###Code for Lecture 1

# this is a comment - R ignores it!

help(exp) #display help for file function in parantheses
?exp #display help for file function in parantheses
??”logistic regression” #search help files for phrase in quotes; quotes not needed for single words

### Basic Math
exp(1.5) ### calculate e to the 1.5 power
x=exp(1.5) ### make 'x' equal to exp(1.5)
x ### tell us what x is - Note that x is a scalar (single value)
x=2.718282^1.5 ### make x equal to e to the 1.5 power; ^ stands for power
x ### tell us what x is
y=log(x) ### make y equal to natural log of x
y ### tell us what y is
help(log) ### pull up the help file on log so we can figure out how to change the base
y=log(x,base=10) ###calculate log (base 10) of x, call it 'y'

###Vectors (lists of values)

x=c(1,2,3)) ### 'c' tells R you are making a list of values; also called a 'vector'
#### single value is a 'scalar'
x ### tell us what x is
x[2] ### tell us what the 2nd value of x is

exp(x) ### calculate exp to the power of each value in x; return a vector

###Fancy ways of making vectors
x=(0:100) ###create a vector of values from 0 to 100 inclusive, call it x
sequence=(0:100) ###create a vector of values from 0 to 100 inclusive, call is sequence
sequence ### tell us what 'sequence' is

sequenceByTen=(0:100)*10 ### create a vector from 0 to 1000 by 10, call it 'sequenceByTen'

###Functions – what they are and how they are used
###a function is any command that takes arguments (in parentheses) and returns results based on a calculation
help(seq) ### display the help file for the function 'seq'
x=seq(0,1000,10) ### create a vector from 0 to 1000 by 10, call it 'x' 
y=rep(c(1,2,3,4,5),20) ### create a vector of values 1,2,3,4,5 repeating 20 times; call it 'y'

###Make your own functions
expTest=function(x){   ###create a function to calculate e to the power of x - bracket starts the calculations
	y=2.718282^x   ###run a calculation using the argument x
	return(y) #### return the answer of the calculation
} ###bracket ends the calculations
expTest(1.5) ###run the expTest function


###Matrices
year=c(1800,1850,1900,1950,2000) ### create a vector called 'year' with 5 values
carbon=c(8,54,534,1630,6611) ###create a vector called 'carbon' with 5 values
### A matrix is a block of numbers with multiple rows and columns
datum=data.frame(year=year,carbon=carbon) #create a matrix with two columns (year and carbon) and 5 rows
datum #### show us the matrix 'datum'
datum[2] ### show just the second column of 'datum'
datum$carbon ### show just second column of 'datum' - the one named 'carbon'



###Easy summaries/analysis of data

summary(datum) ###give mean and quartile of datum
mean(datum)
var(datum) ###variance-covariance matrix)
sd(datum)
plot(datum) ###note that x-axis will be first variable in matrix
Plot(datum$year,plot$carbon)
Plot(datum$year,datum$carbon,type=’l’) #### plot a line graph

#### ways to save work in R
#### can create a 'new script', run the script and/or save the script for later
#### To save "console":

##### 'file', 'save workspace' saves the various objects
##### 'file', 'save history' saves commands that were run, but not the output
##### 'file', 'save file' saves all the text in the console including both commands and output



### Importing data

### Don't forget to change the directory first!!!!

### Don't call your data 'data' - that word already has a meaning in R

help(read.csv)

datum=read.csv("example.csv") ### creates a data frame named datum from imported csv file

### check data was imported properly

names(datum) ### column headers of data file
head(datum) ### column headers of data file plus first 6 rows of data 
head(datum,10) ### number of rows of data can be changed

summary(datum) ### summary statistics for datum

### alternatively:

datum=read.csv(file.choose())