My personal projects for the weekly #TidyTuesday challenge since 2018
| Link | Title | Author |
|---|---|---|
| 🔗 | Graphical data analysis with R | Anton Unwin |
| 🔗 | Discrete Data Analysis with R | Michael Friendly |
| 🔗 | R for Data Science | Garrett Grolemund, Hadley Wickham |
| 🔗 | ggplot2: Elegant Graphics for Data Analysis | Hadley Wickham |
| 🔗 | Data Visualization a practical introduction | Kieran Healy |
| 🔗 | Fundamentals of Data Visualization | Claus O. Wilke |
| 🔗 | UC Business Analytics R Programming Guide | Bradley Boehmke |
| 🔗 | Tidy Text Mining with R | Julia Silge, David Robinson |
| 🔗 | Tidy Tuesday Screencast | David Robinson |
| 🔗 | Tidymodels | Julia Silge |
| 🔗 | Textmining | Lee KiChang |
| 🔗 | MIT 18.06 Linear Algebra, Spring 2005 | Gilbert Strang |
| 🔗 | Korea University DSBA | Kang PilSung |
DuBois Challenge 2022 by Anthony Starks
Dog breeds by American Kennel Club
Spiders by World Spiders Database
Dr. Who by datardis
Emmy Awards by Emmys
Billboard Top 100 by Data.World
Formular 1 by ergast
Bird Baths by Cleary et al, 2016
Star Trek Voice Commands by SpeechInteraction
Paralympics by IPC
US Droughts by Drought Monitor
Scooby Doo by Kaggle
Independence Day by Wikipedia
Du Bois Challenge by Du Bois Data Challenge
Lifetime Earning by Urban Institute
Transit Cost Project by TransitCosts.com
DatasauRus Dozen by Alberto Cairo
Chopped by kaggle
Broadway Musicals by Playbill
CRAN Code by CRAN
Time for Horror Movies? by IMDB
Roman Emperors Reign Duration by Wikipedia / Zonination
Top players in Grand Slams by Wikipedia
Anime by MyAnimeList
Bob Ross painting(PCA analysis) by 538 R package