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-- 지역 | |
CREATE TABLE region ( | |
region_no INT NOT NULL PRIMARY KEY AUTO_INCREMENT, | |
region_name VARCHAR (30) NOT NULL | |
)DEFAULT CHARSET=euckr COMMENT '지역'; | |
-- 도서관 | |
CREATE TABLE library( | |
library_no INT NOT NULL PRIMARY KEY COMMENT '도서관 일련번호', | |
region_no INT NOT NULL COMMENT '지역 번호', |
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<script language="JavaScript"> | |
document.write('<style>'); | |
document.write('.cnj_input { border-width:1; border-style:solid; border-color:#000000; color:#0084D4; background-color:white;}'); | |
document.write('</style>'); | |
// 견적서 자동 계산하기 | |
function onlyNum(objtext1) { | |
var inText = objtext1.value; | |
var ret; | |
for (var i = 0; i < inText.length; i++) { | |
ret = inText.charCodeAt(i); |
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-- mysql 테이블 형식 추출 쿼리 | |
SELECT | |
t1.table_name, ORDINAL_POSITION, column_name 'Column Name', COLUMN_TYPE 'COLUMN TYPE', column_key 'Key', | |
case | |
when is_nullable = 'YES' THEN 'Y' | |
when is_nullable = 'NO' THEN 'N' | |
END AS 'Null able', | |
column_default 'Default Value', column_comment 'Comment',t1.table_comment,extra 'Extra' | |
FROM |
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<!-- Servlet 3.1 --> | |
<web-app xmlns="http://xmlns.jcp.org/xml/ns/javaee" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" | |
xsi:schemaLocation="http://xmlns.jcp.org/xml/ns/javaee http://xmlns.jcp.org/xml/ns/javaee/web-app_3_1.xsd" | |
version="3.1"> | |
</web-app> | |
<!-- Servlet 3.0 --> | |
<web-app xmlns="http://java.sun.com/xml/ns/javaee" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" |
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getwd() | |
# protein.csv 파일을 읽어서 food 데이터 생성 | |
food <- read.csv("./BigData/protein.csv") | |
# 처음 6개의 관측값을 출력/ 더 많은 관측값을 출력하고 싶으면 head(food, n= 출력하고 싶은 수) | |
# 마지막 6개의 관측값을 출력하고 싶을 때에는 tail(food) / 자기 자신이 선택하고싶으면 food[1:6,] | |
head(food) | |
str(food) | |
# 붉은 고기와 흰고기를 대상으로 군집 | |
# kmeans(데이터,centers =) |
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# getwd() | |
# setwd("D:/BigData/Source") | |
# getwd() | |
# 1~20까지의 값을 갖는 5행 4열의 행렬 mData생성 | |
mData <- matrix(c(1:20), nrow=5) | |
mData | |
# mData의 1열을 제외한 2~4열의 값을 갖는 행렬 mdData 생성 | |
mdData <- mData[,-1] # 행이라면 반대로 [-1,] |
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getwd() | |
#R에서 제공하는 기본 데이터인 iris를 이용하여 분류분석 | |
# fix(iris) | |
str(iris) | |
# 분류분석을 위해서 필요한 라이브러리 설치/로드 | |
#install.packages("party") | |
#library(party) |
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getwd() | |
setwd("D:/BigData/Source") | |
# 대부분의 분석 툴은 영문을 기반으로 한다. | |
# 한글은 분석하기 어려움 | |
# 한글을 분석해서 wordCloud 형식으로 출력하기 위한 library를 설치 | |
# 한글 | |
install.packages("KoNLP") | |
# 색상 | |
install.packages("RColorBrewer") | |
#WordCloud |
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getwd() | |
setwd("D:/BigData/source") | |
matrixData <- matrix(c(1:20), nrow=4) | |
matrixData | |
class(matrixData) | |
#matrixData 행렬을 데이터프레임으로 변환 | |
matrixData <- as.data.frame(matrixData) |
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# 현재 작업디렉토리 위치 확인 | |
getwd() | |
# 1일, 2일, 3일, 4일, 5일, 6일, 7일을 데이터로 갖는 벡터데이터 dateInfo 생성 | |
dateInfo <- c("1일","2일","3일","4일","5일","6일","7일") | |
# 07시, 12시, 17시 를 데이터로 갖는 벡터데이터 timeInfo 생성 | |
timeInfo <- c("07시","12시","17시") | |
# 20,19,20,22,23,18,20을 데이터로 갖는 벡터데이터 tempInfo07생성 | |
tempInfo07 <- c(20,19,20,22,23,18,20) | |
# 29,29,28,31,31,27,29를 데이터로 갖는 벡터데이터 tempInfo12생성 |
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