[PPT] - GET UP AND RUNNING TODAYS GOAL: GET ORIENTED TO RSTUDIO, MAKE A PowerPoint Presentation

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GET UP AND RUNNING

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TODAY’S GOAL:

GET ORIENTED TO RSTUDIO, MAKE A PROJECT FOLDER

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https://www.r-project.org https://rstudio.com

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SLIDE 8 >_

RStudio will be the control center for your R Projects

SLIDE 9 >_

Current Document

Console Objects

Files, Graphs, Help

SLIDE 10 > if (is.empty.model(mt)) { x <- NULL z <- list(coefficients = if (mlm) matrix(NA_real_, 0, ncol(y)) else numeric(), residuals = y, fitted.values = 0 * y, weights = w, rank = 0L, df.residual = if (!is.null(w)) sum(w != 0) else ny)

Drives R Produces Plots Generates Documents RStudio

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THE RIGHT FRAME OF MIND

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TYPE OUT YOUR

CODE BY HAND

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RSTUDIO AGAIN

SLIDE 14 install.packages("usethis", repos = "http://cran.rstudio.com")

Paper, Report, Analysis, Notes, etc, in RMarkdown

SLIDE 15 install.packages("usethis", repos = "http://cran.rstudio.com")

Console: Type or send code here, see results

SLIDE 16 install.packages("usethis", repos = "http://cran.rstudio.com")

Project files, Plots, Help

SLIDE 17 install.packages("usethis", repos = "http://cran.rstudio.com")

Inspect objects you create

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TASK:

CREATE A PROJECT FOR YOUR NOTES

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Use RMarkdown TO PRODUCE & REPRODUCE YOUR OWN WORK

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This is what we want to end up with: nicely formatted text, plots, and tables in an HTML, PDF,

r Word file
1. Lorem Ipsum

Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enimad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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In a Literate Programming approach to documents, chunks of code are processed and replaced with their output

library(ggplot2) tea <- rnorm(100) biscuits <- tea + rnorm(100, 0, 1.3) data <- data.frame(tea, biscuits) p <- ggplot(data, aes(x = tea, y = biscuits)) + geom_point() + geom_smooth(method = "lm") + labs(x = "Tea", y = "Biscuits") + theme_bw() print(p) # Lorem Ipsum Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do *eiusmod tempor* incididunt ut labore et dolore magna

aliqua. Ut enimad minim veniam, quis nostrud exercitation

ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint

ccaecat cupidatat non proident, sunt in culpa qui officia

deserunt mollit anim id est laborum.

This is what our file actually looks like: plain text, mixing words and chunks of code

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Markdown is a way to put formatting instructions in plain-text documents

# Header Plain text *italics* **bold** `verbatim` Footnote.[^1] [^1]: The footnote.

1. List
2. List
Bullet 1
Bullet 2

!" Subhead Markdown Output Header Plain text italics bold verbatim Footnote. The footnote.

1. List
2. List

° Bullet 1 ° Bullet 2 Subhead 1 1

Once the chunks of R Code have all been run, a Markdown Processor turns the bits of marked-up plain text into properly-formatted

utput in HTML, PDF, DOCX or
ther file types.

What you type What you end up with

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In a Literate Programming approach to documents, chunks of code are processed and replaced with their output

library(ggplot2) tea <- rnorm(100) biscuits <- tea + rnorm(100, 0, 1.3) data <- data.frame(tea, biscuits) p <- ggplot(data, aes(x = tea, y = biscuits)) + geom_point() + geom_smooth(method = "lm") + labs(x = "Tea", y = "Biscuits") + theme_bw() print(p) # Lorem Ipsum Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do *eiusmod tempor* incididunt ut labore et dolore magna

aliqua. Ut enimad minim veniam, quis nostrud exercitation

ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint

ccaecat cupidatat non proident, sunt in culpa qui officia

deserunt mollit anim id est laborum.

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1. Lorem Ipsum

Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enimad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

In a Literate Programming approach to documents, chunks of code are processed and replaced with their output

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An Rmd document lets you keep your code and notes together in plain text And produce good-looking

utput in a range of formats

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An Rmd document lets you keep your code and notes together in plain text And produce good-looking

utput in a range of formats

knit in R notes.Rmd # Report We can see this *relationship* in a scatterplot. As you can see, this plot looks pretty nice. Report We can see this relationship in a scatterplot. As you can see, this plot looks pretty nice. x y notes.html ```{r my-code} p !" ggplot(data, mapping) p + geom_point() ```

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An Rmd document lets you keep your code and notes together in plain text And produce good-looking

utput in a range of formats

knit in R notes.Rmd # Report We can see this *relationship* in a scatterplot. As you can see, this plot looks pretty nice. Report We can see this relationship in a scatterplot. As you can see, this plot looks pretty nice. x y notes.docx ```{r my-code} p !" ggplot(data, mapping) p + geom_point() ```

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Header section provides metadata and sets options

Code chunk

Text with Markdown formatting In RStudio, code chunks can be "played" one at a time Chunks are replaced by their

utput when the

document is made

Code chunks can have their

wn names and options

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RStudio will do all the work for you when it comes to processing your document—i.e., getting it from plain-text Rmd to HTML, Word, or PDF.

1. Lorem Ipsum

Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enimad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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In general, your code is what’s “real” in your project, not the objects you create.

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Consider not showing your

utput inline

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GETTING ORIENTED

SLIDE 33 library(tidyverse) Loading tidyverse: ggplot2 Loading tidyverse: tibble Loading tidyverse: tidyr Loading tidyverse: readr Loading tidyverse: purrr Loading tidyverse: dplyr

The Tidyverse

Draw graphs Nicer data tables Tidy your data Get data into R Cool functional programming stuff Action verbs for manipulating data library(socviz)

Course-Specific Library

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CODE YOU CAN TYPE AND RUN

## Inside chunks of code, lines beginning with ## the hash character are comments my_numbers <- c(1, 1, 4, 1, 1, 4, 1) my_numbers ## [1] 1 1 4 1 1 4 1

OUTPUT

What R Looks Like

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FOUR THINGS TO KNOW ABOUT R

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1: Everything has a Name

FALSE TRUE Inf for if break function

Some names are forbidden

my_numbers data p

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2. Everything is an Object

my_numbers <- c(1, 2, 3, 1, 3, 5, 25) > letters ## [1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" [20] "t" "u" "v" "w" "x" "y" "z"

You create objects by assigning a thing to a name

named thing "gets" this stuff

SLIDE 38 my_numbers <- c(1, 2, 3, 1, 3, 5, 25)

You create objects by assigning a thing to a name

The assignment operator performs the action of creating objects. Use a keyboard shortcut to type it:

ption - Mac

alt - Windows

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3. You do things with named objects

using functions and operators

my_numbers <- c(1, 2, 3, 1, 3, 5, 25)

named thing "gets" this stuff c() is a function that takes comma-separated numbers or strings and joins them together into a vector

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take arguments, perform actions, produce outputs

mean()

Functions have parentheses at the end of their name. This is where the inputs,

r arguments go.

mean(x = my_numbers)

Named argument. “Calculate the mean of what, please?” These names are internal to functions. “Take this object …”

Functions

SLIDE 41 mean(my_numbers)

If you just write the name of the input, R assigns it to the function’s arguments in order. Look at the function’s help page to see the order it expects its arguments.

take arguments, perform actions, produce outputs

Functions

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You can assign a function’s

utput to a named object

my_summary <- summary(my_numbers) my_sd <- sd(my_numbers) my_summary my_sd

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Objects you create exist until you overwrite or delete them

rm(my_numbers) my_numbers my_numbers <- c(1, 2, 3, 1, 3, 5, 25)

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Objects are of different classes

class(my_numbers) numeric character factor

Vectors

matrix data.frame tibble

Arrays

lm glm

Models

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Things to try on Objects

class(my_numbers) table(my_numbers) x <- c(my_numbers, 5) mean(c(my_numbers, my_numbers))

Notice that these are functions How do x and y differ?

y <- c(my_numbers, "hello")

Functions can be nested, and will be evaluated from the inside out.

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Some operators

+, -, *, /, ^

Arithmetic

<-

Assignment ("gets")

=

r

&, &&, |, ||, !

Logical

%*%, %in%, %>% Special <, >, <=, >=, ==, !=

Relational

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The pipe operator

mean(my_numbers) my_numbers %>% mean()

This will be very convenient later on

round(mean(my_numbers)) my_numbers %>% mean() %>% round()

"and then"

%>%

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4. R will be Frustrating

We’re going to be joining a lot of objects and functions together

ggplot(data = mpg, mapping = aes(x = displ, y = hwy)) + geom_point()

"+"

goes here

ggplot(data = mpg, mapping = aes(x = displ, y = hwy)) + geom_point()

not here

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4. R will be Frustrating

RStudio tries its best to help. Learn to attend to what it’s trying to tell you

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LET’S GO

SLIDE 51 library(gapminder) gapminder # A tibble: 1,704 x 6 country continent year lifeExp pop gdpPercap <fctr> <fctr> <int> <dbl> <int> <dbl> 1 Afghanistan Asia 1952 28.801 8425333 779.4453 2 Afghanistan Asia 1957 30.332 9240934 820.8530 3 Afghanistan Asia 1962 31.997 10267083 853.1007 4 Afghanistan Asia 1967 34.020 11537966 836.1971 5 Afghanistan Asia 1972 36.088 13079460 739.9811 6 Afghanistan Asia 1977 38.438 14880372 786.1134 7 Afghanistan Asia 1982 39.854 12881816 978.0114 8 Afghanistan Asia 1987 40.822 13867957 852.3959 9 Afghanistan Asia 1992 41.674 16317921 649.3414 10 Afghanistan Asia 1997 41.763 22227415 635.3414 # ... with 1,694 more rows

SLIDE 52 p + geom_point() p <- ggplot(data = gapminder, mapping = aes(x = gdpPercap, y = lifeExp)) p

Named thing gets … … the output of this function … … using these arguments Objects created by ggplot() are unusual in that you can “add” things to them, and they will work as though you wrote all the code at once.

SLIDE 53 p <- ggplot(data = gapminder, mapping = aes(x = gdpPercap, y = lifeExp)) p + geom_point()

SLIDE 54 40 60 80 30000 60000 90000 gdpPercap lifeExp

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WEEK

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1. Readings will be provided

in the Slack

3. Finish setting up your

notes.Rmd file. Use it to take notes on the reading

4. Questions or glitches with

R or RStudio: Ask in the Slack

2. Slides will be on the

Website

GET UP AND RUNNING TODAYS GOAL: GET ORIENTED TO RSTUDIO, MAKE A - - PowerPoint PPT Presentation

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WEEK