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plot(cars)

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Giới thiệu đầu bài IRIS

Bước Load Dữ Liệu

Đoạn code load dữ liệu

#LOAD & INSTALL PACKAGE ----
install.packages("dplyr")

Installing package into ‘/cloud/lib/x86_64-pc-linux-gnu-library/4.3’
(as ‘lib’ is unspecified)
trying URL 'http://rspm/default/__linux__/focal/latest/src/contrib/dplyr_1.1.2.tar.gz'
Content type 'application/x-gzip' length 1463430 bytes (1.4 MB)
==================================================
downloaded 1.4 MB

* installing *binary* package ‘dplyr’ ...
* DONE (dplyr)

The downloaded source packages are in
    ‘/tmp/RtmpftV05a/downloaded_packages’

install.packages("reshape2")

Installing package into ‘/cloud/lib/x86_64-pc-linux-gnu-library/4.3’
(as ‘lib’ is unspecified)
trying URL 'http://rspm/default/__linux__/focal/latest/src/contrib/reshape2_1.4.4.tar.gz'
Content type 'application/x-gzip' length 116247 bytes (113 KB)
==================================================
downloaded 113 KB

* installing *binary* package ‘reshape2’ ...
* DONE (reshape2)

The downloaded source packages are in
    ‘/tmp/RtmpftV05a/downloaded_packages’

library(dplyr)

Attaching package: ‘dplyr’

The following objects are masked from ‘package:stats’:

    filter, lag

The following objects are masked from ‘package:base’:

    intersect, setdiff, setequal, union

library(reshape2)

Bước Xử Lý Dữ Liệu

Dùng package Dplyr để tách bảng dữ liệu

#LOAD IRIS DATASET ----
data(iris)
head(iris,10)

tail(iris)

#STEP 1: EXPLORE DATA ----
summary(iris)

  Sepal.Length    Sepal.Width     Petal.Length    Petal.Width          Species  
 Min.   :4.300   Min.   :2.000   Min.   :1.000   Min.   :0.100   setosa    :50  
 1st Qu.:5.100   1st Qu.:2.800   1st Qu.:1.600   1st Qu.:0.300   versicolor:50  
 Median :5.800   Median :3.000   Median :4.350   Median :1.300   virginica :50  
 Mean   :5.843   Mean   :3.057   Mean   :3.758   Mean   :1.199                  
 3rd Qu.:6.400   3rd Qu.:3.300   3rd Qu.:5.100   3rd Qu.:1.800                  
 Max.   :7.900   Max.   :4.400   Max.   :6.900   Max.   :2.500                  

dim(iris)

[1] 150   5

names(iris) <- tolower(names(iris))

class(iris)

[1] "data.frame"

typeof(iris$sepal.length)

[1] "double"

str(iris$sepal.length)

 num [1:150] 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...

str(iris$species)

 Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...