elake/R-study
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

2.19 study

Browse Source
This commit is contained in:
elake
2026-02-19 15:50:45 +09:00
parent 4fbeae0f00
commit e7ad947aca
7 changed files with 428 additions and 9 deletions
Download Patch File Download Diff File Expand all files Collapse all files
.RData
BIN
View File
Binary file not shown.
.Rhistory
+183
View File
@@ -53,3 +53,186 @@ x1 = c(1,'love',TRUE,2+3i)
x1
install.packages('ggplot2')
install.packages('dplyr')
v1 = c(27,35,47,41)
mode(v1)
is.numeric(v1)
is.na(v1)
table(is.na(v1))
xx1 <- c(1:100)
v2 = c(27,35,47,NA,55)
mode(v2)
is.numeric(v2)
is.na(v2)
table(is.na(v1))
table(is.na(v1))
table(is.na(v1))
table(is.na(v2))
length(vw)
length(v1)
length(v2)
names(v1)
names(v1) = c('kim','lee','park','choi')
names(v1)
v1
v1[0]
## 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[-1]
v1[:-1]
v1[1:-1]
v1[-1]
v1[1:3]
v1[-4]
v1[1,3]
v1[3:-1]
v1[c(2,4)]
v1[-4]
v1 = 1:3
v2 = 4:6
v3 = v1+v2
v3 = v1+v2
v1 = 1:3
v2 = 1:6
v3 = v1+v2
v3
gender = c('m','f','f','m','f','f')
gender_facotr = factor(gender)
levels(gender_facotr)
gender = c('m','f','f','m','f','f')
gender_facotr = factor(gender)
levels(gender_facotr)
gender_factor2 = factor(gender, levels = c('m','f'), labels = c('남자','여자'))
gender_factor2
install.packages(c("cluster", "lattice", "viridisLite"))
gender_factor3
gender_factor3 = factor(gender,ordered = TRUE)
gender_factor3
v2 = 4:6
m1 = rbind(v1,v2)
m2 = m2 cbind(v1,v2)
v1 = 1:3
v2 = 4:6
m1 = rbind(v1,v2)
m2 = m2 cbind(v1,v2)
1:3
v2 = 4:6
m1 = rbind(v1,v2)
m2 =
v1 = 1:3
v2 = 4:6
m1 = rbind(v1,v2)
m2 = cbind(v1,v2)
m2
v1 = 1:3
v2 = 4:6
m1 = rbind(v1,v2)
m2 = cbind(v1,v2)
m1
m2
v1 = 1:3
v2 = 4:6
m1 = rbind(v1,v2)
m2 = cbind(v1,v2)
v1
v2
m1
m2
m1[2,1]
m1[2,1] == 8
m1
[2,1] == 8
m1
m1
m1[2,1] == 8
m1[2,1] = 8
m1
m1[,3]
is.na(m1)
table(is.na(m1))
m1[1,1] = NA
m1
table(is.na(m1))
m1[2,3] = NA
table(is.na(m1))
str(m1)
m3 = matrix(1:4, nrow = 2,ncol = 2)
m3
m4 = matrix(1:4, nrow = 2,ncol = 2,byrow = TRUE)
m4
m3
m4
m4[2,1] = NA
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
a3[,,2][3,3]
a3[,,2][3,3] = 100
a3
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)
DF1
DF2
View(DF1)
str(DF1)
DF3 = data.frame(id, age, gender, height, stringsAsFactors=TRUE)
DF3
View(DF2)
View(DF3)
str(DF2)
str(DF3)
DF4 = DF3[-1]
DF4
View(DF4)
str(DF4)
install.packages('psych')
library(psych)
describe(DF4)
.Rproj.user/F3FE0F57/pcs/windowlayoutstate.pper
+1 -1
View File
@@ -1,6 +1,6 @@
{
"left": {
"splitterpos": 285,
"splitterpos": 433,
"topwindowstate": "NORMAL",
"panelheight": 1013,
"windowheight": 1051
.Rproj.user/F3FE0F57/sources/per/t/FEFD8679
+6 -6
View File
@@ -3,25 +3,25 @@
"path": "~/R project/r_study/기초 명령어 실습.R",
"project_path": "기초 명령어 실습.R",
"type": "r_source",
"hash": "3966952176",
"hash": "3000786226",
"contents": "",
"dirty": false,
"created": 1769651679182.0,
"source_on_save": false,
"relative_order": 2,
"relative_order": 1,
"properties": {
"tempName": "Untitled1",
"source_window_id": "",
"Source": "Source",
"cursorPosition": "15,35",
"scrollLine": "0"
"cursorPosition": "154,0",
"scrollLine": "141"
},
"folds": "",
"lastKnownWriteTime": 1770187041,
"lastKnownWriteTime": 1771481370,
"encoding": "UTF-8",
"collab_server": "",
"source_window": "",
"last_content_update": 1770187041612,
"last_content_update": 1771481370916,
"read_only": false,
"read_only_alternatives": []
}
.Rproj.user/F3FE0F57/sources/per/t/FEFD8679-contents
+118
View File
@@ -34,3 +34,121 @@ 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)
.Rproj.user/F3FE0F57/sources/prop/0CB164D0
+2 -2
View File
@@ -2,6 +2,6 @@
"tempName": "Untitled1",
"source_window_id": "",
"Source": "Source",
"cursorPosition": "15,35",
"scrollLine": "0"
"cursorPosition": "154,0",
"scrollLine": "141"
}
기초 명령어 실습.R
+118
View File
@@ -34,3 +34,121 @@ 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)