eechidna
Data package containing tables, shapefiles, etc. for the 2001-2019 Australian elections and Censuses
Science Score: 10.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○codemeta.json file
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○DOI references
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○Academic publication links
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✓Committers with academic emails
4 of 19 committers (21.1%) from academic institutions -
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○Scientific vocabulary similarity
Low similarity (19.3%) to scientific vocabulary
Keywords
australia
auunconf
census-data
election
r
r-package
rstats
unconf
Keywords from Contributors
missing-data
tidy-data
rmarkdown
book
bookdown
ecology
data-manipulation
grammar
demography
spreadsheet
Last synced: 6 months ago
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Repository
Data package containing tables, shapefiles, etc. for the 2001-2019 Australian elections and Censuses
Basic Info
- Host: GitHub
- Owner: jforbes14
- Language: R
- Default Branch: master
- Homepage: https://jforbes14.github.io/eechidna/
- Size: 304 MB
Statistics
- Stars: 44
- Watchers: 15
- Forks: 6
- Open Issues: 3
- Releases: 0
Topics
australia
auunconf
census-data
election
r
r-package
rstats
unconf
Created almost 10 years ago
· Last pushed over 2 years ago
Metadata Files
Readme
Contributing
README.Rmd
---
output: github_document
---
```{r, echo = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "README-"
)
```
# eechidna
[](http://cran.r-project.org/package=eechidna) [](http://cran.rstudio.com/web/packages/eechidna/index.html) [](https://travis-ci.com/github/jforbes14/eechidna) [](https://ci.appveyor.com/project/jforbes14/eechidna)
## Exploring Election and Census Highly Informative Data Nationally for Australia
The R package *eechidna* provides data from the Australian Federal elections in 2001, 2004, 2007, 2010, 2013, 2016 and 2019, along with the Australian Census information for each House of Representatives electorate from the 2001, 2006, 2011 and 2016 Censuses. Additionally, Census information is imputed for electorates in years 2004, 2007, 2010, 2013 and 2019. It also includes tools for visualizing and analysing the data.
This package was developed during the [rOpenSci auunconf event](http://auunconf.ropensci.org/) in Brisbane, Queensland, during 21-22 April 2016. It has been updated many times since to include election and
Census information for 2001, 2011 and 2019. [Peter Ellis'](https://github.com/ellisp/) work on the NZ electoral data was an important inspiration for this package.
## How to install
You can install the latest release of the package from CRAN like this
```{r eval = FALSE}
install.packages("eechidna")
```
Or you can install the development version from github, which may have some changes that are not yet on CRAN, using `devtools`, like this:
```{r eval = FALSE}
devtools::install_github("jforbes14/eechidna",
build_vignettes = TRUE)
library(eechidna)
```
If you are using Linux, you may need some additional libraries for the mapping functions, you can get these with this line:
```
apt-get install libgdal-dev libgeos-dev -y
```
## How to use
The package consists of several datasets, which includes Australian Census data at electorate level, Australian Federal election (House of Representatives) voting data from electorates and polling booths, and shapefiles for Australian electoral districts at various points in time. In addition to the data provided, `eechidna` includes a highly interactive web app for exploring the election and census data together. This app uses the shiny framework, and can be run locally on your computer with the command `eechidna::launchApp()`. There is a video demo of the app here: .
We have many vignettes that show how to access these data in the package, and demonstrate how to analyse the data using R. These can be found in the *articles* tab at the top of this page.
- [An introduction to eechidna](https://jforbes14.github.io/eechidna/articles/eechidna-intro.html): an overview of the package contents and examples of how to use the data.
- [Exploring election data](https://jforbes14.github.io/eechidna/articles/exploring-election-data.html): examples of wrangling data from the 2016 Federal election data to gain insights.
- [Exploring Census data](https://jforbes14.github.io/eechidna/articles/exploring-census-data.html): visualizing 2016 Census data to analyse patterns in electoral population characteristics.
There are also three vignettes that demonstrate how to use the spatial data to make maps. Mapping election data for Australia is not trivial because of the extreme variation in electorate size. In these vignettes we show some methods for effectively visualizing election data in Australia. These too are found in the *articles* tab at the top of this page.
- [Mapping federal electorates](https://jforbes14.github.io/eechidna/articles/plotting-electorates.html): how to plot a map of Australian federal electorates, and how to better visualize electoral voting data using a cartogram.
- [Mapping polling booths](https://jforbes14.github.io/eechidna/articles/plotting-polling-stns.html): examples of how to plot the polling booth locations and associated voting data.
- [Getting Australian electoral maps](https://jforbes14.github.io/eechidna/articles/getting-ozShapefiles.html): details the process to produce usable electoral maps from the original shapefiles.
Additionally, there is a vignette on how we have imputed electoral Census data in election years for which a Census does not exactly align.
- [Imputing Census data for non-Census years](https://jforbes14.github.io/eechidna/articles/imputing-census-data.html): details the procedure used to impute Census data for 2004, 2007, 2010, 2013 and 2019.
## License
This package is free and open source software, licensed under GPL (>= 2).
## Feedback, contributing, etc.
Please open an issue if you find something that doesn't work as expected or have questions or suggestions. Note that this project is released with a [Guide to Contributing](CONTRIBUTING.md) and a [Contributor Code of Conduct](CONDUCT.md). By participating in this project you agree to abide by its terms.
## Acknowledgements
Thanks to Xiaoyue Cheng for her [cartogram](https://github.com/chxy/cartogram) package which supplies the Dorling algorithm for this package. Thanks also to Roger Bivand for his `rgdal` and `rgeos` packages which has some key functions for working with shapefiles. Thanks to Scott Chamberlain and Yihui Xie for help with troubleshooting.
Owner
- Name: Jeremy Forbes
- Login: jforbes14
- Kind: user
- Repositories: 2
- Profile: https://github.com/jforbes14
GitHub Events
Total
- Watch event: 1
Last Year
- Watch event: 1
Committers
Last synced: almost 3 years ago
All Time
- Total Commits: 527
- Total Committers: 19
- Avg Commits per committer: 27.737
- Development Distribution Score (DDS): 0.461
Top Committers
| Name | Commits | |
|---|---|---|
| jforbes14 | j****3@s****u | 284 |
| Ben Marwick | b****k@g****m | 54 |
| Carson Sievert | c****1@g****m | 44 |
| Dianne Cook | v****t@g****m | 34 |
| Rob J Hyndman | r****n@g****m | 31 |
| rstudio | r****o@e****m | 18 |
| Heike Hofmann | h****n@i****u | 14 |
| Bryce Roney | b****y@u****m | 14 |
| Nicholas Tierney | n****y@g****m | 8 |
| Anthony Ebert | a****t@g****m | 5 |
| Emi Tanaka | d****a@g****m | 4 |
| Jeremy Forbes | j****5@g****m | 3 |
| Ben Marwick | b****k@h****m | 3 |
| Emi Tanaka | e****i@E****l | 3 |
| earowang | e****g@g****m | 3 |
| NTomasetti | n****2@s****u | 2 |
| Thomas Lumley | t****y@a****z | 1 |
| Emi Tanaka | e****a@m****u | 1 |
| dan | g****b@e****g | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: over 2 years ago
All Time
- Total issues: 27
- Total pull requests: 17
- Average time to close issues: 9 months
- Average time to close pull requests: about 10 hours
- Total issue authors: 16
- Total pull request authors: 7
- Average comments per issue: 3.11
- Average comments per pull request: 0.24
- Merged pull requests: 16
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 1
- Pull requests: 4
- Average time to close issues: N/A
- Average time to close pull requests: 3 minutes
- Issue authors: 1
- Pull request authors: 2
- Average comments per issue: 3.0
- Average comments per pull request: 0.0
- Merged pull requests: 3
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- dicook (5)
- cpsievert (4)
- danmackinlay (2)
- jforbes14 (2)
- sckott (2)
- benmarwick (2)
- OmidGhasemi21 (1)
- ateucher (1)
- quangvanbui (1)
- 0Isaiah (1)
- KyleHaynes (1)
- ghost (1)
- pajacobson (1)
- onrvam (1)
- rsbivand (1)
Pull Request Authors
- jforbes14 (7)
- earowang (2)
- AnthonyEbert (2)
- dicook (2)
- bryceroney (2)
- danmackinlay (1)
- emitanaka (1)
Top Labels
Issue Labels
help wanted (1)
Pull Request Labels
Packages
- Total packages: 1
-
Total downloads:
- cran 224 last-month
- Total docker downloads: 88,618
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 5
- Total maintainers: 1
cran.r-project.org: eechidna
Exploring Election and Census Highly Informative Data Nationally for Australia
- Homepage: https://github.com/jforbes14/eechidna/
- Documentation: http://cran.r-project.org/web/packages/eechidna/eechidna.pdf
- License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
- Status: removed
-
Latest release: 1.4.1
published almost 5 years ago
Rankings
Stargazers count: 7.8%
Forks count: 10.1%
Average: 23.7%
Dependent packages count: 29.8%
Downloads: 35.4%
Dependent repos count: 35.5%
Maintainers (1)
Last synced:
9 months ago
Dependencies
DESCRIPTION
cran
- R >= 3.5.0 depends
- colourpicker * imports
- dplyr * imports
- ggplot2 * imports
- ggthemes * imports
- graphics * imports
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- methods * imports
- plotly >= 4.5.6 imports
- purrr * imports
- rgdal * imports
- rgeos * imports
- shiny * imports
- sp * imports
- stats * imports
- stringi * imports
- tibble * imports
- tidyr * imports
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- GGally * suggests
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