260220 study

.Rproj.user/F3FE0F57/sources/per/t/FEFD8679

@@ -1,27 +0,0 @@
-{
-    "id": "FEFD8679",
-    "path": "~/R project/r_study/기초 명령어 실습.R",
-    "project_path": "기초 명령어 실습.R",
-    "type": "r_source",
-    "hash": "3000786226",
-    "contents": "",
-    "dirty": false,
-    "created": 1769651679182.0,
-    "source_on_save": false,
-    "relative_order": 1,
-    "properties": {
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-        "Source": "Source",
-        "cursorPosition": "154,0",
-        "scrollLine": "141"
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-    "folds": "",
-    "lastKnownWriteTime": 1771481370,
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-    "read_only": false,
-    "read_only_alternatives": []
-}

.Rproj.user/F3FE0F57/sources/per/t/FEFD8679-contents

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-## 기초 명령어 실습 ##
-
-1+1
-1:10
-dd = c(1:10)
-
-## c()    -> 같은 종류의 요소(numeric, int, float등)만 있을때
-## list() -> 다양한 종류의 요소가 들어올때
-
-dd[-10]
-
-
-## 기본유형 ##
-
-x1 = 3                  # numeric
-x2 = "Love is choice"   # character
-x3 = FALSE              # logical
-x4 = 3-2i               # complex
-x5 = '123'              # character
-x6 = 'false'            # character
-x7 = 'FLASE'            # character
-
-str(x1)
-
-### 문자 - 정수 - 논리
-### 결측값은 95%까지
-
-### 정규분포는 30번이상한것으로 해야한다
-
-xx1 <- c(1:100)
-xx1
-is.na(xx1)
-table(is.na(xx1))
-
-x1 = c(1,'love',TRUE,2+3i)
-x1
-
-v1 = c(27,35,47,41)
-mode(v1)
-is.numeric(v1)
-is.na(v1)
-table(is.na(v1))
-
-v2 = c(27,35,47,NA,55)
-mode(v2)
-is.numeric(v2)
-is.na(v2)
-table(is.na(v2))
-
-length(v1)
-length(v2)
-
-names(v1)
-names(v1) = c('kim','lee','park','choi')
-
-names(v1)
-
-## Indexing ## 대괄호 == [ ] => 추출해라
-
-v1
-v1[1]
-v1[1:3]
-v1[-4]
-v1[c(2,4)]
-
-v1 = 1:3
-v2 = 4:6
-v3 = v1+v2 # can add list
-
-v1 = 1:3
-v2 = 1:6
-v3 = v1+v2 # reusable add
-v3
-
-### 데이터거래사
-
-## Factor, ordered Factor (등급을 정할 수 있는)
-
-gender = c('m','f','f','m','f','f')
-gender_factor = factor(gender)
-
-levels(gender_factor)
-
-gender_factor2 = factor(gender, levels = c('m','f'), labels = c('남자','여자'))
-gender_factor2
-
-gender_factor3 = factor(gender,ordered = TRUE)
-gender_factor3
-
-
-## Matrix ##
-v1 = 1:3
-v2 = 4:6
-m1 = rbind(v1,v2)
-m2 = cbind(v1,v2)
-v1
-v2
-m1
-m2
-
-m1[2,1] == 8
-m1[2,1] = 8
-m1[,3]
-
-is.na(m1)
-table(is.na(m1))
-
-m1[1,1] = NA
-m1[2,3] = NA
-
-table(is.na(m1))
-str(m1)
-
-m3 = matrix(1:4, nrow = 2, ncol = 2)
-m4 = matrix(1:4, nrow = 2, ncol = 2, byrow = TRUE)
-m3
-m4[2,1] = NA
-
-
-## array ##
-a1 = array(1:10, dim=10)
-a2 = array(1:10, dim=c(2, 5))
-a3 = array(1:10, dim=c(3, 3, 4))
-
-a1
-a2
-a3[,,2][3,3] = 100
-a3
-
-## DataFrame ##
-id = 1:5
-age = c(29, 32, 47, 35, 23)
-gender = c('f','m','m','f','f')
-height = c(163, 177, 172, 157, 169)
-DF1 = data.frame(id, age, gender, height)
-DF2 = data.frame(id, age, gender, height, stringsAsFactors=FALSE)
-DF3 = data.frame(id, age, gender, height, stringsAsFactors=TRUE)
-DF1
-DF2
-DF3
-
-View(DF3)
-str(DF3)
-
-DF4 = DF3[-1]
-DF4
-
-View(DF4)
-str(DF4)
-
-## 기술통계량 ##
-library('psych')
-
-describe(DF4)

.gitignore

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+.Rproj.user
+.Rhistory
+.RData
+.Ruserdata

data/survey_blank.txt

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+id gender bt age
+1 남자 A 23
+2 여자 B 21
+3 남자 A 34

data/survey_comma.txt

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+id,height,weight
+1,175,70
+2,167,58
+3,178,82
+4,162,45

data/survey_tab.txt

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+id	major	grade
+1	생물학	3
+2	경영학	2
+3	통계학	4
+4	컴퓨터공학	2

기초 실습 II.R

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+## read text data ##
+k200 = read.csv(file = './data/k100.csv',header = TRUE)
+k200