDUCT.md). By contributing to
this project, you agree to abide by its terms.
