Still fixing Travis...

Author: jeroenjanssens

.gitignore

@@ -2,3 +2,4 @@
 docs/*.md
 book/asciidoc
 _book_output
+.netlify

.netlify

@@ -23,5 +23,5 @@ script:
 
 deploy:
   provider: script
-  script: cd .. && pwd && ls && netlify deploy --prod --dir _book_output
+  script: cd .. && pwd && netlify deploy --prod --dir _book_output
   skip_cleanup: true

.travis.yml

@@ -15,10 +15,17 @@ github-repo: "jeroenjanssens/data-science-at-the-command-line"
 ---
 
 
+
 # Welcome {-}
 
 This is the website for *Data Science at the Command Line*, published by O'Reilly October 2014 First Edition. This hands-on guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. You’ll learn how to combine small, yet powerful, command-line tools to quickly obtain, scrub, explore, and model your data.
 
+<a href="https://www.datascienceworkshops.com/blog/public-workshop-sioux-data-science-at-the-command-line/">
+```{r, out.width = "600px", echo=FALSE, fig.align='center'}
+knitr::include_graphics("images/sioux-2019-06-12.jpg")
+```
+</a>
+
 To get you started---whether you’re on Windows, macOS, or Linux---author [Jeroen Janssens](https://twitter.com/jeroenhjanssens) has developed a [Docker image](https://hub.docker.com/r/datascienceworkshops/data-science-at-the-command-line) packed with over 80 command-line tools.
 
 Discover why the command line is an agile, scalable, and extensible technology. Even if you’re already comfortable processing data with, say, Python or R, you’ll greatly improve your data science workflow by also leveraging the power of the command line.

book/book.rds

@@ -3,27 +3,27 @@ @Manual{R-base
   author = {{R Core Team}},
   organization = {R Foundation for Statistical Computing},
   address = {Vienna, Austria},
-  year = {2017},
+  year = {2019},
   url = {https://www.R-project.org/},
 }
 @Manual{R-bookdown,
   title = {bookdown: Authoring Books and Technical Documents with R Markdown},
   author = {Yihui Xie},
-  year = {2017},
-  note = {R package version 0.5},
-  url = {https://github.com/rstudio/bookdown},
+  year = {2018},
+  note = {R package version 0.9},
+  url = {https://CRAN.R-project.org/package=bookdown},
 }
 @Manual{R-knitr,
   title = {knitr: A General-Purpose Package for Dynamic Report Generation in R},
   author = {Yihui Xie},
-  year = {2017},
-  note = {R package version 1.18},
+  year = {2019},
+  note = {R package version 1.22},
   url = {https://CRAN.R-project.org/package=knitr},
 }
 @Manual{R-rmarkdown,
   title = {rmarkdown: Dynamic Documents for R},
-  author = {JJ Allaire and Yihui Xie and Jonathan McPherson and Javier Luraschi and Kevin Ushey and Aron Atkins and Hadley Wickham and Joe Cheng and Winston Chang},
-  year = {2017},
-  note = {R package version 1.8},
+  author = {JJ Allaire and Yihui Xie and Jonathan McPherson and Javier Luraschi and Kevin Ushey and Aron Atkins and Hadley Wickham and Joe Cheng and Winston Chang and Richard Iannone},
+  year = {2019},
+  note = {R package version 1.12},
   url = {https://CRAN.R-project.org/package=rmarkdown},
 }