Lesson2 RStudio Basics

Question 1

console

Answer 1

lower left, with prompt to type commands

Question 2

workspace

Answer 2

upper right panel, shows history of commands

Question 3

R Markdown

Answer 3

Upper left panel, document

Question 4

Lower right panel

Answer 4

plots show here, browse files, access help, manage packages

Question 5

R Packages

Answer 5

Collections of R functions, data and compiled code in a well-defined format, we use statsr, dplyr, ggplot2

Question 6

Install package commands

Answer 6

install.packages and install_github

Question 7

Command for loading packages in working environment

Answer 7

library
e.g library(dplyr)
You only need to install package once but load each time you relaunch RStudio

Question 8

How to run commands from either Red file or console

Answer 8

-click on the green arrow of the code chunk in the R Markdown(Rmd) file, or
-highlight these lines, and hit the Run button, or
-type the code in the console

Question 9

command to load data

Answer 9

data()
eg. data(arbuthnot)

Question 10

objects

Answer 10

as you work with R, you will create a series of objects, sometimes you will load them with data command, sometimes you create them yourself as byproduct of a computation or analysis

Question 11

How to use dataviewer in the Environment

Answer 11

upper right window, click on name of data set that lists objects in your workspace
e.g. arbuthnot

Question 12

data frame

Answer 12

a kind of spreadsheet or table where R stores data

Question 13

dim() command

Answer 13

command for asking for dimension of data, eg. 82 rows and 3 columns

Question 14

names()

Answer 14

command for asking for variable names

Question 15

how is invoking R commands like math class

Answer 15

invoking R commands means supplying a function with some number of arguments, eg. such as a single argument of the name of a data frame

Question 16

up and down arrow keys at prompt

Answer 16

scroll through your previous commands

Question 17

R Markdown is solution for what problem

Answer 17

documenting your code

Question 18

Knit button on RStudio

Answer 18

type the code for the questions in the code chunks provided in the Rmd document and knit the document to see results

Question 19

$

Answer 19

Access the data in a single column of a data frame separately using a command eg. arbuthnot$boys
“go to the data frame that comes before me, and find the variable that comes after me.”

Question 20

vectors

Answer 20

most common data structure in R, one dimensional array of elements, R will print out a single variable vector with a a number added in brackets, along the left side to indicate locations within the vector, ordered by entry number

Question 21

recursive vector

Answer 21

a list is a recursive vector, a vector that can contain another vector or list in each of its elements

Question 22

or ##

Answer 22

comment out in R

Question 23

ggplot() function, what does it build and what is the format?

Answer 23

function to build plots
ggplot(data= arbuthnot, aes(x = year, y= girls)) + geom-point()

looks like a function, arguments separated by commas

1st argument = dataset
2nd provide the variables to the aesthetic elements of the plot e.g. the and y axes.
3rd use another layer, separated by a + to specify the geometric object for the plot, scatterplot is geom_point

Question 24

how to ask for help for a function

Answer 24

?ggplot
a help file will replace files in the lower right panel, with a new tab

Question 25

how to add vectors

Answer 25

use variable names and addition sign and R will compute all sums simultaneously eg arbuthnot$boys + arbuthnot$$girls

Question 26

how to save new vector

Answer 26

use piping operator %>%, takes the output of the current line and pipes it into the following line of code eg. arbuthnot <- arbuthnot %>% mutate(total = boys + girls)

Question 27

What does this piping code say in English? rbuthnot <- arbuthnot %>% mutate(total = boys + girls)

Answer 27

Take the arbuthnot dataset and pipe it into the mutate function. Using this mutate a new variable called total that is the sum of the variables called boys and girls. Then assign this new resulting dataset to the object called arbuthnot, i.e. overwrite the old arbuthnot dataset with the new one containing the new variable.

Question 28

what does >- symbol do?

Answer 28

assignment, taking the output of one line of code and saving it into an object in your workspace rbuthnot <- arbuthnot %>% mutate(total = boys + girls) in this example, you already have an object called arbuthnot, so this command updates that data set with the new mutated column

Question 29

How to make a line plot instead of a scatter plot

Answer 29

using geom_line() instead of geom_point() ggplot(data = arbuthnot, aes(x = year, y = total)) + geom_line()

Question 30

How to do both a scatter plot and a line plot?

Answer 30

List both ggplot(data = arbuthnot, aes(x = year, y = total)) + geom_line() + geom_point()

Question 31

How to use greater than, less than and equality symbols?

Answer 31

arbuthnot <- arbuthnot %>% mutate (more_boys = boys > girls) generates a column of true/false answers