├── .gitignore ├── assignment ├── HW04_SamplePdf.pdf ├── README.md ├── 03-week4.md ├── 01-week2.md ├── 02-week3.md └── 04-week8.md ├── datasets ├── StudentParents.csv ├── Time.csv ├── Hotels.csv ├── products_original.csv ├── products_clean.csv ├── Marvels.csv ├── Mutual-NoLoad.csv ├── Mutual-Load.csv ├── survey214_v1.csv ├── Survey_INT214.csv ├── SAT_original.csv └── SAT_2012.csv ├── files ├── K02-starwars.R ├── 04-explore02.R ├── 06-DataViz.R ├── 02-Basic.R ├── SampleRDoc.Rmd ├── 03-explore01.R ├── K01-Assignment1.R ├── 07-HypoTesting.R ├── K03-SAT_Workshop.R └── 05-clean.R ├── README.md └── workshop ├── 01-intro-R.md ├── 09-Workshop2.md ├── 06-Workshop1.md ├── 02-Basic-R.md ├── Summary.md ├── 07-DataViz.md ├── 03-Explore-01.md ├── 04-Explore-02.md ├── 08-HypoTesting.md └── 05-Cleaning.md /.gitignore: -------------------------------------------------------------------------------- 1 | files/S0**.R 2 | files/.RData 3 | files/.Rhistory 4 | files/S0**.Rmd -------------------------------------------------------------------------------- /assignment/HW04_SamplePdf.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/safesit23/INT214-Statistics/HEAD/assignment/HW04_SamplePdf.pdf -------------------------------------------------------------------------------- /datasets/StudentParents.csv: -------------------------------------------------------------------------------- 1 | College,High School 2 | 485,442 3 | 534,580 4 | 650,479 5 | 554,486 6 | 550,528 7 | 572,524 8 | 497,492 9 | 592,478 10 | 487,425 11 | 533,485 12 | 526,390 13 | 410,535 14 | 515, 15 | 578, 16 | 448, 17 | 469, -------------------------------------------------------------------------------- /datasets/Time.csv: -------------------------------------------------------------------------------- 1 | Time 2 | 17 3 | 11 4 | 12 5 | 23 6 | 20 7 | 23 8 | 15 9 | 16 10 | 23 11 | 22 12 | 18 13 | 23 14 | 25 15 | 14 16 | 12 17 | 12 18 | 20 19 | 18 20 | 12 21 | 19 22 | 11 23 | 11 24 | 20 25 | 21 26 | 11 27 | 18 28 | 14 29 | 13 30 | 13 31 | 19 32 | 16 33 | 10 34 | 22 35 | 18 36 | 23 -------------------------------------------------------------------------------- /datasets/Hotels.csv: -------------------------------------------------------------------------------- 1 | City,RateperNight 2 | Atlanta,163 3 | Boston,177 4 | Chicago,166 5 | Cleveland,126 6 | Dallas,123 7 | Denver,120 8 | Detroit,144 9 | Houston,173 10 | Los Angeles,160 11 | Miami,192 12 | Minneapolis,125 13 | New Orleans,167 14 | New York,245 15 | Orlando,146 16 | Phoenix,139 17 | Pittsburgh,134 18 | San Francisco,167 19 | Seattle,162 20 | St. Louis,145 21 | Washington D.C.,207 22 | -------------------------------------------------------------------------------- /assignment/README.md: -------------------------------------------------------------------------------- 1 | # Assignment INT214 Statistics for Information Technology 2 | ## Assignments/ Homework 3 | 4 | - [Assignment 1: Individual](01-week2.md) (Week 2: 16 Aug, 20 Aug) 5 | - [Assignment 2: Group](02-week3.md) (Week 3: 23 Aug, 27 Aug) 6 | - [Assignment 3: Group](03-week4.md) (Week 4: 30 Aug, 3 Sep) 7 | - [Assignment 4: Individual](04-week8.md) (Week 8: 11 Oct, 15 Oct) 8 | 9 | ## Project 10 | About's project assignment, we will use this repository to explain about term assignment: 11 | https://github.com/sit-2021-int214/int214-project 12 | -------------------------------------------------------------------------------- /datasets/products_original.csv: -------------------------------------------------------------------------------- 1 | id,name,gender,price,sold 2 | E436507,Japanese seven herbs of fall Open Collar Short Sleeve Shirt,MEN,THB990,100 3 | E422969,DRY-EX Crew Neck Short Sleeve T-Shirt,MEN,THB 590,59 4 | E441012,3D Knit Cotton Crew Neck Sweater Half Sleeve,WOMEN,THB 990,10 5 | E419434,Stretch Wool Slim Fit Jacket,MEN,"THB 4,990",5 6 | E441490,Mickey Photo Days UT,KIDS,THB 390,58 7 | E422969,DRY-EX Crew Neck Short Sleeve T-Shirt,MEN,THB 590,59 8 | E442292,AIRism Low Rise Boxer Briefs,MEN,THB 390,250 9 | E439016,Regular Socks 3 Pairs (Slub Ribbed),WOMEN,THB 390,200 10 | E439016,Regular Socks 3 Pairs (Slub Ribbed),WOMEN,THB 390,200 11 | E443301,Disney Winnie the Pooh Long Sleeve One Piece Outfit,BABY,THB 390, 150 -------------------------------------------------------------------------------- /datasets/products_clean.csv: -------------------------------------------------------------------------------- 1 | id,name,type,price,sold,rating 2 | E436507,Japanese seven herbs of fall Open Collar Short Sleeve Shirt,MEN,990,100,4 3 | E422969,DRY-EX Crew Neck Short Sleeve T-Shirt,MEN,590,59,3.5 4 | E441012,3D Knit Cotton Crew Neck Sweater Half Sleeve,WOMEN,990,10,4.4 5 | E419434,Stretch Wool Slim Fit Jacket,MEN,4990,5,4.5 6 | E441490,Mickey Photo Days UT,KIDS,390,58,5 7 | E442292,AIRism Low Rise Boxer Briefs,MEN,390,250,5 8 | E439016,Regular Socks 3 Pairs (Slub Ribbed),WOMEN,390,200,3 9 | E443301,Disney Winnie the Pooh Long Sleeve One Piece Outfit,BABY,390,150,4.5 10 | E433695,Magic For All Icons UT (Short Sleeve Graphic T-Shirt),MEN,390,100,4 11 | E434366,BABIES TODDLER Dry Pajamas Short Sleeve,BABY,390,30,3.5 -------------------------------------------------------------------------------- /datasets/Marvels.csv: -------------------------------------------------------------------------------- 1 | names,years 2 | Iron Man,2008 3 | The Incredible Hulk,2008 4 | Iron Man 2,2010 5 | Thor,2011 6 | Captain America: The First Avenger,2011 7 | The Avengers,2012 8 | Iron Man 3,2013 9 | Thor: The Dark World,2013 10 | Captain America: The Winter Soldier,2014 11 | Guardians of the Galaxy,2014 12 | Avengers: Age of Ultron,2015 13 | Ant-Man,2015 14 | Captain America: Civil War,2016 15 | Doctor Strange,2016 16 | Guardians of the Galaxy 2,2017 17 | Spider-Man: Homecoming,2017 18 | Thor: Ragnarok,2017 19 | Black Panther,2017 20 | Avengers: Infinity War,2018 21 | Ant-Man and the Wasp,2018 22 | Captain Marvel,2019 23 | Avengers: Endgame,2019 24 | Spider-Man: Far From Home,2019 25 | WandaVision,2021 26 | Falcon and the Winter Soldier,2021 27 | Loki,2021 28 | Black Widow,2021 29 | Shang-Chi and the Legend of the Ten Rings,2021 30 | Eternals,2021 31 | Hawkeye,2021 32 | Spider-Man: No Way Home,2021 -------------------------------------------------------------------------------- /datasets/Mutual-NoLoad.csv: -------------------------------------------------------------------------------- 1 | MutualFunds,Return 2 | Amana Income Fund,13.24 3 | Berger One Hundred,12.13 4 | Columbia International Stock,12.17 5 | Dodge & Cox Balanced,16.06 6 | Evergreen Fund,17.61 7 | Fidelity Fund,20.61 8 | Forthis Advtg Cap App,13.38 9 | Founders Blue Chip Fund,17.15 10 | Goldman Core Fixed Income,10.38 11 | Heartland Value,18.15 12 | Janus Fund,15.82 13 | Manstay Cap Appriciation,17.29 14 | Merrill Spec Value,16.42 15 | Mutual Beacon,19.49 16 | Oberweis Emerging Growth,11.06 17 | Paine Webber Growth & Income,13.89 18 | Pimco Total Return,8.43 19 | Prudential Equity,18.29 20 | Putnam Growth & Income,17.8 21 | Royce FD Micro-Cap,17.05 22 | Scudder Development,12.8 23 | Smith Barney Appreciation,15.09 24 | Stein Roe Capital Oppty,19.7 25 | T Rowe Price Balanced,13.57 26 | Thompson Plumb Growth,18.58 27 | USAA Growth & Tax Strat,11.89 28 | Vanguard Equity Income,19 29 | Vanguard Windsor,20.71 30 | Vontobel Intl Equity,13.56 31 | Weith Value,19.82 -------------------------------------------------------------------------------- /datasets/Mutual-Load.csv: -------------------------------------------------------------------------------- 1 | MutualFunds,Return 2 | American National Growth,15.51 3 | Arch Small Cap Equity,14.57 4 | Bartlett Cap Basic,17.73 5 | Calvert World International,10.31 6 | Colonial Fund A,16.23 7 | Common Sense Growth,16.04 8 | Corefund Core Equity,18.77 9 | Davis Convert Seurities,18.21 10 | Deleware Small Cap,17.27 11 | Dreyfus Premium Value,11.95 12 | Federated Stocks & Bonds,13.81 13 | First Invest FD for Income,12.44 14 | Flag Inv Emerging Growth,15.39 15 | Fortis Equity Capital,13.46 16 | FPA Capital,23.66 17 | Franklin STR GL UT,17.38 18 | Gabelli Value Fund,22.45 19 | IDS New Dimensions,18.38 20 | John Hancock Growth & Income,18.06 21 | Lord Abbett Dev Growth,22.75 22 | Merrill Basic Value,20.35 23 | MFS World Tot Return,13.09 24 | New England Growth Opp,18.16 25 | Oppenhmr Quest Small Cap,14.47 26 | Phoenix Worldwide,15.78 27 | Princor Bond,8.4 28 | Stagecoach Disd Income,16.52 29 | United Contl Income,12.59 30 | Victory OH Regional,18.24 31 | Zweig SR TR Apprec,14.8 -------------------------------------------------------------------------------- /assignment/03-week4.md: -------------------------------------------------------------------------------- 1 | # Assignment 3 (Group): Explore Data with dpylr 2 | 3 | From week 4 that you have using `dpylr` packages and learn from self learning activity. I want you to review and improvement your group assigment #2. Rewrite your function by using `dpylr` at least 5 topics (from 2 datasets). Your group can add new topics to reach 5 topics. 4 | 5 | จากการเรียนรู้ในสัปดาห์ที่ 4 ที่ได้เรียนรู้ใช้ `dpylr` packages และการเรียนรู้ด้วยตนเอง อยากให้ใช้ไปรีวิวและปรับปรุงงานจาก Assignment ครั้งที่ 2 โดยให้เขียน function ใหม่โดยใช้ `dpylr` packages จาก 2 ชุดข้อมูลรวมกันอย่างน้อย 5 หัวข้อ ซึ่งหากของเดิมอันไหนที่ปรับไม่ได้สามารถเพิ่มหัวข้อใหม่เข้าไปได้ 6 | 7 | For example: 8 | 9 | ``` 10 | min(cats$Hwt) 11 | 12 | # Using dplyr 13 | cats %>% dplyr::select(Hwt) %>% min() 14 | ``` 15 | 16 | \*\*ประโยคสรุปจะต้องเป็นประโยคใจความสมบูรณ์เช่น จากกลุ่มตัวอย่างแมวพบว่าหัวใจของแมวมีน้ำหนักน้อยสุดอยู่ที่ 6.3 กรัม 17 | 18 | ## How to send: 19 | 20 | 1. Create new file named `HW3_groupid.md` Ex. `HW3_001.md` 21 | 2. Push to your group repository in folder assignment 22 | 3. Send file link in LEB2 to submit (It help you to check that your group have done this assignment) 23 | -------------------------------------------------------------------------------- /files/K02-starwars.R: -------------------------------------------------------------------------------- 1 | library(dplyr) 2 | #1. Find a list of name and height who is the first 12 tallest star wars characters. 3 | starwars %>% dplyr::select(name,height) %>% arrange(desc(height)) %>% head(12) 4 | 5 | #2. Finding name of star wars characters who is height equal 202. 6 | starwars %>% filter(height=="202") %>% dplyr::select(name) 7 | 8 | #3. How many star wars characters who has blue eye but not human species ? 9 | starwars %>% filter(eye_color=="blue",!(species=="Human")) %>% count() 10 | 11 | #4. From question 3, how many characters in each species ? 12 | starwars %>% group_by(species) %>% filter(eye_color=="blue",!(species=="Human")) %>% count() 13 | 14 | #5. Finding average height and mass of each species then show only 10 species 15 | # that have average height by descending order. 16 | starwars %>% group_by(species) %>% 17 | summarise(height=mean(height,na.rm = T),mass=mean(mass,na.rm = T)) %>% 18 | arrange(desc(height))%>% head(10) 19 | 20 | 21 | #6. From question 5, using `mutate()` to create new column `BMI` and calculate BMI 22 | # and order by BMI in descending order. 23 | starwars %>% group_by(species) %>% 24 | summarise(height=mean(height,na.rm = T),mass=mean(mass,na.rm = T)) %>% 25 | mutate(BMI = mass / ((height/100)^2)) %>% 26 | arrange(desc(BMI)) %>% 27 | head(10) -------------------------------------------------------------------------------- /files/04-explore02.R: -------------------------------------------------------------------------------- 1 | library(dplyr) 2 | glimpse(mtcars) 3 | 4 | # Import datasets from CSV 5 | Hotels <- read.csv("https://raw.githubusercontent.com/safesit23/INT214-Statistics/main/datasets/Hotels.csv") 6 | 7 | # Sample 1: head() 8 | head(Hotels,9) 9 | Hotels %>% head(9) %>% tail(1) 10 | Hotels %>% tail(1) 11 | 12 | # Sample 2: mean() 13 | mean(Hotels$RateperNight) 14 | Hotels$RateperNight %>% mean() 15 | 16 | str(Hotels) 17 | 18 | Hotels <- as_tibble(Hotels) 19 | str(Hotels) 20 | glimpse(Hotels) 21 | 22 | #Starwar 23 | glimpse(starwars) 24 | # MASS is DBL --> double 25 | 26 | starwars$height %>% 27 | mean(na.rm=T) 28 | 29 | # Topic 2 Data Manipulation 30 | # Select 31 | starwars %>% select(-height,-gender) 32 | # Filter 33 | starwars %>% filter(sex == "male") 34 | starwars %>% filter(!(sex == "male")) 35 | starwars %>% filter(sex == "male" | skin_color == "light") # or 36 | starwars %>% filter(sex == "male",skin_color == "light") # and 37 | #Summarise 38 | starwars %>% summarise(avg_height = mean(height, na.rm = TRUE), 39 | max_height = max(height, na.rm = TRUE)) 40 | 41 | # Combining 42 | # Case 1 :correct 43 | starwars %>% select(name,height,mass, skin_color) %>% 44 | filter(skin_color=="light") 45 | #case 2: error 46 | starwars %>% select(name,height,mass) %>% 47 | filter(skin_color=="light") 48 | #case 3: 49 | starwars %>% 50 | filter(skin_color=="light") %>% 51 | select(name,height,mass) 52 | 53 | 54 | 55 | -------------------------------------------------------------------------------- /files/06-DataViz.R: -------------------------------------------------------------------------------- 1 | library(dplyr) 2 | library(readr) 3 | 4 | # Base R 5 | hist(starwars$height) 6 | plot(x=starwars$height, y=starwars$mass) 7 | 8 | # Load data 9 | Marvels <- read_csv("https://raw.githubusercontent.com/safesit23/INT214-Statistics/main/datasets/Marvels.csv") 10 | 11 | # Set data 12 | count_marvel <-table(Marvels$years) 13 | 14 | count_marvel 15 | 16 | # Create graph 17 | barplot(count_marvel) 18 | 19 | barplot(count_marvel, 20 | main = "Number of Released Marvel Movies", # Title of graphs 21 | xlab = "Year Released", # X-Axis Title 22 | ylab = "Number of Movies", # Y-Axis Title 23 | ) 24 | 25 | library(ggplot2) 26 | ## Marvel Dataset - Bar Chart 27 | #Step 1 28 | ggplot(Marvels,aes(x=years)) + geom_bar() 29 | #Step 2-1: Save to object 30 | marvel_plot <- ggplot(Marvels,aes(x=years)) + geom_bar() 31 | #Step 2-2: Adding component 32 | marvel_plot + ggtitle("Number of Released Marvel Movies") + 33 | xlab("Year Released") + ylab("Number of Movies") 34 | 35 | #2-2: Example 2: Scatter Plot 36 | starwars %>% filter(mass>1000) 37 | 38 | starwars %>% ggplot(aes(x=height,y=mass))+geom_point() 39 | 40 | scat_plot <- starwars %>% filter(mass<500) %>% ggplot(aes(x=height,y=mass))+ 41 | geom_point(aes(color=gender)) 42 | scat_plot 43 | 44 | scat_plot+geom_smooth() #default value - loess 45 | scat_plot+geom_smooth(method="lm") #linear model 46 | 47 | # 3: Histogram 48 | starwars %>% ggplot(aes(x=height))+geom_histogram(binwidth = 15) 49 | 50 | 51 | -------------------------------------------------------------------------------- /files/02-Basic.R: -------------------------------------------------------------------------------- 1 | # create variable 2 | x <- 1 3 | y <- 2 4 | x+y 5 | print(x + y) 6 | z <- x+y 7 | z 8 | 9 | # Numeric ex 1, 1.0 10 | varA <- 1.0 11 | class(varA) 12 | ?class 13 | help(class) 14 | # Logical: TRUE, FALSE 15 | varB <- 1!=2 16 | varB 17 | class(varB) 18 | class(1==2) 19 | # Character 20 | varC <- "Hello, My name is Safe" 21 | class(varC) 22 | 23 | # Character Vectors 24 | animals <- c("Ant","Bird","Cat") 25 | class(animals) 26 | length(animals) 27 | animals[2] 28 | 29 | # Create Variable name 30 | v1 <- c(1,2,3,4) 31 | v2 <- c(2,3,0,0) 32 | v1+v2 33 | 34 | # Replicate 35 | v3 <- rep(c(1,2,3),5) 36 | 37 | # Creating integer sequences 38 | v4 <- c(1:100) 39 | # WHAT IF ? 40 | v1+v4 41 | 42 | v5 <- c(1,2,3) 43 | v6 <- c(1,2,0) 44 | v5+v6 45 | 46 | # Initial 47 | name <- c("Antony","Boky","Caty") 48 | age <-c(10,25,30) 49 | club <-c("Sec A","Sec B","Sec A") 50 | retired <- c(T,F,T) 51 | 52 | # Create list 53 | myList <- list(name,age,club,retired) 54 | myList 55 | 56 | # Or assign name 57 | myList <- list(stdName = name, 58 | stdAge = age, 59 | stdClub = club, 60 | retired = retired) 61 | 62 | myList[2] #get variable stdAge 63 | 64 | View(myList) 65 | myList <- data.frame(name,age,club,retired) 66 | 67 | continent <- c("Africa","Asia","Europe","North America","Oceania","South America","Antarctica") 68 | countries <- c(54,48,51,23,14,12,0) 69 | world <- data.frame(continent,countries) 70 | View(world) 71 | 72 | x <- c(1:10) 73 | x 74 | ?mean 75 | mean(x) 76 | sum(x) 77 | 78 | # Summaries 79 | summary(x) 80 | 81 | 82 | 83 | -------------------------------------------------------------------------------- /assignment/01-week2.md: -------------------------------------------------------------------------------- 1 | # Assignment 1 (Individual) 2 | Create script file `HW01_63130500xxx.R` and do exercise in this file and answer by using comment. 3 | ``` 4 | # Example 0 5 | x <- 1 6 | y <- 2 7 | print(x+y) #3 8 | ``` 9 | 10 | ## Exercise 1 11 | 12 | Finding the average, sum, median, sd, variance of `10.4, 5.6, 3.1, 6.4, 21.7` 13 | 14 | ## Exercise 2 15 | 16 | 2.1. Create data structure in varaible named `marvel_movies` and explain why you using this data structure ? 17 | 18 | ``` 19 | # List of Marvel movies (Order by Marvel Phase released) 20 | names <- c("Iron Man","The Incredible Hulk","Iron Man 2","Thor","Captain America: The First Avenger", 21 | "The Avengers","Iron Man 3","Thor: The Dark World","Captain America: The Winter Soldier", 22 | "Guardians of the Galaxy","Avengers: Age of Ultron","Ant-Man","Captain America: Civil War", 23 | "Doctor Strange","Guardians of the Galaxy 2","Spider-Man: Homecoming","Thor: Ragnarok","Black Panther", 24 | "Avengers: Infinity War","Ant-Man and the Wasp","Captain Marvel","Avengers: Endgame", 25 | "Spider-Man: Far From Home","WandaVision","Falcon and the Winter Soldier","Loki","Black Widow") 26 | 27 | # List of released year of Marvel movies 28 | years <- c(2008,2008,2010,2011,2011,2012,2013,2013,2014,2014,2015,2015,2016,2016, 29 | 2017,2017,2017,2017,2018,2018,2019,2019,2019,2021,2021,2021,2021) 30 | 31 | # Or using Function 32 | years <- c(2008,2008,2010,2011,2011,2012,rep(2013:2016,each=2), 33 | rep(2017,4),rep(2018,2),rep(2019,3),rep(2021,4)) 34 | ``` 35 | 36 | 2.2 Finding the information: 37 | 38 | - The numbers of movies 39 | - Finding the 19th movies name 40 | - Which year is most released movies -------------------------------------------------------------------------------- /files/SampleRDoc.Rmd: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Sample R Document" 3 | author: "jatawatsafe" 4 | output: 5 | html_document: 6 | df_print: paged 7 | --- 8 | 9 | ## R Markdown 10 | This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see . 11 | 12 | When you click the **Knit** button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document. You can embed an R code chunk like this: 13 | 14 | ## Import Lib 15 | 16 | ```{r packages, message=FALSE, warning=FALSE} 17 | library(dplyr) 18 | library(rmarkdown) 19 | ``` 20 | 21 | ## Create Varaible 22 | ```{r var} 23 | sample3 <- c("Male","Female","Male","Female","Female") 24 | gender <- factor(sample3) 25 | class(gender) 26 | summary(gender) 27 | ``` 28 | 29 | ## Explore Data 30 | ```{r explore} 31 | glimpse(starwars) 32 | ``` 33 | 34 | ## Plots 35 | 36 | You can also embed plots, for example: 37 | 38 | ```{r} 39 | barplot(starwars$height) 40 | ``` 41 | 42 | ## Transformation Data 43 | ```{R} 44 | starwars %>% group_by(species) %>% 45 | summarise(height=mean(height,na.rm = T),mass=mean(mass,na.rm = T)) %>% 46 | mutate(BMI = mass / ((height/100)^2)) %>% 47 | arrange(desc(BMI)) %>% 48 | head(10) 49 | ``` 50 | 51 | ## Notes 52 | - Note that the `echo = FALSE` parameter was added to the code chunk to prevent printing of the **R code** 53 | but the result will shown 54 | 55 | ### Save 56 | - Click button `Knit` to save in HTML 57 | - If output is `github_document`, run function `render("fileName.Rmd")` in console to save -------------------------------------------------------------------------------- /files/03-explore01.R: -------------------------------------------------------------------------------- 1 | # Sample datasets 2 | sample1 <- c(29,49,42,43,32,38,37,41,27,27,30) 3 | sample2 <- c(1,2,3,5,10,500) 4 | sample3 <- c("Male","Female","Male","Female","Female") 5 | ### Cross Tabulation and Table Creation 6 | table(sample1) 7 | 8 | names <- c("Iron Man","The Incredible Hulk","Iron Man 2","Thor","Captain America: The First Avenger", 9 | "The Avengers","Iron Man 3","Thor: The Dark World","Captain America: The Winter Soldier", 10 | "Guardians of the Galaxy","Avengers: Age of Ultron","Ant-Man","Captain America: Civil War", 11 | "Doctor Strange","Guardians of the Galaxy 2","Spider-Man: Homecoming","Thor: Ragnarok","Black Panther", 12 | "Avengers: Infinity War","Ant-Man and the Wasp","Captain Marvel","Avengers: Endgame", 13 | "Spider-Man: Far From Home","WandaVision","Falcon and the Winter Soldier","Loki","Black Widow") 14 | years <- c(2008,2008,2010,2011,2011,2012,rep(2013:2016,each=2), 15 | rep(2017,4),rep(2018,2),rep(2019,3),rep(2021,4)) 16 | marvel_movies <- data.frame(names,years) 17 | table(marvel_movies$years) 18 | 19 | # DescTools package 20 | install.packages("DescTools") 21 | 22 | library(DescTools) 23 | help(package=DescTools) 24 | 25 | Mode(sample1) 26 | 27 | factor(sample3) 28 | # treats gender as a nominal variable 29 | gender <- factor(sample3) 30 | class(sample3) 31 | class(gender) 32 | summary(gender) 33 | 34 | data() 35 | View(iris) 36 | help(iris) 37 | 38 | str(mtcars) 39 | head(mtcars) 40 | summary(mtcars) 41 | colMeans(mtcars) 42 | ?mtcars 43 | 44 | # Find mean of miles per gallon (mpg) 45 | mean(mtcars$mpg) # 20.09062 46 | 47 | Hotels <- read.csv("https://raw.githubusercontent.com/safesit23/INT214-Statistics/main/datasets/Hotels.csv") 48 | Hotels <- read.csv("../datasets/Hotels.csv") 49 | View(Hotels) 50 | 51 | 52 | 53 | -------------------------------------------------------------------------------- /files/K01-Assignment1.R: -------------------------------------------------------------------------------- 1 | ### Exercise 1 2 | num <- c(10.4, 5.6, 3.1, 6.4, 21.7) 3 | #average 4 | mean(num) #9.44 5 | #sum 6 | sum(num) #47.2 7 | #median 8 | median(num) #6.4 9 | #sd 10 | sd(num) #7.33846 11 | #variance 12 | var(num) #53.853 13 | 14 | ### Exercise 2 15 | names <- c("Iron Man","The Incredible Hulk","Iron Man 2","Thor","Captain America: The First Avenger", 16 | "The Avengers","Iron Man 3","Thor: The Dark World","Captain America: The Winter Soldier", 17 | "Guardians of the Galaxy","Avengers: Age of Ultron","Ant-Man","Captain America: Civil War", 18 | "Doctor Strange","Guardians of the Galaxy 2","Spider-Man: Homecoming","Thor: Ragnarok","Black Panther", 19 | "Avengers: Infinity War","Ant-Man and the Wasp","Captain Marvel","Avengers: Endgame", 20 | "Spider-Man: Far From Home","WandaVision","Falcon and the Winter Soldier","Loki","Black Widow") 21 | years <- c(2008,2008,2010,2011,2011,2012,rep(2013:2016,each=2), 22 | rep(2017,4),rep(2018,2),rep(2019,3),rep(2021,4)) 23 | 24 | # Using Data Frame because names and years are related 25 | marvel_movies <- data.frame(names,years) 26 | 27 | #1.The numbers of movies 28 | length(marvel_movies$names) #27 29 | 30 | #2.Finding the 19th movies name 31 | View(marvel_movies) # Using Data Viewer to view 19th movies name. It is "Avengers: Infinity War" 32 | #or using position 33 | marvel_movies$names[19] 34 | 35 | #3.Which year is most released movies 36 | View(marvel_movies) # Manual you will see 2017 and 2021 37 | ##Or using Table 38 | table(marvel_movies$years) 39 | 40 | #2017 and 2021 41 | table_year <- table(years) 42 | names(table_year)[table_year==max(table_year)] 43 | 44 | ## Using DescTools Library 45 | install.packages("DescTools") 46 | library(DescTools) 47 | Mode(marvel_movies$years) 48 | print(paste("Most released year is:",mode_year[1],mode_year[2])) 49 | 50 | ## Using dplyr Library 51 | install.packages("dplyr") 52 | library(dplyr) 53 | count(marvel_movies,years,sort=TRUE) #2017 and 2021 -------------------------------------------------------------------------------- /files/07-HypoTesting.R: -------------------------------------------------------------------------------- 1 | library(dplyr) 2 | library(readr) 3 | 4 | # Review 5 | sqrt(4) 6 | 1:5 7 | 8 | # 1.) Sample and Population ------------- 9 | # Sample Data 10 | sample(1:5, 3) 11 | sample(1:5, 3,replace = T) # Sample with replacement 12 | 13 | # Sample n rows from a table 14 | View(mtcars) 15 | glimpse(mtcars) 16 | mtcars %>% sample_n(2) 17 | 18 | # Generated Random Data with Normal Distribution 19 | population_1 <- rnorm(20, mean=65, sd=3.5) 20 | population_1 21 | 22 | # Sample Data 23 | sample_1 <- sample(population_1 , 3) 24 | sample_1 25 | 26 | # 2. Point Estimation --------- 27 | # Explore 28 | glimpse(starwars) 29 | count(starwars) 30 | 31 | # Mean 32 | #1.Finding average height of starwars characters. 33 | mean(starwars$height,na.rm = T) 34 | #2.Finding average height of starwars characters which sex is male. 35 | starwars %>% filter(sex=="male") %>% 36 | summarise(avg_height=mean(height,na.rm = T)) %>% pull() 37 | 38 | # Proportion of male 39 | i <- starwars %>% filter(sex=="male") %>% count() %>% pull();i 40 | n <- starwars %>% count() %>% pull();n 41 | p <- i/n; p 42 | 43 | #pull example 44 | mtcars %>% pull(cyl) 45 | starwars %>% pull(height, name) 46 | 47 | # 3.) Normal Distribution 48 | 49 | # Finding Z 50 | x <- 12 51 | xbar <- 10 52 | sd <- 1 53 | z <- (x-xbar)/sd;z 54 | 55 | # Finding Area 56 | prob1 <- pnorm(x,xbar,sd); prob1 57 | # Finding Z 58 | z1 <- qnorm(prob1); z1 59 | 60 | 61 | # 4.) Example 1: Case Study-Hilltop Coffee --------- 62 | n <- 36 63 | sd <- 0.18 64 | xbar <- 2.92 65 | u0 <- 3 66 | 67 | #H0: u>=3, Ha: u<3 68 | alpha <- 1/100;alpha 69 | 70 | z <- (xbar - u0) / (sd/sqrt(n));z 71 | 72 | # P-value approach 73 | pvalue <- pnorm(z); pvalue 74 | 75 | # Critical Value approach 76 | zalpha <- qnorm(alpha);zalpha 77 | # Using p-value approach 78 | if(pvalue<=alpha){ 79 | print("Reject H0") 80 | }else{ 81 | print("Accept H0") 82 | } 83 | 84 | # Using critical value 85 | if(z<=zalpha){ 86 | print("Reject H0") 87 | }else{ 88 | print("Accept H0") 89 | } 90 | 91 | 92 | 93 | 94 | 95 | -------------------------------------------------------------------------------- /assignment/02-week3.md: -------------------------------------------------------------------------------- 1 | # Assignment 2 (Group): Explore Data 2 | From week 3 that you have learned about explore data and learn from self learning activity. I want you to sharing and working in your group. 3 | 4 | 1.) Explore 2 dataset that given then finding descriptive statistics and summary result in form of sentences/paragraph at least 5 subjects. 5 | ##### Datasets: 6 | - Cats (Ref: https://www.rdocumentation.org/packages/MASS/versions/7.3-47/topics/cats) 7 | - Survey (Ref: https://www.rdocumentation.org/packages/MASS/versions/7.3-47/topics/survey) 8 | 9 | ##### For example: 10 | - From survey, most students use left hand writing. 11 | - The average of body weight of cats is xxx kg. 12 | 13 | 2.) Prerequisites: you need to create your group repository following instuction in [Initial with Group Repository in INT214-Project](https://github.com/sit-2021-int214/int214-project) 14 | 15 | 3.) Doing this assignment in Markdown file. (In your repository, it has template in folder assignment/HW2_groupid.md) or you can view in my template file: [HW2_groupid.md](https://github.com/sit-2021-int214/int214-template/blob/main/assignment/HW2_groupid.md) (markdown file) 16 | 17 | 4.) Send file link in LEB2 to submit 18 | 19 | #### อธิบายเพิ่มเติม(ภาษาไทย): 20 | 1. ให้สำรวจข้อมูลจาก 2 ชุดข้อมูลนี้แล้วสรุปเป็นประเด็นที่สนใจพร้อมหาค่าทางสถิติมาอย่างน้อย 5 ประเด็นจากชุดข้อมูล 2 ชุดนี้ 21 | 2. สิ่งที่ต้องทำก่อน: แต่ละกลุ่มจำเป็นต้องสร้าง Group Repository ตามขั้นตอน [Initial with Group Repository ใน INT214-Project](https://github.com/sit-2021-int214/int214-project) ซึ่งขั้นตอนนี้เป็นการเตรียมตัวทำ Term Assignment โดยจะใช้รวบรวมสำหรับส่งงาน Learning Assignment และทำงาน Term Assignment เข้าไว้ด้วยกัน 22 | 3. หลังจากทำขั้นตอนที่ 2 แล้วใน Group Repository ของน้อง ๆ จะต้องมีไฟล์ที่จำเป็นต้องใช้ สัปดาห์นี้จะให้ทำการบ้านลง `Markdown File` ที่มีใน repo ของกลุ่มน้อง ๆ (ซึ่งถ้าสร้าง repo และทำตาม steps ในการสร้าง repo จะต้องมีไฟล์ `HW2_groupid.md` ใน repo ซึ่งจะอยู่ใน Folder `assignment/HW2_groupid.md`) 23 | 4. ให้แชร์ลิงก์ที่เข้าถึงไฟล์การบ้านลงใน LEB2 เพื่อ Submit การบ้านกลุ่มสัปดาห์นี้ -------------------------------------------------------------------------------- /files/K03-SAT_Workshop.R: -------------------------------------------------------------------------------- 1 | library(readr) 2 | library(assertive) 3 | library(stringr) 4 | library(dplyr) 5 | 6 | sat_score <- read_csv("../datasets/SAT_original.csv") 7 | 8 | # Step 1: Observe data 9 | glimpse(sat_score) 10 | colnames(sat_score) 11 | 12 | # Step 2: Change type of data 13 | sat_score$math_score <- as.numeric(sat_score$math_score) 14 | assert_is_numeric(sat_score$math_score) 15 | 16 | sat_score <- sat_score %>% mutate( 17 | reading_score = as.numeric(reading_score), 18 | writing_score = as.numeric(writing_score) 19 | ) 20 | 21 | # Step 3: See the Duplicate Data 22 | sat_score %>% duplicated() %>% table() 23 | sat_score %>% duplicated() %>% sum() 24 | 25 | sat_score %>% group_by(DBN,school_name) %>% count() %>% filter(n>1) 26 | sat_score %>% filter(duplicated(sat_score)) 27 | 28 | # Step 4: Clear duplicate data 29 | sat_score %>% distinct() %>% count() #478 Data 30 | sat_score <- sat_score %>% distinct() 31 | 32 | # Step 5: Check Range of score 33 | sat_score %>% filter( 34 | math_score<200|math_score>800| 35 | reading_score<200|reading_score>800| 36 | writing_score<200|writing_score>800 37 | ) 38 | 39 | as.vector(sat_score$math_score) %>% na.omit() %>% 40 | assert_all_are_in_closed_range(lower=200,upper = 800) 41 | as.vector(sat_score$reading_score) %>% na.omit() %>% 42 | assert_all_are_in_closed_range(lower=200,upper = 800) 43 | as.vector(sat_score$writing_score) %>% na.omit() %>% 44 | assert_all_are_in_closed_range(lower=200,upper = 800) 45 | 46 | # Step 6: Handling out of range 47 | sat_score <- sat_score %>% 48 | mutate( 49 | math_score=replace(math_score, math_score<200|math_score>800,NA), 50 | reading_score=replace(reading_score, reading_score<200|reading_score>800,NA), 51 | writing_score=replace(writing_score, writing_score<200|writing_score>800,NA), 52 | ) 53 | 54 | # Step 7: Calculate total score 55 | sat_score <- sat_score %>% mutate(total_score = math_score+reading_score+writing_score) 56 | 57 | # Step 8: Find Stat 58 | summary(sat_score) 59 | # or 60 | sat_score %>% summarise( 61 | min_score = min(total_score,na.rm = T), 62 | avg_score = mean(total_score,na.rm = T), 63 | max_score = max(total_score,na.rm = T) 64 | ) 65 | 66 | # count school 67 | sat_score %>% count() #478 School which sent data 68 | sat_score %>% filter(is.na(total_score)) %>% count() #62 69 | sat_score %>% na.omit() %>% count() #416 school with complete data 70 | 71 | # School that get highest total score 72 | sat_score %>% arrange(desc(total_score)) 73 | sat_score %>% filter(total_score==max(total_score,na.rm = T)) 74 | 75 | # Step 9: Write file 76 | write_csv(sat_score,file = "SAT_clean.csv") 77 | 78 | 79 | # Don't do like this ---------------- 80 | sat_score %>% filter(sum_score<600|sum_score>2400) #because some data is wrong -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # INT214-Statistics for Information Technology (1/64) 2 | 3 | Using workshop INT214 Statistics for Information Technology 4 | 5 | ## Installation Program 6 | 7 | 1. Install R from https://cran.rstudio.com/ 8 | 2. Download RStudio Desktop from https://rstudio.com/products/rstudio/download/#download 9 | 10 | ## Course Outlines 11 | 12 | | Class R | Topics | Instruction Files | 13 | | ------- | ----------------------------------- | -------------------------------------------- | 14 | | Class 1 | Introduction + Setting up R | [01-Intro-R](workshop/01-intro-R.md) | 15 | | Class 2 | Basic R + Statistics | [02-Basic-R](workshop/02-Basic-R.md) | 16 | | Class 3 | Explore Data Part I | [03-Explore-01](workshop/03-Explore-01.md) | 17 | | Class 4 | Explore Data Part II | [04-Explore-02](workshop/04-Explore-02.md) | 18 | | Class 5 | Data Transformation + Data Cleaning | [05-Cleaning](workshop/05-Cleaning.md) | 19 | | Class 5 | Workshop I | [06-Workshop](workshop/06-Workshop1.md) | 20 | | Class 6 | Data Visualization | [07-DataViz](workshop/07-DataViz.md) | 21 | | Class 7 | Hypothesis Testing with R | [08-HypoTesting](workshop/08-HypoTesting.md) | 22 | | Class 8 | Workshop II | [09-Workshop2](workshop/09-Workshop2.md) | 23 | 24 | ## Resources 25 | 26 | ### Resources in this repository 27 | 28 | - [Summary R Command](workshop/Summary.md) 29 | - [View](https://drive.google.com/drive/folders/0B2HRApZM_XXyfklvV014ZERlSEo0b29STjh4ZXFPdVdZTzNFazhtX0xpbzBLZHB6R3hEbDA?resourcekey=0-OIoRGd_ejSlr0gYZea5dcg&usp=drive_link) All Slides 30 | - [View](https://github.com/safesit23/INT214-Statistics/tree/main/datasets) Dataset Materials 31 | - [View](https://github.com/safesit23/INT214-Statistics/tree/main/files) Materials in class + Key Assignments 32 | - [View](https://github.com/safesit23/INT214-Statistics/tree/main/assignment) All Assignment 33 | - Sample R Document by using [Rmd file](https://github.com/safesit23/INT214-Statistics/blob/main/files/SampleRDoc.Rmd) ([View output here](https://safesit23.github.io/INT214-Statistics/files/SampleRDoc.html)) 34 | 35 | ### Related Repository 36 | 37 | - Term Project Details: [int214-project](https://github.com/sit-2021-int214/int214-project) 38 | - Github Organization: [INT214 Statistics 2021](https://github.com/sit-2021-int214) 39 | - Sample Project: [000-INT214Survey](https://github.com/sit-2021-int214/000-INT214Survey) 40 | 41 | ### Learning Reference 42 | 43 | - https://www.statmethods.net/index.html 44 | - https://www.tutorialspoint.com/r 45 | - https://github.com/andrewgbruce/statistics-for-data-scientists 46 | - https://cran.r-project.org/doc/contrib/Paradis-rdebuts_en.pdf 47 | - https://www.rstudio.com/resources/cheatsheets/ 48 | - https://www.tidyverse.org/ 49 | - https://clauswilke.com/dataviz/ 50 | 51 | --- 52 | 53 | ### Created by Jatawat Xie (P'Safe) 54 | -------------------------------------------------------------------------------- /files/05-clean.R: -------------------------------------------------------------------------------- 1 | library(dplyr) 2 | 3 | cars <- as_tibble(mtcars) 4 | glimpse(cars) 5 | cars %>% head() 6 | head(cars) 7 | 8 | glimpse(starwars) 9 | 10 | starwars %>% select(name,height) 11 | starwars %>% select(-name) 12 | starwars %>% filter(sex == "male",skin_color == "light") 13 | starwars %>% filter(sex == "male"|skin_color == "light") 14 | starwars %>% arrange(height) 15 | starwars %>% summarise(height = mean(height, na.rm = TRUE)) 16 | starwars %>% group_by(sex) %>% select(height) %>% summarise(avg = mean(height, na.rm = TRUE)) 17 | 18 | # Save into new variable 19 | sw <- starwars 20 | # Rename Column named hair_color to hair 21 | sw <- sw %>% rename(hair=hair_color) 22 | glimpse(sw) 23 | 24 | # Mutate 25 | sw %>% mutate(height_m = height / 100) %>% glimpse() 26 | 27 | # Transmute 28 | sw %>% transmute(height_m = height / 100) %>% glimpse() 29 | 30 | # Data Cleaning ---------------------- 31 | 32 | library(readr) # A fast and friendly way to read rectangular data 33 | library(stringr) # Character manipulation 34 | library(assertive) # Readable check functions to ensure code integrity 35 | 36 | products <- read_csv("https://raw.githubusercontent.com/safesit23/INT214-Statistics/main/datasets/products_original.csv") 37 | 38 | glimpse(products) 39 | products %>% head() 40 | products %>% View() 41 | 42 | #3. Checking the types of values 43 | is.numeric(products$price) 44 | assert_is_numeric(products$price) 45 | 46 | is.numeric(products$sold) 47 | assert_is_numeric(products$sold) 48 | 49 | is.factor(products$gender) 50 | 51 | # 4.Changing Type: character to Factor (Gender) 52 | products$gender <- as.factor(products$gender) 53 | summary(products$gender) 54 | 55 | # 5.Handling String with stringr (Price) 56 | products$price %>% as.numeric() # It will change all data as NA / Need to handle string first 57 | 58 | products$price <- 59 | products$price %>% str_remove("THB") %>% 60 | str_trim() %>% str_remove(",") %>% as.numeric() 61 | glimpse(products) 62 | 63 | # 6. Removing duplicate data 64 | # Duplicate elements 65 | products %>% duplicated() %>% table() 66 | products %>% duplicated() %>% sum() 67 | products %>% filter(duplicated(products)) 68 | 69 | # Using only distinct observation 70 | products <- 71 | products %>% distinct() 72 | 73 | ## FINDING (KEY) 74 | # Gross sales of all products from this datasets. 75 | products %>% mutate(sales = price*sold) %>% 76 | summarise(gross_sales = sum(sales)) 77 | # Number of all products from this datasets. 78 | products %>% count() 79 | 80 | # 7. Handling missing data and outliers 81 | std_room <- data.frame( 82 | name=c("Antony","Baifern","Caty","Daniel","Julia","Susan","Tom"), 83 | mid_score = c(29, 26, 15, 19, 22, 50, NA), 84 | final_score = c(NA, 15, 26, 19, 20, 18, 20) 85 | ) 86 | 87 | # Display list of students who absent in each examination. 88 | std_room %>% filter(is.na(mid_score)|is.na(final_score)) %>% count() 89 | 90 | # Display list of students who has taking all exams. 91 | std_room %>% na.omit() 92 | 93 | # Handling Range Values 94 | assert_all_are_in_closed_range(std_room$mid_score, lower = 0, upper = 30) 95 | assert_all_are_in_closed_range(std_room$final_score, lower = 0, upper = 30) 96 | 97 | std_room$mid_score <- replace(std_room$mid_score,std_room$mid_score == 50, 15) 98 | 99 | # Student's who get highest midterm score in this room. 100 | std_room %>% filter(mid_score==max(mid_score,na.rm = T)) 101 | 102 | ## Teacher need your help more: (KEY) 103 | # Cleaning Data 104 | std_room$mid_score <- 105 | replace(std_room$mid_score,is.na(std_room$mid_score), 0) 106 | std_room$final_score <- 107 | replace(std_room$final_score,is.na(std_room$final_score), 0) 108 | 109 | # List all of students with total score in descending order. 110 | std_room %>% mutate(total_score=mid_score+final_score) %>% 111 | select(name,total_score) %>% arrange(desc(total_score)) 112 | 113 | -------------------------------------------------------------------------------- /workshop/01-intro-R.md: -------------------------------------------------------------------------------- 1 | # 01 Introduction to R 2 | ## 0. Installation and Setting Up 3 | - Install R from https://cran.rstudio.com/ 4 | - Download RStudio Desktop from https://rstudio.com/products/rstudio/download/#download 5 | 6 | ### Setting preference (Optional) 7 | You can set appearance and pane layout in Menu `Tools > Global Options...` 8 | 9 | In R Studio compose of 4 Pane: 10 | 1. Source: for script file 11 | 2. Concole: for watch result from running 12 | 3. Environment: show variable that you have assign 13 | 4. Files, Plots, Packages, Help: show other information 14 | 15 | 16 | ## 1. Setup Directory 17 | In this part you need to get and set working directory of program RStudio Desktop. It has 3 Step 18 | - Step 1: Get working directory by using `getwd()` 19 | - Step 2: Create new folder then set working directory to this folder by using `setwd("path")` 20 | - Step 3: Try to add some file then check it that you are setting directory right. 21 | ```` 22 | #Get Working Directory 23 | getwd() 24 | 25 | #Set Working Directory 26 | setwd("path") 27 | 28 | #List the Files in a Directory/Folder 29 | dir() 30 | ```` 31 | ### 1.1. How can we get folder path (Step 2) 32 | #### for macOS: 33 | open terminal app and then go to your folder with `cd` then using command `pwd` to print working directory 34 | ``` 35 | #Terminal App (Sample) 36 | jatawatsafe@Safe-MBP ~ % pwd 37 | /Users/jatawatsafe 38 | 39 | jatawatsafe@Safe-MBP ~ % ls 40 | Desktop Library Postman 41 | 42 | jatawatsafe@Safe-MBP ~ % cd Desktop/R-214 43 | 44 | jatawatsafe@Safe-MBP R-214 % pwd 45 | /Users/jatawatsafe/Desktop/R-214 46 | 47 | # Back to R and put this path in setwd() 48 | setwd("/Users/jatawatsafe/Desktop/R-214") 49 | ``` 50 | ``` 51 | #Linux command in Terminal 52 | ls #List file 53 | cd folderName/folderName #Change directory 54 | pwd #Print Working Directory 55 | ``` 56 | #### for windows: 57 | 1. Open File Explorer and go to your folder 58 | 2. Right click at navigate and copy your address [(or use another ways)](https://www.top-password.com/blog/tag/how-to-find-file-path-windows-10/) 59 | 3. Put in command `setwd()` and change `\` to `/` ***If not change it will Error 60 | ``` 61 | # When you get path from address: 62 | # C:\Users\safe\Desktop\R-INT214 63 | 64 | # When using in R 65 | setwd("C:/Users/safe/Desktop/R-INT214") 66 | ``` 67 | 68 | ### 1.2. Create file and list file (Step 3) 69 | Create file `test.txt` in your folder then go to console in R Studio and using `dir()` to list all files in working directory 70 | #### for macos: 71 | Open Terminal app (make sure that you are right working directory by using `pwd` to check) try to create new file by using command `touch test.txt` to create blank file 72 | #### for windows: 73 | Right click on your folder select `New > Text Document` then save it to folder. 74 | 75 | 76 | 77 | ## Easy way to set Directory: 78 | Setting default working directory by use menu `Session > Set working directory > Choose...` 79 | 80 | 81 | ## 2. Basic Tools 82 | Try to run this in console... 83 | ```{r} 84 | #comment 85 | 1+1 86 | # formula 87 | 2*100 - 5 88 | # Print function 89 | print("Hello") 90 | ``` 91 | 92 | ## 3. Run Script 93 | 3.1. Create Script file and save `1-MyScript.R` 94 | 95 | 3.2. copy code in Topic 2 and paste in script file. 96 | 97 | 3.3. Run Script 98 | - `Command+Enter` Run the current line or selection 99 | - `Command+option+R` Run all 100 | - `Ctrl+L` Clear console 101 | 102 | ## 4. Basic Operation 103 | We can create variable by using `<-` it mean assign value (right) to variable (left) 104 | ``` 105 | # create variable 106 | x <- 1 107 | y <- 2 108 | x+y 109 | print(x + y) 110 | z <- x+y 111 | z 112 | ``` 113 | 114 | ## Notes 115 | ``` 116 | # Directory 117 | getwd() 118 | setwd() 119 | 120 | # Help Function 121 | ? 122 | help() 123 | ``` 124 | -------------------------------------------------------------------------------- /workshop/09-Workshop2.md: -------------------------------------------------------------------------------- 1 | # 09 Workshop II 2 | 3 | ## Outlines 4 | 5 | - Get the data from Database by using SQL 6 | - Working with Rmd file 7 | - Publishing your own portfolio website with Github Pages 8 | 9 | ## 0. Prerequisites 10 | 1. Open progress form [Class 08](https://forms.gle/8C188D1uRwZUozxu5) and checked on Study Check-In 11 | 2. Open R Studio Desktop and install package `rmarkdown` 12 | 3. Checked on 0 prerequisite in progress form 13 | 14 | ## 1. Preparing Repository with `GitHub fork` 15 | A fork is a copy of a repository. Forking a repository allows you to freely experiment with changes without affecting the original project. [Ref: Fork a repo](https://docs.github.com/en/get-started/quickstart/fork-a-repo) 16 | 17 | ### Let's fork repository 18 | 1. On GitHub.com, navigate to the [int214-workshop](https://github.com/sit-2021-int214/int214-workshop) repository. 19 | 2. In the top-right corner of the page, click Fork. 20 | 21 | ![image](https://docs.github.com/assets/images/help/repository/fork_button.jpg) 22 | 23 | 3. Cloning your forked repository for access this repository locally on your computer. [(Guideline: Cloning)](https://docs.github.com/en/get-started/quickstart/fork-a-repo#cloning-your-forked-repository) 24 | 25 | Now, you will have own repository and you can access file on your computer 26 | 27 | 28 | ## 2.) Get the data from Database by using SQL 29 | In this part we will using knowledge about SQL to get data from database. We using **sqliteonline** which is User-friendly interface for data science to connect the database. I have provide `database_int214.db` which is mockup database file to do this step. You can see this file in your repository. 30 | 31 | 1. Go to URL: https://sqliteonline.com/ 32 | 2. Load DB: File > Open DB 33 | 3. Let's try to use sql command to explore dataset in database 34 | 4. Export to csv named `db_int214` which set the first line is column name then saved to your folder. 35 | 36 | ## 3.) Working with Rmd file 37 | R Markdown is a file format for making dynamic documents with R. An R Markdown document is written in markdown (an easy-to-write plain text format) and contains chunks of embedded R code. [Ref: Rmd](https://rmarkdown.rstudio.com/articles_intro.html) We can using Rmd to make a report. 38 | 39 | ``` 40 | install.packages("rmarkdown") 41 | ``` 42 | 43 | ### 3.1. Let's try Rmd file ! 44 | 45 | 1. Open R Studio desktop and **setting working directory** to your repository folder. 46 | 2. Open file `index.Rmd` in your repository folder 47 | 3. Click run all and see result 48 | 49 | ### 3.2. Transform an R Markdown file to HTML file 50 | 51 | Click button `Knit` in R Studio Desktop to save in HTML file 52 | 53 | ## 4.) Publishing your own portfolio website with Github Pages 54 | GitHub Pages is a static site hosting service that takes HTML, CSS, and JavaScript files straight from a repository on GitHub, optionally runs the files through a build process, and publishes a website. [(Ref: GitHub Pages)](https://docs.github.com/en/pages/getting-started-with-github-pages/about-github-pages). We will using Github Pages to publish the website from previous step. 55 | 56 | > Tip: If `index.html` is present, this will be used instead of `index.md`. If neither `index.html` nor `index.md` are present, `README.md` will be used. [(Ref)](https://docs.github.com/en/pages/getting-started-with-github-pages/creating-a-github-pages-site) 57 | 58 | ### Creating a GitHub Pages site 59 | 0. Commit and push file `index.html` to your repository 60 | 1. On GitHub.com, navigate to your repository. 61 | 2. Under your repository name, click Settings. 62 | 3. In the left sidebar, click Pages. 63 | 4. Under "GitHub Pages", use the None or Branch drop-down menu and select a publishing source. 64 | 5. Optionally, use the drop-down menu to select a folder for your publishing source. 65 | 6. Click Save. 66 | 7. Waiting and see the result. (If your Github Pages site is not detecting index.html you can concatenate `/index.html` at the end of your web url) 67 | 68 | > See Instruction with Image at: [GitHub Pages](https://docs.github.com/en/pages/getting-started-with-github-pages/configuring-a-publishing-source-for-your-github-pages-site) -------------------------------------------------------------------------------- /assignment/04-week8.md: -------------------------------------------------------------------------------- 1 | # Assignment 4 (Individual 5%): Data Visualization 2 | 3 | ## Instruction 4 | 5 | - This assignment is Individual Assignment. It divided into Part A and Part B 6 | - Total Score is 20 Pts (See criteria in LEB2) 7 | - Due date: Sec A - 25 Oct 2021 At 23:00 GMT+7 / Sec B - 29 Oct 2021 At 23:00 GMT+7 8 | - Create folder HW04_studentId in Group repository and push all code (R, md or Rmd) in this repository. 9 | - Send in format: [PDF file](https://github.com/safesit23/INT214-Statistics/blob/main/assignment/HW04_SamplePdf.pdf) in LEB2 (ส่งงานเป็นไฟล์ PDF ใน LEB2 โดยให้แปะลิงก์งานที่ทำ Part A สำหรับเข้าถึงไฟล์ต่าง ๆ ใน git และ Part B ที่ทำ Dashboard) 10 | 11 | **พี่ตรวจจากไฟล์ PDF ใน LEB2 แต่ในส่วนของ Code อยากให้อัปโหลดเข้า git และแชร์ link ลง PDF เนื่องจากหากอัปโหลด code ใน LEB2 มาจะมีปัญหาเรื่องการแสดงผลข้อมูลและภาษา 12 | 13 | #### Select one dataset from the given: 14 | 15 | 1. Top 270 Computer Science / Programing Books (Data from Thomas Konstantin, [Kaggle](https://www.kaggle.com/thomaskonstantin/top-270-rated-computer-science-programing-books)) >> [Using CSV](https://raw.githubusercontent.com/safesit23/INT214-Statistics/main/datasets/prog_book.csv) 16 | 17 | 2. Superstore Sales Dataset (Data from Rohit Sahoo,[Kaggle](https://www.kaggle.com/rohitsahoo/sales-forecasting)) >> [Using CSV](https://raw.githubusercontent.com/safesit23/INT214-Statistics/main/datasets/superstore_sales.csv) 18 | 19 | ## Part A: Finding Insight the data in R 20 | 21 | - Goal: Can find insight the data and visualize the data. 22 | - Score: 13 Pts 23 | 24 | ### What you need to do: 25 | 26 | 1. Explore the dataset that you have select. 27 | 2. Transform data with dplyr and finding **insight the data** at least 6 issues. Show your code, result and summary in form of sentence/paragraphs. 28 | 3. Using ggplot2 to create **2 graphs** and explain each graph. 29 | 4. In this part, you need to using command from tidyverse (e.g. lubridate, stringr, forcats) that not learned in class and explain this command how to used it. If you can't implement to this dataset, you can select one command and show example how to used it. 30 | 5. Do in Markdown File (md or Rmd) and push into your folder in Team Repository. (Same as Workshop I) 31 | 6. Copy link to access this folder and paste into PDF file Part A 32 | 33 | Click to see sample: [here](https://github.com/sit-2021-int214/int214-template/tree/main/assignment/HW04_studentId) 34 | 35 | ## Part B: Creating Interaction Dashboard with BI Tools (7 Pts) 36 | 37 | - Goal: Know how to create basic interaction dashboard by using BI Tools 38 | - Score: 7 Pts 39 | - What you need to do: You need to self-learning how to creating Interaction Dashboard with BI Tools and show your result. You can use same dataset or change another dataset. (ให้ใช้ dataset ชุดเดียวกับที่เลือกหรือใช้ dataset จากที่ไปเรียนรู้ด้วยตัวเองมาก็ได้ เช่นไปเรียนใน youtube มี dataset ให้ทำตาม สามารถใช้ได้ แต่อยากให้เขียนอธิบายด้วยว่าได้อะไรบ้าง) 40 | - Using Tools: [Power BI](https://powerbi.microsoft.com/en-au/), [Tableau](https://www.tableau.com/academic/students), [Data Studio](https://datastudio.google.com/) 41 | 42 | ### Requirements: 43 | 1. Create interactive dashboard only 1 page with 2-4 graphs to show interaction between data. 44 | 2. Easy to understand and appropriate graph. 45 | 3. Adding source of data and title of dashboard 46 | 4. UI not has score but you need to implement with best practice to create data visualization. 47 | 5. Writing name and student ID in dashboard 48 | 6. Paste the link that can access the dashboard in PDF file **Don't forget to published link 49 | 7. Write summary what you have learned or done in this dashboard in PDF file (ในส่วนนี้ไม่มีคะแนน แต่อยากให้อธิบายถึงสิ่งที่ทำคร่าว ๆ) 50 | 51 | Click to see sample from P'Safe: [PowerBI](https://app.powerbi.com/view?r=eyJrIjoiNTdmNWY5YTAtOGFmZi00YzczLTkzMmEtYjg3OTEwMzMwNmVmIiwidCI6IjZmNDQzMmRjLTIwZDItNDQxZC1iMWRiLWFjMzM4MGJhNjMzZCIsImMiOjEwfQ%3D%3D), 52 | [Data Studio](https://datastudio.google.com/reporting/224c53b1-e078-4f50-9614-463d9550d6c4) 53 | 54 | #### Guideline to Learning how to create BI Dashboard 55 | 56 | - [Data Camp: Introduction to Power BI](https://learn.datacamp.com/courses/introduction-to-power-bi) 57 | - [Data Camp: Introduction to Tableau](https://www.datacamp.com/courses/introduction-to-tableau) 58 | - [DataTH.com: สอนทำโปรเจควิเคราะห์ข้อมูลไว้ใส่ Portfolio](https://data.go.th/blog/portfolio-10) 59 | - [Microsoft Learn: POWER BI](https://docs.microsoft.com/en-us/learn/powerplatform/power-bi) 60 | -------------------------------------------------------------------------------- /workshop/06-Workshop1.md: -------------------------------------------------------------------------------- 1 | # 06 Workshop I: Data Analysis with Descriptive Statistics 2 | 3 | ## Let's Exploratory Data Analysis (EDA) 4 | 5 | 1. Data Exploration (การสำรวจข้อมูล) 6 | 2. Data Transformation (การแปลงข้อมูล) 7 | 3. Data Analysis with Descriptive Statistics (การวิเคราะห์ข้อมูลโดยใช้สถิติเชิงพรรณนา) 8 | 9 | ## Instruction 10 | 11 | 1. Create folder named `WS01_studentid` with consist of 2 files ([Sample Output](https://github.com/sit-2021-int214/int214-template/tree/main/assignment)) 12 | - R file named `WS01_63130500xxx.R` for your coding ([See sample file](https://raw.githubusercontent.com/sit-2021-int214/int214-template/main/assignment/WS01_studentId/WS01_studentId.R)) 13 | - Markdown file named `WS01_63130500xxx.md` for writing description steps with your code and result ([Copy template files to your files](https://raw.githubusercontent.com/sit-2021-int214/int214-template/main/assignment/WS01_studentId/WS01_studentId.md)) 14 | 2. Read information about SAT Scores dataset. 15 | 3. Explore the data and finding descriptive Statistics. (you can add more question from given question) 16 | 4. Push your folder `WS01_studentid` into your GIT group repository in folder assignment 17 | 18 | ## SAT Scores dataset 19 | 20 | (This dataset is references dataset from [NYC Open Data](https://data.cityofnewyork.us/Education/2012-SAT-Results/f9bf-2cp4)) 21 | 22 | The most recent school level results for New York City on the SAT. Results are available at the school level for the graduating seniors of 2012. Records contain 2012 College-bound seniors mean SAT scores taken during SY 2012. In this dataset, some school didn't send avg scores and some has record wrong data. 23 | 24 | **About SAT** 25 | 26 | The SAT is a standardized test widely used for college admissions in the United States. This test divided into 3 parts. There are Critical Reading, Math, and Writing. (Ref: [Wikipedia](https://en.wikipedia.org/wiki/SAT)) Section scores are reported on a scale of 200 to 800. Total SAT score is in range of 600 to 2400. (ข้อสอบแบ่งออกเป็นสามส่วนโดยคะแนนแต่ละ ส่วนมีคะแนนเต็มอยู่ที่ 800 คะแนน และมีคะแนนต่ำสุดของแต่ละส่วนอยู่ที่ 200 คะแนนแม้ไม่ได้ทำก็ตาม โดยเมื่อรวมคะแนนทั้ง 3 ส่วนแล้วจะอยู่ที่ช่วง 600 ถึง 2400) 27 | 28 | ## Define a question 29 | 30 | 1. How many observation of this dataset (before cleaning) ? 31 | 2. Are there duplicate data sets ? (If have duplicate data, list the data that duplicate) 32 | 3. How many distinct school in this dataset ? (Know after drop duplicate data) 33 | 4. What is min, max, average, quartile of each part in SAT ? 34 | 5. What is min, max, average, quartile of total score in SAT ? 35 | 6. Which school is get highest SAT score ? 36 | 37 | ## Guideline Steps to do: 38 | 39 | 0. Loading dataset from [SAT_original.csv](https://raw.githubusercontent.com/safesit23/INT214-Statistics/main/datasets/SAT_original.csv) and assign variable named `sat_score` 40 | 1. Observe the data and answer the question: 41 | - How many observation before cleaning ? 42 | - List variable name 43 | 2. Changing the types of values 44 | 3. List duplicate data and count number of duplicate data. 45 | 4. Removing duplicate data and reassign value in `sat_score` variable 46 | 5. Check range value of each score by using `filter` 47 | 6. Handling out of range with NA value 48 | 7. Calculate total score and assign in `sum_score` column 49 | 8. Finding descriptive statistics 50 | 51 | ## Extra Knowledge (Optional) 52 | 53 | ### 1. Write CSV file 54 | 55 | Try to save your clean data into CSV file 56 | ``` 57 | write_csv(sat_score,file = "SAT_clean.csv") 58 | ``` 59 | 60 | ### 2. R Markdown files 61 | 62 | R Markdown is a file format for making dynamic documents with R. An R Markdown document is written in markdown (an easy-to-write plain text format) and contains chunks of embedded R code, like the document below. (Read more:[rmarkdown](http://rmarkdown.rstudio.com)) 63 | 64 | - See [Sample Rmd Files](https://github.com/safesit23/INT214-Statistics/blob/main/files/SampleRDoc.Rmd) 65 | - See [Sample HTML output](https://safesit23.github.io/INT214-Statistics/files/SampleRDoc.html) 66 | 67 | **Try with yourself** 68 | 69 | 1. Create new file `R Markdown` named `WS01_studentid.Rmd` 70 | 2. Copy code from [Sample Rmd Files](https://github.com/safesit23/INT214-Statistics/blob/main/files/SampleRDoc.Rmd) to your file 71 | 3. Click button `Knit` to save in HTML (In same tabs of Run button) 72 | 4. Try to instead content with WS01_63130500xxx.md 73 | 5. Click button `Knit` to save in HTML files again 74 | 6. Open recented html file with browser 75 | 76 | You will see that Rmd file can display output of your code. In this way, it not necessary to copy output into md file. You can use Rmd file instead to show output. 77 | 78 | Study more: [Datacamp](https://www.datacamp.com/courses/reporting-with-rmarkdown) 79 | 80 | ### 3. GitHub Pages 81 | In github, it cannot show output of Rmd file or HTML file. You can using [GitHub Pages](https://pages.github.com/) for hosting directly from your GitHub repository. Just edit, push, and your changes are live. 82 | 83 | 1. Go to setting of repository > Pages 84 | 2. Choose Source as 'Main' and then save (Setting Finished !) 85 | 3. Push your file to your repository 86 | 4. Link your HTML file to README.md -------------------------------------------------------------------------------- /workshop/02-Basic-R.md: -------------------------------------------------------------------------------- 1 | # 02 Basic R + Statistics 2 | 3 | ## Agenda 4 | 5 | - Review Basic Operation 6 | - Data Types & Data Structures 7 | - Statistics 8 | 9 | ## 0. Prerequisites 10 | 11 | 1. Open R Studio Desktop 12 | 2. Setting working directory (See in [01-Intro-R](01-intro-R.md)) 13 | 3. Create Script file name `02_63130500xxx.R` and save in your working directory 14 | 4. Open progress form [Class 02](https://forms.gle/syVRfduXskPQXLUs5) and checked on Study Check-In and 0 prerequisite 15 | 16 | ## 1. Review Basic Operation 17 | 18 | ``` 19 | # create variable 20 | x <- 1 21 | y <- 2 22 | x+y 23 | print(x + y) 24 | z <- x+y 25 | z 26 | ``` 27 | 28 | ## 2. Data Types 29 | 30 | There are 3 types: 31 | 32 | - Numeric: Any number with or without a decimal point. Example - 12.3, 5, 999 33 | - Logical: Two possible values — either `TRUE` or `FALSE` 34 | - Character: Any grouping of characters on your keyboard (letters, numbers, spaces, symbols, etc.) or text.Example - "Hello World" 35 | 36 | ``` 37 | # Numeric ex 1, 1.0 38 | varA <- 100 39 | class(varA) 40 | 41 | # Logical: TRUE, FALSE 42 | varB <- TRUE 43 | class(varB) 44 | class(1==2) 45 | 46 | # Character 47 | varC <- "Hello, My name is Safe" 48 | class(varC) 49 | ``` 50 | 51 | ## Data Structure 52 | 53 | Main data structure that we will learn in this course are Vector, List, Data Frame 54 | 55 | ## 3. Vector 56 | 57 | Vector is the simple data structure which is a single entity consisting of an ordered collection of values. We use `c()` function which means to concatenate the elements into a vector. 58 | 59 | ### 3.1.1. Create Vector 60 | 61 | ``` 62 | # Character Vectors 63 | c("Ant","Bird","Cat") 64 | 65 | # Logical Vectors 66 | c(TRUE,FALSE,TRUE) 67 | 68 | # Numeric Vectors 69 | c(100,245,305,411,555) 70 | ``` 71 | 72 | - Use `class()` to see class or type of an object 73 | - Use `length()` to get the length of vectors 74 | - Moreover you can get elements at position x by using `variable[x]` which position is starting with 1 75 | 76 | ### 3.1.2. Operation with Vector 77 | 78 | ``` 79 | # Create Variable name 80 | v1 <- c(1,2,3,4,5) 81 | v2 <- c(6,7,8,9,10) 82 | 83 | # Replicate 84 | v3 <- rep(c(1,2,3),5) 85 | 86 | # Creating integer sequences 87 | v4 <- c(1:100) 88 | ``` 89 | 90 | You can use `+ - * /` with vector 91 | 92 | ``` 93 | v1+v2 94 | ``` 95 | 96 | ## 4. Lists 97 | 98 | An ordered collection of objects (components). A list allows you to gather a variety of (possibly unrelated) objects under one name. 99 | 100 | ``` 101 | # Initial 102 | name <- c("Antony","Boky","Caty") 103 | age <-c(10,25,30) 104 | club <-c("Sec A","Sec B","Sec A") 105 | retired <- c(T,F,T) 106 | 107 | # Create list 108 | myList <- list(name,age,club,retired) 109 | # Or assign name 110 | myList <- list(stdName = name, 111 | stdAge = age, 112 | stdClub = club, 113 | retired = retired) 114 | ``` 115 | 116 | ## 5. Data Frame 117 | 118 | Data frames are tabular data objects. The first column can be numeric while the second column can be character and third column can be logical. It is a list of vectors of equal length. 119 | 120 | Data Frames are created using the `data.frame()` function. 121 | 122 | ``` 123 | continent <- c("Africa","Asia","Europe","North America","Oceania","South America","Antarctica") 124 | countries <- c(54,48,51,23,14,12,0) 125 | world <- data.frame(continent,countries) 126 | View(world) 127 | ``` 128 | 129 | ## 6. Statistics 130 | 131 | ``` 132 | x <- c(1:10) 133 | 134 | mean(x) 135 | sum(x) 136 | 137 | # Summaries 138 | summary(x) 139 | ``` 140 | 141 | ## Summary Notes 142 | 143 | ``` 144 | # Help Function 145 | ? 146 | help() 147 | 148 | # Useful Functions 149 | length(object) # number of elements or components 150 | str(object) # structure of an object 151 | class(object) # class or type of an object 152 | ``` 153 | 154 | Study More... https://www.statmethods.net/input/datatypes.html 155 | 156 | ## Assignment 1 157 | 158 | Create script file `HW01_63130500xxx.R` and do exercise in this file and answer by using comment. Example 159 | 160 | ``` 161 | # Example 0 162 | x <- 1 163 | y <- 2 164 | print(x+y) #3 165 | ``` 166 | After finished send in LEB2 167 | 168 | ### Exercise 1 169 | 170 | Finding the average, sum, median, sd, variance of `10.4, 5.6, 3.1, 6.4, 21.7` 171 | 172 | ### Exercise 2 173 | 174 | 2.1. Create data structure in variable named `marvel_movies` and explain why you using this data structure ? 175 | 176 | ``` 177 | # List of Marvel movies (Order by Marvel Phase released) 178 | names <- c("Iron Man","The Incredible Hulk","Iron Man 2","Thor","Captain America: The First Avenger", 179 | "The Avengers","Iron Man 3","Thor: The Dark World","Captain America: The Winter Soldier", 180 | "Guardians of the Galaxy","Avengers: Age of Ultron","Ant-Man","Captain America: Civil War", 181 | "Doctor Strange","Guardians of the Galaxy 2","Spider-Man: Homecoming","Thor: Ragnarok","Black Panther", 182 | "Avengers: Infinity War","Ant-Man and the Wasp","Captain Marvel","Avengers: Endgame", 183 | "Spider-Man: Far From Home","WandaVision","Falcon and the Winter Soldier","Loki","Black Widow") 184 | 185 | # List of released year of Marvel movies 186 | years <- c(2008,2008,2010,2011,2011,2012,2013,2013,2014,2014,2015,2015,2016,2016, 187 | 2017,2017,2017,2017,2018,2018,2019,2019,2019,2021,2021,2021,2021) 188 | 189 | # Or using Function 190 | years <- c(2008,2008,2010,2011,2011,2012,rep(2013:2016,each=2), 191 | rep(2017,4),rep(2018,2),rep(2019,3),rep(2021,4)) 192 | ``` 193 | 194 | 2.2 Finding the information: 195 | 196 | - The numbers of movies 197 | - Finding the 19th movies name 198 | - Which year is most released movies (In this question can using observation data, not necessary to used command to find answer) -------------------------------------------------------------------------------- /workshop/Summary.md: -------------------------------------------------------------------------------- 1 | # Summary and Collect useful function in R 2 | 3 | **Created by Safe** 4 | 5 | ## 1. Basic Operation 6 | 7 | We can create variable by using `<-` it mean assign value (right) to variable (left) 8 | 9 | ``` 10 | # create variable 11 | x <- 1 12 | y <- 2 13 | x+y 14 | print(x + y) 15 | z <- x+y 16 | z 17 | ``` 18 | 19 | ## 2. Data Types 20 | 21 | ### 2.1. Basic Data Type 22 | 23 | There are 3 types: Numeric, Logical, Character 24 | 25 | ``` 26 | varA <- 100 # Numeric ex 1, 1.0 27 | varB <- TRUE # Logical: TRUE, FALSE 28 | varC <- "Hello" # Character 29 | ``` 30 | 31 | ### 2.2 Factor 32 | 33 | ``` 34 | sample <- c("M","F","M","F","F") 35 | gender <- factor(sample) 36 | summary(gender) 37 | ``` 38 | 39 | ### 2.3. Data Structure 40 | 41 | ``` 42 | vec1 <- c() # Vector 43 | list <- list() # List 44 | world <- data.frame() # Data Frame 45 | ``` 46 | 47 | ### 2.4. Useful Function 48 | 49 | ``` 50 | help(name) # Help Document 51 | length(object) # number of elements or components 52 | str(object) # structure of an object 53 | class(object) # class or type of an object 54 | summary(object) # result summaries 55 | ``` 56 | 57 | ## 3. Descriptive Statistics 58 | 59 | - `mean(), median(), min(), max(), quartile(), range(), sd(), var(), iqr()` 60 | - `mean(nums,na.rm = TRUE)` to handle NA (Not Available’ / Missing Values) Value 61 | 62 | ``` 63 | # Finding mode 64 | library(DescTools) 65 | Mode() 66 | ``` 67 | 68 | ## 4. Explore the datasets in base R 69 | 70 | ### 4.1. Loading Data 71 | 72 | ``` 73 | data() 74 | read.csv("filename") 75 | 76 | # readr package 77 | library(readr) # A fast and friendly way to read rectangular data 78 | read_csv("filename") 79 | write_csv(data,file = "filename") 80 | ``` 81 | 82 | ### 4.2. Useful Function 83 | 84 | ``` 85 | View(obj) # Invoke a Data Viewer 86 | head() # See 6 observation (rows) 87 | str() # Structure of object 88 | colnames() # Column Name 89 | rownames() # Row Name 90 | colMeans() # Mean each column 91 | rowMeans() # Mean each row 92 | colSums() # Sum each column 93 | rowSums() # Sum each row 94 | table() # Cross Tabulation and Table Creation 95 | ``` 96 | 97 | ``` 98 | mtcars[1,] # Select first row with all column 99 | mtcars[,1] # Select all row with only first column 100 | ``` 101 | 102 | ## 5. Packages 103 | 104 | ``` 105 | install.packages(name) # Install Package 106 | library(name) # Loading/Attaching and Listing of Packages 107 | help(package=name) # Read description 108 | ``` 109 | 110 | - `dplyr`: data manipulation 111 | - `tidyr`: help you create tidy data 112 | - `readr`: A fast and friendly way to read rectangular data 113 | - `stringr`: Character manipulation 114 | - `assertive`: Readable check functions to ensure code integrity 115 | - `lubridate`: Handle datetime format 116 | 117 | ## 6. dplyr Package 118 | 119 | ``` 120 | library(dplyr) 121 | ``` 122 | 123 | ## 6.1 Function 124 | 125 | ``` 126 | cars <- as_tibble(mtcars) # enhanced version of data.frames 127 | glimpse(cars) # print the data similar str() function 128 | cars %>% head() # Using The Pipes Operator in R 129 | ``` 130 | 131 | ## 6.2 Data Manipulation and Transformation 132 | 133 | ``` 134 | select() # picks variables based on their names. 135 | filter() # picks cases based on their values. 136 | arrange() # changes the ordering of the rows. 137 | group_by() # takes a data frame and one or more variables to group by 138 | summarise() # reduces multiple values down to a single summary. 139 | mutate() # adds new variables that are functions of existing variables 140 | transmute() # adds new variables and drops existing ones. 141 | rename() # renaming columns 142 | count() # Count observations by group 143 | ``` 144 | 145 | For example 146 | 147 | ``` 148 | starwars %>% select(name,height) 149 | starwars %>% filter(sex == "male",skin_color == "light") 150 | starwars %>% arrange(height) 151 | starwars %>% summarise(height = mean(height, na.rm = TRUE)) 152 | starwars %>% group_by(sex) %>% select(height) %>% summarise(avg = mean(height, na.rm = TRUE)) 153 | starwars %>% rename(hair=hair_color) 154 | starwars %>% mutate(height_m = height / 100) 155 | starwars %>% transmute(height_m = height / 100) 156 | ``` 157 | 158 | ## 7. Checking and Changing the Type of Value 159 | 160 | ``` 161 | library(assertive) # Readable check functions to ensure code integrity 162 | ``` 163 | 164 | ### 7.1. Checking the types of values 165 | 166 | - Logical checking: returns TRUE or FALSE 167 | - `assertive` checking: errors when FALSE (using assertive package) 168 | 169 | ``` 170 | # Logical checking 171 | is.character() 172 | is.numeric() 173 | is.logical() 174 | is.factor() 175 | is.Date() 176 | is.na() 177 | 178 | # assertive 179 | assert_is_character() 180 | assert_is_numeric() 181 | ... 182 | ``` 183 | 184 | ### 7.2. Changing the types of values 185 | 186 | ``` 187 | as.character() 188 | as.factor() 189 | as.numeric() 190 | ``` 191 | 192 | ## 8. Handling String with stringr 193 | 194 | ``` 195 | library(stringr) # Character manipulation 196 | 197 | str_trim(string) # Trim whitespace from a string 198 | str_remove(string, pattern) # Remove matched patterns in a string 199 | str_split(string) # Split up a string into pieces 200 | str_sub(string, start = 1L, end = -1L) # Extract and replace substrings from a character vector 201 | ``` 202 | 203 | ## 9. Removing duplicate data 204 | 205 | ``` 206 | duplicated() # return a logical vector, if duplicate will return TRUE. 207 | distinct() # Select only unique/distinct rows from a data frame. 208 | ``` 209 | 210 | Using with dplyr package 211 | 212 | ``` 213 | products %>% duplicated() %>% sum() 214 | products %>% distinct() 215 | ``` 216 | 217 | ## 10. Handling missing values 218 | 219 | ``` 220 | na.omit() 221 | ``` 222 | 223 | ## 11. Outliers data & Range Values 224 | 225 | ``` 226 | replace(col, condition, replacement) # Replace value with condition 227 | assert_all_are_in_closed_range(col, lower = l1, upper = u1) # Check in range of [l1,u1] 228 | ``` 229 | -------------------------------------------------------------------------------- /workshop/07-DataViz.md: -------------------------------------------------------------------------------- 1 | # 07 Data Visualization 2 | 3 | ## Agenda 4 | 5 | - What is Data Visualization 6 | - Creating a Basic Graph 7 | - Using ggplot2 Package 8 | 9 | ## Objective 10 | 11 | 1. Understand what is Data Visualization. 12 | 2. Know basic command to create graph with ggplot2 package. 13 | 14 | ## 0. Prerequisites 15 | 16 | 1. Open progress form [Class 06](https://forms.gle/RVzkkH18FLRWaavW8) and checked on Study Check-In 17 | 2. Open R Studio Desktop and setting working directory 18 | 3. Create Script file name `06_63130500xxx.R` and save in your working directory 19 | 4. Install new packages: `ggplot2`. 20 | 5. Loading package: `dplyr`,`readr` 21 | 6. Checked on 0 prerequisite in progress form 22 | 23 | ## What is Data Visualization 24 | 25 | Data Visualization (Data Viz) is an interdisciplinary field that deals with the graphic representation of data. It has its roots in the field of Statistics and is therefore generally considered a branch of **Descriptive Statistics**. However, because both design skills and statistical and computing skills are required to visualize effectively, it is argued by some authors that it is both an **Art and a Science**. You can learn Fundamentals of Data Visualization in [https://clauswilke.com/dataviz/](https://clauswilke.com/dataviz/) 26 | 27 | Before to creating a graph in R you need to know that in this class, I want you to learn basic for creating a graphs only. Understand the data more. Don't focus or serious about design in R. After this part,I will let introduce you to using BI Tools with more easily to create and visualize the data. 28 | 29 | ## 1. Creating a Graph (Base R) 30 | 31 | In R, graphs are typically created interactively. You can create several graphs. I have summary basic command to create graph with using data `starwars` from dplyr package: 32 | 33 | | Graph | Command | 34 | | ------------ | ---------------------------------------------------------------------------------- | 35 | | Histogram | `hist(starwars$height)` | 36 | | Density Plot | `plot(density(starwars$height,na.rm = T))` | 37 | | Scatter Plot | `plot(x=starwars$height, y=starwars$mass)` | 38 | | Bar Chart | `barplot(table(starwars$sex))` | 39 | | Pie Chart | `pie(table(starwars$sex))` | 40 | | Box Plot | `boxplot(starwars$mass,data=starwars)` or `boxplot(starwars$height,data=starwars)` | 41 | 42 | ### Marvel Cinematic Universe dataset 43 | 44 | This dataset is about's film and television in Marvel Cinematic Universe. It includes name of movie and years of film that released. Let's using this dataset to explore and create a graph to shown "Number of Released Marvel Movies". 45 | 46 | ``` 47 | # Load data 48 | Marvels <- read_csv("https://raw.githubusercontent.com/safesit23/INT214-Statistics/main/datasets/Marvels.csv") 49 | ``` 50 | 51 | Step 1: Creating a basic Bar Graph 52 | 53 | ``` 54 | # Set data 55 | count_marvel <-table(Marvels$years) 56 | 57 | # Create graph 58 | barplot(count_marvel) 59 | ``` 60 | 61 | Step 2: Adding component of graph 62 | 63 | ``` 64 | barplot(count_marvel, 65 | main = "Number of Released Marvel Movies", # Title of graphs 66 | xlab = "Year Released", # X-Axis Title 67 | ylab = "Number of Movies", # Y-Axis Title 68 | ) 69 | ``` 70 | 71 | ## 2. Using ggplot2 Package 72 | 73 | ggplot2 is a system for declaratively creating graphics, based on **The Grammar of Graphics**. You provide the data, tell ggplot2 how to map variables to aesthetics, what graphical primitives to use, and it takes care of the details. (See more details: [ggplot2 Package](https://ggplot2.tidyverse.org/), [ggplot2: elegant graphics for data analysis](https://ggplot2-book.org/index.html)) 74 | 75 | - Data: The dataset being plotted. 76 | - Aesthetics: The scales onto which we map our data. 77 | - Geometries: The visual elements ued for our data. 78 | 79 | All ggplot2 plots begin with a call to ggplot(), supplying default data and aesthethic mappings, specified by aes(). You can add layers, scales, coords and facets with symbol `+` after ggplot().See more details: [Layers](https://ggplot2.tidyverse.org/reference/) 80 | 81 | ``` 82 | ggplot(dataset,aes(x=colName,y=colName)) + geom_xxxx() 83 | ``` 84 | 85 | ### 2.1. Example 1: Bar chart with Marvels dataset 86 | 87 | Step 1: Creating a basic Bar Graph 88 | 89 | ``` 90 | ggplot(Marvels,aes(x=years)) + geom_bar() 91 | ``` 92 | 93 | Step 2: Adding component of graph 94 | 95 | ``` 96 | # Save to object 97 | marvel_plot <- ggplot(Marvels,aes(x=years)) + geom_bar() 98 | 99 | # Adding component 100 | marvel_plot + ggtitle("Number of Released Marvel Movies") + 101 | xlab("Year Released") + ylab("Number of Movies") 102 | ``` 103 | 104 | ### 2.2. Example 2: Scatter Plot with starwars dataset 105 | 106 | Step 1: Creating a scatter plot 107 | 108 | ``` 109 | starwars %>% ggplot(aes(x=height,y=mass))+geom_point() 110 | ``` 111 | 112 | Step 2: Using filter data to expand more details 113 | 114 | ``` 115 | starwars %>% filter(mass<500) %>% ggplot(aes(x=height,y=mass)) + geom_point() 116 | ``` 117 | 118 | Step 3: Label gender with color 119 | 120 | ``` 121 | scat_plot <- starwars %>% filter(mass<500) %>% ggplot(aes(x=height,y=mass))+ 122 | geom_point(aes(color=gender)) 123 | scat_plot 124 | ``` 125 | 126 | Step 4: Adding a line of best fit to a plot 127 | 128 | ``` 129 | scat_plot+geom_smooth() #default value - loess 130 | scat_plot+geom_smooth(method="lm") #linear model 131 | ``` 132 | 133 | Try another graphs with yourself more: https://www.r-graph-gallery.com/ 134 | 135 | ## 3. Exercise in Class 136 | 137 | - Try to Create histogram graph to see the height \*\*Try to use `binwidth = 10` in geometries. (Read about's binwidth [more](https://ggplot2.tidyverse.org/reference/geom_histogram.html)) 138 | ``` 139 | // Try with yourself 140 | ``` 141 | 142 | ## Self Learning and Extra Knowledge: 143 | 144 | ### A.) Learning more 145 | 146 | It has many free online course about Data Visualization. You can study in these course to more understand by learning with yourself. 147 | 148 | - [Datacamp: Data Visualization in R](https://learn.datacamp.com/courses/data-visualization-in-r) 149 | - [Datacamp: Introduction to Data Visualization with ggplot2](https://learn.datacamp.com/courses/introduction-to-data-visualization-with-ggplot2) 150 | - [Datacamp: Intermediate Data Visualization with ggplot2](https://learn.datacamp.com/courses/intermediate-data-visualization-with-ggplot2) 151 | - [codecademy: Fundamentals of Data Visualization with ggplot2](https://www.codecademy.com/courses/learn-r/lessons/intro-visualization-ggplot2-r) 152 | 153 | ### B.) More Practice 154 | 155 | 1. (Easy) Using [datasets](https://github.com/safesit23/INT214-Statistics/tree/main/datasets) that used in class (e.g. survey, cats, mtcars, products) and visualize the data. 156 | 2. (Advanced) Download full dataset from [Stack Overflow Annual Developer Survey](https://insights.stackoverflow.com/survey) and try to transform data and visualize data same as [result](https://insights.stackoverflow.com/survey/2021) 157 | 158 | ## Individual Assignment (5 %) 159 | 160 | [Click here to see details](../assignment/04-week8.md) 161 | -------------------------------------------------------------------------------- /workshop/03-Explore-01.md: -------------------------------------------------------------------------------- 1 | # 03 Explore Data Part I: Statistic and Datasets 2 | 3 | ## Agenda 4 | 5 | - Review Data Types & Data Structures 6 | - Review Descriptive Statistics 7 | - Install Packages in R 8 | - Factors (One of data type) 9 | - Explore the datasets in base R 10 | - Explore datasets from CSV 11 | 12 | ## 0. Prerequisites 13 | 14 | 1. Open R Studio Desktop and setting working directory 15 | 2. Open Slide [03 Explore Data Part I](https://drive.google.com/file/d/1L9sQGIH_aOA2IHkiXE1XrLKvlr_ge8Il/view) 16 | 3. Create Script file name `03_63130500xxx.R` and save in your working directory 17 | 4. run command `install.packages("DescTools")` (This command will use in Topic 2) 18 | 5. Open progress form [Class 03](https://forms.gle/n34yEsZKmrqv5ydK9) and checked on Study Check-In and 0 prerequisite 19 | 20 | ## Review Week 2: Data Type and Data Structure 21 | 22 | ``` 23 | # Data type 24 | varA <- 100 # Numeric ex 1, 1.0 25 | varB <- TRUE # Logical: TRUE, FALSE 26 | varC <- "Hello World!" # Character 27 | 28 | # Data Structure 29 | vec1 <- c() # Vector 30 | list <- list() # List 31 | world <- data.frame() # Data Frame 32 | 33 | # Useful Functions 34 | length() # number of elements or components 35 | str() # structure of an object 36 | class() # class or type of an object 37 | summary() # result summaries 38 | ``` 39 | 40 | ## 1. Review Descriptive Statistics 41 | 42 | - In R Programming, we can find descriptive statistics by using: 43 | `mean(), median(), min(), max(), quartile(), range(), sd(), var(), iqr()` 44 | - When we using function we need to understand which function is appropriate for data. 45 | 46 | Try to measures of central value (วัดค่ากลาง) of this sample data: 47 | 48 | ``` 49 | # Sample datasets 50 | sample1 <- c(29,49,42,43,32,38,37,41,27,27,30) 51 | sample2 <- c(1,2,3,5,10,500) 52 | sample3 <- c("Male","Female","Male","Female","Female") 53 | ``` 54 | 55 | If you observe, you will find that in base R not has function to find **mode**. The `mode()` in R base is using for get the type mode of an object. You need to finding manually. If the data have more than 1 million. How should you do ? We wouldn't be so mean. 56 | I want to present 2 ways that you will get mode: 57 | 58 | 1. Using function `table()` (enhanced version of data.frames) 59 | 2. Install Packages 60 | 61 | ``` 62 | ### Cross Tabulation and Table Creation 63 | table(sample1) 64 | ``` 65 | 66 | ## 2. Install Packages in R 67 | 68 | A package is a suitable way to organize your own work and, if you want to, share it with others. Typically, a package will include code (not only R code!), documentation for the package and the functions inside, some tests to check everything works as it should, and datasets. [Ref: DataCamp](https://www.datacamp.com/community/tutorials/r-packages-guide) 69 | 70 | ``` 71 | # Install Package 72 | install.packages(name) 73 | 74 | # Loading/Attaching and Listing of Packages 75 | library(name) 76 | 77 | # Read description 78 | help(package=name) 79 | ``` 80 | 81 | Let's try to install **Tools for Descriptive Statistics** package (If you have problem, you can use GUI to install package.) 82 | 83 | ``` 84 | # DescTools package 85 | install.packages("DescTools") 86 | 87 | library(DescTools) 88 | help(package=DescTools) 89 | ``` 90 | 91 | Now you can finding mode by using `Mode()` function 92 | 93 | ``` 94 | Mode(sample1) 95 | ``` 96 | 97 | Try to using this function with `marvel_movies` and tell me the result. 98 | 99 | ## 3. Factors 100 | 101 | Factors is one of data type in R. It's appropriate for nominal value (ข้อมูลเชิงปริมาณ หรือ 102 | ข้อมูลที่ไม่ใช่ตัวเลข) such as: gender (male / female), Class (1st / 2nd / 3rd). We can use `factor()` function to see levels of object 103 | 104 | ``` 105 | factor(sample3) 106 | 107 | # treats gender as a nominal variable 108 | gender <- factor(sample3) 109 | summary(gender) 110 | ``` 111 | 112 | Ref: https://www.statmethods.net/input/datatypes.html 113 | 114 | ## 4. Explore the datasets in base R 115 | 116 | In base R has built-in datasets. To see the list of datasets, you can using `data()` function. 117 | The popular used R demo datasets is mtcars, iris, ToothGrowth, PlantGrowth and USArrests. 118 | 119 | ```{R} 120 | data() 121 | ``` 122 | 123 | ### Explore overview dataset 124 | 125 | ``` 126 | head() # See 6 observation (rows) 127 | str() # Structure of object 128 | colnames() # Column Name 129 | rownames() # Row Name 130 | colMeans() # Mean each column 131 | rowMeans() # Mean each row 132 | colSums() # Sum each column 133 | rowSums() # Sum each row 134 | ``` 135 | 136 | ### Data set: Motor Trend Car Road Tests 137 | 138 | We will use `mtcars` datasets to explore data 139 | 140 | ``` 141 | View(mtcars) 142 | ``` 143 | 144 | ``` 145 | str(mtcars) 146 | head(mtcars) 147 | summary(mtcars) 148 | colMeans(mtcars) 149 | ``` 150 | 151 | ### Inspect inside dataset 152 | 153 | We can select one column to calculate some thing by using `df$col`. Example, we want to finding average of miles per gallon in Motor Trend Car Road Tests. 154 | 155 | ``` 156 | # Find mean of miles per gallon (mpg) 157 | mean(mtcars$mpg) # 20.09062 158 | ``` 159 | 160 | ### Self Study: 161 | 162 | Moreover, we can select row and column by using format: `df[row,col]` 163 | 164 | ``` 165 | mtcars[1,] # Select first row with all column 166 | mtcars[,1] # Select all row with only first column 167 | mtcars["Datsun 710","wt"] # Select by specific row and column 168 | mtcars[1:5,] # Select row 1-5 with all column 169 | ``` 170 | 171 | ## 5. Explore datasets from CSV 172 | 173 | In R, we can import datasets from CSV (comma-separated values) files by using function `read.csv()`. If you import from local you need to set path correctly. 174 | 175 | ```{R} 176 | Hotels <- read.csv("https://raw.githubusercontent.com/safesit23/INT214-Statistics/main/datasets/Hotels.csv") 177 | View(Hotels) 178 | ``` 179 | ### Extra 180 | In R has library named `readr` that can read CSV file by using function `read_csv()` 181 | 182 | ### Exercise: 183 | 184 | - How many observation ? (จำนวนข้อมูล) 185 | - What is the mean hotel room rate ? 186 | - What is the median hotel room rate ? 187 | - What is the mode ? 188 | 189 | Dataset from: Chapter 3, page 92 – 93, Statistic for Business and Economics 190 | 191 | ## Notes 192 | 193 | ### Useful Function in week 3 194 | 195 | ``` 196 | View(obj) # Invoke a Data Viewer 197 | table(obj) # Cross Tabulation and Table Creation 198 | library(obj) # Loading/Attaching and Listing of Packages 199 | Mode(obj) # Mode in descriptive stat 200 | data() # See all datasets in R 201 | head(obj) # See the First 6 observation of an Object 202 | factor(obj) # Category 203 | ``` 204 | 205 | ### Library in week 3 206 | 207 | ``` 208 | library(DescTools) # DescTools package 209 | library(MASS) # Support Functions and Datasets for Venables and Ripley's MASS 210 | ``` 211 | 212 | ## Self Learning Activity: 213 | 214 | ### A. Explore more datasets 215 | 216 | #### 1. Install and loading `MASS` package 217 | 218 | ``` 219 | install.packages("MASS") 220 | library(MASS) 221 | ``` 222 | 223 | #### 2. Explore this 2 dataset that given 224 | 225 | - Cats (Ref: https://www.rdocumentation.org/packages/MASS/versions/7.3-47/topics/cats) 226 | - Survey (Ref: https://www.rdocumentation.org/packages/MASS/versions/7.3-47/topics/survey) 227 | 228 | #### 3. Finding descriptive statistics and summary result in form of sentences/paragraph. For example, 229 | 230 | - From survey, most students use left hand writing. 231 | - The average of body weight of cats is xxx kg. 232 | 233 | After you have done, you need to sharing and working with your group as [Assignment 2](https://github.com/safesit23/INT214-Statistics/tree/main/assignment). 234 | 235 | ### B. What is NA Values ? 236 | 237 | In the survey dataset, it has `NA` values. `NA` mean ‘Not Available’ / Missing Values. 238 | If you try to find `mean()`, it will get result `NA` because in that vector has `NA` value. 239 | You need to handle `NA` values by add parameter `na.rm` in function. For example: 240 | 241 | ``` 242 | nums <- c(1,2,3,4,NA) 243 | mean(nums,na.rm = TRUE) 244 | ``` 245 | 246 | ### C. Pipes Operator in R 247 | 248 | - You need to install and loading `dplyr` package 249 | - `f(x)` can be rewritten as `x %>% f` 250 | - In short, this means that functions that take one argument, function(argument), can be rewritten as follows: `argument %>% function()`. Ref: [Data Camp](https://www.datacamp.com/community/tutorials/pipe-r-tutorial#howto) 251 | 252 | Try to use `%>%` operator and see the result. Is it same ? 253 | 254 | ``` 255 | # In class 256 | mean(mtcars$mpg) 257 | 258 | # Use pipes operator 259 | mtcars$mpg %>% mean() 260 | ``` 261 | -------------------------------------------------------------------------------- /workshop/04-Explore-02.md: -------------------------------------------------------------------------------- 1 | # 04 Explore Data Part II: Data Manipulation 2 | 3 | ## Agenda 4 | 5 | - Review Explore Data Part I 6 | - Introduction to dplyr Package 7 | - Grammar of data manipulation 8 | 9 | ## 0. Prerequisites 10 | 11 | 1. Open R Studio Desktop and setting working directory 12 | 2. Create Script file name `04_63130500xxx.R` and save in your working directory 13 | 3. Install and Loading `dplyr` packages (If install success, you cau using `glimpse(mtcars)` function) 14 | 4. Open progress form [Class 04](https://forms.gle/54xmje433KUDnPNn8) and checked on Study Check-In and 0 prerequisite 15 | 16 | ## Review Explore Data Part I 17 | 18 | In last week, we learnt: 19 | 20 | 1. How to install packages in R 21 | 2. Using `Mode()` function 22 | 3. Factors data type 23 | 4. Explore datasets and import datasets from CSV 24 | 25 | ``` 26 | # Useful Function 27 | library(package) # Loading/Attaching and Listing of Packages 28 | View(obj) # Invoke a Data Viewer 29 | head(obj) # See the First 6 observation of an Object 30 | summary(obj) # Summary data 31 | factor(obj) # Category 32 | ``` 33 | 34 | ``` 35 | # Import datasets from CSV 36 | Hotels <- read.csv("https://raw.githubusercontent.com/safesit23/INT214-Statistics/main/datasets/Hotels.csv") 37 | Hotels <- read.csv("Hotels.csv") 38 | ``` 39 | 40 | ## 1. Introduction to dplyr Package 41 | 42 | The dplyr package in R is designed to make data manipulation tasks simpler and more intuitive than working with base R functions only. Called a **“grammar of data manipulation”**, dplyr provides functions that solve many challenges that arise when organizing tabular data (i.e., data in a table with rows and columns). Tabular data has a lot of the same functionality as tables from SQL or Excel, but dplyr adds the power of R. (Ref: [dpylr](https://dplyr.tidyverse.org)) 43 | 44 | ``` 45 | library(dplyr) 46 | ``` 47 | 48 | Before we learning grammar of data manipulation, you need to know pipes and tibble. 49 | 50 | ### 1.1. The Pipes Operator in R 51 | 52 | All of the dplyr functions take a data frame (or tibble) as the first argument. Rather than forcing the user to either save intermediate objects or nest functions, dplyr provides the `%>%` operator from magrittr. `x %>% f(y)` turns into `f(x, y)` (References: [Data Camp](https://www.datacamp.com/community/tutorials/pipe-r-tutorial#howto), [The pipe](https://dplyr.tidyverse.org/articles/dplyr.html#the-pipe)) 53 | 54 | ``` 55 | # Sample 1: head() 56 | head(Hotels$RateperNight,9) 57 | Hotels$RateperNight %>% head(9) 58 | 59 | # Sample 2: mean() 60 | mean(Hotels$RateperNight) 61 | Hotels$RateperNight %>% mean() 62 | ``` 63 | 64 | ### 1.2. Tibble 65 | 66 | Last week, we learning about `table()` which is enhanced version of data.frames. This week, I want to 67 | introduced a modern reimagining of the data frame named **Tibble**. It’s particularly useful for large datasets because it only prints the first few rows. You can learn more about tibbles at https://tibble.tidyverse.org; in particular you can convert data frames to tibbles with `as_tibble()`. 68 | 69 | ```{R} 70 | Hotels <- as_tibble(Hotels) 71 | str(Hotels) 72 | glimpse(Hotels) 73 | ``` 74 | 75 | Glimpse Output: 76 | 77 | ``` 78 | Rows: 20 79 | Columns: 2 80 | $ City "Atlanta", "Boston", "Chicago", "Cleveland", "Dallas", "Denver", "Detroit", "Houst… 81 | $ RateperNight 163, 177, 166, 126, 123, 120, 144, 173, 160, 192, 125, 167, 245, 146, 139, 134, 16… 82 | ``` 83 | 84 | ### 1.3. Data: starwars 85 | 86 | In dplyr packages has build-in dataset named `starwars` which ia about Starwars characters. (Learn more: [RDocumentation](https://www.rdocumentation.org/packages/dplyr/versions/0.7.8/topics/starwars)) Let's explore this dataset: 87 | 88 | ``` 89 | starwars 90 | glimpse(starwars) 91 | ``` 92 | 93 | Answer following question: 94 | 95 | 1. How many observation and variable ? 96 | 2. What is data type of mass and height ? 97 | 3. What is average height of Starwars characters ? 98 | 99 | ## 2. Grammar of data manipulation 100 | 101 | dplyr is a grammar of data manipulation, providing a consistent set of verbs/adverbs that help you solve the most common data manipulation challenges: 102 | 103 | - `select()` picks variables based on their names. 104 | - `filter()` picks cases based on their values. 105 | - `arrange()` changes the ordering of the rows. 106 | - `group_by()` takes a data frame and one or more variables to group by 107 | - `summarise()` reduces multiple values down to a single summary. 108 | - `mutate()` adds new variables that are functions of existing variables (Next class) 109 | - `transmute()` adds new variables and drops existing ones. (Next class) 110 | - `rename()` renaming columns (Next class) 111 | 112 | Cheatsheets: https://github.com/rstudio/cheatsheets/blob/master/data-transformation.pdf 113 | 114 | ### 2.1. Selecting 115 | 116 | You can using `select()` to select columns (Learn more: [dplyr](https://dplyr.tidyverse.org/articles/dplyr.html#select-columns-with-select)) 117 | 118 | ``` 119 | # Selecting Columns 120 | select(starwars,name,height) 121 | 122 | # In class we use: 123 | starwars %>% select(name,height) 124 | ``` 125 | 126 | \*\*If you import many libraries, it can has same function named such as MASS and dplyr has same function named `select`. You need to specific package like `dplyr::select()` 127 | 128 | Moreover, you can excluding some solumn 129 | 130 | ``` 131 | #Excluding 132 | starwars %>% select(-hair_color,-skin_color,-eye_color) 133 | ``` 134 | 135 | ### 2.2. Filtering 136 | 137 | You can using `filter()` to select a subset of rows in a data frame(Learn more: [dplyr](https://dplyr.tidyverse.org/articles/dplyr.html#filter-rows-with-filter)) 138 | 139 | ``` 140 | starwars %>% filter(sex == "male") 141 | starwars %>% filter(!(sex == "male")) 142 | starwars %>% filter(sex == "male" | skin_color == "light") # or 143 | starwars %>% filter(sex == "male",skin_color == "light") # and 144 | ``` 145 | 146 | ### 2.3. Arranging 147 | 148 | You can using `arrange()` to filter rows (Learn more: [dplyr](https://dplyr.tidyverse.org/articles/dplyr.html#arrange-rows-with-arrange)) 149 | 150 | ``` 151 | starwars %>% arrange(height) 152 | starwars %>% arrange(desc(height)) 153 | ``` 154 | 155 | ### 2.4. Summarise 156 | 157 | You can using `summarise()` to collapses a data frame to a single row. (Learn more: [dplyr](https://dplyr.tidyverse.org/articles/dplyr.html#summarise-values-with-summarise)) 158 | 159 | ``` 160 | starwars %>% summarise(height = mean(height, na.rm = TRUE)) 161 | ``` 162 | 163 | ## 3. Combining functions with %>% 164 | 165 | So you can use it to rewrite multiple operations that you can read left-to-right, top-to-bottom, reading the pipe operator as “then” (Learn more: [dplyr](https://dplyr.tidyverse.org/articles/dplyr.html#combining-functions-with-)) 166 | 167 | #### Example 1: Select name, height, mass, and skin color then shows only skin color is light: 168 | 169 | ``` 170 | starwars %>% select(name,height,mass, skin_color) %>% filter(skin_color=="light") 171 | ``` 172 | 173 | #### Example 2: Find average height of each sex: 174 | 175 | ``` 176 | starwars %>% group_by(sex) %>% select(height) %>% summarise(avg = mean(height, na.rm = TRUE)) 177 | ``` 178 | ** Read more about [group_by](https://dplyr.tidyverse.org/articles/grouping.html#group_by) 179 | 180 | #### Example 3: Mass of Starwars characters who is male in descending order 181 | 182 | ``` 183 | starwars %>% filter(sex=="male") %>% dplyr::select(name,mass) %>% arrange(desc(mass)) 184 | ``` 185 | 186 | ## Self Learning Activity: 187 | 188 | ### A.) Learning more about Data Manipulation 189 | 190 | It has many free online course about Data Manipulation. You can study in these course to more understand by learning with yourself. 191 | 192 | - [codecademy: INTRODUCTION TO DATA FRAMES IN R](https://www.codecademy.com/courses/learn-r/lessons/r-data-frames-intro) 193 | - [datacamp: Data Manipulation with dplyr](https://www.datacamp.com/courses/data-manipulation-with-dplyr) 194 | 195 | ### B.) Read more... 196 | 197 | - tibble: https://tibble.tidyverse.org/ 198 | - Count observations by group: https://dplyr.tidyverse.org/reference/count.html 199 | 200 | ### C.) Try to doing with yourself (Exercise) 201 | 1. Find a list of name and height who is the first 12 tallest star wars characters. 202 | 2. Finding name of star wars characters who is height equal 202. 203 | 3. How many star wars characters who has blue eye but not human species ? 204 | 4. From question 3, how many characters in each species ? 205 | 5. Finding average height and mass of each species then show only 10 species that have average height by descending order. 206 | 6. (Advanced-Optional) From question 5, using `mutate()`(Read how to used: [dplyr](https://dplyr.tidyverse.org/articles/dplyr.html#add-new-columns-with-mutate-)) to create new column `BMI` and calculate BMI and order by BMI in descending order. Result shoule be like this: 207 | ``` 208 | species height mass BMI 209 | 210 | 1 Hutt 175 1358 443. 211 | 2 Vulptereen 94 45 50.9 212 | 3 Droid 131. 69.8 40.5 213 | ... 214 | ``` 215 | 216 | ## Group Assignment: 217 | See in [Assignment 3](../assignment/03-week4.md) 218 | -------------------------------------------------------------------------------- /workshop/08-HypoTesting.md: -------------------------------------------------------------------------------- 1 | # 08 Hypothesis Testing 2 | 3 | ## Agenda 4 | 5 | - Review: Descriptive Statistics 6 | - Sample and Population 7 | - Point Estimation 8 | - Normal Distribution 9 | - Hypothesis testing 10 | 11 | ## 0. Prerequisites 12 | 13 | 1. Open progress form [Class 07](https://forms.gle/GbotmGNTwwa2yf3w7) and checked on Study Check-In 14 | 2. Open R Studio Desktop and setting working directory 15 | 3. Create Script file name `07_63130500xxx.R` and save in your working directory 16 | 4. Checked on 0 prerequisite in progress form 17 | 5. Loading `dplyr`, `readr` packages 18 | 19 | ## Review: Descriptive Statistics 20 | 21 | - In R Programming, we can find descriptive statistics by using: 22 | `mean(), median(), min(), max(), quartile(), range(), sd(), var(), IQR()` 23 | - You can find square-root by using function: `sqrt()` 24 | 25 | ## 1. Sample and Population 26 | 27 | ``` 28 | # Sample Data 29 | sample(1:5, 3) 30 | 31 | # Sample n rows from a table 32 | mtcars %>% sample_n(2) 33 | ``` 34 | 35 | In R, we can using `rnorm()` to generate random data with Normal Distribution 36 | 37 | ``` 38 | # Generated Random Data with Normal Distribution 39 | population_1 <- rnorm(20, mean=65, sd=3.5) 40 | 41 | # Sample Data 42 | sample_1 <- sample(population_1 , 3) 43 | ``` 44 | 45 | ## 2. Point Estimation 46 | 47 | Point estimation involves the use of sample data to calculate a single value. In Statistics, we use 48 | 49 | - Mean: x̄ (sample), μ (population) Using`mean(nums)` 50 | - S.D. : S (sample), σ (population) Using `sd(nums)` 51 | - Proportion: p (sample), p (population) 52 | 53 | ### 2.1. Mean 54 | 55 | 1. Finding average height of `starwars` characters. 56 | 2. Finding average height of `starwars` characters which sex is `male`. 57 | 58 | ``` 59 | #1.Finding average height of starwars characters. 60 | mean(starwars$height,na.rm = T) 61 | 62 | #2.Finding average height of starwars characters which sex is male. 63 | starwars %>% filter(sex=="male") %>% 64 | summarise(avg_height=mean(height,na.rm = T)) %>% pull() 65 | ``` 66 | 67 | ### 2.2. Proportion (สัดส่วน) 68 | 69 | A frequency distribution shows the number (frequency) of items in each of several non-overlapping classes. However, we are often interested in the proportion, or percentage, of items in each class. The relative frequency of a class equals the fraction or proportion of items belonging to a class. 70 | 71 | Formula: p = จำนวนที่สนใจ (i) / จำนวนทั้งหมด (n) 72 | 73 | ``` 74 | # Example Proportion of male 75 | i <- starwars %>% filter(sex=="male") %>% count() %>% pull() 76 | n <- starwars %>% count() %>% pull() 77 | p <- i/n; p 78 | ``` 79 | 80 | \*\* `pull()` is function in `dplyr` packages using for Extract a single column 81 | 82 | ## 3. Normal Distribution 83 | 84 | ### 3.1 Standard Score (Z) 85 | 86 | - Formula: z = x-x̄ / S.D. 87 | 88 | #### Finding Cumulative probability (พื้นที่ใต้กราฟ) 89 | 90 | - In excel, we using `=NORM.DIST(x, mean, S.D ,cumulative)` 91 | - In R, we using 92 | 93 | ``` 94 | pnorm(x, mean, sd) 95 | ``` 96 | 97 | #### Finding Z-Score 98 | 99 | - In excel, we using `=NORM.S.INV(prob)` (ค่าผกผันของการแจกแจงสะสมปกติมาตรฐาน) 100 | - In R, we using 101 | 102 | ``` 103 | qnorm(prob, mean = 0, sd = 1, lower.tail = TRUE) 104 | ``` 105 | 106 | ### 3.2 Student’s t-Distribution 107 | 108 | #### Finding Cumulative probability (พื้นที่ใต้กราฟ) 109 | 110 | - In excel, we using `=T.DIST(x, deg_freedom, cumulative)` or `=T.DIST.RT(x,deg_freedom)` 111 | - In R, we using 112 | 113 | ``` 114 | pt(q, df,lower.tail = TRUE) 115 | ``` 116 | 117 | #### Finding t-score 118 | 119 | - In excel, we using `=T.INV(probability,deg_freedom)` (ค่าผกผันด้านซ้ายของการแจกแจงแบบ t) 120 | - In R, we using 121 | 122 | ``` 123 | qt(p, df, lower.tail = TRUE) 124 | ``` 125 | 126 | ### Let's try It 127 | ``` 128 | # Finding Z 129 | x <- 12 130 | xbar <- 10 131 | sd <- 1 132 | z <- (x-xbar)/sd;z 133 | 134 | # Finding Area 135 | prob1 <- pnorm(x,xbar,sd); prob1 136 | # Finding Z 137 | z1 <- qnorm(prob1); z1 138 | ``` 139 | 140 | ## 4. Hypothesis testing 141 | 142 | is a method of statistical inference. An alternative hypothesis is proposed for the probability distribution of the data, either explicitly or only informally. The comparison of the two models is deemed statistically significant if, according to a threshold probability—the significance level—the data would be unlikely to occur if the null hypothesis were true. [Ref](https://en.wikipedia.org/wiki/Statistical_hypothesis_testing) 143 | 144 | ### Step to do: 145 | 146 | 0. Assign variables: 147 | - u0 or p0 148 | - xbar or pbar 149 | - n 150 | - sd (or sigma) 151 | - alpha (default is 0.05) 152 | 1. State the hypothesis 153 | 2. Select Level of significance (alpha) 154 | 3. Select Test statistic (This formula for one population) 155 | - z/t <- (xbar - u0) / (sd/sqrt(n)) 156 | - z <- (pbar-p0) / sqrt((p0\*(1-p0))/n) 157 | 4. Finding P-value approach or Critical Value approach 158 | - P-value for Z: `pvalue <- pnorm(z)` 159 | - Critical Value for Z: `zalpha <- qnorm(alpha)` 160 | - P-value for T: `pvalue <- pt(q, df,lower.tail = TRUE)` 161 | - talpha for T: `talpha <- qt(p, df, lower.tail = TRUE)` 162 | 5. Compare P-value with alpha or z/t with zalpha/talpha 163 | 6. Conclusion 164 | 165 | ### Example 1 (Ref: Chapter 9 Page 356) 166 | 167 | The Federal Trade Commission (FTC) periodically conducts statistical studies designed to test the claims that manufacturers make about their products. For example, the label on a large can of Hilltop Coffee states that the can contains 3 pounds of coffee. Thus, the FTC interprets the label information on a large can of coffee as a claim by Hilltop that the population mean filling weight is at least 3 pounds per can. The director of the FTC’s testing program willing to risk a 1% chance of making such an error. Suppose a sample of 36 cans of coffee is selected and the population standard deviation can be assumed known with a value of σ = 0.18. Is x̄ = 2.92 pounds small enough to cause us to reject H0 ? 168 | 169 | Step 0: Assign variables 170 | 171 | ``` 172 | n <- 173 | sd <- 174 | xbar <- 175 | u0 <- 176 | ``` 177 | 178 | Step 1: State the hypothesis 179 | 180 | ``` 181 | #h0: ,ha: 182 | ``` 183 | 184 | Step 2: Level of significance 185 | 186 | ``` 187 | alpha <- 188 | ``` 189 | 190 | Step 3: Test statistic 191 | 192 | ``` 193 | z <- (xbar - u0) / (sd/sqrt(n));z 194 | ``` 195 | 196 | Step 4: Finding P-value approach or Critical Value approach 197 | 198 | ``` 199 | # P-value approach 200 | pvalue <- pnorm(z); pvalue 201 | 202 | # Critical Value approach 203 | zalpha <- qnorm(alpha);zalpha 204 | ``` 205 | 206 | Step 5: Compare 207 | 208 | ``` 209 | # Using p-value approach 210 | if(pvalue<=alpha){ 211 | print("Reject H0") 212 | }else{ 213 | print("Accept H0") 214 | } 215 | 216 | # Using critical value 217 | if(z<=zalpha){ 218 | print("Reject H0") 219 | }else{ 220 | print("Accept H0") 221 | } 222 | ``` 223 | 224 | Step 6: Conclusion 225 | 226 | //Answer 227 | 228 | ## 5. Exercise 229 | 230 | ### Practice 1 (Ref: Chapter 9 Question 42, Page 381) 231 | 232 | According to the University of Nevada Center for Logistics Management, 6% of all mer- chandise sold in the United States gets returned (BusinessWeek, January 15, 2007). A Houston department store sampled 80 items sold in January and found that 12 of the items were returned. Construct a 95% confidence interval for the porportion of returns at the Houston store. Is the proportion of returns at the Houston store significantly different from the returns for the nation as a whole? Provide statistical support for your answer. 233 | 234 | ### Practice 2 (Ref: Chapter 9 Question 21, Page 370) 235 | 236 | Fowle Marketing Research, Inc., bases charges to a client on the assumption that telephone surveys can be completed in a mean time of 15 minutes or less. If a longer mean survey time is necessary, a premium rate is charged. A sample of 35 surveys provided the survey times shown in the file named Fowle. Based upon past studies, the population standard deviation is assumed known with σ = 4 minutes. Is the premium rate justified ? 237 | 238 | Get dataset here: 239 | 240 | ``` 241 | https://raw.githubusercontent.com/safesit23/INT214-Statistics/main/datasets/Time.csv 242 | ``` 243 | 244 | ### Practice 3 (Ref: Chapter 10 Question 26, Page 422) 245 | 246 | The College Board provided comparisons of Scholastic Aptitude Test (SAT) scores based on the highest level of education attained by the test taker’s parents. A research hypothesis was that students whose parents had attained a higher level of education would on average score higher on the SAT. During 2003, the overall mean SAT verbal score was 507 (The World Almanac, 2004). SAT verbal scores for independent samples of students follow. The first sample shows the SAT verbal test scores for students whose parents are college graduates with a bachelor’s degree. The second sample shows the SAT verbal test scores for students whose parents are high school graduates but do not have a college degree. 247 | 248 | ``` 249 | https://raw.githubusercontent.com/safesit23/INT214-Statistics/main/datasets/StudentParents.csv 250 | ``` 251 | 252 | a. Formulate the hypotheses that can be used to determine whether the sample data sup- port the hypothesis that students show a higher population mean verbal score on the SAT if their parents attained a higher level of education. 253 | 254 | b. What is the point estimate of the difference between the means for the two populations? 255 | 256 | c. Compute the p-value for the hypothesis test. 257 | 258 | d. At α = .05, what is your conclusion? 259 | 260 | ### Practice 4 (Ref: Chapter 10 Question 40, Page 439) 261 | Mutual funds are classified as load or no-load funds. Load funds require an investor to pay an initial fee based on a percentage of the amount invested in the fund. The no-load funds do not require this initial fee. Some financial advisors argue that the load mutual funds may be worth the extra fee because these funds provide a higher mean rate of return than the no-load mutual funds. A sample of 30 load mutual funds and a sample of 30 no-load mutual funds were selected. Data were collected on the annual return for the funds over a five-year period. The data are contained in the data set Mutual. The data for the load and no-load mutual funds are as follows. 262 | ``` 263 | # Mutual-Load 264 | https://raw.githubusercontent.com/safesit23/INT214-Statistics/main/datasets/Mutual-Load.csv 265 | # Mutual-No Load 266 | https://raw.githubusercontent.com/safesit23/INT214-Statistics/main/datasets/Mutual-NoLoad.csv 267 | ``` 268 | a. Formulate H0 and Ha such that rejection of H0 leads to the conclusion that the load mu- tual funds have a higher mean annual return over the five-year period. 269 | 270 | b. Use the 60 mutual funds in the data set Mutual to conduct the hypothesis test. What is the p-value? At α = .05, what is your conclusion? 271 | 272 | ## Self Learning and Extra Knowledge: 273 | 274 | ### A.) Learning more 275 | 276 | It has many free online course about Hypothesis Testing. You can study in these course to more understand by learning with yourself. 277 | 278 | - [Datacamp: Hypothesis Testing in R](https://www.datacamp.com/courses/hypothesis-testing-in-r) 279 | - [Codecademy: Hypothesis Testing](https://www.codecademy.com/courses/learn-r/lessons/hypothesis-testing-r) 280 | - [Datacamp: Mini case study in A/B Testing](https://www.datacamp.com/courses/ab-testing-in-r) 281 | - [Thepexcel: Statistics with Excel](https://www.thepexcel.com/stats-06-hypothesis-testing/) 282 | -------------------------------------------------------------------------------- /workshop/05-Cleaning.md: -------------------------------------------------------------------------------- 1 | # 05 Data Transformation + Data Cleaning 2 | 3 | ## Agenda 4 | 5 | - Review dplyr Package 6 | - Data Transformation with dplyr (Topic 1) 7 | - Data Cleaning Concepts (Topic 2) 8 | - Guideline Data Cleaning (Topic 3 - 7) 9 | 10 | 11 | ## 0. Prerequisites 12 | 13 | 1. Open progress form [Class 05](https://forms.gle/gr2LN79drqD4hKxB9) and checked on Study Check-In 14 | 2. Open R Studio Desktop and setting working directory 15 | 3. Create Script file name `05_63130500xxx.R` and save in your working directory 16 | 4. Install new packages: `readr`,`assertive`,`stringr` packages and make sure that `dplyr` already installed. 17 | 5. Checked on 0 prerequisite in progress form 18 | 19 | ## Review dplyr Package 20 | 21 | The dplyr package in R is designed to make data manipulation (การจัดการข้อมูล) tasks simpler and more intuitive than working with base R functions only.(Ref: [dplyr](https://dplyr.tidyverse.org)) 22 | 23 | ``` 24 | library(dplyr) 25 | ``` 26 | 27 | Last week, we learned about: 28 | 29 | 1. Using pipes operator by using symbols: `%>%` ex. `starwars %>% head()` 30 | 2. Tibble which is enhanced version of data.frames 31 | 3. Using `glimpse()` function to print the data similar str() function 32 | 4. Explore `starwars` dataset 33 | 34 | ``` 35 | cars <- as_tibble(mtcars) 36 | glimpse(cars) 37 | cars %>% head() 38 | 39 | glimpse(starwars) 40 | ``` 41 | 42 | Moreover, we get to know a set of verbs/adverbs, called a grammar of data manipulation in dplyr 43 | 44 | - `select()` picks variables based on their names. 45 | - `filter()` picks cases based on their values. 46 | - `arrange()` changes the ordering of the rows. 47 | - `group_by()` takes a data frame and one or more variables to group by 48 | - `summarise()` reduces multiple values down to a single summary. 49 | 50 | ### For example: 51 | 52 | ``` 53 | starwars %>% select(name,height) 54 | starwars %>% filter(sex == "male",skin_color == "light") 55 | starwars %>% arrange(height) 56 | starwars %>% summarise(height = mean(height, na.rm = TRUE)) 57 | starwars %>% group_by(sex) %>% select(height) %>% summarise(avg = mean(height, na.rm = TRUE)) 58 | ``` 59 | 60 | Today, we continue learning remaining function from dplyr package in "Data Transformation" topic. 61 | 62 | ## 1. Data Transformation with dplyr 63 | 64 | Data transformation is the process of converting data from one format to another. (Ref Meaning: [trifacta](https://www.trifacta.com/data-transformation/)) We can use dplyr package to modifying data 65 | e.g. calculating new value, changing data type from numeric to character. We can use these function: 66 | 67 | - `rename()` renaming columns 68 | - `mutate()` adds new variables that are functions of existing variables 69 | - `transmute()` adds new variables and drops existing ones. 70 | 71 | ### 1.1. Rename 72 | 73 | `rename()` changes the names of individual variables using new_name = old_name syntax; rename_with() renames columns using a function. (Ref: [dplyr](https://dplyr.tidyverse.org/reference/rename.html)) 74 | 75 | ``` 76 | # Save into new variable 77 | sw <- starwars 78 | 79 | # Rename Column named hair_color to hair 80 | sw <- sw %>% rename(hair=hair_color) 81 | 82 | glimpse(sw) 83 | ``` 84 | 85 | ### 1.2. Mutate and Transmute 86 | 87 | `mutate()` adds new variables and preserves existing ones; `transmute()` adds new variables and drops existing ones. New variables overwrite existing variables of the same name. Variables can be removed by setting their value to NULL.(Ref: [dplyr](https://dplyr.tidyverse.org/reference/mutate.html)) 88 | 89 | ``` 90 | # Mutate 91 | sw %>% mutate(height_m = height / 100) 92 | 93 | # Transmute 94 | sw %>% transmute(height_m = height / 100) 95 | ``` 96 | 97 | ### 1.3. Drop column 98 | 99 | ``` 100 | # Create new Column 101 | sw <- sw %>% mutate(height_m = height / 100) 102 | 103 | # Drop column 104 | sw <- sw %>% select(-height_m) 105 | ``` 106 | 107 | ## 2. Data Cleaning (Concepts) 108 | 109 | Data cleaning is the process of preparing data for analysis by removing or modifying data that is incorrect, incomplete, irrelevant, duplicated, or improperly formatted. (Ref: [sisense](https://www.sisense.com/glossary/data-cleaning/)) If the data is small dataset, you can handle edit by manual but if the data is large dataset, using script is easily and make sure that all data is get treatment. 110 | 111 | Data Cleaning involves repeated cycles of screening, diagnosing, and treatment.(Ref: [Data analysis workflow](http://www.coordinationtoolkit.org/wp-content/uploads/130907-Data-flow.pdf)) I can't tell specific steps to do because it depends on your dataset. Sometimes, we found problem some points after we have analytics something. You need to more practice to more proficient and know how to handle. 112 | 113 | In this workshop we will explain the concept of Data Cleaning and use R Language for cleaning data but in real work, you can select appropiate way or tools to done this work. For example, using spreadsheet to correct the data. 114 | 115 | ### Guideline Checklist 116 | 117 | 1. Diagnosing the data - how much data cleaning we will have to do 118 | 2. Checking the types of values 119 | 3. Changing the types of values 120 | 4. Handling String with stringr 121 | 5. Handling missing data and outliers 122 | 6. Removing duplicate data 123 | 124 | ### Using packages 125 | 126 | ``` 127 | library(readr) # A fast and friendly way to read rectangular data 128 | library(stringr) # Character manipulation 129 | library(assertive) # Readable check functions to ensure code integrity 130 | ``` 131 | 132 | Cheatsheets: [readr](https://github.com/rstudio/cheatsheets/blob/master/data-import.pdf), 133 | [stringr](https://github.com/rstudio/cheatsheets/blob/master/strings.pdf) 134 | 135 | ### Dataset 1: Uniqlo Products dataset 136 | 137 | (Reference products from [UniqloTH](https://www.uniqlo.com/th/en)) This dataset is about's sample uniqlo product that sell in 2021. It includes productID, name of products, type of products, price of products, and number of sold. I want to know: 138 | 139 | 1. Gross sales of all products from this datasets. 140 | 2. Number of all products from this datasets. 141 | 142 | Starting with import [products](https://raw.githubusercontent.com/safesit23/INT214-Statistics/main/datasets/products_original.csv) dataset by using `readr` package. 143 | 144 | ``` 145 | products <- read_csv("https://raw.githubusercontent.com/safesit23/INT214-Statistics/main/datasets/products_original.csv") 146 | ``` 147 | 148 | Then, try to diagnosing the data what you need to do with this dataset. 149 | 150 | ## 3. Checking the types of values 151 | 152 | In this topics, we will focus to check the types of data is it appropriate to use or not. It has 2 ways to check type: 153 | 154 | - Logical checking: returns TRUE or FALSE 155 | - `assertive` checking: errors when FALSE (using assertive package) 156 | 157 | ``` 158 | # Logical checking 159 | is.character() 160 | is.numeric() 161 | is.logical() 162 | is.factor() 163 | is.Date() 164 | 165 | # assertive 166 | assert_is_character() 167 | assert_is_numeric() 168 | ... 169 | ``` 170 | 171 | Let's try to check in products dataset 172 | 173 | ``` 174 | is.numeric(products$price) 175 | assert_is_numeric(products$price) 176 | 177 | is.numeric(products$sold) 178 | assert_is_numeric(products$sold) 179 | 180 | is.factor(products$gender) 181 | ``` 182 | 183 | Another ways, you can used `glimpse` function to see. We found that: 184 | 185 | - `price` is in type of character because it has `THB`. We need to change to numeric 186 | - `sold` is in type of numeric. 187 | - `gender` is in type of character but we need to change to factor. 188 | 189 | ## 4. Changing the types of values 190 | 191 | We need to fix a data type to appropriate type. We using `as.xxxx()` to change data type 192 | 193 | ``` 194 | as.character() 195 | as.factor() 196 | as.numeric() 197 | ``` 198 | 199 | Let's try to change type of `gender` to factor type then, using `summary` function to see result. Don't forget to reassign in same variables 200 | 201 | ``` 202 | products$gender <- as.factor(products$gender) 203 | summary(products$gender) 204 | ``` 205 | 206 | ## 5. Handling String with stringr 207 | 208 | Strings are not glamorous, high-profile components of R, but they do play a big role in many data cleaning and preparation tasks. The stringr package provide a cohesive set of functions designed to make working with strings as easy as possible. (Study more: [stringr](https://stringr.tidyverse.org/)) 209 | All functions in stringr start with `str_` and take a vector of strings as the first argument. 210 | 211 | ### Useful function in stringr 212 | 213 | - `str_trim(string)`: Trim whitespace from a string 214 | - `str_remove(string, pattern)`: Remove matched patterns in a string 215 | - `str_split(string)`: Split up a string into pieces 216 | - `str_sub(string, start = 1L, end = -1L)`: Extract and replace substrings from a character vector 217 | 218 | Learn more function in [stringr package](https://stringr.tidyverse.org/reference/index.html) 219 | 220 | Mostly, we will use stringr to solve comma problem. Let's try to change `price` in products to numeric type and reassign into same variable. 221 | 222 | ``` 223 | products$price <- 224 | products$price %>% str_remove("THB") %>% str_trim() %>% str_remove(",") %>% as.numeric() 225 | ``` 226 | 227 | ## 6. Removing duplicate data 228 | 229 | If you view this dataset you will see the duplicate observation which is same data. We need to eliminate this duplicate data. 230 | 231 | - `duplicated()`: return a logical vector when that elements (rows) are duplicates, it will return TRUE. 232 | - `distinct()`: Select only unique/distinct rows from a data frame. 233 | 234 | ``` 235 | # Duplicate elements 236 | products %>% duplicated() %>% table() 237 | products %>% duplicated() %>% sum() 238 | products %>% filter(duplicated(products)) 239 | 240 | # Using only distinct observation 241 | products <- 242 | products %>% distinct() 243 | ``` 244 | 245 | Now, data is ready to analyze. Let's find: 246 | 247 | - Gross sales of all products from this datasets. 248 | - Number of all products from this datasets. 249 | 250 | ## 7. Handling missing data and outliers 251 | 252 | ### 7.1. Missing Data 253 | 254 | we have known `NA` values in week 3 and known how to handle when we want to find descriptive statistics. Let's quick review: 255 | 256 | ``` 257 | nums <- c(1,2,3,4,NA) 258 | mean(nums,na.rm = TRUE) 259 | ``` 260 | 261 | Now, in this topics we need to handle object 262 | 263 | - `na.omit()`: returns the object which not contain missing values (Remove missing observation) 264 | - `is.na()`: logical checking 265 | 266 | ### 7.2. Outliers data & Range Values 267 | 268 | Outliers data (ค่าผิดปกติ) is a data point that differs significantly from other observations. Some data has range of values. We need to check that the values of that data is in range or not ? For example, the midterm score has value in range between 0 to 30. If value is over 30 or under 0 it mean that the data is out of range. We need to handling out of range data by 269 | 270 | - Remove Rows 271 | - Treat as missing (NA) 272 | - Replace with range limit 273 | - Replace with other value based on domain knowledge 274 | 275 | We use function in dplyr to handling these case and using these function to help: 276 | 277 | - `replace(col, condition, replacement)`: Replace value with condition 278 | - `assert_all_are_in_closed_range(col, lower = l1, upper = u1)`: check in range of [l1,u1] 279 | 280 | ### 7.3. Let's try to do with student's score 281 | 282 | This providing dataset is about 7 student's score of statistics subject which full score of each exam is 30. Student whom absent in that examination will not have scores. During record the score, teacher had record score one of student wrong from 15 to 50. 283 | 284 | ``` 285 | std_room <- data.frame( 286 | name=c("Antony","Baifern","Caty","Daniel","Julia","Susan","Tom"), 287 | mid_score = c(29, 26, 15, 19, 22, 50, NA), 288 | final_score = c(NA, 15, 26, 19, 20, 18, 20) 289 | ) 290 | ``` 291 | 292 | Teacher need you to help cleaning the data and finding following: 293 | 294 | - Display list of students who absent in each examination. 295 | - Number of students who absent in examination. 296 | - Display list of students who has taking all exams. 297 | - Student's who get highest midterm score in this room. 298 | 299 | ``` 300 | # Display list of students who absent in each examination. 301 | std_room %>% filter(is.na(mid_score)|is.na(final_score)) 302 | 303 | # Display list of students who has taking all exams. 304 | std_room %>% na.omit() 305 | 306 | # Handling Range Values 307 | assert_all_are_in_closed_range(std_room$mid_score, lower = 0, upper = 30) 308 | assert_all_are_in_closed_range(std_room$final_score, lower = 0, upper = 30) 309 | 310 | std_room$mid_score <- replace(std_room$mid_score,std_room$mid_score == 50, 15) 311 | 312 | # Student's who get highest midterm score in this room. 313 | std_room %>% filter(mid_score==max(mid_score,na.rm = T)) 314 | ``` 315 | 316 | #### Teacher need your help more: 317 | 318 | - Finding the student who get highest total score in this room. 319 | - List all of students with total score in descending order. 320 | 321 | ``` 322 | # Try to do with yourself 323 | ``` 324 | 325 | Next, we will using knowledge from week 1-6 that you have learned to doing workshop I ([Click here](./06-Workshop1.md)) 326 | 327 | ## Self Learning and Extra Knowledge: 328 | 329 | ### A.) Learning more about Data Cleaning 330 | 331 | It has many free online course about data cleaning. You can study in these course to more understand by learning with yourself. 332 | 333 | - [codecademy: Data Cleaning in R](https://www.codecademy.com/courses/learn-r/lessons/r-data-cleaning) 334 | - [datacamp: Cleaning Data in R](https://www.datacamp.com/courses/cleaning-data-in-r) 335 | - [dataquest: Data Cleaning in R](https://www.dataquest.io/course/r-data-cleaning/) 336 | 337 | ### B.) Read more... 338 | 339 | - [An introduction to data cleaning with R](https://cran.r-project.org/doc/contrib/de_Jonge+van_der_Loo-Introduction_to_data_cleaning_with_R.pdf) 340 | - Handle a list with [Nest and unnest function](https://rstudio-education.github.io/tidyverse-cookbook/transform-tables.html#nest-a-data-frame) 341 | - Change value with [Recode function](https://dplyr.tidyverse.org/reference/recode.html) 342 | - Handle datetime format with [lubridate package](https://lubridate.tidyverse.org/) -------------------------------------------------------------------------------- /datasets/survey214_v1.csv: -------------------------------------------------------------------------------- 1 | timestamp,skill_excel,skill_r,skill_stat,int214_level,int214_att,std_ready,music_genres,salary,sec,gender,birthday,program 2 | "4/8/2021, 18:34:26",ใช้งานประจำ,เคยเขียนบ้าง,Level 2,2,5,5,"Rock, Classic, metal, hiphop 90s",30000,Sec A,เพศชาย,7/1/2002,วิทย์-คณิต 3 | "4/8/2021, 18:40:47",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 2,4,5,5,"Pop, Classic, Indy ",25000,Sec B,เพศชาย,13/6/2001,วิทย์-คณิต 4 | "4/8/2021, 18:45:21",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 2,4,5,2,"Pop, Rap, Jazz, Anime and Japanese",25000,Sec A,เพศชาย,10/4/2002,วิทย์-คณิต 5 | "4/8/2021, 18:48:20",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,4,4,3,"R&B, Rap",16000,Sec A,เพศชาย,19/6/2001,วิทย์-คณิต 6 | "4/8/2021, 18:56:17",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 2,4,3,4,"R&B, Classic, Jazz, Blues",30000,Sec B,เพศชาย,17/11/2001,ศิลป์-คำนวณ 7 | "4/8/2021, 18:59:29",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 2,3,5,4,"Pop, Rock, Rap",40000,Sec B,เพศชาย,1/1/2002,ศิลป์-คำนวณ 8 | "4/8/2021, 19:08:00",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 2,2,5,5,"Pop, Musical, Classic",35000,Sec B,เพศหญิง,7/5/2002,วิทย์-คณิต 9 | "4/8/2021, 19:12:06",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 1,3,3,3,"Pop, Rock, Jazz",15000,Sec A,เพศชาย,11/9/2001,วิทย์-คณิต 10 | "4/8/2021, 19:12:32",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 1,5,2,2,"Pop, R&B",45000,Sec A,เพศหญิง,12/2/2002,วิทย์-คณิต 11 | "4/8/2021, 19:22:13",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,3,4,3,"Pop, R&B, Jazz",40000,Sec A,เพศหญิง,12/8/2001,วิทย์-คณิต 12 | "4/8/2021, 19:49:37",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 3,2,5,5,"Pop, Rock",20000,Sec B,เพศชาย,10/10/2001,ศิลป์-คำนวณ 13 | "4/8/2021, 19:58:01",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,5,3,4,"Pop, Rock, Classic, EDM",100000,Sec A,เพศชาย,5/3/2002,วิทย์-คณิต 14 | "4/8/2021, 20:24:11",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 1,5,4,5,"JPAN,KPOP",35000,Sec A,เพศชาย,29/7/2001,ศิลป์-คำนวณ 15 | "4/8/2021, 20:24:28",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,4,2,3,"Pop, Rock, Classic",15000,Sec A,เพศชาย,12/9/2001,ศิลป์-คำนวณ 16 | "4/8/2021, 20:27:32",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,5,4,4,"Pop, Rock, R&B, Classic",20000,Sec A,เพศชาย,4/5/2001,วิทย์-คณิต 17 | "4/8/2021, 20:28:06",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 3,2,5,4,เพลงเศร้า,30000,Sec B,เพศชาย,6/4/2001,วิทย์-คณิต 18 | "4/8/2021, 20:34:03",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,3,5,5,"Pop, Musical, Classic",30000,Sec B,เพศชาย,30/4/2002,วิทย์-คณิต 19 | "4/8/2021, 20:43:59",เคยใช้บ้าง,เคยเขียนบ้าง,Level 1,4,4,3,"Pop, R&B",18000,Sec A,เพศชาย,21/1/2001,วิทย์-คณิต 20 | "4/8/2021, 21:44:49",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,4,3,3,"Pop, R&B, Rap",30000,Sec B,เพศหญิง,21/4/2002,วิทย์-คณิต 21 | "4/8/2021, 21:58:49",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 0,4,5,5,"Pop, R&B, Classic",20000,Sec A,เพศหญิง,10/7/2001,วิทย์-คณิต 22 | "4/8/2021, 22:08:45",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,4,3,4,"Pop, Rock, R&B, Rap",30000,Sec B,เพศหญิง,18/10/2001,วิทย์-คณิต 23 | "4/8/2021, 22:12:04",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 1,4,4,3,"Pop, Rock, R&B, ชอบทุกเเนวเเค่ได้ฟังกับเธอ;_;",30000,Sec A,เพศหญิง,18/2/2002,วิทย์-คณิต 24 | "4/8/2021, 23:14:32",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,4,3,3,"Pop, Rock, Rap, Classic",20000,Sec B,เพศชาย,6/9/2001,วิทย์-คณิต 25 | "4/8/2021, 23:20:51",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,4,4,3,"Pop, Rock",30000,Sec A,ไม่ระบุ,29/1/2001,วิทย์-คณิต 26 | "4/8/2021, 23:26:17",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,4,4,3,"Pop, R&B",30000,Sec A,เพศชาย,21/7/2002,วิทย์-คณิต 27 | "4/8/2021, 23:31:46",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,3,3,3,"Pop, R&B, Rap",30000,Sec A,เพศชาย,3/7/2544,วิทย์-คณิต 28 | "4/8/2021, 23:45:05",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,3,3,3,"Pop, Rock, R&B, Rap",25000,Sec A,เพศ LGBTQ+,20/5/2002,ศิลป์-คำนวณ 29 | "5/8/2021, 0:01:57",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,3,4,5,Pop,35000,Sec B,เพศหญิง,29/10/2001,วิทย์-คณิต 30 | "5/8/2021, 0:04:04",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,5,3,3,"R&B, Musical, Classic, Jazz",30000,Sec B,เพศชาย,19/11/2001,วิทย์-คณิต 31 | "5/8/2021, 0:57:41",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,5,5,5,"Pop, Rock, R&B",80000,Sec B,เพศหญิง,27/9/2001,ศิลป์-คำนวณ 32 | "5/8/2021, 1:33:24",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,4,4,4,Pop,30000,Sec A,เพศหญิง,10/10/2001,วิทย์-คณิต 33 | "5/8/2021, 8:48:37",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 2,4,3,4,"Pop, Classic",35000,Sec B,เพศชาย,20/12/2001,วิทย์-คณิต 34 | "5/8/2021, 9:08:23",ใช้งานประจำ,ไม่เคยเขียนมาก่อน,Level 3,1,5,5,"Musical, Classic",20000,Sec B,เพศชาย,2/1/2001,วิทย์-คณิต 35 | "5/8/2021, 12:12:18",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,5,4,4,"Pop, R&B, ลูกทุ่ง",20000,Sec B,เพศหญิง,4/12/2001,วิทย์-คณิต 36 | "5/8/2021, 12:28:56",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,4,3,3,Pop,25000,Sec B,เพศชาย,15/11/2021,วิทย์-คณิต 37 | "5/8/2021, 12:41:56",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,5,4,3,"Pop, Kpop",25000,Sec B,เพศหญิง,21/5/2002,วิทย์-คณิต 38 | "5/8/2021, 12:47:20",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,4,2,2,"Pop, Indie",28000,Sec B,เพศหญิง,13/9/2001,วิทย์-คณิต 39 | "5/8/2021, 12:55:26",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 0,4,3,3,"Pop, k-pop, Indie",27000,Sec B,เพศหญิง,10/1/2544,วิทย์-คณิต 40 | "5/8/2021, 13:42:28",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,3,3,4,"Pop, R&B, Koop",50000,Sec A,เพศหญิง,12/1/2545,วิทย์-คณิต 41 | "5/8/2021, 16:50:33",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 0,5,3,2,"Pop, R&B, Rap",30000,Sec A,เพศชาย,4/4/2001,วิทย์-คณิต 42 | "5/8/2021, 17:14:57",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 1,4,3,3,"Pop, Rock, R&B, Rap",28000,Sec A,เพศชาย,17/7/2001,วิทย์-คณิต 43 | "5/8/2021, 19:32:48",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,5,3,2,"Pop, R&B, Hip hop, pop rap",50000,Sec B,เพศหญิง,30/12/2000,วิทย์-คณิต 44 | "5/8/2021, 22:44:04",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,5,5,5,"Pop, ลูกทุ่ง",35000,Sec A,เพศหญิง,31/5/2001,วิทย์-คณิต 45 | "6/8/2021, 0:28:14",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,4,3,4,R&B,20000,Sec B,เพศชาย,5/11/2545,วิทย์-คณิต 46 | "6/8/2021, 2:28:08",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,3,5,5,"Pop, Classic, EDM",35000,Sec A,เพศ LGBTQ+,25/11/2001,วิทย์-คณิต 47 | "6/8/2021, 11:41:40",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 3,3,5,5,ญี่ปุ่น การ์ตูน อนิเมะ,60000,Sec B,เพศหญิง,24/9/2021,วิทย์-คณิต 48 | "6/8/2021, 14:01:21",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 2,4,4,4,"Pop, R&B, Classic",20000,Sec A,เพศหญิง,16/9/2001,วิทย์-คณิต 49 | "6/8/2021, 16:17:43",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,4,3,4,"Pop, R&B",20000,Sec A,เพศหญิง,5/11/2001,วิทย์-คณิต 50 | "6/8/2021, 20:11:52",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 1,5,2,3,"Pop, Rock, R&B",25000,Sec B,เพศชาย,30/6/2001,วิทย์-คณิต 51 | "6/8/2021, 21:05:00",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,5,5,3,"Pop, ลูกทุ่ง, Classic, Jazz",40000,Sec A,เพศชาย,5/6/2001,วิทย์-คณิต 52 | "6/8/2021, 21:10:10",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,4,5,1,"Pop, R&B, Musical",30000,Sec A,เพศหญิง,3/10/2002,ศิลป์-คำนวณ 53 | "6/8/2021, 21:11:46",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,5,2,2,"Pop, R&B, Rap",17000,Sec B,เพศ LGBTQ+,25/12/2001,ศิลป์-คำนวณ 54 | "6/8/2021, 21:16:15",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 0,4,5,4,ลูกทุ่ง,9000,Sec A,เพศชาย,3/8/2001,วิทย์-คณิต 55 | "6/8/2021, 22:41:15",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,4,2,3,"Pop, R&B, Rap",18000,Sec A,เพศหญิง,31/3/2002,วิทย์-คณิต 56 | "7/8/2021, 0:11:24",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 0,5,2,3,"Pop, R&B",30000,Sec B,เพศหญิง,2/2/2002,วิทย์-คณิต 57 | "7/8/2021, 0:52:07",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,4,4,2,"Pop, R&B, Rap, acoustic",35000,Sec A,เพศหญิง,20/11/2001,ศิลป์-คำนวณ 58 | "7/8/2021, 1:03:41",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,4,2,3,"Pop, Rap",40000,Sec A,ไม่ระบุ,17/9/2001,วิทย์-คณิต 59 | "7/8/2021, 1:08:49",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,4,4,4,"Pop, R&B, ลูกทุ่ง",40000,Sec B,ไม่ระบุ,29/8/2002,วิทย์-คณิต 60 | "7/8/2021, 5:29:36",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,4,4,4,"Pop, Rock, Musical, Classic",25000,Sec B,เพศชาย,14/2/2002,วิทย์-คณิต 61 | "7/8/2021, 10:49:35",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,4,5,5,"Pop, Rock, Classic",20000,Sec B,เพศชาย,25/8/2001,ศิลป์-คำนวณ 62 | "7/8/2021, 12:10:45",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 2,4,3,2,"Pop, Rock, R&B, Rap",20000,Sec A,เพศชาย,31/3/2002,วิทย์-คณิต 63 | "7/8/2021, 13:26:51",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,4,4,4,"Rock, Classic",50000,Sec A,เพศชาย,27/5/2001,ศิลป์-คำนวณ 64 | "7/8/2021, 21:22:24",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 0,4,3,3,"Pop, Rock, Musical, hip hop,Electronic",25000,Sec A,เพศหญิง,23/12/2001,วิทย์-คณิต 65 | "7/8/2021, 21:49:11",ใช้งานประจำ,ไม่เคยเขียนมาก่อน,Level 1,2,3,2,"Pop, R&B, Classic, Jazz",200000,Sec B,เพศ LGBTQ+,22/8/2001,วิทย์-คณิต 66 | "7/8/2021, 22:59:24",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,5,4,4,"Pop, R&B, ลูกทุ่ง",30000,Sec B,เพศหญิง,25/5/2545,วิทย์-คณิต 67 | "8/8/2021, 0:49:25",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 1,5,3,2,"Pop, Rock, Rap, Classic",25000,Sec B,เพศชาย,7/4/2002,วิทย์-คณิต 68 | "8/8/2021, 10:54:29",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,4,5,5,R&B,30000,Sec B,เพศชาย,14/8/2544,วิทย์-คณิต 69 | "8/8/2021, 11:26:04",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,3,3,2,"Pop, Rock",20000,Sec A,เพศชาย,15/11/2001,วิทย์-คณิต 70 | "8/8/2021, 11:59:16",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,3,3,3,Pop,40000,Sec A,เพศชาย,16/11/2001,วิทย์-คณิต 71 | "8/8/2021, 12:35:32",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,3,4,4,"Pop, Rock",20000,Sec B,เพศชาย,,วิทย์-คณิต 72 | "8/8/2021, 16:30:59",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,3,3,3,Pop,28000,Sec A,เพศชาย,25/1/2002,ศิลป์-คำนวณ 73 | "8/8/2021, 20:00:38",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,4,4,5,"Pop, R&B",25000,Sec B,เพศ LGBTQ+,12/3/2001,วิทย์-คณิต 74 | "8/8/2021, 20:13:32",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 1,3,3,2,"Pop, R&B",30000,Sec A,เพศชาย,7/6/2001,วิทย์-คณิต 75 | "8/8/2021, 20:14:11",ใช้งานประจำ,ไม่เคยเขียนมาก่อน,Level 2,3,3,4,"Pop, Rock, Classic, Alternative / Indie",25000,Sec B,เพศชาย,4/11/2002,วิทย์-คณิต 76 | "8/8/2021, 20:21:25",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,3,4,4,"Pop, R&B, Jazz",20000,Sec A,เพศหญิง,8/5/2002,วิทย์-คณิต 77 | "8/8/2021, 20:22:50",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,5,3,1,"Musical, Classic, Jazz",20000,Sec B,เพศชาย,11/3/2002,วิทย์-คณิต 78 | "8/8/2021, 20:32:08",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,4,3,4,"Pop, R&B, Classic",30000,Sec B,เพศหญิง,15/8/2001,วิทย์-คณิต 79 | "8/8/2021, 20:42:07",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 0,5,3,2,"Pop, R&B",20000,Sec A,เพศชาย,17/10/2001,วิทย์-คณิต 80 | "8/8/2021, 20:42:17",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,4,1,1,Pop,30000,Sec A,เพศหญิง,8/2/2002,ศิลป์-คำนวณ 81 | "8/8/2021, 20:56:18",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,4,5,5,"Pop, R&B, ลูกทุ่ง, Rap",200000,Sec A,เพศชาย,24/9/2001,วิทย์-คณิต 82 | "8/8/2021, 20:58:09",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,4,5,5,"Pop, Rock, Rap",50000,Sec B,เพศชาย,12/9/2001,วิทย์-คณิต 83 | "8/8/2021, 21:58:34",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 0,4,4,2,"Pop, Rock, R&B, pop rock,Electronic,groove,jazz",30000,Sec A,ไม่ระบุ,31/5/2001,วิทย์-คณิต 84 | "8/8/2021, 22:21:49",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,3,3,5,"R&B, Rap",20000,Sec B,เพศหญิง,30/10/2001,วิทย์-คณิต 85 | "8/8/2021, 23:30:55",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 1,5,4,4,"Pop, R&B, Rap, Jazz",35000,Sec A,เพศชาย,30/3/2002,ศิลป์-คำนวณ 86 | "8/8/2021, 23:46:26",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,3,5,4,"Pop, Rock, R&B, Rap",30000,Sec A,เพศชาย,25/5/2001,วิทย์-คณิต 87 | "9/8/2021, 2:09:59",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,3,3,3,"R&B, Rap",50000,Sec A,เพศหญิง,18/10/2544,วิทย์-คณิต 88 | "9/8/2021, 4:30:45",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 2,3,4,5,"Pop, Rock, Classic, Jazz",20000,Sec A,เพศชาย,22/10/2001,วิทย์-คณิต 89 | "9/8/2021, 9:06:42",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,4,3,4,"R&B, Rap",20000,Sec A,เพศชาย,9/6/2002,ศิลป์-คำนวณ 90 | "9/8/2021, 10:30:04",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,5,4,2,"Pop, R&B, Rap",60000,Sec A,เพศหญิง,13/6/2001,วิทย์-คณิต 91 | "9/8/2021, 10:30:40",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,4,4,3,"Pop, R&B, Rap",30000,Sec A,เพศหญิง,17/6/2001,วิทย์-คณิต 92 | "9/8/2021, 10:39:57",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,4,3,3,Pop,50000,Sec B,เพศชาย,28/11/2001,สหศิลป์ 93 | "9/8/2021, 10:41:15",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 1,3,3,3,"Pop, R&B, Rap",100000,Sec A,เพศชาย,18/2/2002,ศิลป์-คำนวณ 94 | "9/8/2021, 10:46:33",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 0,5,3,3,Pop,30000,Sec A,เพศหญิง,9/10/2544,วิทย์-คณิต 95 | "9/8/2021, 10:47:34",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,4,3,3,"Pop, Musical, Classic, Jazz",35000,Sec B,เพศหญิง,18/10/2001,วิทย์-คณิต 96 | "9/8/2021, 10:53:08",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 0,4,3,2,,60000,Sec B,เพศชาย,5/11/2000,วิทย์-คณิต 97 | "9/8/2021, 10:54:31",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,3,4,3,"Pop, Musical",30000,Sec B,เพศชาย,23/5/2002,วิทย์-คณิต 98 | "9/8/2021, 11:02:55",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,5,4,4,Pop,40000,Sec A,ไม่ระบุ,26/5/2001,วิทย์-คณิต 99 | "9/8/2021, 11:11:01",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,5,2,4,Pop,20000,Sec A,เพศชาย,15/6/2002,วิทย์-คณิต 100 | "9/8/2021, 11:40:51",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 2,5,5,5,"Pop, Rap, Classic",100000,Sec B,เพศชาย,6/6/1998,วิทย์-คณิต 101 | "9/8/2021, 12:19:24",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 0,5,3,1,"Pop, R&B, ลูกทุ่ง, Rap",25000,Sec A,เพศหญิง,19/1/2002,ศิลป์-คำนวณ 102 | "9/8/2021, 12:26:50",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,5,3,2,"Pop, Rock, R&B, Jazz",30000,Sec A,เพศชาย,18/9/2001,ศิลป์-คำนวณ 103 | "9/8/2021, 12:57:17",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,5,4,3,"Pop, R&B, Classic, Jazz",30000,Sec A,เพศชาย,18/8/2001,วิทย์-คณิต 104 | "9/8/2021, 12:58:48",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,5,3,3,"Pop, R&B, Rap",50000,Sec A,เพศชาย,7/11/2001,วิทย์-คณิต 105 | "9/8/2021, 12:58:51",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,1,5,5,Classic,100000,Sec A,เพศชาย,1/8/2001,วิทย์-คณิต 106 | "9/8/2021, 12:59:55",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 1,4,3,3,"Pop, R&B, Rap",20000,Sec A,เพศชาย,5/10/2001,วิทย์-คณิต 107 | "9/8/2021, 13:03:47",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,3,5,3,"Pop, R&B, Musical",50000,Sec A,เพศชาย,8/1/2002,วิทย์-คณิต 108 | "9/8/2021, 13:08:12",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 2,3,4,4,"Pop, Rap, Musical",35000,Sec A,เพศชาย,4/4/2002,วิทย์-คณิต 109 | "9/8/2021, 13:09:46",เคยใช้บ้าง,เคยเขียนบ้าง,Level 2,3,4,4,"R&B, Rap",40000,Sec A,เพศชาย,31/8/2001,วิทย์-คณิต 110 | "9/8/2021, 13:11:08",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,5,3,3,"Pop, Classic, Jazz, Anime Song",35000,Sec A,เพศชาย,5/1/2002,วิทย์-คณิต 111 | "9/8/2021, 13:22:21",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 1,5,3,3,"Pop, R&B, Rap, Classic",30000,Sec A,เพศชาย,25/9/2001,ศิลป์-คำนวณ 112 | "9/8/2021, 13:26:13",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,2,3,4,R&B,70000,Sec A,เพศชาย,18/10/2001,ศิลป์-คำนวณ 113 | "9/8/2021, 13:27:14",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,3,4,3,Rock,30000,Sec B,เพศชาย,28/2/2002,วิทย์-คณิต 114 | "9/8/2021, 13:28:15",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,3,4,3,"Pop, R&B, Rap, Classic",30000,Sec A,เพศชาย,18/12/2544,ศิลป์-คำนวณ 115 | "9/8/2021, 13:28:25",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 2,3,3,3,Classic,100000,Sec A,เพศชาย,7/8/2001,ศิลป์-คำนวณ 116 | "9/8/2021, 16:37:08",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,5,3,3,Pop,30000,Sec A,เพศชาย,16/7/2001,วิทย์-คณิต 117 | "11/8/2021, 9:34:03",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,5,4,4,"Pop, R&B, ลูกทุ่ง",30000,Sec B,เพศหญิง,25/5/2545,วิทย์-คณิต 118 | "12/8/2021, 20:47:54",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,4,4,4,"Rock, R&B",30000,Sec B,เพศชาย,26/1/2002,วิทย์-คณิต 119 | "12/8/2021, 23:54:23",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 0,2,2,2,Pop,22000,Sec B,เพศชาย,19/3/2002,วิทย์-คณิต 120 | "13/8/2021, 1:48:18",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,3,3,5,"Pop, R&B, Classic, Jazz",10000000,Sec B,เพศชาย,11/1/2000,วิทย์-คณิต 121 | "13/8/2021, 1:54:40",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,5,3,5,"Pop, Rock, R&B, Rap",50000,Sec B,เพศชาย,4/12/2001,วิทย์-คณิต 122 | "13/8/2021, 4:21:51",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,4,3,3,"Pop, Musical, Classic",30000,Sec B,เพศชาย,9/5/2002,วิทย์-คณิต 123 | "13/8/2021, 11:19:34",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,3,4,4,"Pop, Rap, folk",100000,Sec B,เพศชาย,3/12/2001,วิทย์-คณิต 124 | "13/8/2021, 11:19:58",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 0,5,2,2,"R&B, Rap",26000,Sec B,เพศหญิง,24/9/2544,ศิลป์-คำนวณ 125 | "13/8/2021, 11:20:08",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 1,4,4,3,"Rock, แนวเก่าๆ",19000,Sec B,เพศชาย,21/8/2001,วิทย์-คณิต 126 | "13/8/2021, 11:20:13",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,3,4,4,ระบุแนวไม่ได้คับแล้วแต่moodช่วงนั้น ๆ เพราะเปลี่ยนแนวไปเรื่อยๆตลอด,25000,Sec B,เพศชาย,5/11/2002,วิทย์-คณิต 127 | "13/8/2021, 11:20:18",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,3,4,3,"Pop, Rock",30000,Sec B,เพศชาย,20/6/2001,วิทย์-คณิต 128 | "13/8/2021, 11:20:20",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,4,5,4,Pop,20000,Sec B,เพศชาย,29/7/2002,วิทย์-คณิต 129 | "13/8/2021, 11:21:56",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,5,4,3,"Pop, R&B",18000,Sec B,เพศหญิง,21/6/2001,วิทย์-คณิต 130 | "13/8/2021, 11:23:27",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,3,3,4,"Pop, R&B",25000,Sec B,เพศชาย,13/5/2002,วิทย์-คณิต 131 | "13/8/2021, 11:24:34",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 2,3,3,4,"Pop, R&B, Rap, Jazz",35000,Sec B,เพศชาย,30/10/2001,วิทย์-คณิต 132 | "13/8/2021, 11:24:49",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 0,5,2,2,"Pop, Rock, R&B, Rap",60000,Sec B,เพศหญิง,15/6/2001,วิทย์-คณิต 133 | "13/8/2021, 11:28:53",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,3,3,4,,18000,Sec B,เพศชาย,23/6/2001,วิทย์-คณิต 134 | "13/8/2021, 11:31:46",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,4,5,3,"Pop, Rock, R&B, Rap",50000,Sec B,เพศชาย,5/6/2001,ศิลป์-คำนวณ 135 | "13/8/2021, 11:32:56",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,3,4,3,"Pop, R&B",30000,Sec B,เพศหญิง,23/5/2001,วิทย์-คณิต 136 | "13/8/2021, 13:08:19",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,3,3,3,"Pop, R&B, Rap, Classic",60000,Sec B,เพศชาย,19/9/2002,วิทย์-คณิต 137 | "14/8/2021, 11:37:14",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,3,2,3,"Pop, Classic, Jazz",30000,Sec B,เพศหญิง,17/3/2002,วิทย์-คณิต 138 | "14/8/2021, 11:38:21",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,4,3,4,Rock,40000,Sec B,ไม่ระบุ,,วิทย์-คณิต 139 | "16/8/2021, 0:49:21",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0,5,2,3,"Pop, Classic",40000,Sec A,เพศชาย,16/7/2001,วิทย์-คณิต 140 | "16/8/2021, 16:40:29",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,3,4,4,Pop,30000,Sec A,เพศหญิง,25/12/2001,วิทย์-คณิต 141 | "16/8/2021, 21:35:57",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 1,5,3,4,"Pop, R&B, ลูกทุ่ง, Rap",100000,Sec B,เพศหญิง,18/2/2002,วิทย์-คณิต 142 | -------------------------------------------------------------------------------- /datasets/Survey_INT214.csv: -------------------------------------------------------------------------------- 1 | ประทับเวลา,1. ทักษะการใช้งาน Excel/Google Sheet,2. ทักษะภาษา R,3. ประเมินตัวเองหน่อย คิดว่ามีความรู้เกี่ยวกับสถิติอยู่ขั้นไหน,4. คิดว่า INT214 ที่กำลังจะเรียนมีความง่าย-ยากเพียงใด,5. คิดว่า INT214 น่าเรียนมากน้อยแค่ไหน,6. นักศึกษามีความพร้อมที่จะเรียนมากน้อยเพียงใด,แนวเพลงที่ชอบฟัง,เงินเดือนที่อยากได้เมื่อเรียนจบ (พิมพ์เป็นตัวเลข),เรียน Sec ไหน,เพศ,วันเดือนปีเกิด,มัธยมปลาย เรียนสายการเรียนอะไร 2 | "4/8/2021, 18:34:26",ใช้งานประจำ,เคยเขียนบ้าง,"Level 2 (พอจำ concept จากม.ปลายได้เช่น s.d., z-score, normal distribution, variance)",2,5,5,"Rock, Classic, metal, hiphop 90s",30000,Sec A (id 01-81),เพศชาย,7/1/2002,วิทย์-คณิต 3 | "4/8/2021, 18:40:47",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 2 (พอจำ concept จากม.ปลายได้เช่น s.d., z-score, normal distribution, variance)",4,5,5,"Pop, Classic, Indy ",25000,Sec B (id 82-161),เพศชาย,13/6/2001,วิทย์-คณิต 4 | "4/8/2021, 18:45:21",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 2 (พอจำ concept จากม.ปลายได้เช่น s.d., z-score, normal distribution, variance)",4,5,2,"Pop, Rap, Jazz, Anime and Japanese",25000,Sec A (id 01-81),เพศชาย,10/4/2002,วิทย์-คณิต 5 | "4/8/2021, 18:48:20",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),4,4,3,"R&B, Rap",16000,Sec A (id 01-81),เพศชาย,19/6/2001,วิทย์-คณิต 6 | "4/8/2021, 18:56:17",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 2 (พอจำ concept จากม.ปลายได้เช่น s.d., z-score, normal distribution, variance)",4,3,4,"R&B, Classic, Jazz, Blues",30000,Sec B (id 82-161),เพศชาย,17/11/2001,ศิลป์-คำนวณ 7 | "4/8/2021, 18:59:29",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 2 (พอจำ concept จากม.ปลายได้เช่น s.d., z-score, normal distribution, variance)",3,5,4,"Pop, Rock, Rap",40000,Sec B (id 82-161),เพศชาย,1/1/2002,ศิลป์-คำนวณ 8 | "4/8/2021, 19:08:00",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 2 (พอจำ concept จากม.ปลายได้เช่น s.d., z-score, normal distribution, variance)",2,5,5,"Pop, Musical, Classic",35000,Sec B (id 82-161),เพศหญิง,7/5/2002,วิทย์-คณิต 9 | "4/8/2021, 19:12:06",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",3,3,3,"Pop, Rock, Jazz",15000,Sec A (id 01-81),เพศชาย,11/9/2001,วิทย์-คณิต 10 | "4/8/2021, 19:12:32",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",5,2,2,"Pop, R&B",45000,Sec A (id 01-81),เพศหญิง,12/2/2002,วิทย์-คณิต 11 | "4/8/2021, 19:22:13",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",3,4,3,"Pop, R&B, Jazz",40000,Sec A (id 01-81),เพศหญิง,12/8/2001,วิทย์-คณิต 12 | "4/8/2021, 19:49:37",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 3 (จำได้ดี ถ้ามีสูตรมาสามารถคำนวณหาค่าได้ทันที),2,5,5,"Pop, Rock",20000,Sec B (id 82-161),เพศชาย,10/10/2001,ศิลป์-คำนวณ 13 | "4/8/2021, 19:58:01",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),5,3,4,"Pop, Rock, Classic, EDM",100000,Sec A (id 01-81),เพศชาย,5/3/2002,วิทย์-คณิต 14 | "4/8/2021, 20:24:11",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",5,4,5,"JPAN,KPOP",35000,Sec A (id 01-81),เพศชาย,29/7/2001,ศิลป์-คำนวณ 15 | "4/8/2021, 20:24:28",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),4,2,3,"Pop, Rock, Classic",15000,Sec A (id 01-81),เพศชาย,12/9/2001,ศิลป์-คำนวณ 16 | "4/8/2021, 20:27:32",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",5,4,4,"Pop, Rock, R&B, Classic",20000,Sec A (id 01-81),เพศชาย,4/5/2001,วิทย์-คณิต 17 | "4/8/2021, 20:28:06",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 3 (จำได้ดี ถ้ามีสูตรมาสามารถคำนวณหาค่าได้ทันที),2,5,4,เพลงเศร้า,30000,Sec B (id 82-161),เพศชาย,6/4/2001,วิทย์-คณิต 18 | "4/8/2021, 20:34:03",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",3,5,5,"Pop, Musical, Classic",30000,Sec B (id 82-161),เพศชาย,30/4/2002,วิทย์-คณิต 19 | "4/8/2021, 20:43:59",เคยใช้บ้าง,เคยเขียนบ้าง,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",4,4,3,"Pop, R&B",18000,Sec A (id 01-81),เพศชาย,21/1/2001,วิทย์-คณิต 20 | "4/8/2021, 21:44:49",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",4,3,3,"Pop, R&B, Rap",30000,Sec B (id 82-161),เพศหญิง,21/4/2002,วิทย์-คณิต 21 | "4/8/2021, 21:58:49",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),4,5,5,"Pop, R&B, Classic",20000,Sec A (id 01-81),เพศหญิง,10/7/2001,วิทย์-คณิต 22 | "4/8/2021, 22:08:45",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",4,3,4,"Pop, Rock, R&B, Rap",30000,Sec B (id 82-161),เพศหญิง,18/10/2001,วิทย์-คณิต 23 | "4/8/2021, 22:12:04",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",4,4,3,"Pop, Rock, R&B, ชอบทุกเเนวเเค่ได้ฟังกับเธอ;_;",30000,Sec A (id 01-81),เพศหญิง,18/2/2002,วิทย์-คณิต 24 | "4/8/2021, 23:14:32",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",4,3,3,"Pop, Rock, Rap, Classic",20000,Sec B (id 82-161),เพศชาย,6/9/2001,วิทย์-คณิต 25 | "4/8/2021, 23:20:51",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",4,4,3,"Pop, Rock",30000,Sec A (id 01-81),ไม่ระบุ,29/1/2001,วิทย์-คณิต 26 | "4/8/2021, 23:26:17",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",4,4,3,"Pop, R&B",30000,Sec A (id 01-81),เพศชาย,21/7/2002,วิทย์-คณิต 27 | "4/8/2021, 23:31:46",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",3,3,3,"Pop, R&B, Rap",30000,Sec A (id 01-81),เพศชาย,3/7/2544,วิทย์-คณิต 28 | "4/8/2021, 23:45:05",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",3,3,3,"Pop, Rock, R&B, Rap",25000,Sec A (id 01-81),เพศ LGBTQ+,20/5/2002,ศิลป์-คำนวณ 29 | "5/8/2021, 0:01:57",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),3,4,5,Pop,35000,Sec B (id 82-161),เพศหญิง,29/10/2001,วิทย์-คณิต 30 | "5/8/2021, 0:04:04",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",5,3,3,"R&B, Musical, Classic, Jazz",30000,Sec B (id 82-161),เพศชาย,19/11/2001,วิทย์-คณิต 31 | "5/8/2021, 0:57:41",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),5,5,5,"Pop, Rock, R&B",80000,Sec B (id 82-161),เพศหญิง,27/9/2001,ศิลป์-คำนวณ 32 | "5/8/2021, 1:33:24",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),4,4,4,Pop,30000,Sec A (id 01-81),เพศหญิง,10/10/2001,วิทย์-คณิต 33 | "5/8/2021, 8:48:37",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 2 (พอจำ concept จากม.ปลายได้เช่น s.d., z-score, normal distribution, variance)",4,3,4,"Pop, Classic",35000,Sec B (id 82-161),เพศชาย,20/12/2001,วิทย์-คณิต 34 | "5/8/2021, 9:08:23",ใช้งานประจำ,ไม่เคยเขียนมาก่อน,Level 3 (จำได้ดี ถ้ามีสูตรมาสามารถคำนวณหาค่าได้ทันที),1,5,5,"Musical, Classic",20000,Sec B (id 82-161),เพศชาย,2/1/2001,วิทย์-คณิต 35 | "5/8/2021, 12:12:18",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),5,4,4,"Pop, R&B, ลูกทุ่ง",20000,Sec B (id 82-161),เพศหญิง,4/12/2001,วิทย์-คณิต 36 | "5/8/2021, 12:28:56",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",4,3,3,Pop,25000,Sec B (id 82-161),เพศชาย,15/11/2021,วิทย์-คณิต 37 | "5/8/2021, 12:41:56",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),5,4,3,"Pop, Kpop",25000,Sec B (id 82-161),เพศหญิง,21/5/2002,วิทย์-คณิต 38 | "5/8/2021, 12:47:20",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),4,2,2,"Pop, Indie",28000,Sec B (id 82-161),เพศหญิง,13/9/2001,วิทย์-คณิต 39 | "5/8/2021, 12:55:26",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),4,3,3,"Pop, k-pop, Indie",27000,Sec B (id 82-161),เพศหญิง,10/1/2544,วิทย์-คณิต 40 | "5/8/2021, 13:42:28",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",3,3,4,"Pop, R&B, Koop",50000,Sec A (id 01-81),เพศหญิง,12/1/2545,วิทย์-คณิต 41 | "5/8/2021, 16:50:33",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),5,3,2,"Pop, R&B, Rap",30000,Sec A (id 01-81),เพศชาย,4/4/2001,วิทย์-คณิต 42 | "5/8/2021, 17:14:57",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",4,3,3,"Pop, Rock, R&B, Rap",28000,Sec A (id 01-81),เพศชาย,17/7/2001,วิทย์-คณิต 43 | "5/8/2021, 19:32:48",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),5,3,2,"Pop, R&B, Hip hop, pop rap",50000,Sec B (id 82-161),เพศหญิง,30/12/2000,วิทย์-คณิต 44 | "5/8/2021, 22:44:04",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),5,5,5,"Pop, ลูกทุ่ง",35000,Sec A (id 01-81),เพศหญิง,31/5/2001,วิทย์-คณิต 45 | "6/8/2021, 0:28:14",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",4,3,4,R&B,20000,Sec B (id 82-161),เพศชาย,5/11/2545,วิทย์-คณิต 46 | "6/8/2021, 2:28:08",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",3,5,5,"Pop, Classic, EDM",35000,Sec A (id 01-81),เพศ LGBTQ+,25/11/2001,วิทย์-คณิต 47 | "6/8/2021, 11:41:40",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 3 (จำได้ดี ถ้ามีสูตรมาสามารถคำนวณหาค่าได้ทันที),3,5,5,ญี่ปุ่น การ์ตูน อนิเมะ,60000,Sec B (id 82-161),เพศหญิง,24/9/2021,วิทย์-คณิต 48 | "6/8/2021, 14:01:21",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 2 (พอจำ concept จากม.ปลายได้เช่น s.d., z-score, normal distribution, variance)",4,4,4,"Pop, R&B, Classic",20000,Sec A (id 01-81),เพศหญิง,16/9/2001,วิทย์-คณิต 49 | "6/8/2021, 16:17:43",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",4,3,4,"Pop, R&B",20000,Sec A (id 01-81),เพศหญิง,5/11/2001,วิทย์-คณิต 50 | "6/8/2021, 20:11:52",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",5,2,3,"Pop, Rock, R&B",25000,Sec B (id 82-161),เพศชาย,30/6/2001,วิทย์-คณิต 51 | "6/8/2021, 21:05:00",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",5,5,3,"Pop, ลูกทุ่ง, Classic, Jazz",40000,Sec A (id 01-81),เพศชาย,5/6/2001,วิทย์-คณิต 52 | "6/8/2021, 21:10:10",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",4,5,1,"Pop, R&B, Musical",30000,Sec A (id 01-81),เพศหญิง,3/10/2002,ศิลป์-คำนวณ 53 | "6/8/2021, 21:11:46",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",5,2,2,"Pop, R&B, Rap",17000,Sec B (id 82-161),เพศ LGBTQ+,25/12/2001,ศิลป์-คำนวณ 54 | "6/8/2021, 21:16:15",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),4,5,4,ลูกทุ่ง,9000,Sec A (id 01-81),เพศชาย,3/8/2001,วิทย์-คณิต 55 | "6/8/2021, 22:41:15",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",4,2,3,"Pop, R&B, Rap",18000,Sec A (id 01-81),เพศหญิง,31/3/2002,วิทย์-คณิต 56 | "7/8/2021, 0:11:24",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),5,2,3,"Pop, R&B",30000,Sec B (id 82-161),เพศหญิง,2/2/2002,วิทย์-คณิต 57 | "7/8/2021, 0:52:07",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",4,4,2,"Pop, R&B, Rap, acoustic",35000,Sec A (id 01-81),เพศหญิง,20/11/2001,ศิลป์-คำนวณ 58 | "7/8/2021, 1:03:41",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),4,2,3,"Pop, Rap",40000,Sec A (id 01-81),ไม่ระบุ,17/9/2001,วิทย์-คณิต 59 | "7/8/2021, 1:08:49",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",4,4,4,"Pop, R&B, ลูกทุ่ง",40000,Sec B (id 82-161),ไม่ระบุ,29/8/2002,วิทย์-คณิต 60 | "7/8/2021, 5:29:36",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",4,4,4,"Pop, Rock, Musical, Classic",25000,Sec B (id 82-161),เพศชาย,14/2/2002,วิทย์-คณิต 61 | "7/8/2021, 10:49:35",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",4,5,5,"Pop, Rock, Classic",20000,Sec B (id 82-161),เพศชาย,25/8/2001,ศิลป์-คำนวณ 62 | "7/8/2021, 12:10:45",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 2 (พอจำ concept จากม.ปลายได้เช่น s.d., z-score, normal distribution, variance)",4,3,2,"Pop, Rock, R&B, Rap",20000,Sec A (id 01-81),เพศชาย,31/3/2002,วิทย์-คณิต 63 | "7/8/2021, 13:26:51",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",4,4,4,"Rock, Classic",50000,Sec A (id 01-81),เพศชาย,27/5/2001,ศิลป์-คำนวณ 64 | "7/8/2021, 21:22:24",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),4,3,3,"Pop, Rock, Musical, hip hop,Electronic",25000,Sec A (id 01-81),เพศหญิง,23/12/2001,วิทย์-คณิต 65 | "7/8/2021, 21:49:11",ใช้งานประจำ,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",2,3,2,"Pop, R&B, Classic, Jazz",200000,Sec B (id 82-161),เพศ LGBTQ+,22/8/2001,วิทย์-คณิต 66 | "7/8/2021, 22:59:24",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",5,4,4,"Pop, R&B, ลูกทุ่ง",30000,Sec B (id 82-161),เพศหญิง,25/5/2545,วิทย์-คณิต 67 | "8/8/2021, 0:49:25",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",5,3,2,"Pop, Rock, Rap, Classic",25000,Sec B (id 82-161),เพศชาย,7/4/2002,วิทย์-คณิต 68 | "8/8/2021, 10:54:29",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",4,5,5,R&B,30000,Sec B (id 82-161),เพศชาย,14/8/2544,วิทย์-คณิต 69 | "8/8/2021, 11:26:04",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",3,3,2,"Pop, Rock",20000,Sec A (id 01-81),เพศชาย,15/11/2001,วิทย์-คณิต 70 | "8/8/2021, 11:59:16",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",3,3,3,Pop,40000,Sec A (id 01-81),เพศชาย,16/11/2001,วิทย์-คณิต 71 | "8/8/2021, 12:35:32",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",3,4,4,"Pop, Rock",20000,Sec B (id 82-161),เพศชาย,,วิทย์-คณิต 72 | "8/8/2021, 16:30:59",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",3,3,3,Pop,28000,Sec A (id 01-81),เพศชาย,25/1/2002,ศิลป์-คำนวณ 73 | "8/8/2021, 20:00:38",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),4,4,5,"Pop, R&B",25000,Sec B (id 82-161),เพศ LGBTQ+,12/3/2001,วิทย์-คณิต 74 | "8/8/2021, 20:13:32",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",3,3,2,"Pop, R&B",30000,Sec A (id 01-81),เพศชาย,7/6/2001,วิทย์-คณิต 75 | "8/8/2021, 20:14:11",ใช้งานประจำ,ไม่เคยเขียนมาก่อน,"Level 2 (พอจำ concept จากม.ปลายได้เช่น s.d., z-score, normal distribution, variance)",3,3,4,"Pop, Rock, Classic, Alternative / Indie",25000,Sec B (id 82-161),เพศชาย,4/11/2002,วิทย์-คณิต 76 | "8/8/2021, 20:21:25",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",3,4,4,"Pop, R&B, Jazz",20000,Sec A (id 01-81),เพศหญิง,8/5/2002,วิทย์-คณิต 77 | "8/8/2021, 20:22:50",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),5,3,1,"Musical, Classic, Jazz",20000,Sec B (id 82-161),เพศชาย,11/3/2002,วิทย์-คณิต 78 | "8/8/2021, 20:32:08",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),4,3,4,"Pop, R&B, Classic",30000,Sec B (id 82-161),เพศหญิง,15/8/2001,วิทย์-คณิต 79 | "8/8/2021, 20:42:07",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),5,3,2,"Pop, R&B",20000,Sec A (id 01-81),เพศชาย,17/10/2001,วิทย์-คณิต 80 | "8/8/2021, 20:42:17",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),4,1,1,Pop,30000,Sec A (id 01-81),เพศหญิง,8/2/2002,ศิลป์-คำนวณ 81 | "8/8/2021, 20:56:18",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",4,5,5,"Pop, R&B, ลูกทุ่ง, Rap",200000,Sec A (id 01-81),เพศชาย,24/9/2001,วิทย์-คณิต 82 | "8/8/2021, 20:58:09",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),4,5,5,"Pop, Rock, Rap",50000,Sec B (id 82-161),เพศชาย,12/9/2001,วิทย์-คณิต 83 | "8/8/2021, 21:58:34",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),4,4,2,"Pop, Rock, R&B, pop rock,Electronic,groove,jazz",30000,Sec A (id 01-81),ไม่ระบุ,31/5/2001,วิทย์-คณิต 84 | "8/8/2021, 22:21:49",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),3,3,5,"R&B, Rap",20000,Sec B (id 82-161),เพศหญิง,30/10/2001,วิทย์-คณิต 85 | "8/8/2021, 23:30:55",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",5,4,4,"Pop, R&B, Rap, Jazz",35000,Sec A (id 01-81),เพศชาย,30/3/2002,ศิลป์-คำนวณ 86 | "8/8/2021, 23:46:26",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",3,5,4,"Pop, Rock, R&B, Rap",30000,Sec A (id 01-81),เพศชาย,25/5/2001,วิทย์-คณิต 87 | "9/8/2021, 2:09:59",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),3,3,3,"R&B, Rap",50000,Sec A (id 01-81),เพศหญิง,18/10/2544,วิทย์-คณิต 88 | "9/8/2021, 4:30:45",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 2 (พอจำ concept จากม.ปลายได้เช่น s.d., z-score, normal distribution, variance)",3,4,5,"Pop, Rock, Classic, Jazz",20000,Sec A (id 01-81),เพศชาย,22/10/2001,วิทย์-คณิต 89 | "9/8/2021, 9:06:42",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",4,3,4,"R&B, Rap",20000,Sec A (id 01-81),เพศชาย,9/6/2002,ศิลป์-คำนวณ 90 | "9/8/2021, 10:30:04",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",5,4,2,"Pop, R&B, Rap",60000,Sec A (id 01-81),เพศหญิง,13/6/2001,วิทย์-คณิต 91 | "9/8/2021, 10:30:40",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",4,4,3,"Pop, R&B, Rap",30000,Sec A (id 01-81),เพศหญิง,17/6/2001,วิทย์-คณิต 92 | "9/8/2021, 10:39:57",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),4,3,3,Pop,50000,Sec B (id 82-161),เพศชาย,28/11/2001,สหศิลป์ 93 | "9/8/2021, 10:41:15",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",3,3,3,"Pop, R&B, Rap",100000,Sec A (id 01-81),เพศชาย,18/2/2002,ศิลป์-คำนวณ 94 | "9/8/2021, 10:46:33",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),5,3,3,Pop,30000,Sec A (id 01-81),เพศหญิง,9/10/2544,วิทย์-คณิต 95 | "9/8/2021, 10:47:34",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),4,3,3,"Pop, Musical, Classic, Jazz",35000,Sec B (id 82-161),เพศหญิง,18/10/2001,วิทย์-คณิต 96 | "9/8/2021, 10:53:08",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),4,3,2,,60000,Sec B (id 82-161),เพศชาย,5/11/2000,วิทย์-คณิต 97 | "9/8/2021, 10:54:31",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",3,4,3,"Pop, Musical",30000,Sec B (id 82-161),เพศชาย,23/5/2002,วิทย์-คณิต 98 | "9/8/2021, 11:02:55",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),5,4,4,Pop,40000,Sec A (id 01-81),ไม่ระบุ,26/5/2001,วิทย์-คณิต 99 | "9/8/2021, 11:11:01",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),5,2,4,Pop,20000,Sec A (id 01-81),เพศชาย,15/6/2002,วิทย์-คณิต 100 | "9/8/2021, 11:40:51",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 2 (พอจำ concept จากม.ปลายได้เช่น s.d., z-score, normal distribution, variance)",5,5,5,"Pop, Rap, Classic",100000,Sec B (id 82-161),เพศชาย,6/6/1998,วิทย์-คณิต 101 | "9/8/2021, 12:19:24",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),5,3,1,"Pop, R&B, ลูกทุ่ง, Rap",25000,Sec A (id 01-81),เพศหญิง,19/1/2002,ศิลป์-คำนวณ 102 | "9/8/2021, 12:26:50",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",5,3,2,"Pop, Rock, R&B, Jazz",30000,Sec A (id 01-81),เพศชาย,18/9/2001,ศิลป์-คำนวณ 103 | "9/8/2021, 12:57:17",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),5,4,3,"Pop, R&B, Classic, Jazz",30000,Sec A (id 01-81),เพศชาย,18/8/2001,วิทย์-คณิต 104 | "9/8/2021, 12:58:48",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",5,3,3,"Pop, R&B, Rap",50000,Sec A (id 01-81),เพศชาย,7/11/2001,วิทย์-คณิต 105 | "9/8/2021, 12:58:51",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),1,5,5,Classic,100000,Sec A (id 01-81),เพศชาย,1/8/2001,วิทย์-คณิต 106 | "9/8/2021, 12:59:55",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",4,3,3,"Pop, R&B, Rap",20000,Sec A (id 01-81),เพศชาย,5/10/2001,วิทย์-คณิต 107 | "9/8/2021, 13:03:47",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",3,5,3,"Pop, R&B, Musical",50000,Sec A (id 01-81),เพศชาย,8/1/2002,วิทย์-คณิต 108 | "9/8/2021, 13:08:12",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 2 (พอจำ concept จากม.ปลายได้เช่น s.d., z-score, normal distribution, variance)",3,4,4,"Pop, Rap, Musical",35000,Sec A (id 01-81),เพศชาย,4/4/2002,วิทย์-คณิต 109 | "9/8/2021, 13:09:46",เคยใช้บ้าง,เคยเขียนบ้าง,"Level 2 (พอจำ concept จากม.ปลายได้เช่น s.d., z-score, normal distribution, variance)",3,4,4,"R&B, Rap",40000,Sec A (id 01-81),เพศชาย,31/8/2001,วิทย์-คณิต 110 | "9/8/2021, 13:11:08",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),5,3,3,"Pop, Classic, Jazz, Anime Song",35000,Sec A (id 01-81),เพศชาย,5/1/2002,วิทย์-คณิต 111 | "9/8/2021, 13:22:21",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",5,3,3,"Pop, R&B, Rap, Classic",30000,Sec A (id 01-81),เพศชาย,25/9/2001,ศิลป์-คำนวณ 112 | "9/8/2021, 13:26:13",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",2,3,4,R&B,70000,Sec A (id 01-81),เพศชาย,18/10/2001,ศิลป์-คำนวณ 113 | "9/8/2021, 13:27:14",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",3,4,3,Rock,30000,Sec B (id 82-161),เพศชาย,28/2/2002,วิทย์-คณิต 114 | "9/8/2021, 13:28:15",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",3,4,3,"Pop, R&B, Rap, Classic",30000,Sec A (id 01-81),เพศชาย,18/12/2544,ศิลป์-คำนวณ 115 | "9/8/2021, 13:28:25",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 2 (พอจำ concept จากม.ปลายได้เช่น s.d., z-score, normal distribution, variance)",3,3,3,Classic,100000,Sec A (id 01-81),เพศชาย,7/8/2001,ศิลป์-คำนวณ 116 | "9/8/2021, 16:37:08",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),5,3,3,Pop,30000,Sec A (id 01-81),เพศชาย,16/7/2001,วิทย์-คณิต 117 | "11/8/2021, 9:34:03",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",5,4,4,"Pop, R&B, ลูกทุ่ง",30000,Sec B (id 82-161),เพศหญิง,25/5/2545,วิทย์-คณิต 118 | "12/8/2021, 20:47:54",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",4,4,4,"Rock, R&B",30000,Sec B (id 82-161),เพศชาย,26/1/2002,วิทย์-คณิต 119 | "12/8/2021, 23:54:23",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),2,2,2,Pop,22000,Sec B (id 82-161),เพศชาย,19/3/2002,วิทย์-คณิต 120 | "13/8/2021, 1:48:18",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),3,3,5,"Pop, R&B, Classic, Jazz",10000000,Sec B (id 82-161),เพศชาย,11/1/2000,วิทย์-คณิต 121 | "13/8/2021, 1:54:40",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),5,3,5,"Pop, Rock, R&B, Rap",50000,Sec B (id 82-161),เพศชาย,4/12/2001,วิทย์-คณิต 122 | "13/8/2021, 4:21:51",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",4,3,3,"Pop, Musical, Classic",30000,Sec B (id 82-161),เพศชาย,9/5/2002,วิทย์-คณิต 123 | "13/8/2021, 11:19:34",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",3,4,4,"Pop, Rap, folk",100000,Sec B (id 82-161),เพศชาย,3/12/2001,วิทย์-คณิต 124 | "13/8/2021, 11:19:58",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),5,2,2,"R&B, Rap",26000,Sec B (id 82-161),เพศหญิง,24/9/2544,ศิลป์-คำนวณ 125 | "13/8/2021, 11:20:08",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",4,4,3,"Rock, แนวเก่าๆ",19000,Sec B (id 82-161),เพศชาย,21/8/2001,วิทย์-คณิต 126 | "13/8/2021, 11:20:13",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",3,4,4,ระบุแนวไม่ได้คับแล้วแต่moodช่วงนั้น ๆ เพราะเปลี่ยนแนวไปเรื่อยๆตลอด,25000,Sec B (id 82-161),เพศชาย,5/11/2002,วิทย์-คณิต 127 | "13/8/2021, 11:20:18",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",3,4,3,"Pop, Rock",30000,Sec B (id 82-161),เพศชาย,20/6/2001,วิทย์-คณิต 128 | "13/8/2021, 11:20:20",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",4,5,4,Pop,20000,Sec B (id 82-161),เพศชาย,29/7/2002,วิทย์-คณิต 129 | "13/8/2021, 11:21:56",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",5,4,3,"Pop, R&B",18000,Sec B (id 82-161),เพศหญิง,21/6/2001,วิทย์-คณิต 130 | "13/8/2021, 11:23:27",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",3,3,4,"Pop, R&B",25000,Sec B (id 82-161),เพศชาย,13/5/2002,วิทย์-คณิต 131 | "13/8/2021, 11:24:34",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 2 (พอจำ concept จากม.ปลายได้เช่น s.d., z-score, normal distribution, variance)",3,3,4,"Pop, R&B, Rap, Jazz",35000,Sec B (id 82-161),เพศชาย,30/10/2001,วิทย์-คณิต 132 | "13/8/2021, 11:24:49",ไม่เคยใช้งานมาก่อน,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),5,2,2,"Pop, Rock, R&B, Rap",60000,Sec B (id 82-161),เพศหญิง,15/6/2001,วิทย์-คณิต 133 | "13/8/2021, 11:28:53",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",3,3,4,,18000,Sec B (id 82-161),เพศชาย,23/6/2001,วิทย์-คณิต 134 | "13/8/2021, 11:31:46",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),4,5,3,"Pop, Rock, R&B, Rap",50000,Sec B (id 82-161),เพศชาย,5/6/2001,ศิลป์-คำนวณ 135 | "13/8/2021, 11:32:56",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",3,4,3,"Pop, R&B",30000,Sec B (id 82-161),เพศหญิง,23/5/2001,วิทย์-คณิต 136 | "13/8/2021, 13:08:19",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",3,3,3,"Pop, R&B, Rap, Classic",60000,Sec B (id 82-161),เพศชาย,19/9/2002,วิทย์-คณิต 137 | "14/8/2021, 11:37:14",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),3,2,3,"Pop, Classic, Jazz",30000,Sec B (id 82-161),เพศหญิง,17/3/2002,วิทย์-คณิต 138 | "14/8/2021, 11:38:21",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",4,3,4,Rock,40000,Sec B (id 82-161),ไม่ระบุ,,วิทย์-คณิต 139 | "16/8/2021, 0:49:21",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,Level 0 (ไม่มีความรู้เลย คืนครูคณิตม.ปลายไปหมดแล้ว),5,2,3,"Pop, Classic",40000,Sec A (id 01-81),เพศชาย,16/7/2001,วิทย์-คณิต 140 | "16/8/2021, 16:40:29",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",3,4,4,Pop,30000,Sec A (id 01-81),เพศหญิง,25/12/2001,วิทย์-คณิต 141 | "16/8/2021, 21:35:57",เคยใช้บ้าง,ไม่เคยเขียนมาก่อน,"Level 1 (พอจำได้เรื่องการหาค่ากลางได้เช่น Average, Median, mode)",5,3,4,"Pop, R&B, ลูกทุ่ง, Rap",100000,Sec B (id 82-161),เพศหญิง,18/2/2002,วิทย์-คณิต -------------------------------------------------------------------------------- /datasets/SAT_original.csv: -------------------------------------------------------------------------------- 1 | DBN,school_name,math_score,reading_score,writing_score 2 | 01M292,HENRY STREET SCHOOL FOR INTERNATIONAL STUDIES,404,355,363 3 | 01M448,UNIVERSITY NEIGHBORHOOD HIGH SCHOOL,423,383,366 4 | 01M450,EAST SIDE COMMUNITY SCHOOL,402,377,370 5 | 01M458,FORSYTH SATELLITE ACADEMY,401,414,359 6 | 01M509,MARTA VALLE HIGH SCHOOL,433,390,384 7 | 01M515,LOWER EAST SIDE PREPARATORY HIGH SCHOOL,557,332,316 8 | 01M539,"NEW EXPLORATIONS INTO SCIENCE, TECHNOLOGY AND MATH HIGH SCHOOL",574,522,525 9 | 01M650,CASCADES HIGH SCHOOL,418,417,411 10 | 01M696,BARD HIGH SCHOOL EARLY COLLEGE,604,624,628 11 | 02M047,47 THE AMERICAN SIGN LANGUAGE AND ENGLISH SECONDARY SCHOOL,400,395,387 12 | 02M288,FOOD AND FINANCE HIGH SCHOOL,393,409,392 13 | 02M294,ESSEX STREET ACADEMY,384,394,378 14 | 02M296,HIGH SCHOOL OF HOSPITALITY MANAGEMENT,375,374,362 15 | 02M298,PACE HIGH SCHOOL,438,423,432 16 | 02M300,"URBAN ASSEMBLY SCHOOL OF DESIGN AND CONSTRUCTION, THE",449,404,416 17 | 02M303,"FACING HISTORY SCHOOL, THE",358,353,340 18 | 02M305,"URBAN ASSEMBLY ACADEMY OF GOVERNMENT AND LAW, THE",388,375,385 19 | 02M308,LOWER MANHATTAN ARTS ACADEMY,392,403,405 20 | 02M313,"JAMES BALDWIN SCHOOL, THE: A SCHOOL FOR EXPEDITIONARY LEARNING",390,408,390 21 | 02M316,"URBAN ASSEMBLY SCHOOL OF BUSINESS FOR YOUNG WOMEN, THE",370,373,384 22 | 02M374,GRAMERCY ARTS HIGH SCHOOL,391,391,394 23 | 02M376,NYC ISCHOOL,483,473,479 24 | 02M376,NYC ISCHOOL,483,473,479 25 | 02M392,MANHATTAN BUSINESS ACADEMY,s,s,s 26 | 02M393,BUSINESS OF SPORTS SCHOOL,s,s,s 27 | 02M394,EMMA LAZARUS HIGH SCHOOL,512,319,357 28 | 02M399,THE HIGH SCHOOL FOR LANGUAGE AND DIPLOMACY,s,s,s 29 | 02M400,HIGH SCHOOL FOR ENVIRONMENTAL STUDIES,493,465,461 30 | 02M407,INSTITUTE FOR COLLABORATIVE EDUCATION,465,492,467 31 | 02M408,PROFESSIONAL PERFORMING ARTS HIGH SCHOOL,490,509,523 32 | 02M411,BARUCH COLLEGE CAMPUS HIGH SCHOOL,563,496,518 33 | 02M412,N.Y.C. LAB SCHOOL FOR COLLABORATIVE STUDIES,590,537,550 34 | 02M413,SCHOOL OF THE FUTURE HIGH SCHOOL,533,517,515 35 | 02M414,N.Y.C. MUSEUM SCHOOL,492,468,459 36 | 02M416,ELEANOR ROOSEVELT HIGH SCHOOL,594,572,592 37 | 02M418,MILLENNIUM HIGH SCHOOL,553,528,533 38 | 02M419,LANDMARK HIGH SCHOOL,399,390,381 39 | 02M420,HIGH SCHOOL FOR HEALTH PROFESSIONS AND HUMAN SERVICES,449,429,428 40 | 02M425,LEADERSHIP AND PUBLIC SERVICE HIGH SCHOOL,426,416,391 41 | 02M427,MANHATTAN ACADEMY FOR ARTS & LANGUAGE,s,s,s 42 | 02M429,LEGACY SCHOOL FOR INTEGRATED STUDIES,357,356,349 43 | 02M437,HUDSON HIGH SCHOOL OF LEARNING TECHNOLOGIES,s,s,s 44 | 02M438,INTERNATIONAL HIGH SCHOOL AT UNION SQUARE,s,s,s 45 | 02M439,MANHATTAN VILLAGE ACADEMY,473,441,458 46 | 02M440,BAYARD RUSTIN EDUCATIONAL COMPLEX,365,378,368 47 | 02M449,VANGUARD HIGH SCHOOL,416,395,388 48 | 02M459,MANHATTAN INTERNATIONAL HIGH SCHOOL,460,376,391 49 | 02M460,WASHINGTON IRVING HIGH SCHOOL,387,373,360 50 | 02M473,WASHINGTON IRVING YABC,s,s,s 51 | 02M475,STUYVESANT HIGH SCHOOL,7735,679,682 52 | 02M489,HIGH SCHOOL OF ECONOMICS AND FINANCE,489,443,442 53 | 02M500,UNITY CENTER FOR URBAN TECHNOLOGIES,34,37,35 54 | 02M519,TALENT UNLIMITED HIGH SCHOOL,472,469,475 55 | 02M520,MURRY BERGTRAUM HIGH SCHOOL FOR BUSINESS CAREERS,440,407,393 56 | 02M529,JACQUELINE KENNEDY ONASSIS HIGH SCHOOL,425,414,400 57 | 02M531,REPERTORY COMPANY HIGH SCHOOL FOR THEATRE ARTS,404,429,420 58 | 02M542,MANHATTAN BRIDGES HIGH SCHOOL,378,336,344 59 | 02M543,NEW DESIGN HIGH SCHOOL,395,391,382 60 | 02M544,INDEPENDENCE HIGH SCHOOL,371,389,335 61 | 02M545,HIGH SCHOOL FOR DUAL LANGUAGE AND ASIAN STUDIES,581,412,431 62 | 02M550,LIBERTY HIGH SCHOOL ACADEMY FOR NEWCOMERS,436,368,352 63 | 02M551,THE URBAN ASSEMBLY NEW YORK HARBOR SCHOOL,423,405,384 64 | 02M560,HIGH SCHOOL M560 s CITY AS SCHOOL,440,498,477 65 | 02M565,URBAN ACADEMY LABORATORY HIGH SCHOOL,508,527,512 66 | 02M570,SATELLITE ACADEMY HIGH SCHOOL,337,350,345 67 | 02M575,MANHATTAN COMPREHENSIVE NIGHT AND DAY HIGH SCHOOL,517,345,343 68 | 02M580,RICHARD R. GREEN HIGH SCHOOL OF TEACHING,384,408,4030 69 | 02M586,HARVEY MILK HIGH SCHOOL,416,458,429 70 | 02M600,THE HIGH SCHOOL OF FASHION INDUSTRIES,423,423,411 71 | 02M605,HUMANITIES PREPARATORY ACADEMY,403,426,426 72 | 02M615,CHELSEA CAREER AND TECHNICAL EDUCATION HIGH SCHOOL,418,399,390 73 | 02M620,NORMAN THOMAS HIGH SCHOOL,379,370,359 74 | 02M625,HIGH SCHOOL OF GRAPHIC COMMUNICATION ARTS,382,395,376 75 | 02M630,ART AND DESIGN HIGH SCHOOL,441,444,430 76 | 02M655,LIFE SCIENCES SECONDARY SCHOOL,424,409,403 77 | 03M283,MANHATTAN THEATRE LAB HIGH SCHOOL,379,406,408 78 | 03M299,"HIGH SCHOOL FOR ARTS, IMAGINATION AND INQUIRY",384,374,374 79 | 03M307,"URBAN ASSEMBLY SCHOOL FOR MEDIA STUDIES, THE",390,384,370 80 | 03M402,THE URBAN ASSEMBLY SCHOOL FOR GREEN CAREERS,s,s,s 81 | 03M403,THE GLOBAL LEARNING COLLABORATIVE,s,s,s 82 | 03M404,INNOVATION DIPLOMA PLUS,403,416,381 83 | 03M415,WADLEIGH SECONDARY SCHOOL FOR THE PERFORMING & VISUAL ARTS,368,371,370 84 | 03M417,FRANK MCCOURT HIGH SCHOOL,s,s,s 85 | 03M470,LOUIS D. BRANDEIS HIGH SCHOOL,39,37,35 86 | 03M479,BEACON HIGH SCHOOL,575,577,592 87 | 03M485,FIORELLO H. LAGUARDIA HIGH SCHOOL OF MUSIC & ART AND PERFORMING ARTS,564,566,577 88 | 03M492,"HIGH SCHOOL FOR LAW, ADVOCACY AND COMMUNITY JUSTICE",398,396,402 89 | 03M494,HIGH SCHOOL OF ARTS AND TECHNOLOGY,433,433,411 90 | 03M505,EDWARD A. REYNOLDS WEST SIDE HIGH SCHOOL,369,401,351 91 | 03M541,MANHATTAN / HUNTER SCIENCE HIGH SCHOOL,506,473,467 92 | 03M577,YOUNG ADULT BOROUGH CENTER AT LOUIS D. BRANDEIS HS,s,s,s 93 | 03M860,FREDERICK DOUGLASS ACADEMY II SECONDARY SCHOOL,379,356,361 94 | 04M409,COALITION SCHOOL FOR SOCIAL CHANGE,357,354,373 95 | 04M435,MANHATTAN CENTER FOR SCIENCE AND MATHEMATICS,514,461,455 96 | 04M495,PARK EAST HIGH SCHOOL,379,373,376 97 | 04M555,CENTRAL PARK EAST HIGH SCHOOL,421,405,395 98 | 04M610,YOUNG WOMEN'S LEADERSHIP SCHOOL,446,432,448 99 | 04M635,ACADEMY OF ENVIRONMENTAL SCIENCE SECONDARY HIGH SCHOOL,369,369,357 100 | 04M680,"HERITAGE SCHOOL, THE",351,358,345 101 | 05M285,HARLEM RENAISSANCE HIGH SCHOOL,318,357,333 102 | 05M304,MOTT HALL HIGH SCHOOL,399,413,398 103 | 05M362,"COLUMBIA SECONDARY SCHOOL FOR MATH, SCIENCE, AND ENGINEERING",s,s,s 104 | 05M367,ACADEMY FOR SOCIAL ACTION: A COLLEGE BOARD SCHOOL,366,354,342 105 | 05M369,URBAN ASSEMBLY SCHOOL FOR THE PERFORMING ARTS,353,360,364 106 | 05M469,CHOIR ACADEMY OF HARLEM,360,354,385 107 | 05M499,FREDERICK DOUGLASS ACADEMY,474,458,442 108 | 05M670,THURGOOD MARSHALL ACADEMY FOR LEARNING AND SOCIAL CHANGE,402,396,404 109 | 05M685,BREAD & ROSES INTEGRATED ARTS HIGH SCHOOL,361,369,355 110 | 05M692,"HIGH SCHOOL FOR MATHEMATICS, SCIENCE AND ENGINEERING AT CITY COLLEGE",654,605,588 111 | 06M293,CITY COLLEGE ACADEMY OF THE ARTS,446,408,416 112 | 06M346,COMMUNITY HEALTH ACADEMY OF THE HEIGHTS,376,362,367 113 | 06M348,WASHINGTON HEIGHTS EXPEDITIONARY LEARNING SCHOOL,395,380,399 114 | 06M423,HIGH SCHOOL FOR EXCELLENCE AND INNOVATION,s,s,s 115 | 06M457,GEORGE WASHINGTON YABC,357,394,346 116 | 06M462,HIGH SCHOOL FOR INTERNATIONAL BUSINESS AND FINANCE,384,365,378 117 | 06M463,HIGH SCHOOL FOR MEDIA AND COMMUNICATIONS,380,369,349 118 | 06M467,HIGH SCHOOL FOR LAW AND PUBLIC SERVICE,378,363,361 119 | 06M468,HIGH SCHOOL FOR HEALTH CAREERS AND SCIENCES,422,400,402 120 | 06M540,A. PHILIP RANDOLPH CAMPUS HIGH SCHOOL,456,430,423 121 | 06M552,GREGORIO LUPERON HIGH SCHOOL FOR SCIENCE AND MATHEMATICS,349,339,326 122 | 07X221,SOUTH BRONX PREPARATORY: A COLLEGE BOARD SCHOOL,378,364,348 123 | 07X321,CROTONA ACADEMY HIGH SCHOOL,364,379,382 124 | 07X334,INTERNATIONAL COMMUNITY HIGH SCHOOL,324,310,311 125 | 07X379,JILL CHAIFETZ TRANSFER HIGH SCHOOL,s,s,s 126 | 07X381,BRONX HAVEN HIGH SCHOOL,s,s,s 127 | 07X427,COMMUNITY SCHOOL FOR SOCIAL JUSTICE,359,361,357 128 | 07X473,MOTT HAVEN VILLAGE PREPARATORY HIGH SCHOOL,375,351,371 129 | 07X495,UNIVERSITY HEIGHTS SECONDARY SCHOOL,394,403,404 130 | 07X500,HOSTOSsLINCOLN ACADEMY OF SCIENCE,426,420,411 131 | 07X520,FOREIGN LANGUAGE ACADEMY OF GLOBAL STUDIES,396,399,391 132 | 07X527,BRONX LEADERSHIP ACADEMY II HIGH SCHOOL,378,362,363 133 | 07X547,NEW EXPLORERS HIGH SCHOOL,356,367,361 134 | 07X548,URBAN ASSEMBLY SCHOOL FOR CAREERS IN SPORTS,411,387,383 135 | 07X551,BRONX ACADEMY OF LETTERS,381,413,407 136 | 07X600,ALFRED E. SMITH CAREER AND TECHNICAL EDUCATION HIGH SCHOOL,400,394,364 137 | 07X655,SAMUEL GOMPERS CAREER AND TECHNICAL EDUCATION HIGH SCHOOL,416,398,370 138 | 07X670,HEALTH OPPORTUNITIES HIGH SCHOOL,368,363,364 139 | 08X269,BRONX STUDIO SCHOOL FOR WRITERS AND ARTISTS,s,s,s 140 | 08X282,WOMEN'S ACADEMY OF EXCELLENCE,386,407,378 141 | 08X293,RENAISSANCE HIGH SCHOOL FOR MUSICAL THEATER & TECHNOLOGY,385,384,389 142 | 08X295,GATEWAY SCHOOL FOR ENVIRONMENTAL RESEARCH AND TECHNOLOGY,390,416,394 143 | 08X305,PABLO NERUDA ACADEMY FOR ARCHITECTURE AND WORLD STUDIES,361,337,340 144 | 08X312,MILLENNIUM ART ACADEMY,402,387,375 145 | 08X332,HOLCOMBE L. RUCKER SCHOOL OF COMMUNITY RESEARCH,371,363,350 146 | 08X367,"ARCHIMEDES ACADEMY FOR MATH, SCIENCE AND TECHNOLOGY APPLICATIONS",s,s,s 147 | 08X376,"ANTONIA PANTOJA PREPARATORY ACADEMY, A COLLEGE BOARD SCHOOL",s,s,s 148 | 08X377,BRONX COMMUNITY HIGH SCHOOL,969,367,376 149 | 08X405,HERBERT H. LEHMAN HIGH SCHOOL,436,412,393 150 | 08X408,HERBERT H. LEHMAN YABC,373,402,413 151 | 08X432,BRONX BRIDGES HIGH SCHOOL,s,s,s 152 | 08X452,BRONX GUILD,371,369,365 153 | 08X507,STEVENSON YABC,s,s,s 154 | 08X519,"FELISA RINCON DE GAUTIER INSTITUTE FOR LAW AND PUBLIC POLICY, THE",370,373,356 155 | 08X530,BANANA KELLY HIGH SCHOOL,381,373,377 156 | 08X537,BRONX ARENA HIGH SCHOOL,s,s,s 157 | 08X540,SCHOOL FOR COMMUNITY RESEARCH AND LEARNING,400,366,368 158 | 08X560,HIGH SCHOOL X560 s BRONX ACADEMY HIGH SCHOOL,368,404,399 159 | 08X650,JANE ADDAMS HIGH SCHOOL FOR ACADEMIC CAREERS,359,377,376 160 | 09X227,BRONX EXPEDITIONARY LEARNING HIGH SCHOOL,376,324,349 161 | 09X231,EAGLE ACADEMY FOR YOUNG MEN,387,373,374 162 | 09X239,"URBAN ASSEMBLY ACADEMY FOR HISTORY AND CITIZENSHIP FOR YOUNG MEN, THE",355,372,357 163 | 09X241,"URBAN ASSEMBLY SCHOOL FOR APPLIED MATH AND SCIENCE, THE",464,411,415 164 | 09X250,EXIMIUS COLLEGE PREPARATORY ACADEMY: A COLLEGE BOARD SCHOOL,394,393,382 165 | 09X252,MOTT HALL BRONX HIGH SCHOOL,367,369,356 166 | 09X260,BRONX CENTER FOR SCIENCE AND MATHEMATICS,480,459,457 167 | 09X263,VALIDUS PREPARATORY ACADEMY: AN EXPEDITIONARY LEARNING SCHOOL,363,356,356 168 | 09X276,LEADERSHIP INSTITUTE,353,361,367 169 | 09X297,MORRIS ACADEMY FOR COLLABORATIVE STUDIES,386,386,376 170 | 09X324,BRONX EARLY COLLEGE ACADEMY FOR TEACHING & LEARNING,s,s,s 171 | 09X329,DREAMYARD PREPARATORY SCHOOL,365,382,391 172 | 09X365,ACADEMY FOR LANGUAGE AND TECHNOLOGY,339,315,297 173 | 09X403,BRONX INTERNATIONAL HIGH SCHOOL,312,314,339 174 | 09X404,SCHOOL FOR EXCELLENCE,360,363,351 175 | 09X412,BRONX HIGH SCHOOL OF BUSINESS,376,356,351 176 | 09X413,BRONX HIGH SCHOOL FOR MEDICAL SCIENCE,419,400,402 177 | 09X414,JONATHAN LEVIN HIGH SCHOOL FOR MEDIA AND COMMUNICATIONS,364,379,379 178 | 09X505,"BRONX SCHOOL FOR LAW, GOVERNMENT AND JUSTICE",418,404,402 179 | 09X517,FREDERICK DOUGLASS ACADEMY III SECONDARY SCHOOL,384,368,369 180 | 09X525,BRONX LEADERSHIP ACADEMY HIGH SCHOOL,394,384,388 181 | 09X543,HIGH SCHOOL FOR VIOLIN AND DANCE,315,353,371 182 | 10X141,RIVERDALE / KINGSBRIDGE ACADEMY (MIDDLE SCHOOL / HIGH SCHOOL 141),455,438,440 183 | 10X213,BRONX ENGINEERING AND TECHNOLOGY ACADEMY,412,373,365 184 | 10X225,THEATRE ARTS PRODUCTION COMPANY SCHOOL,391,405,394 185 | 10X237,"THE MARIE CURIE SCHOOL FOR MEDICINE, NURSING, AND HEALTH PROFESSIONS",393,382,382 186 | 10X243,WEST BRONX ACADEMY FOR THE FUTURE,406,382,370 187 | 10X268,KINGSBRIDGE INTERNATIONAL HIGH SCHOOL,356,304,302 188 | 10X284,BRONX SCHOOL OF LAW AND FINANCE,395,402,385 189 | 10X319,PROVIDING URBAN LEARNERS SUCCESS IN EDUCATION HIGH SCHOOL,s,s,s 190 | 10X342,INTERNATIONAL SCHOOL FOR LIBERAL ARTS,333,300,301 191 | 10X368,INsTECH ACADEMY (M.S. / HIGH SCHOOL 368),408,390,383 192 | 10X374,KNOWLEDGE AND POWER PREPARATORY ACADEMY INTERNATIONAL HIGH SCHOOL (KAPPA),401,392,387 193 | 10X397,ENGLISH LANGUAGE LEARNERS AND INTERNATIONAL SUPPORT PREPARATORY ACADEMY (ELLIS),356,343,330 194 | 10X433,HIGH SCHOOL FOR TEACHING AND THE PROFESSIONS,371,370,365 195 | 10X434,BELMONT PREPARATORY HIGH SCHOOL,418,404,400 196 | 10X437,FORDHAM HIGH SCHOOL FOR THE ARTS,350,355,372 197 | 10X438,FORDHAM LEADERSHIP ACADEMY FOR BUSINESS AND TECHNOLOGY,385,367,367 198 | 10X439,BRONX HIGH SCHOOL FOR LAW AND COMMUNITY SERVICE,364,366,352 199 | 10X440,DEWITT CLINTON HIGH SCHOOL,426,419,410 200 | 10X442,"CELIA CRUZ BRONX HIGH SCHOOL OF MUSIC, THE",420,423,427 201 | 10X445,BRONX HIGH SCHOOL OF SCIENCE,688,632,649 202 | 10X475,JOHN F. KENNEDY HIGH SCHOOL,362,351,339 203 | 10X477,MARBLE HILL HIGH SCHOOL FOR INTERNATIONAL STUDIES,435,414,414 204 | 10X478,LEARNING TO WORK GED AT JOHN F. KENNEDY,s,s,s 205 | 10X546,BRONX THEATRE HIGH SCHOOL,362,348,354 206 | 10X549,DISCOVERY HIGH SCHOOL,379,372,364 207 | 10X660,GRACE DODGE CAREER AND TECHNICAL EDUCATION HIGH SCHOOL,382,362,356 208 | 10X667,GRACE DODGE YABC,356,350,317 209 | 10X696,HIGH SCHOOL OF AMERICAN STUDIES AT LEHMAN COLLEGE,648,636,636 210 | 11X249,BRONX HEALTH SCIENCES HIGH SCHOOL,381,370,382 211 | 11X253,BRONX HIGH SCHOOL FOR WRITING AND COMMUNICATION ARTS,357,400,390 212 | 11X265,BRONX LAB SCHOOL,391,377,367 213 | 11X270,ACADEMY FOR SCHOLARSHIP AND ENTREPRENEURSHIP: A COLLEGE BOARD SCHOOL,394,386,361 214 | 11X275,HIGH SCHOOL OF COMPUTERS AND TECHNOLOGY,376,381,354 215 | 11X288,COLLEGIATE INSTITUTE FOR MATH AND SCIENCE,471,444,433 216 | 11X290,BRONX ACADEMY OF HEALTH CAREERS,365,387,383 217 | 11X299,ASTOR COLLEGIATE ACADEMY,391,387,391 218 | 11X415,CHRISTOPHER COLUMBUS HIGH SCHOOL,361,367,353 219 | 11X417,YOUNG ADULT BOROUGH CNTR CHRISTOPHER COLUMBUS HS,s,s,s 220 | 11X418,BRONX HIGH SCHOOL FOR THE VISUAL ARTS,433,419,416 221 | 11X455,HARRY S TRUMAN HIGH SCHOOL,397,386,368 222 | 11X456,LEARNING TO WORK YABC AT TRUMAN HIGH SCHOOL,s,s,s 223 | 11X513,NEW WORLD HIGH SCHOOL,381,332,335 224 | 11X514,THE BRONXWOOD PREPARATORY ACADEMY,372,377,363 225 | 11X541,GLOBAL ENTERPRISE HIGH SCHOOL,382,372,375 226 | 11X542,PELHAM PREPARATORY ACADEMY,438,431,419 227 | 11X544,HIGH SCHOOL FOR CONTEMPORARY ARTS,378,383,365 228 | 11X545,BRONX AEROSPACE HIGH SCHOOL,393,388,382 229 | 12X245,NEW DAY ACADEMY,344,348,354 230 | 12X248,"METROPOLITAN HIGH SCHOOL, THE",367,347,341 231 | 12X251,EXPLORATIONS ACADEMY,381,381,360 232 | 12X262,PERFORMANCE CONSERVATORY HIGH SCHOOL,353,361,360 233 | 12X267,BRONX LATIN,432,408,411 234 | 12X271,EAST BRONX ACADEMY FOR THE FUTURE,378,366,358 235 | 12X278,PEACE AND DIVERSITY ACADEMY,401,390,364 236 | 12X388,PAN AMERICAN INTERNATIONAL HIGH SCHOOL AT MONROE,351,321,298 237 | 12X428,LEARNING TO WORK YABC AT MONROE ACADEMY,s,s,s 238 | 12X446,ARTURO A. SCHOMBURG SATELLITE ACADEMY BRONX,372,380,349 239 | 12X478,THE CINEMA SCHOOL,s,s,s 240 | 12X479,BRONX CAREER AND COLLEGE PREPARATORY HIGH SCHOOL,s,s,s 241 | 12X480,BRONX REGIONAL HIGH SCHOOL,385,398,398 242 | 12X550,HIGH SCHOOL OF WORLD CULTURES,323,304,312 243 | 12X682,FANNIE LOU HAMER FREEDOM HIGH SCHOOL,346,342,341 244 | 12X684,WINGS ACADEMY,374,378,362 245 | 12X690,MONROE ACADEMY FOR BUSINESS/LAW,387,375,376 246 | 12X692,MONROE ACADEMY FOR VISUAL ARTS & DESIGN,357,332,349 247 | 13K265,DR. SUSAN S. MCKINNEY SECONDARY SCHOOL OF THE ARTS,349,352,373 248 | 13K336,ACADEMY OF BUSINESS AND COMMUNITY DEVELOPMENT,374,439,418 249 | 13K350,URBAN ASSEMBLY HIGH SCHOOL OF MUSIC AND ART,364,360,356 250 | 13K412,"BROOKLYN COMMUNITY HIGH SCHOOL OF COMMUNICATION, ARTS AND MEDIA",355,375,384 251 | 13K419,"SCIENCE SKILLS CENTER HIGH SCHOOL FOR SCIENCE, TECHNOLOGY AND THE CREATIVE ARTS",417,399,395 252 | 13K430,BROOKLYN TECHNICAL HIGH SCHOOL,659,587,587 253 | 13K439,BROOKLYN INTERNATIONAL HIGH SCHOOL,364,305,312 254 | 13K483,THE URBAN ASSEMBLY SCHOOL FOR LAW AND JUSTICE,417,400,389 255 | 13K499,ACORN COMMUNITY HIGH SCHOOL,364,384,368 256 | 13K509,FREEDOM ACADEMY HIGH SCHOOL,390,400,403 257 | 13K527,URBAN ASSEMBLY INSTITUTE OF MATH AND SCIENCE FOR YOUNG WOMEN,s,s,s 258 | 13K553,BROOKLYN ACADEMY HIGH SCHOOL,383,435,379 259 | 13K575,BEDFORD STUYVESANT PREPARATORY HIGH SCHOOL,391,398,394 260 | 13K595,BEDFORD ACADEMY HIGH SCHOOL,443,438,431 261 | 13K605,GEORGE WESTINGHOUSE CAREER AND TECHNICAL EDUCATION HIGH SCHOOL,391,406,392 262 | 13K616,BROOKLYN HIGH SCHOOL FOR LEADERSHIP AND COMMUNITY SERVICE,s,s,s 263 | 13K670,BENJAMIN BANNEKER ACADEMY,472,471,448 264 | 13K674,"CITY POLYTECHNIC HIGH SCHOOL OF ENGINEERING, ARCHITECTURE, AND TECHNOLOGY",499,441,413 265 | 14K071,JUAN MOREL CAMPOS SECONDARY SCHOOL,361,365,359 266 | 14K322,FOUNDATIONS ACADEMY,s,s,s 267 | 14K404,ACADEMY FOR YOUNG WRITERS,357,387,381 268 | 14K449,"BROOKLYN LATIN SCHOOL, THE",584,586,570 269 | 14K454,GREEN SCHOOL: AN ACADEMY FOR ENVIRONMENTAL CAREERS,386,407,396 270 | 14K474,PROGRESS HIGH SCHOOL FOR PROFESSIONAL CAREERS,379,364,371 271 | 14K477,SCHOOL FOR LEGAL STUDIES,396,413,395 272 | 14K478,"THE HIGH SCHOOL FOR ENTERPRISE, BUSINESS AND TECHNOLOGY",421,398,396 273 | 14K488,BROOKLYN PREPARATORY HIGH SCHOOL,373,367,350 274 | 14K558,WILLIAMSBURG HIGH SCHOOL FOR ARCHITECTURE AND DESIGN,385,363,364 275 | 14K561,WILLIAMSBURG PREPARATORY SCHOOL,410,397,380 276 | 14K586,LYONS COMMUNITY SCHOOL,377,371,355 277 | 14K610,AUTOMOTIVE HIGH SCHOOL,376,367,350 278 | 14K632,FRANCES PERKINS ACADEMY,372,382,368 279 | 14K685,EL PUENTE ACADEMY FOR PEACE AND JUSTICE,335,359,341 280 | 14K923,AUTOMOTIVE HIGH SCHOOL YABC,s,s,s 281 | 15K429,BROOKLYN SCHOOL FOR GLOBAL STUDIES,367,361,383 282 | 15K448,BROOKLYN SECONDARY SCHOOL FOR COLLABORATIVE STUDIES,399,393,387 283 | 15K462,SECONDARY SCHOOL FOR LAW,411,398,394 284 | 15K463,SECONDARY SCHOOL FOR JOURNALISM,391,397,381 285 | 15K464,PARK SLOPE COLLEGIATE,416,379,380 286 | 15K497,SCHOOL FOR INTERNATIONAL STUDIES,415,405,392 287 | 15K519,COBBLE HILL SCHOOL OF AMERICAN STUDIES,402,398,385 288 | 15K520,PACIFIC HIGH SCHOOL,341,352,300 289 | 15K529,WEST BROOKLYN COMMUNITY HIGH SCHOOL,s,s,s 290 | 15K530,METROPOLITAN CORPORATE ACADEMY HIGH SCHOOL,365,368,368 291 | 15K656,BROOKLYN HIGH SCHOOL OF THE ARTS,421,426,411 292 | 15K667,SUNSET PARK HIGH SCHOOL,s,s,s 293 | 15K698,SOUTH BROOKLYN COMMUNITY HIGH SCHOOL,416,430,425 294 | 16K393,FREDERICK DOUGLASS ACADEMY IV SECONDARY SCHOOL,355,355,358 295 | 16K455,BOYS AND GIRLS HIGH SCHOOL,370,365,362 296 | 16K498,BROOKLYN HIGH SCHOOL FOR LAW AND TECHNOLOGY,372,362,358 297 | 16K594,GOTHAM PROFESSIONAL ARTS ACADEMY,372,370,351 298 | 16K688,THE BROOKLYN ACADEMY OF GLOBAL FINANCE,s,s,s 299 | 17K382,ACADEMY FOR COLLEGE PREPARATION AND CAREER EXPLORATION: A COLLEGE BOARD SCHOOL,374,396,369 300 | 17K408,ACADEMY OF HOSPITALITY AND TOURISM,342,352,351 301 | 17K467,ERASMUS YABC,s,s,s 302 | 17K489,W.E.B. DUBOIS ACADEMIC HIGH SCHOOL,364,394,334 303 | 17K524,INTERNATIONAL HIGH SCHOOL AT PROSPECT HEIGHTS,335,287,291 304 | 17K528,THE HIGH SCHOOL FOR GLOBAL CITIZENSHIP,385,403,388 305 | 17K531,"SCHOOL FOR HUMAN RIGHTS, THE",381,348,359 306 | 17K533,SCHOOL FOR DEMOCRACY AND LEADERSHIP,404,377,372 307 | 17K537,HIGH SCHOOL FOR YOUTH AND COMMUNITY DEVELOPMENT AT ERASMUS,349,338,340 308 | 17K539,HIGH SCHOOL FOR SERVICE & LEARNING AT ERASMUS,375,362,368 309 | 17K543,"SCIENCE, TECHNOLOGY AND RESEARCH EARLY COLLEGE HIGH SCHOOL AT ERASMUS",462,457,441 310 | 17K544,INTERNATIONAL ARTS BUSINESS SCHOOL,391,386,369 311 | 17K546,HIGH SCHOOL FOR PUBLIC SERVICE: HEROES OF TOMORROW,441,418,414 312 | 17K547,BROOKLYN ACADEMY OF SCIENCE AND THE ENVIRONMENT,382,388,373 313 | 17K548,BROOKLYN SCHOOL FOR MUSIC & THEATRE,393,385,373 314 | 17K568,BROWNSVILLE ACADEMY HIGH SCHOOL,356,372,335 315 | 17K590,MEDGAR EVERS COLLEGE PREPARATORY SCHOOL,481,476,479 316 | 17K600,CLARA BARTON HIGH SCHOOL,413,425,413 317 | 17K625,PAUL ROBESON HIGH SCHOOL,363,365,355 318 | 17K751,ACADEMY FOR HEALTH CAREERS,s,s,s 319 | 18K563,IT TAKES A VILLAGE ACADEMY,320,313,330 320 | 18K566,BROOKLYN GENERATION SCHOOL,377,374,394 321 | 18K567,BROOKLYN THEATRE ARTS HIGH SCHOOL,358,383,377 322 | 18K569,KURT HAHN EXPEDITIONARY LEARNING SCHOOL,378,368,346 323 | 18K576,VICTORY COLLEGIATE HIGH SCHOOL,377,387,379 324 | 18K578,BROOKLYN BRIDGE ACADEMY,362,384,351 325 | 18K589,ARTS & MEDIA PREPARATORY ACADEMY,360,361,359 326 | 18K617,HIGH SCHOOL FOR INNOVATION IN ADVERTISING AND MEDIA,393,404,386 327 | 18K629,CULTURAL ACADEMY FOR THE ARTS AND SCIENCES,395,393,381 328 | 18K633,HIGH SCHOOL FOR MEDICAL PROFESSIONS,380,386,393 329 | 18K635,OLYMPUS ACADEMY,370,400,370 330 | 18K637,ACADEMY FOR CONSERVATION AND THE ENVIRONMENT,381,363,367 331 | 18K642,URBAN ACTION ACADEMY,385,376,374 332 | 18K673,EAST BROOKLYN COMMUNITY HIGH SCHOOL,403,410,378 333 | 19K409,EAST NEW YORK FAMILY ACADEMY,432,416,394 334 | 19K420,FRANKLIN K. LANE HIGH SCHOOL,s,s,s 335 | 19K431,THOMAS JEFFERSON YABC,s,s,s 336 | 19K502,FDNY HIGH SCHOOL FOR FIRE AND LIFE SAFETY,349,341,333 337 | 19K504,HIGH SCHOOL FOR CIVIL RIGHTS,349,363,342 338 | 19K507,PERFORMING ARTS AND TECHNOLOGY HIGH SCHOOL,386,380,383 339 | 19K507,PERFORMING ARTS AND TECHNOLOGY HIGH SCHOOL,386,380,383 340 | 19K510,WORLD ACADEMY FOR TOTAL COMMUNITY HEALTH HIGH SCHOOL,365,371,370 341 | 19K583,MULTICULTURAL HIGH SCHOOL,322,279,286 342 | 19K615,TRANSIT TECH CAREER AND TECHNICAL EDUCATION HIGH SCHOOL,418,395,380 343 | 19K618,ACADEMY OF INNOVATIVE TECHNOLOGY,371,371,354 344 | 19K639,BROOKLYN LAB SCHOOL,385,360,363 345 | 19K659,CYPRESS HILLS COLLEGIATE PREPARATORY SCHOOL,385,376,368 346 | 19K660,W. H. MAXWELL CAREER AND TECHNICAL EDUCATION HIGH SCHOOL,369,370,363 347 | 19K683,"THE SCHOOL FOR CLASSICS: AN ACADEMY OF THINKERS, WRITERS AND PERFORMERS",400,383,374 348 | 20K445,NEW UTRECHT HIGH SCHOOL,471,402,399 349 | 20K485,HIGH SCHOOL OF TELECOMMUNICATION ARTS AND TECHNOLOGY,474,425,424 350 | 20K490,FORT HAMILTON HIGH SCHOOL,478,417,411 351 | 20K505,FRANKLIN DELANO ROOSEVELT HIGH SCHOOL,486,383,375 352 | 20K609,THE URBAN ASSEMBLY SCHOOL FOR CRIMINAL JUSTICE,s,s,s 353 | 20K658,FRANKLIN DELANO ROOSEVELT YABC,477,338,316 354 | 21K337,INTERNATIONAL HIGH SCHOOL AT LAFAYETTE,386,326,314 355 | 21K344,RACHEL CARSON HIGH SCHOOL FOR COASTAL STUDIES,427,402,408 356 | 21K348,HIGH SCHOOL OF SPORTS MANAGEMENT,398,388,378 357 | 21K410,ABRAHAM LINCOLN HIGH SCHOOL,437,396,393 358 | 21K412/21K411,ABRAHAM LINCOLN YABC/LEARNING TO WORK GED AT ABRAHAM LINCOLN,s,s,s 359 | 21K468,KINGSBOROUGH EARLY COLLEGE SCHOOL,s,s,s 360 | 21K525,EDWARD R. MURROW HIGH SCHOOL,496,468,467 361 | 21K540,JOHN DEWEY HIGH SCHOOL,468,404,390 362 | 21K559,LIFE ACADEMY HIGH SCHOOL FOR FILM AND MUSIC,375,384,365 363 | 21K572,EXPEDITIONARY LEARNING SCHOOL FOR COMMUNITY LEADERS,370,353,356 364 | 21K620,WILLIAM E. GRADY CAREER AND TECHNICAL EDUCATION HIGH SCHOOL,414,394,376 365 | 21K690,BROOKLYN STUDIO SECONDARY SCHOOL,449,429,435 366 | 21K728,LIBERATION DIPLOMA PLUS,369,411,373 367 | 22K405,MIDWOOD HIGH SCHOOL,519,478,476 368 | 22K425,JAMES MADISON HIGH SCHOOL,475,436,439 369 | 22K495,SHEEPSHEAD BAY HIGH SCHOOL,392,383,370 370 | 22K535,LEON M. GOLDSTEIN HIGH SCHOOL FOR THE SCIENCES,561,524,542 371 | 22K555,BROOKLYN COLLEGE ACADEMY,456,456,440 372 | 23K493,BROOKLYN COLLEGIATE: A COLLEGE BOARD SCHOOL,409,389,387 373 | 23K514,FREDERICK DOUGLASS ACADEMY VII HIGH SCHOOL,371,361,359 374 | 23K643,BROOKLYN DEMOCRACY ACADEMY,338,349,331 375 | 23K646,ASPIRATIONS DIPLOMA PLUS HIGH SCHOOL,371,311,311 376 | 23K647,METROPOLITAN DIPLOMA PLUS HIGH SCHOOL,346,350,332 377 | 23K697,TEACHERS PREPARATORY HIGH SCHOOL,416,392,388 378 | 24Q264,ACADEMY OF FINANCE AND ENTERPRISE,454,405,421 379 | 24Q267,HIGH SCHOOL OF APPLIED COMMUNICATION,413,406,400 380 | 24Q267,HIGH SCHOOL OF APPLIED COMMUNICATION,413,406,400 381 | 24Q293,CIVIC LEADERSHIP ACADEMY,429,404,407 382 | 24Q296,PAN AMERICAN INTERNATIONAL HIGH SCHOOL,323,317,311 383 | 24Q299,BARD HIGH SCHOOL EARLY COLLEGE II,568,545,550 384 | 24Q455,NEWTOWN HIGH SCHOOL,440,383,380 385 | 24Q457,YOUNG ADULT BOROUGH CENTER AT ARTS AND BUSINESS HS,s,s,s 386 | 24Q485,GROVER CLEVELAND HIGH SCHOOL,420,395,396 387 | 24Q520,MIDDLE COLLEGE HIGH SCHOOL AT LAGUARDIA COMMUNITY COLLEGE,393,399,385 388 | 24Q530,INTERNATIONAL HIGH SCHOOL AT LAGUARDIA COMMUNITY COLLEGE,409,326,329 389 | 24Q550,HIGH SCHOOL FOR ARTS AND BUSINESS,403,391,380 390 | 24Q560,"ROBERT F. WAGNER, JR. SECONDARY SCHOOL FOR ARTS AND TECHNOLOGY",447,443,440 391 | 24Q600,QUEENS VOCATIONAL AND TECHNICAL HIGH SCHOOL,447,417,406 392 | 24Q610,AVIATION CAREER & TECHNICAL EDUCATION HIGH SCHOOL,496,445,423 393 | 24Q744,VOYAGES PREPARATORY,s,s,s 394 | 25Q252,"QUEENS SCHOOL OF INQUIRY, THE",498,455,443 395 | 25Q263,FLUSHING INTERNATIONAL HIGH SCHOOL,417,314,318 396 | 25Q281,EASTsWEST SCHOOL OF INTERNATIONAL STUDIES,463,416,392 397 | 25Q285,WORLD JOURNALISM PREPARATORY: A COLLEGE BOARD SCHOOL,489,471,481 398 | 25Q425,JOHN BOWNE HIGH SCHOOL,451,397,395 399 | 25Q460,FLUSHING HIGH SCHOOL,441,393,382 400 | 25Q467,FLUSHING YABC,373,378,344 401 | 25Q525,TOWNSEND HARRIS HIGH SCHOOL,651,621,638 402 | 25Q540,QUEENS ACADEMY HIGH SCHOOL,382,398,388 403 | 25Q670,ROBERT F. KENNEDY COMMUNITY HIGH SCHOOL,458,431,441 404 | 25Q792,NORTH QUEENS COMMUNITY HIGH SCHOOL,421,379,377 405 | 26Q415,BENJAMIN N. CARDOZO HIGH SCHOOL,545,480,489 406 | 26Q430,FRANCIS LEWIS HIGH SCHOOL,539,468,467 407 | 26Q435,MARTIN VAN BUREN HIGH SCHOOL,397,391,384 408 | 26Q495,BAYSIDE HIGH SCHOOL,523,462,464 409 | 26Q566,"QUEENS HIGH SCHOOL OF TEACHING, LIBERAL ARTS AND THE SCIENCES",434,425,420 410 | 27Q260,FREDERICK DOUGLASS ACADEMY VI HIGH SCHOOL,385,387,373 411 | 27Q262,CHANNEL VIEW SCHOOL FOR RESEARCH,419,432,401 412 | 27Q302,"QUEENS HIGH SCHOOL FOR INFORMATION, RESEARCH, AND TECHNOLOGY",401,391,364 413 | 27Q308,ROBERT H. GODDARD HIGH SCHOOL OF COMMUNICATION ARTS AND TECHNOLOGY,426,423,416 414 | 27Q309,ACADEMY OF MEDICAL TECHNOLOGY: A COLLEGE BOARD SCHOOL,379,367,348 415 | 27Q323,SCHOLARS' ACADEMY,537,499,496 416 | 27Q400,AUGUST MARTIN HIGH SCHOOL,371,377,360 417 | 27Q400,AUGUST MARTIN HIGH SCHOOL,371,377,360 418 | 27Q410,BEACH CHANNEL HIGH SCHOOL,396,384,354 419 | 27Q475,RICHMOND HILL HIGH SCHOOL,404,382,368 420 | 27Q480,JOHN ADAMS HIGH SCHOOL,409,391,392 421 | 27Q650,"HIGH SCHOOL FOR CONSTRUCTION TRADES, ENGINEERING AND ARCHITECTURE",491,429,425 422 | 28Q284,YORK EARLY COLLEGE ACADEMY,s,s,s 423 | 28Q310,QUEENS COLLEGIATE: A COLLEGE BOARD SCHOOL,445,420,400 424 | 28Q325,HILLSIDE ARTS & LETTERS ACADEMY,s,s,s 425 | 28Q338,QUEENS SATELLITE HIGH SCHOOL FOR OPPORTUNITY,408,403,367 426 | 28Q350,JAMAICA GATEWAY TO THE SCIENCES,452,430,425 427 | 28Q440,FOREST HILLS HIGH SCHOOL,497,456,454 428 | 28Q470,JAMAICA HIGH SCHOOL,368,342,353 429 | 28Q505,HILLCREST HIGH SCHOOL,413,395,386 430 | 28Q620,THOMAS A. EDISON CAREER AND TECHNICAL EDUCATION HIGH SCHOOL,478,452,442 431 | 28Q680,QUEENS GATEWAY TO HEALTH SCIENCES SECONDARY SCHOOL,523,513,502 432 | 28Q686,QUEENS METROPOLITAN HIGH SCHOOL,s,s,s 433 | 28Q687,QUEENS HIGH SCHOOL FOR THE SCIENCES AT YORK COLLEGE,660,612,596 434 | 28Q690,HIGH SCHOOL FOR LAW ENFORCEMENT AND PUBLIC SAFETY,406,406,384 435 | 28Q896,"YOUNG WOMEN'S LEADERSHIP SCHOOL, QUEENS",445,439,432 436 | 29Q248,QUEENS PREPARATORY ACADEMY,380,360,359 437 | 29Q259,PATHWAYS COLLEGE PREPARATORY SCHOOL: A COLLEGE BOARD SCHOOL,397,401,375 438 | 29Q265,EXCELSIOR PREPARATORY HIGH SCHOOL,398,402,402 439 | 29Q272,GEORGE WASHINGTON CARVER HIGH SCHOOL FOR THE SCIENCES,427,436,424 440 | 29Q283,PREPARATORY ACADEMY FOR WRITERS: A COLLEGE BOARD SCHOOL,367,370,363 441 | 29Q326,CAMBRIA HEIGHTS ACADEMY,s,s,s 442 | 29Q492,"MATHEMATICS, SCIENCE RESEARCH AND TECHNOLOGY MAGNET HIGH SCHOOL",426,400,394 443 | 29Q494,"LAW, GOVERNMENT AND COMMUNITY SERVICE HIGH SCHOOL",377,385,377 444 | 29Q496,"BUSINESS, COMPUTER APPLICATIONS & ENTREPRENEURSHIP HIGH SCHOOL",414,379,359 445 | 29Q498,HUMANITIES & ARTS MAGNET HIGH SCHOOL,381,393,377 446 | 30Q286,"YOUNG WOMEN'S LEADERSHIP SCHOOL, ASTORIA",s,s,s 447 | 30Q301,ACADEMY FOR CAREERS IN TELEVISION AND FILM,440,410,405 448 | 30Q445,WILLIAM CULLEN BRYANT HIGH SCHOOL,449,414,412 449 | 30Q450,LONG ISLAND CITY HIGH SCHOOL,420,403,395 450 | 30Q501,FRANK SINATRA SCHOOL OF THE ARTS HIGH SCHOOL,496,504,494 451 | 30Q502,INFORMATION TECHNOLOGY HIGH SCHOOL,434,407,398 452 | 30Q502,INFORMATION TECHNOLOGY HIGH SCHOOL,434,407,398 453 | 30Q555,NEWCOMERS HIGH SCHOOL,475,323,329 454 | 30Q575,ACADEMY OF AMERICAN STUDIES,492,487,491 455 | 30Q580,BACCALAUREATE SCHOOL FOR GLOBAL EDUCATION,568,524,544 456 | 31R047,CSI HIGH SCHOOL FOR INTERNATIONAL STUDIES,451,452,450 457 | 31R064,GAYNOR MCCOWN EXPEDITIONARY LEARNING SCHOOL,412,398,385 458 | 31R080,THE MICHAEL J. PETRIDES SCHOOL,488,472,466 459 | 31R080,THE MICHAEL J. PETRIDES SCHOOL,488,472,466 460 | 31R440,NEW DORP HIGH SCHOOL,437,424,416 461 | 31R445,PORT RICHMOND HIGH SCHOOL,438,424,417 462 | 31R450,CURTIS HIGH SCHOOL,435,437,429 463 | 31R455,TOTTENVILLE HIGH SCHOOL,486,462,470 464 | 31R460,SUSAN E. WAGNER HIGH SCHOOL,474,455,459 465 | 31R470,CONCORD HIGH SCHOOL,455,466,414 466 | 31R600,RALPH R. MCKEE CAREER AND TECHNICAL EDUCATION HIGH SCHOOL,422,416,397 467 | 31R605,STATEN ISLAND TECHNICAL HIGH SCHOOL,682,635,636 468 | 31R607,YOUNG ADULT BOROUGH CENTER AT STATEN IS TECH HS,375,405,370 469 | 32K403,ACADEMY FOR ENVIRONMENTAL LEADERSHIP,366,380,352 470 | 32K545,EBC HIGH SCHOOL FOR PUBLIC SERVICE–BUSHWICK,409,384,361 471 | 32K549,BUSHWICK SCHOOL FOR SOCIAL JUSTICE,353,348,334 472 | 32K552,ACADEMY OF URBAN PLANNING,364,342,354 473 | 32K554,ALL CITY LEADERSHIP SECONDARY SCHOOL,465,428,422 474 | 32K556,BUSHWICK LEADERS HIGH SCHOOL FOR ACADEMIC EXCELLENCE,358,347,350 475 | 32K564,BUSHWICK COMMUNITY HIGH SCHOOL,317,359,358 476 | 75K371,P.S. 371 s LILLIAN L. RASHKIS,s,s,s 477 | 75M035,P.S. 035,s,s,s 478 | 75Q256,P.S. Q256,s,s,s 479 | 75Q811,P.S. Q811,444,429,433 480 | 75R025,SOUTH RICHMOND HIGH SCHOOL I.S./P.S. 25,s,s,s 481 | 75X012,P.S. X012 LEWIS AND CLARK SCHOOL,s,s,s 482 | 75X754,J. M. RAPPORT SCHOOL CAREER DEVELOPMENT,s,s,s 483 | 79M645,SCHOOL FOR COOPERATIVE TECHNICAL EDUCATION,s,s,s 484 | 79Q950,GED PLUS s CITYWIDE,400,496,426 485 | 79X490,PHOENIX ACADEMY,370,367,360 486 | 79X490,PHOENIX ACADEMY,370,367,360 -------------------------------------------------------------------------------- /datasets/SAT_2012.csv: -------------------------------------------------------------------------------- 1 | DBN,SCHOOL NAME,Num of SAT Test Takers,SAT Critical Reading Avg. Score,SAT Math Avg. Score,SAT Writing Avg. Score 2 | 01M292,HENRY STREET SCHOOL FOR INTERNATIONAL STUDIES,29,355,404,363 3 | 01M448,UNIVERSITY NEIGHBORHOOD HIGH SCHOOL,91,383,423,366 4 | 01M450,EAST SIDE COMMUNITY SCHOOL,70,377,402,370 5 | 01M458,FORSYTH SATELLITE ACADEMY,7,414,401,359 6 | 01M509,MARTA VALLE HIGH SCHOOL,44,390,433,384 7 | 01M515,LOWER EAST SIDE PREPARATORY HIGH SCHOOL,112,332,557,316 8 | 01M539,"NEW EXPLORATIONS INTO SCIENCE, TECHNOLOGY AND MATH HIGH SCHOOL",159,522,574,525 9 | 01M650,CASCADES HIGH SCHOOL,18,417,418,411 10 | 01M696,BARD HIGH SCHOOL EARLY COLLEGE,130,624,604,628 11 | 02M047,47 THE AMERICAN SIGN LANGUAGE AND ENGLISH SECONDARY SCHOOL,16,395,400,387 12 | 02M288,FOOD AND FINANCE HIGH SCHOOL,62,409,393,392 13 | 02M294,ESSEX STREET ACADEMY,53,394,384,378 14 | 02M296,HIGH SCHOOL OF HOSPITALITY MANAGEMENT,58,374,375,362 15 | 02M298,PACE HIGH SCHOOL,85,423,438,432 16 | 02M300,"URBAN ASSEMBLY SCHOOL OF DESIGN AND CONSTRUCTION, THE",48,404,449,416 17 | 02M303,"FACING HISTORY SCHOOL, THE",76,353,358,340 18 | 02M305,"URBAN ASSEMBLY ACADEMY OF GOVERNMENT AND LAW, THE",50,375,388,385 19 | 02M308,LOWER MANHATTAN ARTS ACADEMY,40,403,392,405 20 | 02M313,"JAMES BALDWIN SCHOOL, THE: A SCHOOL FOR EXPEDITIONARY LEARNING",69,408,390,390 21 | 02M316,"URBAN ASSEMBLY SCHOOL OF BUSINESS FOR YOUNG WOMEN, THE",42,373,370,384 22 | 02M374,GRAMERCY ARTS HIGH SCHOOL,60,391,391,394 23 | 02M376,NYC ISCHOOL,92,473,483,479 24 | 02M392,MANHATTAN BUSINESS ACADEMY,s,s,s,s 25 | 02M393,BUSINESS OF SPORTS SCHOOL,s,s,s,s 26 | 02M394,EMMA LAZARUS HIGH SCHOOL,79,319,512,357 27 | 02M399,THE HIGH SCHOOL FOR LANGUAGE AND DIPLOMACY,s,s,s,s 28 | 02M400,HIGH SCHOOL FOR ENVIRONMENTAL STUDIES,263,465,493,461 29 | 02M407,INSTITUTE FOR COLLABORATIVE EDUCATION,54,492,465,467 30 | 02M408,PROFESSIONAL PERFORMING ARTS HIGH SCHOOL,94,509,490,523 31 | 02M411,BARUCH COLLEGE CAMPUS HIGH SCHOOL,104,496,563,518 32 | 02M412,N.Y.C. LAB SCHOOL FOR COLLABORATIVE STUDIES,114,537,590,550 33 | 02M413,SCHOOL OF THE FUTURE HIGH SCHOOL,66,517,533,515 34 | 02M414,N.Y.C. MUSEUM SCHOOL,103,468,492,459 35 | 02M416,ELEANOR ROOSEVELT HIGH SCHOOL,127,572,594,592 36 | 02M418,MILLENNIUM HIGH SCHOOL,144,528,553,533 37 | 02M419,LANDMARK HIGH SCHOOL,62,390,399,381 38 | 02M420,HIGH SCHOOL FOR HEALTH PROFESSIONS AND HUMAN SERVICES,336,429,449,428 39 | 02M425,LEADERSHIP AND PUBLIC SERVICE HIGH SCHOOL,84,416,426,391 40 | 02M427,MANHATTAN ACADEMY FOR ARTS & LANGUAGE,s,s,s,s 41 | 02M429,LEGACY SCHOOL FOR INTEGRATED STUDIES,29,356,357,349 42 | 02M437,HUDSON HIGH SCHOOL OF LEARNING TECHNOLOGIES,s,s,s,s 43 | 02M438,INTERNATIONAL HIGH SCHOOL AT UNION SQUARE,s,s,s,s 44 | 02M439,MANHATTAN VILLAGE ACADEMY,95,441,473,458 45 | 02M440,BAYARD RUSTIN EDUCATIONAL COMPLEX,59,378,365,368 46 | 02M449,VANGUARD HIGH SCHOOL,72,395,416,388 47 | 02M459,MANHATTAN INTERNATIONAL HIGH SCHOOL,49,376,460,391 48 | 02M460,WASHINGTON IRVING HIGH SCHOOL,151,373,387,360 49 | 02M473,WASHINGTON IRVING YABC,s,s,s,s 50 | 02M475,STUYVESANT HIGH SCHOOL,832,679,735,682 51 | 02M489,HIGH SCHOOL OF ECONOMICS AND FINANCE,167,443,489,442 52 | 02M500,UNITY CENTER FOR URBAN TECHNOLOGIES,25,370,349,351 53 | 02M519,TALENT UNLIMITED HIGH SCHOOL,81,469,472,475 54 | 02M520,MURRY BERGTRAUM HIGH SCHOOL FOR BUSINESS CAREERS,264,407,440,393 55 | 02M529,JACQUELINE KENNEDY ONASSIS HIGH SCHOOL,131,414,425,400 56 | 02M531,REPERTORY COMPANY HIGH SCHOOL FOR THEATRE ARTS,42,429,404,420 57 | 02M542,MANHATTAN BRIDGES HIGH SCHOOL,66,336,378,344 58 | 02M543,NEW DESIGN HIGH SCHOOL,73,391,395,382 59 | 02M544,INDEPENDENCE HIGH SCHOOL,14,389,371,335 60 | 02M545,HIGH SCHOOL FOR DUAL LANGUAGE AND ASIAN STUDIES,78,412,581,431 61 | 02M550,LIBERTY HIGH SCHOOL ACADEMY FOR NEWCOMERS,26,368,436,352 62 | 02M551,THE URBAN ASSEMBLY NEW YORK HARBOR SCHOOL,77,405,423,384 63 | 02M560,HIGH SCHOOL M560 s CITY AS SCHOOL,56,498,440,477 64 | 02M565,URBAN ACADEMY LABORATORY HIGH SCHOOL,30,527,508,512 65 | 02M570,SATELLITE ACADEMY HIGH SCHOOL,33,350,337,345 66 | 02M575,MANHATTAN COMPREHENSIVE NIGHT AND DAY HIGH SCHOOL,121,345,517,343 67 | 02M580,RICHARD R. GREEN HIGH SCHOOL OF TEACHING,84,408,384,403 68 | 02M586,HARVEY MILK HIGH SCHOOL,9,458,416,429 69 | 02M600,THE HIGH SCHOOL OF FASHION INDUSTRIES,335,423,423,411 70 | 02M605,HUMANITIES PREPARATORY ACADEMY,36,426,403,426 71 | 02M615,CHELSEA CAREER AND TECHNICAL EDUCATION HIGH SCHOOL,83,399,418,390 72 | 02M620,NORMAN THOMAS HIGH SCHOOL,154,370,379,359 73 | 02M625,HIGH SCHOOL OF GRAPHIC COMMUNICATION ARTS,191,395,382,376 74 | 02M630,ART AND DESIGN HIGH SCHOOL,270,444,441,430 75 | 02M655,LIFE SCIENCES SECONDARY SCHOOL,61,409,424,403 76 | 03M283,MANHATTAN THEATRE LAB HIGH SCHOOL,27,406,379,408 77 | 03M299,"HIGH SCHOOL FOR ARTS, IMAGINATION AND INQUIRY",49,374,384,374 78 | 03M307,"URBAN ASSEMBLY SCHOOL FOR MEDIA STUDIES, THE",41,384,390,370 79 | 03M402,THE URBAN ASSEMBLY SCHOOL FOR GREEN CAREERS,s,s,s,s 80 | 03M403,THE GLOBAL LEARNING COLLABORATIVE,s,s,s,s 81 | 03M404,INNOVATION DIPLOMA PLUS,12,416,403,381 82 | 03M415,WADLEIGH SECONDARY SCHOOL FOR THE PERFORMING & VISUAL ARTS,32,371,368,370 83 | 03M417,FRANK MCCOURT HIGH SCHOOL,s,s,s,s 84 | 03M470,LOUIS D. BRANDEIS HIGH SCHOOL,131,370,390,358 85 | 03M479,BEACON HIGH SCHOOL,261,577,575,592 86 | 03M485,FIORELLO H. LAGUARDIA HIGH SCHOOL OF MUSIC & ART AND PERFORMING ARTS,531,566,564,577 87 | 03M492,"HIGH SCHOOL FOR LAW, ADVOCACY AND COMMUNITY JUSTICE",66,396,398,402 88 | 03M494,HIGH SCHOOL OF ARTS AND TECHNOLOGY,75,433,433,411 89 | 03M505,EDWARD A. REYNOLDS WEST SIDE HIGH SCHOOL,35,401,369,351 90 | 03M541,MANHATTAN / HUNTER SCIENCE HIGH SCHOOL,111,473,506,467 91 | 03M577,YOUNG ADULT BOROUGH CENTER AT LOUIS D. BRANDEIS HS,s,s,s,s 92 | 03M860,FREDERICK DOUGLASS ACADEMY II SECONDARY SCHOOL,43,356,379,361 93 | 04M409,COALITION SCHOOL FOR SOCIAL CHANGE,48,354,357,373 94 | 04M435,MANHATTAN CENTER FOR SCIENCE AND MATHEMATICS,375,461,514,455 95 | 04M495,PARK EAST HIGH SCHOOL,51,373,379,376 96 | 04M555,CENTRAL PARK EAST HIGH SCHOOL,73,405,421,395 97 | 04M610,YOUNG WOMEN'S LEADERSHIP SCHOOL,70,432,446,448 98 | 04M635,ACADEMY OF ENVIRONMENTAL SCIENCE SECONDARY HIGH SCHOOL,48,369,369,357 99 | 04M680,"HERITAGE SCHOOL, THE",31,358,351,345 100 | 05M285,HARLEM RENAISSANCE HIGH SCHOOL,29,357,318,333 101 | 05M304,MOTT HALL HIGH SCHOOL,54,413,399,398 102 | 05M362,"COLUMBIA SECONDARY SCHOOL FOR MATH, SCIENCE, AND ENGINEERING",s,s,s,s 103 | 05M367,ACADEMY FOR SOCIAL ACTION: A COLLEGE BOARD SCHOOL,33,354,366,342 104 | 05M369,URBAN ASSEMBLY SCHOOL FOR THE PERFORMING ARTS,56,360,353,364 105 | 05M469,CHOIR ACADEMY OF HARLEM,20,354,360,385 106 | 05M499,FREDERICK DOUGLASS ACADEMY,214,458,474,442 107 | 05M670,THURGOOD MARSHALL ACADEMY FOR LEARNING AND SOCIAL CHANGE,66,396,402,404 108 | 05M685,BREAD & ROSES INTEGRATED ARTS HIGH SCHOOL,61,369,361,355 109 | 05M692,"HIGH SCHOOL FOR MATHEMATICS, SCIENCE AND ENGINEERING AT CITY COLLEGE",101,605,654,588 110 | 06M293,CITY COLLEGE ACADEMY OF THE ARTS,60,408,446,416 111 | 06M346,COMMUNITY HEALTH ACADEMY OF THE HEIGHTS,55,362,376,367 112 | 06M348,WASHINGTON HEIGHTS EXPEDITIONARY LEARNING SCHOOL,70,380,395,399 113 | 06M423,HIGH SCHOOL FOR EXCELLENCE AND INNOVATION,s,s,s,s 114 | 06M457,GEORGE WASHINGTON YABC,7,394,357,346 115 | 06M462,HIGH SCHOOL FOR INTERNATIONAL BUSINESS AND FINANCE,76,365,384,378 116 | 06M463,HIGH SCHOOL FOR MEDIA AND COMMUNICATIONS,63,369,380,349 117 | 06M467,HIGH SCHOOL FOR LAW AND PUBLIC SERVICE,94,363,378,361 118 | 06M468,HIGH SCHOOL FOR HEALTH CAREERS AND SCIENCES,24,400,422,402 119 | 06M540,A. PHILIP RANDOLPH CAMPUS HIGH SCHOOL,228,430,456,423 120 | 06M552,GREGORIO LUPERON HIGH SCHOOL FOR SCIENCE AND MATHEMATICS,56,339,349,326 121 | 07X221,SOUTH BRONX PREPARATORY: A COLLEGE BOARD SCHOOL,65,364,378,348 122 | 07X321,CROTONA ACADEMY HIGH SCHOOL,9,379,364,382 123 | 07X334,INTERNATIONAL COMMUNITY HIGH SCHOOL,34,310,324,311 124 | 07X379,JILL CHAIFETZ TRANSFER HIGH SCHOOL,s,s,s,s 125 | 07X381,BRONX HAVEN HIGH SCHOOL,s,s,s,s 126 | 07X427,COMMUNITY SCHOOL FOR SOCIAL JUSTICE,43,361,359,357 127 | 07X473,MOTT HAVEN VILLAGE PREPARATORY HIGH SCHOOL,63,351,375,371 128 | 07X495,UNIVERSITY HEIGHTS SECONDARY SCHOOL,79,403,394,404 129 | 07X500,HOSTOSsLINCOLN ACADEMY OF SCIENCE,66,420,426,411 130 | 07X520,FOREIGN LANGUAGE ACADEMY OF GLOBAL STUDIES,64,399,396,391 131 | 07X527,BRONX LEADERSHIP ACADEMY II HIGH SCHOOL,62,362,378,363 132 | 07X547,NEW EXPLORERS HIGH SCHOOL,28,367,356,361 133 | 07X548,URBAN ASSEMBLY SCHOOL FOR CAREERS IN SPORTS,44,387,411,383 134 | 07X551,BRONX ACADEMY OF LETTERS,51,413,381,407 135 | 07X600,ALFRED E. SMITH CAREER AND TECHNICAL EDUCATION HIGH SCHOOL,76,394,400,364 136 | 07X655,SAMUEL GOMPERS CAREER AND TECHNICAL EDUCATION HIGH SCHOOL,47,398,416,370 137 | 07X670,HEALTH OPPORTUNITIES HIGH SCHOOL,114,363,368,364 138 | 08X269,BRONX STUDIO SCHOOL FOR WRITERS AND ARTISTS,s,s,s,s 139 | 08X282,WOMEN'S ACADEMY OF EXCELLENCE,44,407,386,378 140 | 08X293,RENAISSANCE HIGH SCHOOL FOR MUSICAL THEATER & TECHNOLOGY,52,384,385,389 141 | 08X295,GATEWAY SCHOOL FOR ENVIRONMENTAL RESEARCH AND TECHNOLOGY,41,416,390,394 142 | 08X305,PABLO NERUDA ACADEMY FOR ARCHITECTURE AND WORLD STUDIES,67,337,361,340 143 | 08X312,MILLENNIUM ART ACADEMY,67,387,402,375 144 | 08X332,HOLCOMBE L. RUCKER SCHOOL OF COMMUNITY RESEARCH,39,363,371,350 145 | 08X367,"ARCHIMEDES ACADEMY FOR MATH, SCIENCE AND TECHNOLOGY APPLICATIONS",s,s,s,s 146 | 08X376,"ANTONIA PANTOJA PREPARATORY ACADEMY, A COLLEGE BOARD SCHOOL",s,s,s,s 147 | 08X377,BRONX COMMUNITY HIGH SCHOOL,9,367,369,376 148 | 08X405,HERBERT H. LEHMAN HIGH SCHOOL,415,412,436,393 149 | 08X408,HERBERT H. LEHMAN YABC,6,402,373,413 150 | 08X432,BRONX BRIDGES HIGH SCHOOL,s,s,s,s 151 | 08X452,BRONX GUILD,39,369,371,365 152 | 08X507,STEVENSON YABC,s,s,s,s 153 | 08X519,"FELISA RINCON DE GAUTIER INSTITUTE FOR LAW AND PUBLIC POLICY, THE",68,373,370,356 154 | 08X530,BANANA KELLY HIGH SCHOOL,54,373,381,377 155 | 08X537,BRONX ARENA HIGH SCHOOL,s,s,s,s 156 | 08X540,SCHOOL FOR COMMUNITY RESEARCH AND LEARNING,16,366,400,368 157 | 08X560,HIGH SCHOOL X560 s BRONX ACADEMY HIGH SCHOOL,9,404,368,399 158 | 08X650,JANE ADDAMS HIGH SCHOOL FOR ACADEMIC CAREERS,78,377,359,376 159 | 09X227,BRONX EXPEDITIONARY LEARNING HIGH SCHOOL,39,324,376,349 160 | 09X231,EAGLE ACADEMY FOR YOUNG MEN,78,373,387,374 161 | 09X239,"URBAN ASSEMBLY ACADEMY FOR HISTORY AND CITIZENSHIP FOR YOUNG MEN, THE",33,372,355,357 162 | 09X241,"URBAN ASSEMBLY SCHOOL FOR APPLIED MATH AND SCIENCE, THE",80,411,464,415 163 | 09X250,EXIMIUS COLLEGE PREPARATORY ACADEMY: A COLLEGE BOARD SCHOOL,50,393,394,382 164 | 09X252,MOTT HALL BRONX HIGH SCHOOL,67,369,367,356 165 | 09X260,BRONX CENTER FOR SCIENCE AND MATHEMATICS,81,459,480,457 166 | 09X263,VALIDUS PREPARATORY ACADEMY: AN EXPEDITIONARY LEARNING SCHOOL,74,356,363,356 167 | 09X276,LEADERSHIP INSTITUTE,30,361,353,367 168 | 09X297,MORRIS ACADEMY FOR COLLABORATIVE STUDIES,38,386,386,376 169 | 09X324,BRONX EARLY COLLEGE ACADEMY FOR TEACHING & LEARNING,s,s,s,s 170 | 09X329,DREAMYARD PREPARATORY SCHOOL,51,382,365,391 171 | 09X365,ACADEMY FOR LANGUAGE AND TECHNOLOGY,54,315,339,297 172 | 09X403,BRONX INTERNATIONAL HIGH SCHOOL,49,314,312,339 173 | 09X404,SCHOOL FOR EXCELLENCE,32,363,360,351 174 | 09X412,BRONX HIGH SCHOOL OF BUSINESS,34,356,376,351 175 | 09X413,BRONX HIGH SCHOOL FOR MEDICAL SCIENCE,64,400,419,402 176 | 09X414,JONATHAN LEVIN HIGH SCHOOL FOR MEDIA AND COMMUNICATIONS,35,379,364,379 177 | 09X505,"BRONX SCHOOL FOR LAW, GOVERNMENT AND JUSTICE",80,404,418,402 178 | 09X517,FREDERICK DOUGLASS ACADEMY III SECONDARY SCHOOL,50,368,384,369 179 | 09X525,BRONX LEADERSHIP ACADEMY HIGH SCHOOL,114,384,394,388 180 | 09X543,HIGH SCHOOL FOR VIOLIN AND DANCE,27,353,315,371 181 | 10X141,RIVERDALE / KINGSBRIDGE ACADEMY (MIDDLE SCHOOL / HIGH SCHOOL 141),113,438,455,440 182 | 10X213,BRONX ENGINEERING AND TECHNOLOGY ACADEMY,86,373,412,365 183 | 10X225,THEATRE ARTS PRODUCTION COMPANY SCHOOL,59,405,391,394 184 | 10X237,"THE MARIE CURIE SCHOOL FOR MEDICINE, NURSING, AND HEALTH PROFESSIONS",79,382,393,382 185 | 10X243,WEST BRONX ACADEMY FOR THE FUTURE,26,382,406,370 186 | 10X268,KINGSBRIDGE INTERNATIONAL HIGH SCHOOL,52,304,356,302 187 | 10X284,BRONX SCHOOL OF LAW AND FINANCE,54,402,395,385 188 | 10X319,PROVIDING URBAN LEARNERS SUCCESS IN EDUCATION HIGH SCHOOL,s,s,s,s 189 | 10X342,INTERNATIONAL SCHOOL FOR LIBERAL ARTS,49,300,333,301 190 | 10X368,INsTECH ACADEMY (M.S. / HIGH SCHOOL 368),111,390,408,383 191 | 10X374,KNOWLEDGE AND POWER PREPARATORY ACADEMY INTERNATIONAL HIGH SCHOOL (KAPPA),61,392,401,387 192 | 10X397,ENGLISH LANGUAGE LEARNERS AND INTERNATIONAL SUPPORT PREPARATORY ACADEMY (ELLIS),38,343,356,330 193 | 10X433,HIGH SCHOOL FOR TEACHING AND THE PROFESSIONS,57,370,371,365 194 | 10X434,BELMONT PREPARATORY HIGH SCHOOL,51,404,418,400 195 | 10X437,FORDHAM HIGH SCHOOL FOR THE ARTS,48,355,350,372 196 | 10X438,FORDHAM LEADERSHIP ACADEMY FOR BUSINESS AND TECHNOLOGY,63,367,385,367 197 | 10X439,BRONX HIGH SCHOOL FOR LAW AND COMMUNITY SERVICE,65,366,364,352 198 | 10X440,DEWITT CLINTON HIGH SCHOOL,443,419,426,410 199 | 10X442,"CELIA CRUZ BRONX HIGH SCHOOL OF MUSIC, THE",52,423,420,427 200 | 10X445,BRONX HIGH SCHOOL OF SCIENCE,731,632,688,649 201 | 10X475,JOHN F. KENNEDY HIGH SCHOOL,109,351,362,339 202 | 10X477,MARBLE HILL HIGH SCHOOL FOR INTERNATIONAL STUDIES,99,414,435,414 203 | 10X478,LEARNING TO WORK GED AT JOHN F. KENNEDY,s,s,s,s 204 | 10X546,BRONX THEATRE HIGH SCHOOL,68,348,362,354 205 | 10X549,DISCOVERY HIGH SCHOOL,55,372,379,364 206 | 10X660,GRACE DODGE CAREER AND TECHNICAL EDUCATION HIGH SCHOOL,73,362,382,356 207 | 10X667,GRACE DODGE YABC,10,350,356,317 208 | 10X696,HIGH SCHOOL OF AMERICAN STUDIES AT LEHMAN COLLEGE,92,636,648,636 209 | 11X249,BRONX HEALTH SCIENCES HIGH SCHOOL,74,370,381,382 210 | 11X253,BRONX HIGH SCHOOL FOR WRITING AND COMMUNICATION ARTS,46,400,357,390 211 | 11X265,BRONX LAB SCHOOL,81,377,391,367 212 | 11X270,ACADEMY FOR SCHOLARSHIP AND ENTREPRENEURSHIP: A COLLEGE BOARD SCHOOL,56,386,394,361 213 | 11X275,HIGH SCHOOL OF COMPUTERS AND TECHNOLOGY,72,381,376,354 214 | 11X288,COLLEGIATE INSTITUTE FOR MATH AND SCIENCE,97,444,471,433 215 | 11X290,BRONX ACADEMY OF HEALTH CAREERS,69,387,365,383 216 | 11X299,ASTOR COLLEGIATE ACADEMY,60,387,391,391 217 | 11X415,CHRISTOPHER COLUMBUS HIGH SCHOOL,121,367,361,353 218 | 11X417,YOUNG ADULT BOROUGH CNTR CHRISTOPHER COLUMBUS HS,s,s,s,s 219 | 11X418,BRONX HIGH SCHOOL FOR THE VISUAL ARTS,48,419,433,416 220 | 11X455,HARRY S TRUMAN HIGH SCHOOL,189,386,397,368 221 | 11X456,LEARNING TO WORK YABC AT TRUMAN HIGH SCHOOL,s,s,s,s 222 | 11X513,NEW WORLD HIGH SCHOOL,72,332,381,335 223 | 11X514,THE BRONXWOOD PREPARATORY ACADEMY,48,377,372,363 224 | 11X541,GLOBAL ENTERPRISE HIGH SCHOOL,57,372,382,375 225 | 11X542,PELHAM PREPARATORY ACADEMY,76,431,438,419 226 | 11X544,HIGH SCHOOL FOR CONTEMPORARY ARTS,55,383,378,365 227 | 11X545,BRONX AEROSPACE HIGH SCHOOL,46,388,393,382 228 | 12X245,NEW DAY ACADEMY,25,348,344,354 229 | 12X248,"METROPOLITAN HIGH SCHOOL, THE",49,347,367,341 230 | 12X251,EXPLORATIONS ACADEMY,57,381,381,360 231 | 12X262,PERFORMANCE CONSERVATORY HIGH SCHOOL,30,361,353,360 232 | 12X267,BRONX LATIN,36,408,432,411 233 | 12X271,EAST BRONX ACADEMY FOR THE FUTURE,46,366,378,358 234 | 12X278,PEACE AND DIVERSITY ACADEMY,34,390,401,364 235 | 12X388,PAN AMERICAN INTERNATIONAL HIGH SCHOOL AT MONROE,30,321,351,298 236 | 12X428,LEARNING TO WORK YABC AT MONROE ACADEMY,s,s,s,s 237 | 12X446,ARTURO A. SCHOMBURG SATELLITE ACADEMY BRONX,14,380,372,349 238 | 12X478,THE CINEMA SCHOOL,s,s,s,s 239 | 12X479,BRONX CAREER AND COLLEGE PREPARATORY HIGH SCHOOL,s,s,s,s 240 | 12X480,BRONX REGIONAL HIGH SCHOOL,16,398,385,398 241 | 12X550,HIGH SCHOOL OF WORLD CULTURES,42,304,323,312 242 | 12X682,FANNIE LOU HAMER FREEDOM HIGH SCHOOL,72,342,346,341 243 | 12X684,WINGS ACADEMY,66,378,374,362 244 | 12X690,MONROE ACADEMY FOR BUSINESS/LAW,31,375,387,376 245 | 12X692,MONROE ACADEMY FOR VISUAL ARTS & DESIGN,43,332,357,349 246 | 13K265,DR. SUSAN S. MCKINNEY SECONDARY SCHOOL OF THE ARTS,29,352,349,373 247 | 13K336,ACADEMY OF BUSINESS AND COMMUNITY DEVELOPMENT,9,439,374,418 248 | 13K350,URBAN ASSEMBLY HIGH SCHOOL OF MUSIC AND ART,52,360,364,356 249 | 13K412,"BROOKLYN COMMUNITY HIGH SCHOOL OF COMMUNICATION, ARTS AND MEDIA",37,375,355,384 250 | 13K419,"SCIENCE SKILLS CENTER HIGH SCHOOL FOR SCIENCE, TECHNOLOGY AND THE CREATIVE ARTS",92,399,417,395 251 | 13K430,BROOKLYN TECHNICAL HIGH SCHOOL,1277,587,659,587 252 | 13K439,BROOKLYN INTERNATIONAL HIGH SCHOOL,90,305,364,312 253 | 13K483,THE URBAN ASSEMBLY SCHOOL FOR LAW AND JUSTICE,105,400,417,389 254 | 13K499,ACORN COMMUNITY HIGH SCHOOL,72,384,364,368 255 | 13K509,FREEDOM ACADEMY HIGH SCHOOL,29,400,390,403 256 | 13K527,URBAN ASSEMBLY INSTITUTE OF MATH AND SCIENCE FOR YOUNG WOMEN,s,s,s,s 257 | 13K553,BROOKLYN ACADEMY HIGH SCHOOL,8,435,383,379 258 | 13K575,BEDFORD STUYVESANT PREPARATORY HIGH SCHOOL,13,398,391,394 259 | 13K595,BEDFORD ACADEMY HIGH SCHOOL,89,438,443,431 260 | 13K605,GEORGE WESTINGHOUSE CAREER AND TECHNICAL EDUCATION HIGH SCHOOL,85,406,391,392 261 | 13K616,BROOKLYN HIGH SCHOOL FOR LEADERSHIP AND COMMUNITY SERVICE,s,s,s,s 262 | 13K670,BENJAMIN BANNEKER ACADEMY,185,471,472,448 263 | 13K674,"CITY POLYTECHNIC HIGH SCHOOL OF ENGINEERING, ARCHITECTURE, AND TECHNOLOGY",20,441,499,413 264 | 14K071,JUAN MOREL CAMPOS SECONDARY SCHOOL,102,365,361,359 265 | 14K322,FOUNDATIONS ACADEMY,s,s,s,s 266 | 14K404,ACADEMY FOR YOUNG WRITERS,68,387,357,381 267 | 14K449,"BROOKLYN LATIN SCHOOL, THE",72,586,584,570 268 | 14K454,GREEN SCHOOL: AN ACADEMY FOR ENVIRONMENTAL CAREERS,41,407,386,396 269 | 14K474,PROGRESS HIGH SCHOOL FOR PROFESSIONAL CAREERS,144,364,379,371 270 | 14K477,SCHOOL FOR LEGAL STUDIES,134,413,396,395 271 | 14K478,"THE HIGH SCHOOL FOR ENTERPRISE, BUSINESS AND TECHNOLOGY",142,398,421,396 272 | 14K488,BROOKLYN PREPARATORY HIGH SCHOOL,42,367,373,350 273 | 14K558,WILLIAMSBURG HIGH SCHOOL FOR ARCHITECTURE AND DESIGN,72,363,385,364 274 | 14K561,WILLIAMSBURG PREPARATORY SCHOOL,113,397,410,380 275 | 14K586,LYONS COMMUNITY SCHOOL,31,371,377,355 276 | 14K610,AUTOMOTIVE HIGH SCHOOL,94,367,376,350 277 | 14K632,FRANCES PERKINS ACADEMY,12,382,372,368 278 | 14K685,EL PUENTE ACADEMY FOR PEACE AND JUSTICE,28,359,335,341 279 | 14K923,AUTOMOTIVE HIGH SCHOOL YABC,s,s,s,s 280 | 15K429,BROOKLYN SCHOOL FOR GLOBAL STUDIES,52,361,367,383 281 | 15K448,BROOKLYN SECONDARY SCHOOL FOR COLLABORATIVE STUDIES,76,393,399,387 282 | 15K462,SECONDARY SCHOOL FOR LAW,59,398,411,394 283 | 15K463,SECONDARY SCHOOL FOR JOURNALISM,58,397,391,381 284 | 15K464,PARK SLOPE COLLEGIATE,72,379,416,380 285 | 15K497,SCHOOL FOR INTERNATIONAL STUDIES,64,405,415,392 286 | 15K519,COBBLE HILL SCHOOL OF AMERICAN STUDIES,77,398,402,385 287 | 15K520,PACIFIC HIGH SCHOOL,9,352,341,300 288 | 15K529,WEST BROOKLYN COMMUNITY HIGH SCHOOL,s,s,s,s 289 | 15K530,METROPOLITAN CORPORATE ACADEMY HIGH SCHOOL,28,368,365,368 290 | 15K656,BROOKLYN HIGH SCHOOL OF THE ARTS,141,426,421,411 291 | 15K667,SUNSET PARK HIGH SCHOOL,s,s,s,s 292 | 15K698,SOUTH BROOKLYN COMMUNITY HIGH SCHOOL,8,430,416,425 293 | 16K393,FREDERICK DOUGLASS ACADEMY IV SECONDARY SCHOOL,20,355,355,358 294 | 16K455,BOYS AND GIRLS HIGH SCHOOL,131,365,370,362 295 | 16K498,BROOKLYN HIGH SCHOOL FOR LAW AND TECHNOLOGY,46,362,372,358 296 | 16K594,GOTHAM PROFESSIONAL ARTS ACADEMY,36,370,372,351 297 | 16K688,THE BROOKLYN ACADEMY OF GLOBAL FINANCE,s,s,s,s 298 | 17K382,ACADEMY FOR COLLEGE PREPARATION AND CAREER EXPLORATION: A COLLEGE BOARD SCHOOL,59,396,374,369 299 | 17K408,ACADEMY OF HOSPITALITY AND TOURISM,57,352,342,351 300 | 17K467,ERASMUS YABC,s,s,s,s 301 | 17K489,W.E.B. DUBOIS ACADEMIC HIGH SCHOOL,7,394,364,334 302 | 17K524,INTERNATIONAL HIGH SCHOOL AT PROSPECT HEIGHTS,71,287,335,291 303 | 17K528,THE HIGH SCHOOL FOR GLOBAL CITIZENSHIP,46,403,385,388 304 | 17K531,"SCHOOL FOR HUMAN RIGHTS, THE",35,348,381,359 305 | 17K533,SCHOOL FOR DEMOCRACY AND LEADERSHIP,38,377,404,372 306 | 17K537,HIGH SCHOOL FOR YOUTH AND COMMUNITY DEVELOPMENT AT ERASMUS,73,338,349,340 307 | 17K539,HIGH SCHOOL FOR SERVICE & LEARNING AT ERASMUS,61,362,375,368 308 | 17K543,"SCIENCE, TECHNOLOGY AND RESEARCH EARLY COLLEGE HIGH SCHOOL AT ERASMUS",69,457,462,441 309 | 17K544,INTERNATIONAL ARTS BUSINESS SCHOOL,54,386,391,369 310 | 17K546,HIGH SCHOOL FOR PUBLIC SERVICE: HEROES OF TOMORROW,79,418,441,414 311 | 17K547,BROOKLYN ACADEMY OF SCIENCE AND THE ENVIRONMENT,63,388,382,373 312 | 17K548,BROOKLYN SCHOOL FOR MUSIC & THEATRE,48,385,393,373 313 | 17K568,BROWNSVILLE ACADEMY HIGH SCHOOL,16,372,356,335 314 | 17K590,MEDGAR EVERS COLLEGE PREPARATORY SCHOOL,165,476,481,479 315 | 17K600,CLARA BARTON HIGH SCHOOL,259,425,413,413 316 | 17K625,PAUL ROBESON HIGH SCHOOL,53,365,363,355 317 | 17K751,ACADEMY FOR HEALTH CAREERS,s,s,s,s 318 | 18K563,IT TAKES A VILLAGE ACADEMY,56,313,320,330 319 | 18K566,BROOKLYN GENERATION SCHOOL,29,374,377,394 320 | 18K567,BROOKLYN THEATRE ARTS HIGH SCHOOL,54,383,358,377 321 | 18K569,KURT HAHN EXPEDITIONARY LEARNING SCHOOL,43,368,378,346 322 | 18K576,VICTORY COLLEGIATE HIGH SCHOOL,63,387,377,379 323 | 18K578,BROOKLYN BRIDGE ACADEMY,17,384,362,351 324 | 18K589,ARTS & MEDIA PREPARATORY ACADEMY,48,361,360,359 325 | 18K617,HIGH SCHOOL FOR INNOVATION IN ADVERTISING AND MEDIA,37,404,393,386 326 | 18K629,CULTURAL ACADEMY FOR THE ARTS AND SCIENCES,33,393,395,381 327 | 18K633,HIGH SCHOOL FOR MEDICAL PROFESSIONS,75,386,380,393 328 | 18K635,OLYMPUS ACADEMY,7,400,370,370 329 | 18K637,ACADEMY FOR CONSERVATION AND THE ENVIRONMENT,35,363,381,367 330 | 18K642,URBAN ACTION ACADEMY,40,376,385,374 331 | 18K673,EAST BROOKLYN COMMUNITY HIGH SCHOOL,12,410,403,378 332 | 19K409,EAST NEW YORK FAMILY ACADEMY,54,416,432,394 333 | 19K420,FRANKLIN K. LANE HIGH SCHOOL,s,s,s,s 334 | 19K431,THOMAS JEFFERSON YABC,s,s,s,s 335 | 19K502,FDNY HIGH SCHOOL FOR FIRE AND LIFE SAFETY,37,341,349,333 336 | 19K504,HIGH SCHOOL FOR CIVIL RIGHTS,47,363,349,342 337 | 19K507,PERFORMING ARTS AND TECHNOLOGY HIGH SCHOOL,61,380,386,383 338 | 19K510,WORLD ACADEMY FOR TOTAL COMMUNITY HEALTH HIGH SCHOOL,68,371,365,370 339 | 19K583,MULTICULTURAL HIGH SCHOOL,29,279,322,286 340 | 19K615,TRANSIT TECH CAREER AND TECHNICAL EDUCATION HIGH SCHOOL,182,395,418,380 341 | 19K618,ACADEMY OF INNOVATIVE TECHNOLOGY,60,371,371,354 342 | 19K639,BROOKLYN LAB SCHOOL,57,360,385,363 343 | 19K659,CYPRESS HILLS COLLEGIATE PREPARATORY SCHOOL,51,376,385,368 344 | 19K660,W. H. MAXWELL CAREER AND TECHNICAL EDUCATION HIGH SCHOOL,74,370,369,363 345 | 19K683,"THE SCHOOL FOR CLASSICS: AN ACADEMY OF THINKERS, WRITERS AND PERFORMERS",38,383,400,374 346 | 20K445,NEW UTRECHT HIGH SCHOOL,456,402,471,399 347 | 20K485,HIGH SCHOOL OF TELECOMMUNICATION ARTS AND TECHNOLOGY,238,425,474,424 348 | 20K490,FORT HAMILTON HIGH SCHOOL,694,417,478,411 349 | 20K505,FRANKLIN DELANO ROOSEVELT HIGH SCHOOL,385,383,486,375 350 | 20K609,THE URBAN ASSEMBLY SCHOOL FOR CRIMINAL JUSTICE,s,s,s,s 351 | 20K658,FRANKLIN DELANO ROOSEVELT YABC,18,338,477,316 352 | 21K337,INTERNATIONAL HIGH SCHOOL AT LAFAYETTE,54,326,386,314 353 | 21K344,RACHEL CARSON HIGH SCHOOL FOR COASTAL STUDIES,54,402,427,408 354 | 21K348,HIGH SCHOOL OF SPORTS MANAGEMENT,39,388,398,378 355 | 21K410,ABRAHAM LINCOLN HIGH SCHOOL,475,396,437,393 356 | 21K412/21K411,ABRAHAM LINCOLN YABC/LEARNING TO WORK GED AT ABRAHAM LINCOLN,s,s,s,s 357 | 21K468,KINGSBOROUGH EARLY COLLEGE SCHOOL,s,s,s,s 358 | 21K525,EDWARD R. MURROW HIGH SCHOOL,727,468,496,467 359 | 21K540,JOHN DEWEY HIGH SCHOOL,448,404,468,390 360 | 21K559,LIFE ACADEMY HIGH SCHOOL FOR FILM AND MUSIC,40,384,375,365 361 | 21K572,EXPEDITIONARY LEARNING SCHOOL FOR COMMUNITY LEADERS,40,353,370,356 362 | 21K620,WILLIAM E. GRADY CAREER AND TECHNICAL EDUCATION HIGH SCHOOL,95,394,414,376 363 | 21K690,BROOKLYN STUDIO SECONDARY SCHOOL,119,429,449,435 364 | 21K728,LIBERATION DIPLOMA PLUS,10,411,369,373 365 | 22K405,MIDWOOD HIGH SCHOOL,824,478,519,476 366 | 22K425,JAMES MADISON HIGH SCHOOL,518,436,475,439 367 | 22K495,SHEEPSHEAD BAY HIGH SCHOOL,236,383,392,370 368 | 22K535,LEON M. GOLDSTEIN HIGH SCHOOL FOR THE SCIENCES,259,524,561,542 369 | 22K555,BROOKLYN COLLEGE ACADEMY,131,456,456,440 370 | 23K493,BROOKLYN COLLEGIATE: A COLLEGE BOARD SCHOOL,60,389,409,387 371 | 23K514,FREDERICK DOUGLASS ACADEMY VII HIGH SCHOOL,55,361,371,359 372 | 23K643,BROOKLYN DEMOCRACY ACADEMY,11,349,338,331 373 | 23K646,ASPIRATIONS DIPLOMA PLUS HIGH SCHOOL,7,311,371,311 374 | 23K647,METROPOLITAN DIPLOMA PLUS HIGH SCHOOL,17,350,346,332 375 | 23K697,TEACHERS PREPARATORY HIGH SCHOOL,69,392,416,388 376 | 24Q264,ACADEMY OF FINANCE AND ENTERPRISE,89,405,454,421 377 | 24Q267,HIGH SCHOOL OF APPLIED COMMUNICATION,39,406,413,400 378 | 24Q293,CIVIC LEADERSHIP ACADEMY,69,404,429,407 379 | 24Q296,PAN AMERICAN INTERNATIONAL HIGH SCHOOL,55,317,323,311 380 | 24Q299,BARD HIGH SCHOOL EARLY COLLEGE II,155,545,568,550 381 | 24Q455,NEWTOWN HIGH SCHOOL,320,383,440,380 382 | 24Q457,YOUNG ADULT BOROUGH CENTER AT ARTS AND BUSINESS HS,s,s,s,s 383 | 24Q485,GROVER CLEVELAND HIGH SCHOOL,241,395,420,396 384 | 24Q520,MIDDLE COLLEGE HIGH SCHOOL AT LAGUARDIA COMMUNITY COLLEGE,58,399,393,385 385 | 24Q530,INTERNATIONAL HIGH SCHOOL AT LAGUARDIA COMMUNITY COLLEGE,69,326,409,329 386 | 24Q550,HIGH SCHOOL FOR ARTS AND BUSINESS,138,391,403,380 387 | 24Q560,"ROBERT F. WAGNER, JR. SECONDARY SCHOOL FOR ARTS AND TECHNOLOGY",80,443,447,440 388 | 24Q600,QUEENS VOCATIONAL AND TECHNICAL HIGH SCHOOL,155,417,447,406 389 | 24Q610,AVIATION CAREER & TECHNICAL EDUCATION HIGH SCHOOL,396,445,496,423 390 | 24Q744,VOYAGES PREPARATORY,s,s,s,s 391 | 25Q252,"QUEENS SCHOOL OF INQUIRY, THE",58,455,498,443 392 | 25Q263,FLUSHING INTERNATIONAL HIGH SCHOOL,45,314,417,318 393 | 25Q281,EASTsWEST SCHOOL OF INTERNATIONAL STUDIES,59,416,463,392 394 | 25Q285,WORLD JOURNALISM PREPARATORY: A COLLEGE BOARD SCHOOL,63,471,489,481 395 | 25Q425,JOHN BOWNE HIGH SCHOOL,558,397,451,395 396 | 25Q460,FLUSHING HIGH SCHOOL,347,393,441,382 397 | 25Q467,FLUSHING YABC,9,378,373,344 398 | 25Q525,TOWNSEND HARRIS HIGH SCHOOL,278,621,651,638 399 | 25Q540,QUEENS ACADEMY HIGH SCHOOL,17,398,382,388 400 | 25Q670,ROBERT F. KENNEDY COMMUNITY HIGH SCHOOL,99,431,458,441 401 | 25Q792,NORTH QUEENS COMMUNITY HIGH SCHOOL,7,379,421,377 402 | 26Q415,BENJAMIN N. CARDOZO HIGH SCHOOL,888,480,545,489 403 | 26Q430,FRANCIS LEWIS HIGH SCHOOL,934,468,539,467 404 | 26Q435,MARTIN VAN BUREN HIGH SCHOOL,334,391,397,384 405 | 26Q495,BAYSIDE HIGH SCHOOL,708,462,523,464 406 | 26Q566,"QUEENS HIGH SCHOOL OF TEACHING, LIBERAL ARTS AND THE SCIENCES",175,425,434,420 407 | 27Q260,FREDERICK DOUGLASS ACADEMY VI HIGH SCHOOL,87,387,385,373 408 | 27Q262,CHANNEL VIEW SCHOOL FOR RESEARCH,74,432,419,401 409 | 27Q302,"QUEENS HIGH SCHOOL FOR INFORMATION, RESEARCH, AND TECHNOLOGY",44,391,401,364 410 | 27Q308,ROBERT H. GODDARD HIGH SCHOOL OF COMMUNICATION ARTS AND TECHNOLOGY,93,423,426,416 411 | 27Q309,ACADEMY OF MEDICAL TECHNOLOGY: A COLLEGE BOARD SCHOOL,36,367,379,348 412 | 27Q323,SCHOLARS' ACADEMY,89,499,537,496 413 | 27Q400,AUGUST MARTIN HIGH SCHOOL,101,377,371,360 414 | 27Q410,BEACH CHANNEL HIGH SCHOOL,78,384,396,354 415 | 27Q475,RICHMOND HILL HIGH SCHOOL,404,382,404,368 416 | 27Q480,JOHN ADAMS HIGH SCHOOL,403,391,409,392 417 | 27Q650,"HIGH SCHOOL FOR CONSTRUCTION TRADES, ENGINEERING AND ARCHITECTURE",194,429,491,425 418 | 28Q284,YORK EARLY COLLEGE ACADEMY,s,s,s,s 419 | 28Q310,QUEENS COLLEGIATE: A COLLEGE BOARD SCHOOL,68,420,445,400 420 | 28Q325,HILLSIDE ARTS & LETTERS ACADEMY,s,s,s,s 421 | 28Q338,QUEENS SATELLITE HIGH SCHOOL FOR OPPORTUNITY,6,403,408,367 422 | 28Q350,JAMAICA GATEWAY TO THE SCIENCES,25,430,452,425 423 | 28Q440,FOREST HILLS HIGH SCHOOL,762,456,497,454 424 | 28Q470,JAMAICA HIGH SCHOOL,90,342,368,353 425 | 28Q505,HILLCREST HIGH SCHOOL,462,395,413,386 426 | 28Q620,THOMAS A. EDISON CAREER AND TECHNICAL EDUCATION HIGH SCHOOL,422,452,478,442 427 | 28Q680,QUEENS GATEWAY TO HEALTH SCIENCES SECONDARY SCHOOL,99,513,523,502 428 | 28Q686,QUEENS METROPOLITAN HIGH SCHOOL,s,s,s,s 429 | 28Q687,QUEENS HIGH SCHOOL FOR THE SCIENCES AT YORK COLLEGE,121,612,660,596 430 | 28Q690,HIGH SCHOOL FOR LAW ENFORCEMENT AND PUBLIC SAFETY,74,406,406,384 431 | 28Q896,"YOUNG WOMEN'S LEADERSHIP SCHOOL, QUEENS",68,439,445,432 432 | 29Q248,QUEENS PREPARATORY ACADEMY,52,360,380,359 433 | 29Q259,PATHWAYS COLLEGE PREPARATORY SCHOOL: A COLLEGE BOARD SCHOOL,46,401,397,375 434 | 29Q265,EXCELSIOR PREPARATORY HIGH SCHOOL,49,402,398,402 435 | 29Q272,GEORGE WASHINGTON CARVER HIGH SCHOOL FOR THE SCIENCES,59,436,427,424 436 | 29Q283,PREPARATORY ACADEMY FOR WRITERS: A COLLEGE BOARD SCHOOL,43,370,367,363 437 | 29Q326,CAMBRIA HEIGHTS ACADEMY,s,s,s,s 438 | 29Q492,"MATHEMATICS, SCIENCE RESEARCH AND TECHNOLOGY MAGNET HIGH SCHOOL",78,400,426,394 439 | 29Q494,"LAW, GOVERNMENT AND COMMUNITY SERVICE HIGH SCHOOL",52,385,377,377 440 | 29Q496,"BUSINESS, COMPUTER APPLICATIONS & ENTREPRENEURSHIP HIGH SCHOOL",49,379,414,359 441 | 29Q498,HUMANITIES & ARTS MAGNET HIGH SCHOOL,62,393,381,377 442 | 30Q286,"YOUNG WOMEN'S LEADERSHIP SCHOOL, ASTORIA",s,s,s,s 443 | 30Q301,ACADEMY FOR CAREERS IN TELEVISION AND FILM,98,410,440,405 444 | 30Q445,WILLIAM CULLEN BRYANT HIGH SCHOOL,395,414,449,412 445 | 30Q450,LONG ISLAND CITY HIGH SCHOOL,392,403,420,395 446 | 30Q501,FRANK SINATRA SCHOOL OF THE ARTS HIGH SCHOOL,174,504,496,494 447 | 30Q502,INFORMATION TECHNOLOGY HIGH SCHOOL,148,407,434,398 448 | 30Q555,NEWCOMERS HIGH SCHOOL,143,323,475,329 449 | 30Q575,ACADEMY OF AMERICAN STUDIES,135,487,492,491 450 | 30Q580,BACCALAUREATE SCHOOL FOR GLOBAL EDUCATION,61,524,568,544 451 | 31R047,CSI HIGH SCHOOL FOR INTERNATIONAL STUDIES,137,452,451,450 452 | 31R064,GAYNOR MCCOWN EXPEDITIONARY LEARNING SCHOOL,61,398,412,385 453 | 31R080,THE MICHAEL J. PETRIDES SCHOOL,107,472,488,466 454 | 31R440,NEW DORP HIGH SCHOOL,391,424,437,416 455 | 31R445,PORT RICHMOND HIGH SCHOOL,271,424,438,417 456 | 31R450,CURTIS HIGH SCHOOL,375,437,435,429 457 | 31R455,TOTTENVILLE HIGH SCHOOL,807,462,486,470 458 | 31R460,SUSAN E. WAGNER HIGH SCHOOL,535,455,474,459 459 | 31R470,CONCORD HIGH SCHOOL,10,466,455,414 460 | 31R600,RALPH R. MCKEE CAREER AND TECHNICAL EDUCATION HIGH SCHOOL,94,416,422,397 461 | 31R605,STATEN ISLAND TECHNICAL HIGH SCHOOL,227,635,682,636 462 | 31R607,YOUNG ADULT BOROUGH CENTER AT STATEN IS TECH HS,10,405,375,370 463 | 32K403,ACADEMY FOR ENVIRONMENTAL LEADERSHIP,50,380,366,352 464 | 32K545,EBC HIGH SCHOOL FOR PUBLIC SERVICE–BUSHWICK,88,384,409,361 465 | 32K549,BUSHWICK SCHOOL FOR SOCIAL JUSTICE,75,348,353,334 466 | 32K552,ACADEMY OF URBAN PLANNING,67,342,364,354 467 | 32K554,ALL CITY LEADERSHIP SECONDARY SCHOOL,39,428,465,422 468 | 32K556,BUSHWICK LEADERS HIGH SCHOOL FOR ACADEMIC EXCELLENCE,23,347,358,350 469 | 32K564,BUSHWICK COMMUNITY HIGH SCHOOL,24,359,317,358 470 | 75K371,P.S. 371 s LILLIAN L. RASHKIS,s,s,s,s 471 | 75M035,P.S. 035,s,s,s,s 472 | 75Q256,P.S. Q256,s,s,s,s 473 | 75Q811,P.S. Q811,32,429,444,433 474 | 75R025,SOUTH RICHMOND HIGH SCHOOL I.S./P.S. 25,s,s,s,s 475 | 75X012,P.S. X012 LEWIS AND CLARK SCHOOL,s,s,s,s 476 | 75X754,J. M. RAPPORT SCHOOL CAREER DEVELOPMENT,s,s,s,s 477 | 79M645,SCHOOL FOR COOPERATIVE TECHNICAL EDUCATION,s,s,s,s 478 | 79Q950,GED PLUS s CITYWIDE,8,496,400,426 479 | 79X490,PHOENIX ACADEMY,9,367,370,360 480 | --------------------------------------------------------------------------------