# R Basics
## Basic Objects
### Vectors (Classes)
| Type | Example |
| --------- | --------------- |
| Logical | TRUE, FALSE |
| Numeric | 1, 55, 999 |
| Integer | 1L, 32L, 0L |
| Complex | 2 + 3i |
| Character | "great", "23.4" |
Creating a vector & print statement example
```r
apple <- c('red','green','yellow')
print(apple)
# Get the class of the vector
print(class(apple))
```
Output:
```r
"red" "green" "yellow"
"character"
```
### Anchors
Anchor
Special Character
Example
Beginning of line
^
^New
End of line
\\$
y$
Beginning of string
\\A
\\AHello
End of string
\\Z or \\z
End\\Z
### Lists
Contain many different types of elements inside
```r
# Create a list.
list1 <- list(c(2,5,3),21.3)
# Print the list.
print(list1)
```
Output:
```r
[[1]]
2 5 3
[[2]]
21.3
```
### Matrices
Two-dimensional rectangular data set
```r
M = matrix( c('a','a','b','b','c','c'), nrow = 2, ncol = 3, byrow = TRUE)
print(M)
```
Output:
```r
[,1] [,2] [,3]
[1,] "a" "a" "b"
[2,] "b" "c" "c"
```
### Arrays
Multi-dimensional data set
```r
a <- array(c('a','b'),dim = c(4,4,2))
print(a)
```
Output:
```r
, , 1
[,1] [,2] [,3] [,4]
[1,] "a" "a" "a" "a"
[2,] "b" "b" "b" "b"
[3,] "a" "a" "a" "a"
[4,] "b" "b" "b" "b"
, , 2
[,1] [,2] [,3] [,4]
[1,] "a" "a" "a" "a"
[2,] "b" "b" "b" "b"
[3,] "a" "a" "a" "a"
[4,] "b" "b" "b" "b"
```
### Factors
Stores the vector along with the distinct values of the elements in the vector as labels
```r
apple <- c('red','green','yellow')
factor_apple <- factor(apple)
print(factor_apple)
```
Output:
```r
red green yellow
Levels: green red yellow
```
### Data Frames
Tabular data objects
```r
# Create the data frame.
BMI <- data.frame(
gender = c('Male', 'Female','Female'),
height = c(182, 141.5, 165),
weight = c(101,95, 88),
Age = c(35,43,22)
)
print(BMI)
```
Output:
```r
gender height weight Age
1 Male 182.0 101 35
2 Female 141.5 95 43
3 Female 165.0 88 22
```
## Loops
### Repeat Loop
```r
repeat {
commands
if(condition) {
break
}
}
```
### While Loop
```r
while (test_expression) {
statement
}
```
### For Loop
```r
while (test_expression) {
statement
}
```
## Working with Data
### Useful Packages
| Tasks | Lists |
| --------------- | ------------------------------------- |
| Load data | utils, openxlsx, foreign, haven |
| Manipulate data | tidyverse, dplyr,tidyr |
| Visualize data | ggplot2, lattice, plotly |
| Modeling | 2 + 3i |
| Character | glmnet, randomForest, caret, survival |
### Import Data
```r
#CSV
df <- read.csv("c:/data.csv", header = T)
#Excel
df <- read.xlsx("c:/data.xlsx")
```
For the following examples, use package called datasets
### Data Exploration
Use dataset called mtcars from package datasets
* str(data): gives a quick overview of the rows and columns of the dataset.
```r
import Pkg; Pkg.add("RCall")
import Pkg; Pkg.add("RDatasets")
using RCall
using RDatasets
mtcars = dataset("datasets","mtcars");
@rput mtcars
R"str(mtcars)"
```
Output:
```r
e[?25le[2Ke[?25hUnable to automatically install 'Zlib' from '/home/runner/.julia/packages/Zlib_jll/BGVLi/Artifacts.toml'
```
* head(data,n) and tail(data,n)
head(): Top n elements
tail(): Bottom n elements
```r
@rput mtcars
R"print(head(mtcars, n = 3))"
R"print(tail(mtcars, n = 3))"
```
Output:
```r
LoadError: UndefVarError: @rput not defined
in expression starting at none:1
```
### Descriptive Statistics
* summary(data): gives descriptive statistics for each variable
Common Functions
| Tasks | Functions |
| ------------------- | ---------- |
| Mean | mean() |
| Standard deviation | sd() |
| Variance | var() |
| Minimum | min() |
| Maximum | max() |
| Median | median() |
| Range of values | range() |
| Sample quantiles | quantile() |
| Interquartile range | IQR() |
#### **Case of missing values**
* na.rm = T
```r
@rput mtcars
R"print(mean(mtcars$MPG, na.rm = T))"
```
Output:
```r
LoadError: UndefVarError: @rput not defined
in expression starting at none:1
```
### Basic Plots
* plot()
```r
using RCall
using RDatasets
mtcars = dataset("datasets","mtcars");
@rput mtcars
R"
png('plot2.png')
plot(mtcars$Disp, mtcars$DRat)
dev.off()
"
```
* barplot()
```r
R"
png('barplot2.png')
barplot(mtcars$Cyl,main = 'Number of Cylinders',xlab = 'cyl', col='blue',horiz = FALSE)
dev.off()
"
```
Output:
* histogram()
```r
R"
png('histogram.png')
hist(mtcars$Disp,main = 'Displacement (cu.in.)',xlab = 'disp', col='red')
dev.off()
"
```
Output:
* boxplot()
```r
using RCall
using RDatasets
mtcars = dataset("datasets","mtcars");
@rput mtcars
R"
png('boxplot2.png')
boxplot(mtcars$Disp)
dev.off()
"
```
Output:
* qqplot() or qqnorm(): check whether the data is normally distributed
* qqline(): adds a reference line
```r
using RCall
using RDatasets
mtcars = dataset("datasets","mtcars");
@rput mtcars
R"
png('qqnorm.png')
qqnorm(mtcars$Disp)
qqline(mtcars$Disp)
dev.off()
"
```
Output:
```r
ArgumentError: Package RCall not found in current path:
- Run `import Pkg; Pkg.add("RCall")` to install the RCall package.
```
## Statistical Analysis
| Analysis | Continuous Outcome(Y) | Binary Outcome(Y) |
| -------------------- | --------------------- | ----------------- |
| Correlation Analysis | | |
| X: Continuous | cor.test() | t.test() |
| X: Categorical | t.test(), ANOVA() | chisq.test() |
| Regression Model | lm() | glm() |
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