|
gptkbp:instance_of
|
gptkb:book
|
|
gptkbp:bfsLayer
|
5
|
|
gptkbp:bfsParent
|
gptkb:Hadley_Wickham
gptkb:Python_for_Data_Analysis
|
|
gptkbp:author
|
gptkb:Garrett_Grolemund
gptkb:Hadley_Wickham
|
|
gptkbp:contains
|
gptkb:tidyr
gptkb:dplyr
gptkb:ggplot2
gptkb:tidyverse
shiny
purrr
readr
stringr
lubridate
rmarkdown
|
|
gptkbp:focus
|
Machine learning
Data visualization
Statistical modeling
Data manipulation
|
|
gptkbp:format
|
gptkb:printer
gptkb:book
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
R for Data Science
|
|
gptkbp:is_available_on
|
gptkb:Book_Depository
gptkb:Google_Books
gptkb:Barnes_&_Noble
gptkb:book
O' Reilly's website
|
|
gptkbp:is_described_as
|
A practical guide to data science using R.
|
|
gptkbp:is_reviewed_by
|
gptkb:Library_Journal
gptkb:Kirkus_Reviews
Choice
|
|
gptkbp:isbn
|
9781492045602
|
|
gptkbp:language
|
English
|
|
gptkbp:page_count
|
432
|
|
gptkbp:published_by
|
gptkb:O'_Reilly_Media
|
|
gptkbp:published_year
|
gptkb:2016
|
|
gptkbp:related_to
|
gptkb:R_programming_language
Big data
Data analysis
Data mining
Data analysis software
Data-driven decision making
Predictive analytics
Machine learning algorithms
Statistical inference
Data visualization tools
Data ethics
Data storytelling
Data visualization techniques
Open data
Statistical computing
Data science frameworks
Data science projects
Data wrangling
Reproducible research
|
|
gptkbp:subject
|
gptkb:physicist
|
|
gptkbp:target_audience
|
Beginners
Intermediate users
|