Intro to R

Question 1

Install packages

Answer 1

install.packages(“packagename”)

Question 2

Load packages

Answer 2

library(packagename)

Question 3

Set working directory

Answer 3

setwd(location)

Question 4

Load data from computer

Answer 4

read.csv(“filename”)

Question 5

Load pre-assigned dataset

Answer 5

data(“filename”)

Question 6

Select specific value

Answer 6

select(filename, row, column)

Question 7

Summary statistics

Answer 7

summary(datafile).

Question 8

See specific rows

Answer 8

head(datafile, #)
tail(datafile, #)

Question 9

Omit NA values

Answer 9

na.omit(datafile)

Question 10

Remove columns

Answer 10

dplyr::select(dataset, -contains(“colname”))

Question 11

Filter values

Answer 11

filter(datafile, col <= #)

Question 12

Histogram

Answer 12

hist(dataset$col)

Question 13

Create new column/mutate using a formula

Answer 13

dataset %>% mutate (newcolname= (formula))

Question 14

Determine if columns are identical

Answer 14

identical(dataset$col1, dataset$col2)

Question 15

Save data as CSV

Answer 15

write.csv(newname)

Question 16

returns the number of columns in the dataset

Answer 16

ncol(datafile)

Question 17

returns the number of rows in the dataset

Answer 17

nrow(datafile)

Question 18

returns the names of the columns

Answer 18

colnames(datafile)

Question 19

provides information about the data types of the columns

Answer 19

str(datafile)

Question 20

Replicability

Answer 20

the ability to recreate your results using a different dataset

Question 21

Reproducibility

Answer 21

the ability to recreate you results using the same dataset

Question 22

IDE

Answer 22

Integrated development environmen (r-studio)

Question 23

Packages

Answer 23

extensions of the r-lanuage that allow you to run additional functions

R comes with built-in functions, but if you want to do functions outside that pre-set, you can download packages

Question 24

Clean code

Answer 24

making your code easy to understand and consistent, and therefore reusable

Question 25

7 tenets of clean code

Answer 25

Meaningful Variable and Function Names: each name of the variable or function should convey a purpose, do not make it vague

Modularization: If the script is too long, break up so its easier to understand

Consistent Formatting: Choose a style and stick to it

Comments and Documentation: explain what and why you did

Avoid Magic Numbers and Hard Coding: Don’t use unexplained numeric values, assign them to a constant/a variable name

Avoid Duplicate Code.

The Single Responsibility Principle (SRP): Each script should have one clear purpose or responsibility