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RStudio and R Resources Happy Scientist Seminar Emil Hvitfeldt 2019-1-22

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Motivation We will talk about what you are able to do in RStudio with R and where to find information and rescources to do it great.

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- Data analysis scripts - Interactive web applications - Documents - Reports - Graphs - more - Syntax highlighting - code completion - smart indentation - Integrated R help - data viewer - Version control with Git

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Packages Idea -> Code -> Package -> Share -> Happiness If you want to do something, chance has it someone have worked on it before

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CRAN (The Comprehensive R Archive Network) https://cran.r-project.org/

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https://cran.r- project.org/web/packages/available_packages_by_name.html

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https://cran.r-project.org/web/views/

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https://www.bioconductor.org/

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https://www.bioconductor.org/packages/release/BiocViews.html#___Software

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R Markdown - Compile a single R Markdown document to a report in different formats, such as PDF, HTML, or Word. - Make slides for presentations (HTML5, LaTeX Beamer, or PowerPoint). - Build interactive applications based on Shiny. - Write journal articles. - Much more.

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Creating a R Markdown file

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Creating a R Markdown file

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Creating a R Markdown file

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Creating a R Markdown file

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Creating a R Markdown file

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--- title: "Amazing Document" author: "Emil Hvitfeldt" date: "1/20/2019" output: html_document --- YAML (optional)

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--- title: "Amazing Document" author: "Emil Hvitfeldt" date: "1/20/2019" output: html_document --- YAML: YAML Ain't Markup Language

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--- title: "Amazing Document" author: "Emil Hvitfeldt" date: "1/20/2019" output: html_document --- Chunks of code surrounded by ``` YAML (optional) The R in R Markdown

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--- title: "Amazing Document" author: "Emil Hvitfeldt" date: "1/20/2019" output: html_document --- Chunks of code surrounded by ``` Text with simple text formating. YAML (optional) The R in R Markdown The Markdown in R Markdown

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What we write --- author: "Emil Hvitfeldt" date: "1/20/2019" output: html_document --- We built a **linear** regression model. ```{r} fit <- lm(mpg ~ disp, data = mtcars) b <- coef(fit) plot(mpg ~ disp, mtcars) ``` The slope of the regression is `r round(b[1], digits = 1)` in the output.

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What we write --- author: "Emil Hvitfeldt" date: "1/20/2019" output: html_document --- We built a **linear** regression model. ```{r} fit <- lm(mpg ~ disp, data = mtcars) b <- coef(fit) plot(mpg ~ disp, mtcars) ``` The slope of the regression is `r round(b[1], digits = 1)` in the output. What we get

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What we write --- author: "Emil Hvitfeldt" date: "1/20/2019" output: pdf_document --- We built a **linear** regression model. ```{r} fit <- lm(mpg ~ disp, data = mtcars) b <- coef(fit) plot(mpg ~ disp, mtcars) ``` The slope of the regression is `r round(b[1], digits = 1)` in the output.

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What we write --- author: "Emil Hvitfeldt" date: "1/20/2019" output: pdf_document --- We built a **linear** regression model. ```{r} fit <- lm(mpg ~ disp, data = mtcars) b <- coef(fit) plot(mpg ~ disp, mtcars) ``` The slope of the regression is `r round(b[1], digits = 1)` in the output. What we get

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- github_document - html_document - latex_document - md_document - odt_document - pdf_document - rtf_document - word_document - ioslides_presentation - powerpoint_presentation - slidy_presentation - beamer_presentation Build-in Formats

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Notable Extensions

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Notable Extensions - xaringan

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Notable Extensions - xaringan - flexdashboard

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Notable Extensions - xaringan - flexdashboard - learnr

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Notable Extensions - xaringan - flexdashboard - learnr - rticles

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https://github.com/yihui/xaringan

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Sales Forecast Sales by State Series ETS(M,A,M) level 90

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Welcome Visualisation is an important tool for generating insights, but your data wonʼt always arrive ready to visualize. Often youʼll need to filter unwanted observations from your data or create new variables and summaries to visualize. In this tutorial, you will learn how to filter your data, including: How to use filter() to extract observations that pass a logical test How to write logical comparisons in R How to combine logical comparisons with Boolean operators How to handle missing values within comparisons The readings in this tutorial follow R for Data Science (http://r4ds.had.co.nz/), section 5.2. Continue

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Shiny Combines the computational power of R with the interactivity of the modern web. Powerful web framework.

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https://gallery.shinyapps.io/050-kmeans-example/ Iris k-means clustering X Variable Y Variable Cluster count 3 Kmeans example by Joe Cheng (http://www.rstudio.com/)  show with app function(input, output, session) { # Combine the selected variables into a new data frame selectedData <- reactive({ server.R ui.R Sepal.Length Sepal.Width

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https://gallery.shinyapps.io/082-word-cloud/ Word Cloud Choose a book: Change Minimum Frequency: Maximum Number of Words: 1 50 15 1 11 21 31 41 1 300 100 1 61 121 241 Word cloud by Fereshteh Karimeddini (http://www.rstudio.com/) A simple word cloud generator, based on  show with app # Text of the books downloaded from: # A Mid Summer Night's Dream: # http://www.gutenberg.org/cache/epub/2242/pg2242.txt global.R server.R ui.R A Mid Summer Night's Dream

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https://gallery.shinyapps.io/086-bus-dashboard/ Show Note: a route number can have several different trips, each with a different path. Only the most commonly- used path will be displayed on the map. Zoom to fit buses Northbound Southbound Eastbound Westbound Refresh interval Refresh now Source data updates every 30 seconds. 1 minute

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https://apps.garrickadenbuie.com/rstudioconf-2019/ 40 Tweets Today  39 Tweeters Today  2.16 Tweets/hr Today  56,006 rstudio::conf Likes  4,120 rstudio::conf Tweets  10,597 #rstats Tweets  Tweet Volume Tweets by Hour of Day Most Liked in 12 Hours

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http://www.dataseries.org/ TIDIED UP Switzerland's data series in one place Choose variable, e.g., GDP

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Where do I go for more information? - Cheatsheets - Books - rweekly.org - Forums - USCbiostats/software-dev

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Have a question? Google it https://www.google.com/

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https://rseek.org/

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https://rseek.org/

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Cheatsheets https://www.rstudio.com/resources/cheatsheets/

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Books https://bookdown.org/

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Books

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https://www.rweekly.org/

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https://community.rstudio.com/ https://stackoverflow.com/

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https://github.com/USCbiostats/software-dev