20 R Packages You Should Know

Опубликовано: 11 Апрель 2026
на канале: RichardOnData
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Skip ahead:
2:43 - dplyr
3:54 - data.table
5:09 - tidyr
6:12 - ggplot2
7:50 - ggThemeAssist
10:08 - esquisse
13:04 - plotly
14:51 - purrr
16:20 - stringr
16:54 - lubridate
17:44 - forcats
18:59 - rmarkdown
20:24 - kableExtra
21:25 - shiny
22:30 - shinyDashboard
23:17 - caret
24:10 - tidymodels
25:45 - keras
27:03 - fable
28:26 - reticulate

RichardOnData tutorials:
dplyr:    • Manipulating Data in R with "dplyr" | R Tu...  
ggplot2/ggThemeAssist:    • Visualizing Data in R with "ggplot2" and "...  
tidyr:    • Tidying Data in R with "tidyr" | R Tutoria...  
lubridate:    • Handling Datetimes in R with "lubridate" |...  
forcats:    • Conquering Factors in R with "forcats" | R...  
stringr:    • Manipulating Text in R with "stringr" | R ...  
kableExtra:    • Designing tables in R with "knitr" and "ka...  
caret (part 1):    • Preprocessing Data in R for ML with "caret...  
caret (part 2):    • Feature Elimination and Variable Importanc...  
caret (part 3):    • Training and Tuning ML Models in R with "c...  
caret (part 4):    • Creating ROC curves and ensembling models ...  

#LearnR #RPackages #BreakingIntoDataScience

Reference links:
dplyr: https://dplyr.tidyverse.org/
data.table: https://cran.r-project.org/web/packag...
tidyr: https://tidyr.tidyverse.org/
ggplot2: https://ggplot2.tidyverse.org/
esquisse: https://rdrr.io/cran/esquisse/
plotly: https://plotly.com/r/
purrr: https://purrr.tidyverse.org/
stringr: https://stringr.tidyverse.org/
lubridate: https://lubridate.tidyverse.org/
forcats: https://forcats.tidyverse.org/
rmarkdown: https://rstudio.com/wp-content/upload...
kableExtra: https://cran.r-project.org/web/packag...
shiny: https://rstudio.com/wp-content/upload...
shinyDashboard: https://rstudio.github.io/shinydashbo...
caret: https://cran.r-project.org/web/packag...
tidymodels: https://rviews.rstudio.com/2019/06/19...
keras: https://tensorflow.rstudio.com/guide/...
fable: http://fable.tidyverts.org/
reticulate: https://ugoproto.github.io/ugo_r_doc/...

"R for Data Science" digital version: https://r4ds.had.co.nz/
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"Deep Learning with R": https://amzn.to/3txjtdA

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