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markjrieke committed Sep 28, 2024
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# Open Source Software
## Open Source Software

## [workboots](https://markjrieke.github.io/workboots/)
* [workboots](https://markjrieke.github.io/workboots/): Generate bootstrap 🥾 prediction intervals from a tidymodel workflow.
* [nplyr](https://markjrieke.github.io/nplyr/): A grammar of (nested) data manipulation 🐦.
* [riekelib](https://markjrieke.github.io/riekelib/): A collection of functions I use regularly.
* [heRmann](https://markjrieke.github.io/heRmann/): A collection of functions for the CXA team at Memorial Hermann.

<img src="img/workboots_logo.png" align="right" width="120" />
## Forecasts

**Author:** [Mark Rieke](https://www.thedatadiary.net/about/about.html) <br/>
**License:** [MIT](https://github.com/markjrieke/workboots/blob/main/LICENSE)
* [2024 Presidential Forecast](../2024-potus/National.qmd): A dynamic Bayesian forecast of the 2024 presidential election.
* [2022 Senate Forecast](2022-midterms/senate.qmd): A simulation-based forecast of Senate elections in 2022.
* [2022 House Forecast](2022-midterms/house.qmd): A simulation-based forecast of House elections in 2022.
* [2022 Governor Forecasts](2022-midterms/governor.qmd): A simulation-based forecast of Governor elections in 2022.

<!-- badges: start -->
[![R-CMD-check](https://github.com/markjrieke/workboots/workflows/R-CMD-check/badge.svg)](https://github.com/markjrieke/workboots/actions)
[![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental)
[![CRAN status](https://www.r-pkg.org/badges/version/workboots)](https://CRAN.R-project.org/package=workboots)
[![](https://cranlogs.r-pkg.org/badges/grand-total/workboots)](https://cran.r-project.org/package=workboots)
<!-- badges: end -->
## Talks, Presetntations, etc.

Generate bootstrap 🥾 prediction intervals from a tidymodel workflow.

## [nplyr](https://markjrieke.github.io/nplyr/)

<img src="img/nplyr_logo.png" align="right" width="120" />

**Author:** [Mark Rieke](https://www.thedatadiary.net/about/about.html)<br/>
**License:** [MIT](https://github.com/markjrieke/nplyr/blob/main/LICENSE)

<!-- badges: start -->
[![R-CMD-check](https://github.com/markjrieke/nplyr/workflows/R-CMD-check/badge.svg)](https://github.com/markjrieke/nplyr/actions)
[![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental)
[![CRAN status](https://www.r-pkg.org/badges/version/nplyr)](https://CRAN.R-project.org/package=nplyr)
[![](https://cranlogs.r-pkg.org/badges/grand-total/nplyr)](https://cran.r-project.org/package=nplyr)
<!-- badges: end -->

nplyr: a grammar of (nested) data manipulation 🐦.

## [riekelib](https://markjrieke.github.io/riekelib/)

<img src="img/riekelib_logo.png" align="right" width="120" />

**Author:** [Mark Rieke](https://www.thedatadiary.net/about/about.html) <br/>
**License:**
[MIT](https://github.com/markjrieke/riekelib/blob/master/LICENSE.md)

A collection of functions I use regularly.

# Other

## [2022 Midterm Forecast](https://github.com/markjrieke/2022-midterm-forecasts)

A daily forecast for each seat in each congressional chamber.

### [Senate](2022-midterms/senate.qmd)

:::{layout="[[1, 1]]" layout-valign="center"}
![](2022-midterms/img/senate_dist.png)

![](2022-midterms/img/senate_prob.png)
:::

### [House](2022-midterms/house.qmd)

:::{layout="[[1, 1]]" layout-valign="center"}
![](2022-midterms/img/house_dist.png)

![](2022-midterms/img/house_prob.png)
:::

### [Governor](2022-midterms/governor.qmd)

:::{layout="[[-20, 60, -20]]"}
![](2022-midterms/img/governor_map.png)
:::

## rstudio::conf(2022)

:::{layout="[[-10, 80, -10]]"}
{{< video https://www.youtube.com/embed/F4osY469UoY >}}
:::
* [rstudio::conf(2022)](https://www.youtube.com/watch?v=F4osY469UoY): Intro to Workboots: Make Prediction Intervals from Tidymodel Workflows
* [Data Humans Podcast](https://open.spotify.com/episode/3WYo7Fmiv03ujIJHUs8sYh): Meet Mark Rieke: career transition from mechanical engineering, craving more technical work, and how we all belong in data

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