Week 1 Flashcards
1
Q
library()
A
- List of all packages installed on your computer
- displayed in R editor
2
Q
search()
A
List of all packages currently active on your computer
3
Q
install.packages(“< lib_name >”)
A
- package is downloaded from CRAN and installed on your computer
- also in Tools Menu (RStudio)
4
Q
library(“< lib_name >”)
A
- loads the library
- used after install.packages(_)
5
Q
library(help = “< lib_name >”)
A
package documentation listed in editor
6
Q
update.packages ()
A
- updates all packages
- also in Tools Menu (RStudio)
7
Q
detach(“ package:< lib_name> “, unload=TRUE)
A
- Package is removed
- Package can also be removed from the right hand side window
8
Q
Task
Clear the console
A
- Edit -> Clear Console
- Ctrl + L
9
Q
comments
A
- start with #
- single lines only
10
Q
run single command from script
A
- Ctrl + Enter
11
Q
index number
A
- first number displayed in [ ]
- indexes start at 1
12
Q
print(“string”)
A
- prints string and quotes
13
Q
assignment operator
A
- <-
- can also use =
14
Q
display variable value
A
type variable name in editor and execute
15
Q
concatenate vectors
A
c(x,y) = x values, y values
16
Q
multiple vectors subtraction
A
performs operation on values of same index
- x <- 5,5,5
- y <- 1,2,3
- x - y = 4,3,2
17
Q
vector multiplication
A
y * 3 = each value in y vector x 3
18
Q
table commands
dim(table_name)
A
- gives dimensions of table
- rows then columns
19
Q
summary(table_name)
A
- gives summary stats for each column
- min, 1st quart, median, mean, 3rd, quart, max
20
Q
head(table_name)
A
prints first 6 rows of table
21
Q
names(table_name)
A
prints column headers / names
22
Q
table( table_name $ column_name )
A
- makes a new table with the counts for each value type (new headers) in specified column
- eg. table(iris$species) = setosa 50 versicolor 50 virginica 50
23
Q
pie(table(table name $ table column)
A
- creates pie chart for counts of each value in specified table column
24
Q
pie(table(iris$Species ), col= purple”,”red”,”green”
A
assigns pie chart colors to each iris species in same order species are listed
25
variable names
| rules
- case-sensitive
- can't begin with number or symbol
- no blank spaces
- can use period (eg. abc.x)
26
vector creation
| methods (3)
1. Concatenate (c)
2. Sequence (seq)
3. Repeat (rep)
27
# vector creation
concatenate
- c( )
- eg. y <- c(2,3,5,6)
- x <- c(first = "alpha", second="beta", third="gamma")
28
# concatenate
order of restriction for conversion
(Least to most restrictive)
1. Strings
2. Numerics
3. True/False
29
repeat function
rep(...)
used to create vector with repeating pattern
- v = c(11,22,33)
- x = rep(v,3)
11 22 33 11 22 33 11 22 33
- gender = c("male","female")
- y = rep(gender,c(2,5))
"male" "male" "female" "female" "female" "female" "female"
30
vector value assignment
assigning nonexistent value to vector, matrix, array, or list expands structure to accomodate new value
- x < c(8,6,4)
- x[7] < 10
- x = 8 6 4 NA NA NA 10
31
# repeat function
array declaration
- n <- 10
- y < rep (0,n)
- y = 0 0 0 0 0 0 0 0 0 0
32
R Data Input
| Sources (5)
1. Text Files (eg. ASCII, XML, webscraping)
2. Statistical Packages (eg. SPSS, SAS, Stata)
3. Keyboard
4. Database Management Systems (eg. MySql, Oracle, Access)
5. Other (eg. Excel, NetCFD, HDF5)
33
# Import / Export
Flat Files
**Import**
- AHW < read.csv(“AHW_1.csv”, header=TRUE)
- weatherdata <-read.table (file="C:/work/DM1/weather.csv", header=TRUE, sep=",")
**Export**
write.table(z,"D t RDataFiles Output z.txt")
34
# Import / Expoort
Databases
**Import**
connection < dbConnect (driver, user, password, host, dbname
AHW < dbSendQuery (connection, “SELECT * FROM AHW")
**Export**
connnection <- dbConnect (driver, user, password, host,dbname
dbWriteTable (connnection , “AHW”, AHW)
35
# Import / Export
R objects
- **Import**: > load(‘AHW.Rdata')
- **Export**: > save(AHW, file= “New_AHW.Rdata")
36
# Import
Web
connection <- url (‘http://pace.sdsc.edu/sites/bootcamp/images/AHW_1.csv')
AHW <- read.csv(connection, header=TRUE)
37
How to enter data in R
| 5
1. **Sequential Data**: assignment operator and vector definition (x = 1:5)
2.** Non-sequential Data**: concatenation operator
3. **List Objects**
4. **Read a CSV**
5. **Structure**: provides info about data frame
38
ls()
displays list objects
eg. x = 5, y = 3
ls() = "x" "y"
39
Read data from a spreadsheet
| process
1. convert spreadsheet to .csv file
2. variable -< read.csv("Path")
- need forward slash or 2 back slashes in path
- example variable name: sn.csv
40
str(csv_variable)
- provides details of Data frame from csv file
-
41
# Data input
keyboard
| example
mydata <- data.frame (age=numeric(0), gender=character(0),
weight=numeric(0))
mydata <- edit( mydata)
42
Data Types
1. Vector (1 dimensional)
2. Matrix (2 dimensional)
3. Array (3 dimensional)
4. Data Frame
- Column can be different modes
5. List
- Vectors, matrix, arrays, data frames, lists
43
Data Frame
- More general than a matrix
- Different columns can contain different modes of data
- concatenate values for individual columns
variable <- data.frame(column1, column2, column3, etc)
44
Specifying Data Frame Elements
- patientdata [1:2] = all rows of 1st 2 data columns
- patientdata [ diabetes","status"]) = all rows of specified columns
- patientdata$age = all values in age column (without header)
