[Ӌһ] Basic r programming final0918
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This document provides an introduction to R for econometric analysis. It discusses installing R and RStudio, why R is useful for data science and analysis tasks, basic R syntax like variables, functions, modules and packages. It also demonstrates some R code examples and covers flow control, objects, operators, sampling, common functions and basic graphics. The document is intended to give students a quick start in learning the R programming language.
![Function ʽ
like a collection of computation
Ҳf, һ\
do some computation
a function:length
[1,2,3,4] 4
return
# R code
a = c(1,2,3,4)
result = length(a)
result
input](https://image.slidesharecdn.com/basicrprogramming-final0918-140320003136-phpapp02/85/Basic-r-programming-final0918-18-320.jpg)
![Function ʽ
do some computation
function: mean
[1,2,3,4] 2.5
return
output
Built-in
self-defined
(package)
# Built-in
data = 1:4
output= mean(data)
data
# Self-defined
MyMean = function(data){
total = sum(data)
len = length(data)
result = total / len
return(result)
}
data = 1:4
output = MyMean(data)
input](https://image.slidesharecdn.com/basicrprogramming-final0918-140320003136-phpapp02/85/Basic-r-programming-final0918-19-320.jpg)
![Module ģM
like a collection of function
[example] data_preprocess.R](https://image.slidesharecdn.com/basicrprogramming-final0918-140320003136-phpapp02/85/Basic-r-programming-final0918-20-320.jpg)
![Flow Control
#3 For
For( i in 1: 3){
statement (i)
}
# R code
data = rnorm(100) #Ę˜ʳBг
100ӱc
mu = mean(data)
mu > 0
while (mu > 0){
print("mean is greater than 0")
# mu = "tested"
}
# loFޒȦԇwhileȵ]
_
i = 1 , һ
i = 2 ,وһ
i = 3 ,وһ
YޒȦ](https://image.slidesharecdn.com/basicrprogramming-final0918-140320003136-phpapp02/85/Basic-r-programming-final0918-26-320.jpg)
[Ӌһ] Basic r programming final0918
- 1. Econometric Theory (I) A Quick Introduction to R Yen, Chia-Yi NTU Sep 18, 2014
- 2. TA info x T о209 о yen.chiayi@gmail.com r01323019@ntu.edu.tw R user : Taiwan R user group
- 3. Installatioan Having trouble? http://homepage.ntu.edu.tw/~ckuan/courses.html (prof. Chung-Ming Kuan s website) optional, but believe me its super charming! R Engine http://cran.rstudio.com/ R IDE: Rstudio http://www.rstudio.com/ide/download/desktop
- 4. a FREE software environment for statistical computing and graphics Ris .
- 5. Why R Data Science is Hot ! ʹõĽyӋZ Y # \ # yӋ # cC++
- 6. Software used in data analysis competitions in 2011. source :http://r4stats.com/articles/popularity/ http://blog.revolutionanalytics.com/2012/08/r-language- popularity-for-data-mining.html
- 8. Why R: demo
- 9. Why Rdemo
- 10. R Engine
- 12. a quick look at R Expression Variable (׃) Function (ʽ) Module (ģM) Package () calculation numeric, string, boolean vector,matrix, data.frame built-in, package, self-defined # Input / Output (I/O) # Linear Algebra # Regression
- 13. Lets Demo ! Open "0918_firstR.R in Rstudio. Whats the difference between... Interactive mode v.s. Script mode
- 14. Expression # 䌍ӋC... # TRUE FALSE # R code 1+1 (1+1)^4 ((1+1)^4-2)%%3 sin(((1+1)^4-2)%%3) # R code 2<3 2==3 2!=3
- 15. data Variable ׃ like a container that stores # ע: "=" & "==" ܲͬ # "="oֵ (assign) # "==": (equal to) numeric string boolean # R code x = 3 # numeric ֵ x = "Hi, Everyone ~~" # string ִ x = 'Hi, Everyone ~~' # һҪ̖. x = TRUE # boolean ֵ x = T # һҪ x = 2<3
- 16. data Variable ׃ like a container that stores vector matrix data.frame etc. vec mat
- 17. Variable ׃ 1 2 3 4 # R code # vector a = c(1,2,3,4) # numeric vector ֵ b = c("1", "2", "3","4") # string vector ִ c = c( T, F, T, T) # boolean vector # matrix d = matrix(a, nrow=2, ncol=2) dim(a) = c(2,2) # data.frame e = data.frame(string = b, booling = c) #it can store different type data 1 3 2 4 1 T 2 F 3 T 4 F numeric vector numeric matrix data.frame
- 18. Function ʽ like a collection of computation Ҳf, һ\ do some computation a function:length [1,2,3,4] 4 return # R code a = c(1,2,3,4) result = length(a) result input
- 19. Function ʽ do some computation function: mean [1,2,3,4] 2.5 return output Built-in self-defined (package) # Built-in data = 1:4 output= mean(data) data # Self-defined MyMean = function(data){ total = sum(data) len = length(data) result = total / len return(result) } data = 1:4 output = MyMean(data) input
- 20. Module ģM like a collection of function [example] data_preprocess.R
- 21. Package you can expand your built-in function by installing a packages like a collection of module
- 22. Package how to use PACKAGES ? # R code x = 1:10 # OxS y = sin(3*x) # OyS plot(x,y) # ԭRAOĮDʽ # ˮ^ƯĈD.... install.packages(ggplot2) # ggplot2@ĹپWdC #̖DZҪ library(ggplot2) # ıC load @ݳʽae qplot(x,y) # ʹ ggplot2e挑õĺʽ qplot
- 23. eĺ... Help & Google # R code help(mean) ?mean example(mean)
- 24. Flow Control #1 if if (expression){ statement } # R code data = rnorm(100) #Ę˜ʳBг 100ӱc mu = mean(data) mu > 0 if ( mu > 0 ){ print("mean is greater than 0") }else{ print("mean is less than 0") } ɜyTRUE, ͈дȔ t
- 25. Flow Control #2 while while (expression){ statement } # R code for ( i in 1:3){ data = rnorm(i) print(data) } ֻҪɜyTRUE, дȔ t
- 26. Flow Control #3 For For( i in 1: 3){ statement (i) } # R code data = rnorm(100) #Ę˜ʳBг 100ӱc mu = mean(data) mu > 0 while (mu > 0){ print("mean is greater than 0") # mu = "tested" } # loFޒȦԇwhileȵ] _ i = 1 , һ i = 2 ,وһ i = 3 ,وһ YޒȦ
- 27. Homework (optional) Code School http://tryr.codeschool.com DataMind http://www.datamind.org/#/
- 28. Thanks for your listening :)
- 34. Appendix: Basic Graphics (1)
- 35. Appendix: Basic Graphics (2)