Türkiye’deki İl Bazında Gerçekleşen Covid Vakaları için Bir Raporlama ve Karşılaştırma Uygulaması: R Shiny Örneği

Yıl 2021, Cilt: 4 Sayı: 2, 9 - 18, 19.08.2021

Cenk İçöz

Öz

Covid-19 pandemisi Çin’in Vuhan kentinde ortaya çıktıktan sonra tüm dünya ülkeleri ile birlikte Türkiye’de de etkisini bir yılı aşkın bir süredir göstermektedir. Ülke hükümetleri pandeminin önüne geçebilmek için çeşitli birçok kısıtlama getirmiş ve önlemler alma yoluna gitmiştir. Bu bağlamda ülkemizde illerin haftalık vaka sayılarına göre renk odaklı bir risk sınıflandırma yöntemi geliştirilmiş ve farklı renge sahip risk sınıflarındaki iller için farklı önlemler tercih edilmiştir. Bu çalışmada Türkiye’de il bazında açıklanmakta olan yüz binde gerçekleşen haftalık vaka sayılarının zaman ve mekân içerisinde karşılaştırılması ve raporlanmasında interaktif grafikler içeren kullanıcı dostu bir R Shiny uygulamasının tasarlanması ele alınmıştır. Uygulamada otomatik rapor ve görsellerin herkes tarafından elde edilip yorumlanması ve zamansal ve mekânsal karşılaştırılmalarının yapılması amaçlanmıştır.

Anahtar Kelimeler

R, Shiny, İnteraktif Grafikler, Covid-19

An Application of Reporting and Comparing Province Based Covid Cases in Turkey: R Shiny Example

Öz

After the Covid-19 pandemic emerged in Wuhan, China, it has been still effective for more than a year in whole countries of the world alongside with Turkey. Governments of the countries introduced many restrictions and took preventive measures to control the pandemics. A color-oriented risk classification method has been developed according to the weekly number of cases of the provinces in Turkey within this framework and different measures have been preferred for provinces with different risk classes. In this study, a user-friendly R Shiny application is designed which includes interactive graphs for comparing and reporting weekly announced number of cases per hundred thousand in Turkey both spatially and temporally. Interpretation and obtaining of automated reports and graphs by using the application is aimed to enable spatial and temporal comparisons for everyone.

Anahtar Kelimeler

R, Shiny, Interactive Graphs, COVID-19

Kaynakça

• T.C. Sağlık Bakanlığı. “Covid-19 Nedir?” https://covid19.saglik.gov.tr/TR-66300/covid-19-nedir-.html (04.05.2021). Wikipedia: “COVID -19 lockdowns” https://en.wikipedia.org/wiki/COVID-19_lockdowns (04.05.2021).
• Wikipedia. “Türkiye'de COVID-19 pandemisi zaman çizelgesi”.https://tr.wikipedia.org/wiki/T%C3%BCrkiye%27de_COVID-19_pandemisi_zaman_%C3%A7izelgesi (04.05.2021).
• DW. “Kontrollü normalleşme hakkında merak edilenler”. https://www.dw.com/tr/kontroll%C3%BCnormalle%C5%9Fme-hakk%C4%B1nda-merak-edilenler/a-56747527 (04.05.2021).
• İBB Açık Veri Portalı. https://data.ibb.gov.tr/tr/ (04.05.2021).
• Türkiye İstatistik Kurumu. https://www.tuik.gov.tr/ (04.05.2021).
• The official data portal for European data https://data.europa.eu/en (04.05.2021).
• Keim AD, Information visualization andvisual data mining. IEEE Transaction on Visualization and Computer Graphics, 8. January-March, 2002.
• Zararsiz G, Cenk I, and Erdener O. "Visualization of High Dimensional Data." In Encyclopedia of Business Analytics and Optimization, pp. 2653-2664. IGI Global, 2014.
• https://icaci.org/files/documents/wom/06_IMY_WoM_en.pdf (04.05.2021).
• R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.,2020
• Er F , Bal C . "COVID-19 ve Grafiksel Veri Analizi". Osmangazi Tıp Dergisi2020;42(4):450-461,Doi: 10.20515/otd.735753
• https://blog.revolutionanalytics.com/2017/01/cran-10000.html (04.05.2021).
• Wickham H. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag, New York, 2016
• Deepayan S Lattice: Multivariate Data Visualization with R. Springer, New York. ISBN 978-0-387-75968-5, 2008
• Chang W., Cheng J., Allaire J., Xie Y. and McPherson J., 2017. Shiny: web application framework for R. R package version, 1(5), p.2017.
• Towards Data Science: “Top 100 R resources on Novel COVID-19 Coronavirus”. https://towardsdatascience.com/top-5-r-resources-on-covid-19-coronavirus-1d4c8df6d85f (05.05.2021).
• Covid 19-r. https://mine-cetinkaya-rundel.github.io/covid19-r/ (05.05.2021).
• Covid-19 Country Comparison. https://scitilab.shinyapps.io/Covid19/ (05.05.2021).
• Covid -19 Tracker. https://shiny.rstudio.com/gallery/covid19-tracker.html (05.05.2021).
• Daily summary: Coranavirus in the UK. https://coronavirus.data.gov.uk/ (05.05.2021).
• Spatial neighbors in R - an interactive illustration. http://personal.tcu.edu/kylewalker/spatial-neighbors-in-r.html (05.05.2021).
• Bivand RS, Pebesma EJ, Gomez-Rubio V, Pebesma EJ. Applied spatial data analysis with R. New York: Springer; 2013 Mar 19.
• Tennekes M “tmap: Thematic Maps in R.” _Journal of StatisticalSoftware_, *84*(6), 1-39. doi: 10.18637/jss.v084.i06 (URL:https://doi.org/10.18637/jss.v084.i06).
• Sievert C Interactive Web-Based Data Visualization with R, plotly, and shiny. Chapman and Hall/CRC Florida, 2020.
• Bivand R, Keitt T and Rowlingson B rgdal: Bindings for the 'Geospatial' Data Abstraction Library. R package version 1.5-23,2021.https://CRAN.R-project.org/package=rgdal
• Hijmans RJ raster: Geographic Data Analysis and Modeling. R package version 3.4-5. 2020, https://CRAN.R-project.org/package=raster
• Wickham H “Reshaping Data with the reshape Package”. Journal of Statistical Software, 21(12), 1-20. 2007 URL http://www.jstatsoft.org/v21/i12/.
• Bivand R and Colin R rgeos: Interface to Geometry Engine -Open Source ('GEOS'). R package version 0.5-5, 2020, https://CRAN.R-project.org/package=rgeos
• https://github.com/cenkicoz26/covid (05.05.2021).
• https://cenkicoz.shinyapps.io/covidshiny/?_ga=2.108085440.338756453.1619906678-857120237.1618862014 (05.05.2021).