https://github.com/meghall06/betweenthepipes
This package hosts tutorials (created with the learnr package) and sample data sets that are designed to facilitate learning the tidyverse with hockey data.
https://github.com/meghall06/betweenthepipes
hockey-data learnr tidyverse
Last synced: 4 months ago
JSON representation
This package hosts tutorials (created with the learnr package) and sample data sets that are designed to facilitate learning the tidyverse with hockey data.
- Host: GitHub
- URL: https://github.com/meghall06/betweenthepipes
- Owner: meghall06
- Created: 2020-06-28T19:28:46.000Z (almost 5 years ago)
- Default Branch: master
- Last Pushed: 2020-10-29T13:56:12.000Z (over 4 years ago)
- Last Synced: 2024-08-13T07:14:18.495Z (8 months ago)
- Topics: hockey-data, learnr, tidyverse
- Language: R
- Homepage:
- Size: 182 KB
- Stars: 21
- Watchers: 1
- Forks: 5
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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- jimsghstars - meghall06/betweenthepipes - This package hosts tutorials (created with the learnr package) and sample data sets that are designed to facilitate learning the tidyverse with hockey data. (R)
README
`betweenthepipes` is an R package that currently holds two tutorials, created with [learnr](https://rstudio.github.io/learnr/index.html). There are also two sample data sets that are useful for learning to work with hockey data.
First, download this package via Github: `devtools::install_github("meghall06/betweenthepipes")`.
### Tutorial Details
* **Introduction to R with Hockey Data**. A beginner-friendly introduction to R and the tidyverse with sample hockey data. Introduces the basic tidyverse functions: `filter()`, `select()`, `arrange()`, `filter()`, `mutate()`, `group_by()`, and `summarize()`.
* **More Data Manipulation**. Going further into data manipulation with details on pivoting data (using `pivot_longer()` and `pivot_wider()`), joining data, and working with strings.
### How to Access Tutorials
Once the package has been downloaded, there are two options to access the tutorial. You can access each tutorial individually with the following code:
```
library(betweenthepipes)
intro()
data_manip()
```
Or, if you have an RStudio version 1.3 or later, there should be a Tutorial pane in the upper right corner (near Environment and Git). That pane should list all the tutorials available from the packages you've downloaded.
### How to Access Data
There are two data sets available in this package: `pbp_example` and `bio_example`. `pbp_example` is a data set containing NHL play-by-play data for four Philadelphia Flyers games from November 2019. `bio_example` is a data set containing some NHL biographic data from 2019, useful for practicing joins with the data in `pbp_example`. More information on the data sets is available with `?betweenthepipes::bio_example` or `?betweenthepipes::pbp_example`.
```
# To load the data sets into the global environment
library(betweenthepipes)
bio_example <- bio_example
pbp_example <- pbp_example
```
### Other Resources
In October 2020, I gave a tidyverse-focused workshop at the [Carnegie Mellon Sports Analytics Conference](http://www.stat.cmu.edu/cmsac/conference/2020/) using the data available in this package. The slides and code from the workshop are available on my website [here](https://meghan.rbind.io/talk/cmsac/).
#### Data Source
The play-by-play data was scraped using the [Evolving-Hockey](https://evolving-hockey.com/) [R scraper](https://github.com/evolvingwild/evolving-hockey/blob/master/EH_scrape_functions.R) and the biographic data was downloaded from [NaturalStatTrick](http://www.naturalstattrick.com/).