bigData_01

#ctrl+alt+i

library(dplyr)

## 
## 다음의 패키지를 부착합니다: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

data("iris")
glimpse(iris) #데이터구조 파악함수 (dplyr 안에 있음)

## Rows: 150
## Columns: 5
## $ Sepal.Length <dbl> 5.1, 4.9, 4.7, 4.6, 5.0, 5.4, 4.6, 5.0, 4.4, 4.9, 5.4, 4.…
## $ Sepal.Width  <dbl> 3.5, 3.0, 3.2, 3.1, 3.6, 3.9, 3.4, 3.4, 2.9, 3.1, 3.7, 3.…
## $ Petal.Length <dbl> 1.4, 1.4, 1.3, 1.5, 1.4, 1.7, 1.4, 1.5, 1.4, 1.5, 1.5, 1.…
## $ Petal.Width  <dbl> 0.2, 0.2, 0.2, 0.2, 0.2, 0.4, 0.3, 0.2, 0.2, 0.1, 0.2, 0.…
## $ Species      <fct> setosa, setosa, setosa, setosa, setosa, setosa, setosa, s…

View(iris) #엑셀처럼 데이터를 보여주는 함수
#dbl = double(실수) fct = factor?(그룹형 데이터)
x<-c(1,2,3)
mode(x)

## [1] "numeric"

is.numeric(x)

## [1] TRUE

is.logical(x)

## [1] FALSE

is.character(x)

## [1] FALSE

length(x)

## [1] 3

x<-c(1,10);y<-c("apple","melon")
xy<-c(x,y)
xy

## [1] "1"     "10"    "apple" "melon"