class: inverse, center, middle background-image: url(figures/danielle1.png) background-size: cover # A remote glimpse into the useR! 2021 conference .large[Anna Quaglieri | R-Ladies Melbourne Meetup | 3 Aug 2021] .left[.footnote[Art by Danielle Navarro, *Silhouette in Teal* (2021) Random walk, flametree L-system]] --- name: intro ## A bit about me -- Got my Bachelor and Master in Statistics between the Universities of Bologna, Glasgow and Melbourne .center[<img class="circle" src="figures/uni.png" width="900px" height = "300px"/>] --- ### A bit of research - Master research in Population Genetics at the WEHI + worked for 1.5 years as RA - PhD in Cancer Genomics at the WEHI -- ### A bit outside of research - After my PhD, I Decided to try a different path outside of research - Worked as Data Science consultant for 1.5 years at the AI consultancy Eliiza --- class: center ## Since two months I'm a Bioinformatics Data Scientist at the Melbourne based startup [Mass Dynamics](https://www.massdynamics.com/) -- .pull-left[ > Mass Dynamics is on a mission to free humanity and society from the burden of disease by helping more life scientists transform proteomics data to knowledge - better, faster and easier. <img class="circle" src="figures/md3.png" width="200px" height = "200px"/> ] -- .pull-right[  ] --- name: whatme ## What I actually do every day -- 🏡💻 **Work in a fun team**: Work with a fun interdisciplinary team of scientists, developers, marketing savvy. -- 📙 **Learn**: Learn the intricacies and amazingness of mass spectrometry (= most used technique to quantify proteins in a sample) & what life scientists need to make the best use of their experiment. -- 👩‍💻 **Code in R**: Assemble workflows in R to analyse mass spectrometry data. -- 👐 **Open Science**: Learn and strive for reproducibility and openness in what we produce. -- 🥜 **In a nutshell**: Study & Learn, think, build solutions (mainly in R packages)‚ debug, debug, debug, repeat. --- class: centre, inverse background-image: url(figures/will.png) background-size: cover # useR! 2021 .left[.footnote[Art by Will Chase, USA, *Terrazzo, confetti* (2021) Voronoi Tessellation, Poisson disc sampling]] --- class: center # useR! is one of my favorite conferences! .pull-left[ #### R-Ladies dinner useR! 2018 <img class="circle" src="figures/user2018.png" width="300px" height = "400px"/>] .pull-right[ #### R-Ladies online cathcup 2021 <img class="circle" src="figures/user2021.png" width="300px" height = "400px"/> ] --- # Disclaimer - My highlights also corresponds to talks presented in our timezone -- - All talks and workshops will be made available online very very soon! I'll keep you posted .center[] --- # Topics that I will cover - [Teaching and Learning R & Statistics](#teaching) - [Data visualisation](#viz) - [Data Validation and Package Testing](#valid) - [Surprise!](#surprise) - [Keynote: **Heidi Seibold** on *Research Software Engineers (RSE) & Academia*](#heidi) - [R in Production and Package dependencies](#prodr) - [aRt gallery](#art) --- name: teaching class: top ## Teaching and learning statistics .centre[<img class="circle" src="figures/penguins.png" width="800px" height = "500px"/>] .footnote[ Artwork by [@allison_horst](https://www.allisonhorst.com/)] --- ## Developing a datasets based R package to teach environmental data science #### Author and speaker: Allison Horst - 🔗[Introduced the `{lterdatasampler}`](https://lter.github.io/lterdatasampler/): LTER Data Sampler 📦 (LTER = Long Term Ecological Research program (LTER) Network) - LTER goal is education and training -- #### Lesson learnt from this talk - A great way to learn how to build an R 📦 is to create a data-package (package that only includes data) -- - I don't have super complex, cool new functions... I cannot write an R 📦 -- - Free gift! Data packages are an enormously useful tool for teaching purposes (how many times have you used the [`{iris}` dataset [1]](https://en.wikipedia.org/wiki/Iris_flower_data_set)??!!) .footnote[R. A. Fisher (1936). "The use of multiple measurements in taxonomic problems". Annals of Eugenics. 7 (2): 179–188. doi:10.1111/j.1469-1809.1936.tb02137.x. hdl:2440/15227] --- ## 🐧 `{palmerpenguins}` is the new `{iris}` 🌷 .pull-left[ #### Authors: Allison Horst, Alison Hill, Kristen Gorman The 🔗[`{palmerpenguins}` 📦](https://allisonhorst.github.io/palmerpenguins/) provides a great dataset for data exploration & visualization, as an alternative to iris. ```r install.packages("palmerpenguins") library(palmerpenguins) ``` .center[<img class="circle" src="figures/penguins-sticker.png" width="200px" height = "200px"/>] ] -- .pull-right[ Meet the penguins! .center[<img class="circle" src="figures/penguins-photo.png" width="300px" height = "200px"/>] .center[<img class="circle" src="figures/penguins-cartoon.png" width="400px" height = "200px"/>] ] .footnote[ Artwork by [@allison_horst](https://www.allisonhorst.com/)] --- ```r library(palmerpenguins) library(dplyr) library(DT) penguins %>% head() ``` ``` ## # A tibble: 6 × 8 ## species island bill_length_mm bill_depth_mm flipper_length_… body_mass_g sex ## <fct> <fct> <dbl> <dbl> <int> <int> <fct> ## 1 Adelie Torge… 39.1 18.7 181 3750 male ## 2 Adelie Torge… 39.5 17.4 186 3800 fema… ## 3 Adelie Torge… 40.3 18 195 3250 fema… ## 4 Adelie Torge… NA NA NA NA <NA> ## 5 Adelie Torge… 36.7 19.3 193 3450 fema… ## 6 Adelie Torge… 39.3 20.6 190 3650 male ## # … with 1 more variable: year <int> ``` --- class: middle, center <img src="index_files/figure-html/unnamed-chunk-4-1.png" width="100%" /> ---  --- ## Creating R packages: resources that I found super useful! Get started with 🔗[R Packages](https://r-pkgs.org/) by Hadley Wickham. Easy to read and very comprehensive. What you need to get started: 1. Code (one function is enough) AND/OR data (it doesn't have to be large!) -- 2. An R project in a new folder `/path/to/myPackage` -- 3. Run the code `usethis::create_package("/path/to/myPackage")` (more info https://r-pkgs.org/workflows101.html). This will create the metadata and other files that you need to package the package up! -- 4. You're setup! --- ## To recapitulate: Setup your R package in a few lines! .pull-left[ ```r usethis::create_package("/path/to/myPackage") ``` .center[] ] -- .pull-right[ ```r data_fake <- data.frame(First = seq(1:200), Second = rep("A", 200)) *usethis::use_data(data_fake) ``` .center[]  ] .footnote[ [R Packages](https://r-pkgs.org/) by Hadley Wickham ] --- ## `{fusen}` 📦: Create a package from Rmd -- #### Speaker and author: Sébastien Rochette > If you know how to create a Rmarkdown file, then you know how to build a package. #### 🔗[Introduction to `{fusen}` ](https://thinkr-open.github.io/fusen/) -- **Philosophy** You don't need to move around functions and files to create a package, you only need your Rmd with functions, documentation, tests, examples. -- .pull-left[ ```r install.packages("fusen") library(fusen) ``` .center[<img class="circle" src="figures/fusen.png" width="180px" height = "180px"/>] ] .pull-right[.center[]] --- ## `Rmd` first approach to write an R 📦 .pull-left[ 1. Write your `Rmd` using some prefix to name code chunks, e.g. `description`, `function`, `tests`, `examples` 2. These prefixes will tell `{fusen}` how to create your package ] -- .pull-right[ **Inflate!** .center[<img class="circle" src="figures/fusen-wroflow.png" width="600px" height = "400px"/>] ] --- ## Building and maintaining OpenIntro using the R ecosystem #### Speaker: Cetinkaya-Rundel, Mine - 🔗[OpenIntro website](https://www.openintro.org/) has loads of resources to teach and learn statistics (for free!) - 🔗[OpenIntro R 📦](https://github.com/OpenIntroStat/openintro) has supplemental functions and data for OpenIntro resources. .pull-left[ .center[<img class="circle" src="figures/openintro.png" width="800px" height = "300px"/>] ] .pull-right[ .center[<img class="circle" src="figures/openintro-sticker.png" width="300px" height = "300px"/>] ] --- ## Another lesson to build a data-centric-package! .center[<img class="circle" src="figures/openintro-eco.png" width="800px" height = "450px"/>] `{OpenIntro}` depends on 3 other data packages. See package 🔗[DESCRIPTION](https://github.com/OpenIntroStat/openintro/blob/master/DESCRIPTION) --- ## Teaching and learning Bayesian statistics with `{bayesrules}` 📦 #### Speaker: Mine Dogucu (🔗[GitHub repo](https://github.com/bayes-rules/bayesrules) and 🔗[Talk slides](https://mdogucu.github.io/user-2021/#1) ) .pull-left[ - The `{bayesrules}` package contains tools for teaching and learning tools for teaching (and learning) Bayesian statistics - The package accompanies the open-access 🔗[Bayes Rules! An Introduction to Bayesian Modeling with R](https://www.bayesrulesbook.com/) ] .pull-right[ .center[<img class="circle" src="figures/bayes.png" width="350px" height = "350px"/>] ] --- class: top, middle background-image: url(figures/iema.png) name: viz ## Data Visualisation .left[.footnote[Art by Ijeamaka Anyene, USA, *Sunset* (2021)]] --- ## Keynote: Expanding the vocabulary of R graphics #### Speaker: Paul Murrel author of `{grDevices}` 📦 .pull-left[ - A graphics engine containing functions for both base and grid graphics. - The `{grid}`📦 is low-level system for plotting within R (`{ggplot2}`📦 is based on this) - Grid graphics and R’s base graphics are two separate systems. - Usually worth using grid graphics when you need to create a very unusual plot that cannot be created using `ggplot2` ] .pull-right[ <img class="circle" src="figures/grdevices.png" width="500px" height = "400px"/> ] --- ## 🔗[Paul Murrel's New Features in the R Graphics Engine](https://developer.r-project.org/Blog/public/2020/07/15/new-features-in-the-r-graphics-engine/) ### Gradient and radial fill ```r library(grid) ``` .pull-left[ <img class="circle" src="figures/gradient-fill.png"/> ] .pull-right[ <img class="circle" src="figures/radial-fill.png"/> ] --- ### Pattern fills ```r library(grid) ``` <img class="circle" src="figures/pattern-fill.png"/> --- class: center # Going beyond statistical plots #### 🔗[Paul Murrel's talk: *Going beyond statistical plots*](https://www.stat.auckland.ac.nz/~paul/Talks/ANZSC2021/index.html) You can build illustrator like viz! <img class="circle" src="figures/grid-illustrator.png" width="400px" height = "300px"/> --- ## The `{virgo}` 📦 #### Speaker: [Stuart Lee](https://github.com/sa-lee) #### Authors: Stuart Lee and [Earo Wang](https://earo.me/) 🔗[Introduction to `virgo`](https://vegawidget.github.io/virgo/) -- - Allows to easily build interactive graphics for exploratory data analysis -- - Allows cross interactivity between plots without having to build a Shiny app -- - `virgo` plots also works within Shiny --- ## `{virgo}` in action! .pull-left[ ```r library(virgo) library(palmerpenguins) ``` ```r selection <- select_interval() ``` ```r p <- penguins %>% vega() %>% mark_circle( enc( x = bill_length_mm, y = bill_depth_mm, color = encode_if(selection, species, "black") ) ) ``` ] .pull-right[ ```r p ``` <div id="htmlwidget-3bfe07e2299611538f29" style="width:auto;height:auto;" class="vegawidget html-widget"></div> <script type="application/json" data-for="htmlwidget-3bfe07e2299611538f29">{"x":{ "chart_spec": { "$schema": "https://vega.github.io/schema/vega-lite/v4.json", "data": { "values": [ { "species": "Adelie", "island": "Torgersen", "bill_length_mm": 39.1, "bill_depth_mm": 18.7, "flipper_length_mm": 181, "body_mass_g": 3750, "sex": "male", "year": 2007, "\"black\"": "black" }, { "species": "Adelie", "island": "Torgersen", "bill_length_mm": 39.5, "bill_depth_mm": 17.4, "flipper_length_mm": 186, 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185, "body_mass_g": 3950, "sex": "male", "year": 2007, "\"black\"": "black" }, { "species": "Adelie", "island": "Biscoe", "bill_length_mm": 38.8, "bill_depth_mm": 17.2, "flipper_length_mm": 180, "body_mass_g": 3800, "sex": "male", "year": 2007, "\"black\"": "black" }, { "species": "Adelie", "island": "Biscoe", "bill_length_mm": 35.3, "bill_depth_mm": 18.9, "flipper_length_mm": 187, "body_mass_g": 3800, "sex": "female", "year": 2007, "\"black\"": "black" }, { "species": "Adelie", "island": "Biscoe", "bill_length_mm": 40.6, "bill_depth_mm": 18.6, "flipper_length_mm": 183, "body_mass_g": 3550, "sex": "male", "year": 2007, "\"black\"": "black" }, { "species": "Adelie", "island": "Biscoe", "bill_length_mm": 40.5, "bill_depth_mm": 17.9, "flipper_length_mm": 187, "body_mass_g": 3200, "sex": "female", "year": 2007, "\"black\"": "black" }, { "species": "Adelie", "island": "Biscoe", "bill_length_mm": 37.9, "bill_depth_mm": 18.6, "flipper_length_mm": 172, "body_mass_g": 3150, "sex": "female", "year": 2007, "\"black\"": "black" }, { "species": "Adelie", "island": "Biscoe", "bill_length_mm": 40.5, "bill_depth_mm": 18.9, "flipper_length_mm": 180, "body_mass_g": 3950, "sex": "male", "year": 2007, "\"black\"": "black" }, { "species": "Adelie", "island": "Dream", "bill_length_mm": 39.5, "bill_depth_mm": 16.7, "flipper_length_mm": 178, "body_mass_g": 3250, "sex": "female", "year": 2007, "\"black\"": "black" }, { "species": "Adelie", "island": "Dream", "bill_length_mm": 37.2, "bill_depth_mm": 18.1, "flipper_length_mm": 178, "body_mass_g": 3900, "sex": "male", "year": 2007, "\"black\"": "black" }, { "species": "Adelie", "island": "Dream", "bill_length_mm": 39.5, "bill_depth_mm": 17.8, "flipper_length_mm": 188, "body_mass_g": 3300, "sex": "female", "year": 2007, "\"black\"": "black" }, { "species": "Adelie", "island": "Dream", "bill_length_mm": 40.9, "bill_depth_mm": 18.9, "flipper_length_mm": 184, "body_mass_g": 3900, "sex": "male", "year": 2007, "\"black\"": "black" }, { "species": "Adelie", "island": "Dream", "bill_length_mm": 36.4, "bill_depth_mm": 17, "flipper_length_mm": 195, "body_mass_g": 3325, "sex": "female", "year": 2007, "\"black\"": "black" }, { "species": "Adelie", "island": "Dream", "bill_length_mm": 39.2, "bill_depth_mm": 21.1, "flipper_length_mm": 196, "body_mass_g": 4150, "sex": "male", "year": 2007, "\"black\"": "black" }, { "species": "Adelie", "island": "Dream", "bill_length_mm": 38.8, "bill_depth_mm": 20, "flipper_length_mm": 190, "body_mass_g": 3950, "sex": "male", "year": 2007, "\"black\"": "black" }, { "species": "Adelie", "island": "Dream", "bill_length_mm": 42.2, "bill_depth_mm": 18.5, "flipper_length_mm": 180, "body_mass_g": 3550, "sex": "female", "year": 2007, "\"black\"": "black" }, { "species": "Adelie", "island": "Dream", "bill_length_mm": 37.6, "bill_depth_mm": 19.3, "flipper_length_mm": 181, "body_mass_g": 3300, "sex": "female", "year": 2007, "\"black\"": "black" }, { "species": "Adelie", "island": "Dream", "bill_length_mm": 39.8, "bill_depth_mm": 19.1, "flipper_length_mm": 184, "body_mass_g": 4650, "sex": "male", "year": 2007, "\"black\"": "black" }, { "species": "Adelie", "island": "Dream", "bill_length_mm": 36.5, "bill_depth_mm": 18, "flipper_length_mm": 182, "body_mass_g": 3150, "sex": "female", "year": 2007, "\"black\"": "black" }, { "species": "Adelie", "island": "Dream", "bill_length_mm": 40.8, "bill_depth_mm": 18.4, "flipper_length_mm": 195, "body_mass_g": 3900, "sex": "male", "year": 2007, "\"black\"": "black" }, { "species": "Adelie", "island": "Dream", "bill_length_mm": 36, "bill_depth_mm": 18.5, "flipper_length_mm": 186, "body_mass_g": 3100, "sex": "female", "year": 2007, "\"black\"": "black" }, { "species": "Adelie", "island": "Dream", "bill_length_mm": 44.1, "bill_depth_mm": 19.7, "flipper_length_mm": 196, "body_mass_g": 4400, "sex": "male", "year": 2007, "\"black\"": "black" }, { "species": "Adelie", "island": "Dream", "bill_length_mm": 37, "bill_depth_mm": 16.9, "flipper_length_mm": 185, 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}, { "species": "Adelie", "island": "Biscoe", "bill_length_mm": 39.6, "bill_depth_mm": 17.7, "flipper_length_mm": 186, "body_mass_g": 3500, "sex": "female", "year": 2008, "\"black\"": "black" }, { "species": "Adelie", "island": "Biscoe", "bill_length_mm": 40.1, "bill_depth_mm": 18.9, "flipper_length_mm": 188, "body_mass_g": 4300, "sex": "male", "year": 2008, "\"black\"": "black" }, { "species": "Adelie", "island": "Biscoe", "bill_length_mm": 35, "bill_depth_mm": 17.9, "flipper_length_mm": 190, "body_mass_g": 3450, "sex": "female", "year": 2008, "\"black\"": "black" }, { "species": "Adelie", "island": "Biscoe", "bill_length_mm": 42, "bill_depth_mm": 19.5, "flipper_length_mm": 200, "body_mass_g": 4050, "sex": "male", "year": 2008, "\"black\"": "black" }, { "species": "Adelie", "island": "Biscoe", "bill_length_mm": 34.5, "bill_depth_mm": 18.1, "flipper_length_mm": 187, "body_mass_g": 2900, "sex": "female", "year": 2008, "\"black\"": "black" }, { "species": "Adelie", "island": "Biscoe", 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"canvas", "actions": false, "defaultStyle": true } },"evals":[],"jsHooks":[]}</script> ] .footnote[🔗[Introduction to `virgo`](https://vegawidget.github.io/virgo/)] --- .pull-left[ ```r p_right <- penguins %>% vega(enc(x = body_mass_g)) %>% mark_histogram(bin = list(maxbins = 20)) %>% mark_histogram(color = "purple", bin = list(maxbins = 20), selection = selection) %>% mark_rule(enc(x = vg_mean(body_mass_g)), color = "red", size = 4, selection = selection) ``` ] .pull-right[ ```r p_right ``` <div id="htmlwidget-47b196a3e70ea64b6f2e" style="width:auto;height:auto;" class="vegawidget html-widget"></div> <script type="application/json" data-for="htmlwidget-47b196a3e70ea64b6f2e">{"x":{ "chart_spec": { "$schema": "https://vega.github.io/schema/vega-lite/v4.json", "data": { "values": [ { "species": "Adelie", "island": "Torgersen", "bill_length_mm": 39.1, "bill_depth_mm": 18.7, "flipper_length_mm": 181, "body_mass_g": 3750, "sex": "male", "year": 2007 }, { "species": "Adelie", "island": 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The `{microshades}` 📦 .pull-left[ #### Speaker and Author: [Lisa Karstens, PhD](https://www.ohsu.edu/people/lisa-a-karstens-phd) 🔗[Introduction to `microshades`](https://github.com/KarstensLab/microshades) Provide custom color shading palettes that improves: - **accessibility** for Color Vision Deficient (CVD) people - **data organization** ```r remotes::install_github("KarstensLab/microshades") ``` ] -- .pull-right[ Two crafted colour palettes: - `microshades_cvd_palettes` - `microshades_palettes` Total of 30 available colours per palette. <img class="circle" src="figures/microshades1.png" width="400px" height = "200px"/> ] --- ## `{microshades}` in action!  .footnote[🐧 `{palmerpenguins}` with `{microshades}` example code: https://karstenslab.github.io/microshades/articles/non-microbiome_data.html ] --- class: inverse, centre, middle name: valid background-image: url(figures/antonio.png) background-size: cover ## Data validation and Unit testing .left[.footnote[Art by Antonio Sánchez, Spain, *Jellyfish* (2018), Sines and cosines]] --- ## `{autotest}` 📦: Automatic testing for R packages #### Speaker and author: [Mark Padgham](https://mpadge.github.io/), Software Research Scientst at [`rOpenSci`](https://ropensci.org/) 🔗[Introduction to `{autotest}` <svg aria-hidden="true" role="img" viewBox="0 0 496 512" style="height:1em;width:0.97em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>](https://github.com/ropensci-review-tools/autotest) ```r install.packages("autotest") ``` -- - `{autotest}` goes into the examples of your R 📦 functions and *mutates* (aka changes) the inputs parameters to function calls. -- - This allows to check for robustness of the package to several inputs --- ## `{autotest}` in actions ```r library(autotest) y <- autotest_package(package = "stats", functions = "var", test = TRUE) ``` .pull-left[  ] .pull-right[  ] --- ## A fresh look at unit testing with `{tinytest}` 📦 .pull-left[ #### Speaker and author: Mark van der Loo 🔗[Introduction to `{tinytest}` <svg aria-hidden="true" role="img" viewBox="0 0 496 512" style="height:1em;width:0.97em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>](https://github.com/markvanderloo/tinytest) ```r install.packages("tinytest") ``` - The purpose is to facilitate the development of unit testing of R 📦 - It provides you with better stats and ideas where the errors actually occurred ] -- .pull-right[ .center[<img class="circle" src="figures/tinytest.png" width="400px" height = "400px"/>] ] .footnote[ [1] M van der Loo (2017). tinytest: R package version 1.2.4. https://cran.r-project.org/package=tinytest [2] MPJ van der Loo (2020) A method for deriving information from running R code. R-Journal (Accepted) https://arxiv.org/abs/2002.07472 ] --- ## `{tinytest}` in action! 🔗[Overview of `{tinytest}` functionalities](https://github.com/markvanderloo/tinytest/blob/master/pkg/README.md) ```r library(tinytest) addOne <- function(x) x + 1 subOne <- function(x) x - 2 ``` -- ```r # this test should pass tinytest::expect_equal(addOne(1), 2 ) ``` ``` ## ----- PASSED : <--> ## call| tinytest::expect_equal(addOne(1), 2) ``` -- ```r # this test will fail tinytest::expect_equal(subOne(2), 1 ) ``` ``` ## ----- FAILED[data]: <--> ## call| tinytest::expect_equal(subOne(2), 1) ## diff| Expected '1', got '0' ``` --- ## Tutorial: Data validation with the `{validate}` 📦 #### Author: Mark van der Loo The purpose is to provide easy to use tools to check that you're data is valid! - 🔗[Easy data validation for the masses <svg aria-hidden="true" role="img" viewBox="0 0 496 512" style="height:1em;width:0.97em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>](https://github.com/data-cleaning/validate) - 🔗[The Data Validation Cookbook](https://data-cleaning.github.io/validate/) .footnote[ [1] MPJ van der Loo and E de Jonge (2020). Data Validation Infrastructure for R. Journal of Statistical Software, Accepted for publication. https://arxiv.org/abs/1912.09759 [2] MPJ van der Loo (2020) The Data Validation Cookbook version 1.0.1. https://data-cleaning.github.io/validate ] --- ## {validate} in action! ```r library(palmerpenguins) head(penguins) ``` ``` ## # A tibble: 6 × 8 ## species island bill_length_mm bill_depth_mm flipper_length_… body_mass_g sex ## <fct> <fct> <dbl> <dbl> <int> <int> <fct> ## 1 Adelie Torge… 39.1 18.7 181 3750 male ## 2 Adelie Torge… 39.5 17.4 186 3800 fema… ## 3 Adelie Torge… 40.3 18 195 3250 fema… ## 4 Adelie Torge… NA NA NA NA <NA> ## 5 Adelie Torge… 36.7 19.3 193 3450 fema… ## 6 Adelie Torge… 39.3 20.6 190 3650 male ## # … with 1 more variable: year <int> ``` ```r table(penguins$island, penguins$species) ``` ``` ## ## Adelie Chinstrap Gentoo ## Biscoe 44 0 124 ## Dream 56 68 0 ## Torgersen 52 0 0 ``` --- #### Create a `validator` with rules -- - Separate multiple validations by a comma -- - The example shows multivariate validation including completeness validation (`is_complete`) and conditional validations. -- ```r library(validate) rules <- validator(flipper_length_mm > 0, is_complete(bill_depth_mm, flipper_length_mm, bill_depth_mm), if(island %in% "Biscoe") species %in% c("Adelie")) ``` -- ```r confront(penguins, rules) %>% summary() ``` ``` ## name items passes fails nNA error warning ## 1 V1 344 342 0 2 FALSE FALSE ## 2 V2 344 342 2 0 FALSE FALSE ## 3 V3 344 220 124 0 FALSE FALSE ## expression ## 1 flipper_length_mm > 0 ## 2 is_complete(bill_depth_mm, flipper_length_mm, bill_depth_mm) ## 3 !(island %vin% "Biscoe") | (species %vin% c("Adelie")) ``` --- class: center, middle, inverse name: surprise background-image: url(figures/will-chase2.png) background-size: cover # Teasing your appetite for next month R-Ladies Melbourne event # Spoiler Alert! .left[.footnote[Art by Will Chase, USA, *Triangle disintegration* (2019), Curl noise, trigonometry]] --- ## Here is the anomalous-down! -- .pull-left[ #### Author and speaker [Dr Sevvandi Kandanaarachchi](https://www.rmit.edu.au/contact/staff-contacts/academic-staff/k/kandanaarachchi-dr-sevvandi) R packages that Sevvandi developed to find anomalies in high-dimensional data: - 🔗[Introduction to dobin](https://cran.r-project.org/web/packages/dobin/vignettes/dobin.html) - 🔗[Introduction to lookout](https://sevvandi.github.io/lookout/) .center[<img class="circle" src="figures/dobin-lookout.png" width="400px" height = "200px"/>] ] -- .pull-right[ .center[] ] --- class: centre, inverse name: heidi background-image: url(figures/iema3.png) background-size: cover .left[.footnote[Art by Ijeamaka Anyene, USA, *Clouds* (2021)]] # Keynote: Heidi Seibold # Research Software Engineers (RSE) & Academia --- ## What is an RSE? https://researchsoftware.org/ .center[<img class="circle" src="figures/rse.png" width="600px" height = "450px"/>] --- ## Heidi’s path .pull-left[ .center[<img class="circle" src="figures/heidi-path1.png" width="600px" height = "450px"/>] ] .pull-right[ .center[<img class="circle" src="figures/heidi-path2.png" width="700px" height = "450px"/>] ] --- background-image: url(figures/open-stories.png) ### [Heidi's Podcast](https://anchor.fm/opensciencestories) --- ### What does an RSE do? - An RSE builds software for research -- - Generally writes code and teaches about software to researchers -- - Consult researcher with any kind of software problem -- .center[<img class="circle" src="figures/rse-dos.png" width="550px" height = "400px"/>] --- ## Tools for Open and Reproducible Science It's a bit too much to expect that the researcher would do all of those things + their research! The RSE comes to help! .center[<img class="circle" src="figures/toold-open-science.png" width="570px" height = "400px"/>] --- ## If you think this does for you... You can become part of the community! .center[<img class="circle" src="figures/rse-comms.png" width="670px" height = "400px"/>] --- class: center, middle, inverse name: prodr background-image: url(figures/will-chase3.png) background-size: cover .left[.footnote[Art by Will Chase, USA, *Bubble strings* (2021), Flow fields, circle packing, perlin noise]] # R in production --- ## What does "R in production" mean? Example from my experience. - 👩‍💻 I'm a data scientist at Mass Dynamics and I build R 📦 to analyse mass spectrometry data -- - But, Mass Dynamics wants to make the functionalities of the R packages easily available also to 👩‍🔬 life scientist, reducing the barrier of having to learn to code -- - The solution: the life scientist can interact with an easy user interface (UI, aka *frontend*) which runs my R 📦 in the background (aka *backend*) -- - Every time a scientist interacts with the UI, the R 📦 is run -> This is R in production 🎉! --- ## How do we do that? There is a bit of engineering setup and jargon to digest & there are various of way of accomplishing this task! -- Tricky aspects: -- - A lot of aspects are around the engineering setup (which is not my expertise!) -- - However, from my side I need to make sure that: - all dependencies needed by my R packages are available in production -- - all packages are put into production with a defined version to allow *reproducibility* -- - Managing dependencies can be really tricky! - How do you know all that you need, when a package will depends on another package, and anothe rpackage will depend on another one etc... --- ## What are package dependencies? -- You find them in the `DESCRIPTION` file of a package, disguising under: - `Depends`, `Imports`, `SystemRequirements` (dependencies external from R) - Example from the `{sf}` 📦 https://github.com/r-spatial/sf/blob/master/DESCRIPTION --- ## How to find them all? How do you determine all the dependencies needed to reproduce an R package/project environment to make it reporodcible, open, shareable, safe for production? My summary of suggestions after discussing with speakers at useR! 2021: - [`{renv}` 📦](https://rstudio.github.io/renv/articles/renv.html): - is the emerging method to manage package/project dependencies in R. - Calling `renv::snapshot()` saves the state of the project library to the lockfile (called `renv.lock`) - Really useful but for a given project it could give you more than you need (may affect speed). -- - Hard code your dependency, start minimal and grow: - It's really useful to grow your dependency list little by little. - Start with package `imports` (looking at the `DESCRIPTION` file) and then look for system dependencies --- ## Ways to find out system dependencies of a 📦 - [r-hub/sysreqs 📦](https://github.com/r-hub/sysreqs) provides a database with API to quickly find out which packages or other software needs to be available to build and use R packages. - Usage: `sysreqs::sysreq_commands(desc = "path/to/a/DESCRIPTION/file")` runs all the commands to install the necessary runtime system dependencies. -- - [rstudio/r-system-requirements](https://github.com/rstudio/r-system-requirements): RStudio independently maintained catalogue of dependencies, used to power the [RStudio package manager](https://packagemanager.rstudio.com/client/#/repos/1/packages/A3) -- - [{maketools} 📦](https://cran.r-project.org/web/packages/maketools/vignettes/sysdeps.html) To get runtime dependencies (only for Linux) ```r maketools::package_sysdeps("stringi") ``` ``` ## # A tibble: 1 × 6 ## shlib package headers source version url ## <chr> <chr> <chr> <chr> <chr> <chr> ## 1 libc++.1.dylib <NA> <NA> <NA> <NA> <NA> ``` --- ## These awesome suggestions from: Suggestions from speakers at useR! 2021: - Peter Solymos speaker for *Data science serverless-style with R and [OpenFaas](https://www.openfaas.com/)* - [Max Held](https://www.maxheld.de/) speaker for: *Bridging the Unproductive Valley: Building Data Products Strictly Without Magic* Other resources: - Interesting blog: [Determining system dependencies for R projects](https://mdneuzerling.com/post/determining-system-dependencies-for-r-projects/) - R-blogger post about useR! 2021 [Integrating R into production talks](https://www.r-bloggers.com/2021/07/user2021-integrating-r-into-production/) --- ## Productionising ML models developed in R #### Author: [Surya Avala](https://github.com/suryaavala), ML Engineer at [@whispr](https://github.com/whispir) ([Talk slides](https://github.com/suryaavala/prodr/blob/main/prodr.pdf)) (Not from useR!) But I found it really useful! Phylosphy: Wrapping up everything with Docker 🐳 and using [`{plumber}` 📦](https://www.rplumber.io/) to generate and API for R. .center[<img class="circle" src="figures/suryas-approach.png" width="670px" height = "350px"/>] --- background-image: url(figures/thoams.png) background-size: cover class: center, middle name: art # [aRt gallery](https://user_2021.gitlab.io/user2021_art_gallery/#46) .left[.footnote[*Yonder 1831*, 2021 by Thomas Lin Pedersen (Denmark). Flow lines, nearest neighbour, texture blending]] --- ## Thanks to - useR! organisers and speakers! - Mass Dynamics for letting me take part to the conference - [`Meet Xaringan: Making slides in R Markdown`](https://arm.rbind.io/slides/xaringan.html#1) by Alison Hill, learn how to make beautiful slides using `{xaringan}`. - These slides were created using the `{xaringan}` 📦 by Yihui Xie (2021). xaringan: Presentation Ninja. R package version 0.22. https://CRAN.R-project.org/package=xaringan - Shazia Ruybal [Xaringan's slides from her previous R-Ladies Melbourne talk](https://github.com/shaziaruybal) for examples --- ## Glossary of R packages mentioned .pull-left[ #### Teaching and Learning R & Statistics - [`{lterdatasampler}`](https://lter.github.io/lterdatasampler/) - [`{palmerpenguins}`](https://allisonhorst.github.io/palmerpenguins/) - [`{usethis}`](https://usethis.r-lib.org/) - [`{fusen}`](https://thinkr-open.github.io/fusen/) - [`{OpenIntro}`](https://github.com/OpenIntroStat/openintro) - [`{bayesrules}`](https://github.com/bayes-rules/bayesrules) #### Data visualisation - [`{grid}`](https://developer.r-project.org/Blog/public/2020/07/15/new-features-in-the-r-graphics-engine/) - [`{virgo}`](https://vegawidget.github.io/virgo/) - [`{microshades}`](https://github.com/KarstensLab/microshades) ] .pull-right[ #### Data Validation and Package Testing - [`{autotest}`](https://github.com/ropensci-review-tools/autotest) - [`{tinytest}`](https://github.com/markvanderloo/tinytest) - [`{validate}`](https://github.com/data-cleaning/validate) #### Next month surprise! - [`{dobin}`](https://github.com/sevvandi/dobin) - [`{lookout}`](https://github.com/sevvandi/lookout) #### Manage package dependencies - [`{renv}`](https://rstudio.github.io/renv/articles/renv.html) - [`{sysreqs}`](https://github.com/r-hub/sysreqs) - [`{maktools}`](https://cran.r-project.org/web/packages/maketools/vignettes/sysdeps.html) ] --- class: top, middle background-image: url(figures/iema4.png) .footnote[Art by Ijeamaka Anyene, USA, *Arcs IV* (2020)] # Any question? You can fine me at: - [<svg aria-hidden="true" role="img" viewBox="0 0 512 512" style="height:1em;width:1em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg> @annaquagli](https://twitter.com/annaquagli) - [<svg aria-hidden="true" role="img" viewBox="0 0 496 512" style="height:1em;width:0.97em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg> @annaquaglieri16](https://github.com/annaquaglieri16)