Date: 19:55:20, 18 - 01 - 2024

NHIỆM VỤ 2.1

Đọc dữ liệu từ file csv

data <- read.csv(file.choose(), header = T)
data

STT	Năm	CÔNG.TY	Y	X2	X3
1	1935	GE	33.10	1170.6	97.8
2	1936	GE	45.00	2015.8	104.4
3	1937	GE	77.20	2803.3	118.0
4	1938	GE	44.60	2039.7	156.2
5	1939	GE	48.10	2256.2	172.6
6	1940	GE	74.40	2132.2	186.6
7	1941	GE	113.00	1834.1	220.9
8	1942	GE	91.90	1588.0	287.8
9	1943	GE	61.30	1749.4	319.9
10	1944	GE	56.80	1687.2	321.3
11	1945	GE	93.60	2007.7	319.6
12	1946	GE	159.90	2208.3	346.0
13	1947	GE	147.20	1656.7	456.4
14	1948	GE	146.30	1604.4	543.4
15	1949	GE	98.30	1431.8	618.3
16	1950	GE	93.50	1610.5	647.4
17	1951	GE	135.20	1819.4	671.3
18	1952	GE	157.30	2079.7	726.1
19	1953	GE	179.50	2371.6	800.3
20	1954	GE	189.60	2759.9	888.9
21	1935	US	209.90	1362.4	53.8
22	1936	US	355.30	1807.1	50.5
23	1937	US	469.90	2673.3	118.1
24	1938	US	262.30	1801.9	260.2
25	1939	US	230.40	1957.3	312.7
26	1940	US	361.60	2202.9	254.2
27	1941	US	472.80	2380.5	261.4
28	1942	US	445.60	2168.6	298.7
29	1943	US	361.60	1985.1	301.8
30	1944	US	288.20	1813.9	279.1
31	1945	US	258.70	1850.2	213.8
32	1946	US	420.30	2067.7	232.6
33	1947	US	420.50	1796.3	264.8
34	1948	US	494.50	1625.8	306.9
35	1949	US	405.10	1667.0	351.1
36	1950	US	418.80	1677.4	357.8
37	1951	US	588.20	2289.5	341.1
38	1952	US	645.20	2159.4	444.2
39	1953	US	641.00	2031.3	623.6
40	1954	US	459.30	2115.5	669.7
41	1935	GM	317.60	3078.5	2.8
42	1936	GM	391.80	4661.7	52.6
43	1937	GM	410.60	5387.1	156.9
44	1938	GM	257.70	2792.2	209.2
45	1939	GM	330.80	4313.2	203.4
46	1940	GM	461.20	4643.9	207.2
47	1941	GM	512.00	4551.2	255.2
48	1942	GM	448.00	3244.1	303.7
49	1943	GM	499.60	4053.7	264.1
50	1944	GM	547.50	4379.3	201.6
51	1945	GM	561.20	4840.9	265.0
52	1946	GM	688.10	4900.0	402.0
53	1947	GM	568.90	3526.5	761.5
54	1948	GM	529.20	3245.7	922.4
55	1949	GM	555.10	3700.2	1020.1
56	1950	GM	642.90	3755.6	1099.0
57	1951	GM	755.90	4833.0	1207.7
58	1952	GM	891.20	4926.9	1430.5
59	1953	GM	1304.40	6241.7	1777.3
60	1954	GM	1486.70	5593.6	226.3
61	1935	WEST	12.93	191.5	1.8
62	1936	WEST	25.90	516.0	0.8
63	1937	WEST	35.05	729.0	7.4
64	1938	WEST	22.89	560.4	18.1
65	1939	WEST	18.84	519.9	23.5
66	1940	WEST	28.57	628.5	26.5
67	1941	WEST	48.51	537.1	36.2
68	1942	WEST	43.34	561.2	60.8
69	1943	WEST	37.02	617.2	84.4
70	1944	WEST	37.81	626.7	91.2
71	1945	WEST	39.27	737.2	92.4
72	1946	WEST	53.46	760.5	86.0
73	1947	WEST	55.56	581.4	111.1
74	1948	WEST	49.56	662.3	130.6
75	1949	WEST	32.04	583.8	141.8
76	1950	WEST	32.24	635.2	136.7
77	1951	WEST	54.38	732.8	129.7
78	1952	WEST	71.78	864.1	145.5
79	1953	WEST	90.08	1193.5	174.8
80	1954	WEST	68.60	1188.9	213.5

library(xlsx)
Data <- read.xlsx(file.choose(), sheetIndex = 1, header = T)
Data

STT	Năm	CÔNG.TY	Y	X2	X3	NA.
1	1935	GE	33.10	1170.6	97.8	NA
2	1936	GE	45.00	2015.8	104.4	NA
3	1937	GE	77.20	2803.3	118.0	NA
4	1938	GE	44.60	2039.7	156.2	NA
5	1939	GE	48.10	2256.2	172.6	NA
6	1940	GE	74.40	2132.2	186.6	NA
7	1941	GE	113.00	1834.1	220.9	NA
8	1942	GE	91.90	1588.0	287.8	NA
9	1943	GE	61.30	1749.4	319.9	NA
10	1944	GE	56.80	1687.2	321.3	NA
11	1945	GE	93.60	2007.7	319.6	NA
12	1946	GE	159.90	2208.3	346.0	NA
13	1947	GE	147.20	1656.7	456.4	NA
14	1948	GE	146.30	1604.4	543.4	NA
15	1949	GE	98.30	1431.8	618.3	NA
16	1950	GE	93.50	1610.5	647.4	NA
17	1951	GE	135.20	1819.4	671.3	NA
18	1952	GE	157.30	2079.7	726.1	NA
19	1953	GE	179.50	2371.6	800.3	NA
20	1954	GE	189.60	2759.9	888.9	NA
21	1935	US	209.90	1362.4	53.8	NA
22	1936	US	355.30	1807.1	50.5	NA
23	1937	US	469.90	2673.3	118.1	NA
24	1938	US	262.30	1801.9	260.2	NA
25	1939	US	230.40	1957.3	312.7	NA
26	1940	US	361.60	2202.9	254.2	NA
27	1941	US	472.80	2380.5	261.4	NA
28	1942	US	445.60	2168.6	298.7	NA
29	1943	US	361.60	1985.1	301.8	NA
30	1944	US	288.20	1813.9	279.1	NA
31	1945	US	258.70	1850.2	213.8	NA
32	1946	US	420.30	2067.7	232.6	NA
33	1947	US	420.50	1796.3	264.8	NA
34	1948	US	494.50	1625.8	306.9	NA
35	1949	US	405.10	1667.0	351.1	NA
36	1950	US	418.80	1677.4	357.8	NA
37	1951	US	588.20	2289.5	341.1	NA
38	1952	US	645.20	2159.4	444.2	NA
39	1953	US	641.00	2031.3	623.6	NA
40	1954	US	459.30	2115.5	669.7	NA
41	1935	GM	317.60	3078.5	2.8	NA
42	1936	GM	391.80	4661.7	52.6	NA
43	1937	GM	410.60	5387.1	156.9	NA
44	1938	GM	257.70	2792.2	209.2	NA
45	1939	GM	330.80	4313.2	203.4	NA
46	1940	GM	461.20	4643.9	207.2	NA
47	1941	GM	512.00	4551.2	255.2	NA
48	1942	GM	448.00	3244.1	303.7	NA
49	1943	GM	499.60	4053.7	264.1	NA
50	1944	GM	547.50	4379.3	201.6	NA
51	1945	GM	561.20	4840.9	265.0	NA
52	1946	GM	688.10	4900.0	402.0	NA
53	1947	GM	568.90	3526.5	761.5	NA
54	1948	GM	529.20	3245.7	922.4	NA
55	1949	GM	555.10	3700.2	1020.1	NA
56	1950	GM	642.90	3755.6	1099.0	NA
57	1951	GM	755.90	4833.0	1207.7	NA
58	1952	GM	891.20	4926.9	1430.5	NA
59	1953	GM	1304.40	6241.7	1777.3	NA
60	1954	GM	1486.70	5593.6	226.3	NA
61	1935	WEST	12.93	191.5	1.8	NA
62	1936	WEST	25.90	516.0	0.8	NA
63	1937	WEST	35.05	729.0	7.4	NA
64	1938	WEST	22.89	560.4	18.1	NA
65	1939	WEST	18.84	519.9	23.5	NA
66	1940	WEST	28.57	628.5	26.5	NA
67	1941	WEST	48.51	537.1	36.2	NA
68	1942	WEST	43.34	561.2	60.8	NA
69	1943	WEST	37.02	617.2	84.4	NA
70	1944	WEST	37.81	626.7	91.2	NA
71	1945	WEST	39.27	737.2	92.4	NA
72	1946	WEST	53.46	760.5	86.0	NA
73	1947	WEST	55.56	581.4	111.1	NA
74	1948	WEST	49.56	662.3	130.6	NA
75	1949	WEST	32.04	583.8	141.8	NA
76	1950	WEST	32.24	635.2	136.7	NA
77	1951	WEST	54.38	732.8	129.7	NA
78	1952	WEST	71.78	864.1	145.5	NA
79	1953	WEST	90.08	1193.5	174.8	NA
80	1954	WEST	68.60	1188.9	213.5	NA

Sử dụng dữ liệu có sẵn trong R

library(datasets)
data(package = 'datasets')
b <- women
b

height	weight
58	115
59	117
60	120
61	123
62	126
63	129
64	132
65	135
66	139
67	142
68	146
69	150
70	154
71	159
72	164

library(ggplot2)
data(package = 'ggplot2')
a <- msleep
a

name	genus	vore	order	conservation	sleep_total	sleep_rem	sleep_cycle	awake	brainwt	bodywt
Cheetah	Acinonyx	carni	Carnivora	lc	12.1	NA	NA	11.90	NA	50.000
Owl monkey	Aotus	omni	Primates	NA	17.0	1.8	NA	7.00	0.01550	0.480
Mountain beaver	Aplodontia	herbi	Rodentia	nt	14.4	2.4	NA	9.60	NA	1.350
Greater short-tailed shrew	Blarina	omni	Soricomorpha	lc	14.9	2.3	0.1333333	9.10	0.00029	0.019
Cow	Bos	herbi	Artiodactyla	domesticated	4.0	0.7	0.6666667	20.00	0.42300	600.000
Three-toed sloth	Bradypus	herbi	Pilosa	NA	14.4	2.2	0.7666667	9.60	NA	3.850
Northern fur seal	Callorhinus	carni	Carnivora	vu	8.7	1.4	0.3833333	15.30	NA	20.490
Vesper mouse	Calomys	NA	Rodentia	NA	7.0	NA	NA	17.00	NA	0.045
Dog	Canis	carni	Carnivora	domesticated	10.1	2.9	0.3333333	13.90	0.07000	14.000
Roe deer	Capreolus	herbi	Artiodactyla	lc	3.0	NA	NA	21.00	0.09820	14.800
Goat	Capri	herbi	Artiodactyla	lc	5.3	0.6	NA	18.70	0.11500	33.500
Guinea pig	Cavis	herbi	Rodentia	domesticated	9.4	0.8	0.2166667	14.60	0.00550	0.728
Grivet	Cercopithecus	omni	Primates	lc	10.0	0.7	NA	14.00	NA	4.750
Chinchilla	Chinchilla	herbi	Rodentia	domesticated	12.5	1.5	0.1166667	11.50	0.00640	0.420
Star-nosed mole	Condylura	omni	Soricomorpha	lc	10.3	2.2	NA	13.70	0.00100	0.060
African giant pouched rat	Cricetomys	omni	Rodentia	NA	8.3	2.0	NA	15.70	0.00660	1.000
Lesser short-tailed shrew	Cryptotis	omni	Soricomorpha	lc	9.1	1.4	0.1500000	14.90	0.00014	0.005
Long-nosed armadillo	Dasypus	carni	Cingulata	lc	17.4	3.1	0.3833333	6.60	0.01080	3.500
Tree hyrax	Dendrohyrax	herbi	Hyracoidea	lc	5.3	0.5	NA	18.70	0.01230	2.950
North American Opossum	Didelphis	omni	Didelphimorphia	lc	18.0	4.9	0.3333333	6.00	0.00630	1.700
Asian elephant	Elephas	herbi	Proboscidea	en	3.9	NA	NA	20.10	4.60300	2547.000
Big brown bat	Eptesicus	insecti	Chiroptera	lc	19.7	3.9	0.1166667	4.30	0.00030	0.023
Horse	Equus	herbi	Perissodactyla	domesticated	2.9	0.6	1.0000000	21.10	0.65500	521.000
Donkey	Equus	herbi	Perissodactyla	domesticated	3.1	0.4	NA	20.90	0.41900	187.000
European hedgehog	Erinaceus	omni	Erinaceomorpha	lc	10.1	3.5	0.2833333	13.90	0.00350	0.770
Patas monkey	Erythrocebus	omni	Primates	lc	10.9	1.1	NA	13.10	0.11500	10.000
Western american chipmunk	Eutamias	herbi	Rodentia	NA	14.9	NA	NA	9.10	NA	0.071
Domestic cat	Felis	carni	Carnivora	domesticated	12.5	3.2	0.4166667	11.50	0.02560	3.300
Galago	Galago	omni	Primates	NA	9.8	1.1	0.5500000	14.20	0.00500	0.200
Giraffe	Giraffa	herbi	Artiodactyla	cd	1.9	0.4	NA	22.10	NA	899.995
Pilot whale	Globicephalus	carni	Cetacea	cd	2.7	0.1	NA	21.35	NA	800.000
Gray seal	Haliochoerus	carni	Carnivora	lc	6.2	1.5	NA	17.80	0.32500	85.000
Gray hyrax	Heterohyrax	herbi	Hyracoidea	lc	6.3	0.6	NA	17.70	0.01227	2.625
Human	Homo	omni	Primates	NA	8.0	1.9	1.5000000	16.00	1.32000	62.000
Mongoose lemur	Lemur	herbi	Primates	vu	9.5	0.9	NA	14.50	NA	1.670
African elephant	Loxodonta	herbi	Proboscidea	vu	3.3	NA	NA	20.70	5.71200	6654.000
Thick-tailed opposum	Lutreolina	carni	Didelphimorphia	lc	19.4	6.6	NA	4.60	NA	0.370
Macaque	Macaca	omni	Primates	NA	10.1	1.2	0.7500000	13.90	0.17900	6.800
Mongolian gerbil	Meriones	herbi	Rodentia	lc	14.2	1.9	NA	9.80	NA	0.053
Golden hamster	Mesocricetus	herbi	Rodentia	en	14.3	3.1	0.2000000	9.70	0.00100	0.120
Vole	Microtus	herbi	Rodentia	NA	12.8	NA	NA	11.20	NA	0.035
House mouse	Mus	herbi	Rodentia	nt	12.5	1.4	0.1833333	11.50	0.00040	0.022
Little brown bat	Myotis	insecti	Chiroptera	NA	19.9	2.0	0.2000000	4.10	0.00025	0.010
Round-tailed muskrat	Neofiber	herbi	Rodentia	nt	14.6	NA	NA	9.40	NA	0.266
Slow loris	Nyctibeus	carni	Primates	NA	11.0	NA	NA	13.00	0.01250	1.400
Degu	Octodon	herbi	Rodentia	lc	7.7	0.9	NA	16.30	NA	0.210
Northern grasshopper mouse	Onychomys	carni	Rodentia	lc	14.5	NA	NA	9.50	NA	0.028
Rabbit	Oryctolagus	herbi	Lagomorpha	domesticated	8.4	0.9	0.4166667	15.60	0.01210	2.500
Sheep	Ovis	herbi	Artiodactyla	domesticated	3.8	0.6	NA	20.20	0.17500	55.500
Chimpanzee	Pan	omni	Primates	NA	9.7	1.4	1.4166667	14.30	0.44000	52.200
Tiger	Panthera	carni	Carnivora	en	15.8	NA	NA	8.20	NA	162.564
Jaguar	Panthera	carni	Carnivora	nt	10.4	NA	NA	13.60	0.15700	100.000
Lion	Panthera	carni	Carnivora	vu	13.5	NA	NA	10.50	NA	161.499
Baboon	Papio	omni	Primates	NA	9.4	1.0	0.6666667	14.60	0.18000	25.235
Desert hedgehog	Paraechinus	NA	Erinaceomorpha	lc	10.3	2.7	NA	13.70	0.00240	0.550
Potto	Perodicticus	omni	Primates	lc	11.0	NA	NA	13.00	NA	1.100
Deer mouse	Peromyscus	NA	Rodentia	NA	11.5	NA	NA	12.50	NA	0.021
Phalanger	Phalanger	NA	Diprotodontia	NA	13.7	1.8	NA	10.30	0.01140	1.620
Caspian seal	Phoca	carni	Carnivora	vu	3.5	0.4	NA	20.50	NA	86.000
Common porpoise	Phocoena	carni	Cetacea	vu	5.6	NA	NA	18.45	NA	53.180
Potoroo	Potorous	herbi	Diprotodontia	NA	11.1	1.5	NA	12.90	NA	1.100
Giant armadillo	Priodontes	insecti	Cingulata	en	18.1	6.1	NA	5.90	0.08100	60.000
Rock hyrax	Procavia	NA	Hyracoidea	lc	5.4	0.5	NA	18.60	0.02100	3.600
Laboratory rat	Rattus	herbi	Rodentia	lc	13.0	2.4	0.1833333	11.00	0.00190	0.320
African striped mouse	Rhabdomys	omni	Rodentia	NA	8.7	NA	NA	15.30	NA	0.044
Squirrel monkey	Saimiri	omni	Primates	NA	9.6	1.4	NA	14.40	0.02000	0.743
Eastern american mole	Scalopus	insecti	Soricomorpha	lc	8.4	2.1	0.1666667	15.60	0.00120	0.075
Cotton rat	Sigmodon	herbi	Rodentia	NA	11.3	1.1	0.1500000	12.70	0.00118	0.148
Mole rat	Spalax	NA	Rodentia	NA	10.6	2.4	NA	13.40	0.00300	0.122
Arctic ground squirrel	Spermophilus	herbi	Rodentia	lc	16.6	NA	NA	7.40	0.00570	0.920
Thirteen-lined ground squirrel	Spermophilus	herbi	Rodentia	lc	13.8	3.4	0.2166667	10.20	0.00400	0.101
Golden-mantled ground squirrel	Spermophilus	herbi	Rodentia	lc	15.9	3.0	NA	8.10	NA	0.205
Musk shrew	Suncus	NA	Soricomorpha	NA	12.8	2.0	0.1833333	11.20	0.00033	0.048
Pig	Sus	omni	Artiodactyla	domesticated	9.1	2.4	0.5000000	14.90	0.18000	86.250
Short-nosed echidna	Tachyglossus	insecti	Monotremata	NA	8.6	NA	NA	15.40	0.02500	4.500
Eastern american chipmunk	Tamias	herbi	Rodentia	NA	15.8	NA	NA	8.20	NA	0.112
Brazilian tapir	Tapirus	herbi	Perissodactyla	vu	4.4	1.0	0.9000000	19.60	0.16900	207.501
Tenrec	Tenrec	omni	Afrosoricida	NA	15.6	2.3	NA	8.40	0.00260	0.900
Tree shrew	Tupaia	omni	Scandentia	NA	8.9	2.6	0.2333333	15.10	0.00250	0.104
Bottle-nosed dolphin	Tursiops	carni	Cetacea	NA	5.2	NA	NA	18.80	NA	173.330
Genet	Genetta	carni	Carnivora	NA	6.3	1.3	NA	17.70	0.01750	2.000
Arctic fox	Vulpes	carni	Carnivora	NA	12.5	NA	NA	11.50	0.04450	3.380
Red fox	Vulpes	carni	Carnivora	NA	9.8	2.4	0.3500000	14.20	0.05040	4.230

Bộ dữ liệu “Data trong bài MP05 của Fulltight”

e <- data
is.data.frame(e)

## [1] TRUE

is.matrix(e)

## [1] FALSE

length(e)

## [1] 6

names(e)

## [1] "STT"     "Năm"     "CÔNG.TY" "Y"       "X2"      "X3"

dim(e)

## [1] 80  6

library(skimr)
skim(e)

Data summary
Name	e
Number of rows	80
Number of columns	6
_______________________
Column type frequency:
character	1
numeric	5
________________________
Group variables	None

Variable type: character

skim_variable	n_missing	complete_rate	min	max	empty	n_unique	whitespace
CÔNG.TY	0	1	2	4	0	4	0

Variable type: numeric

skim_variable	complete_rate	mean	sd	p0	p25	p50	p75	p100	hist
STT	1	40.50	23.24	1.00	20.75	40.50	60.25	80.0	▇▇▇▇▇
Năm	1	1944.50	5.80	1935.00	1939.75	1944.50	1949.25	1954.0	▇▇▇▇▇
Y	1	290.92	284.85	12.93	55.26	199.75	459.78	1486.7	▇▅▁▁▁
X2	1	2229.45	1430.01	191.50	1192.35	1971.20	2794.97	6241.7	▅▇▂▂▁
X3	1	333.51	337.71	0.80	118.07	243.40	352.78	1777.3	▇▁▁▁▁

head(e, 10)

STT	Năm	CÔNG.TY	Y	X2	X3
1	1935	GE	33.1	1170.6	97.8
2	1936	GE	45.0	2015.8	104.4
3	1937	GE	77.2	2803.3	118.0
4	1938	GE	44.6	2039.7	156.2
5	1939	GE	48.1	2256.2	172.6
6	1940	GE	74.4	2132.2	186.6
7	1941	GE	113.0	1834.1	220.9
8	1942	GE	91.9	1588.0	287.8
9	1943	GE	61.3	1749.4	319.9
10	1944	GE	56.8	1687.2	321.3

tail(e,12)

	STT	Năm	CÔNG.TY	Y	X2	X3
69	69	1943	WEST	37.02	617.2	84.4
70	70	1944	WEST	37.81	626.7	91.2
71	71	1945	WEST	39.27	737.2	92.4
72	72	1946	WEST	53.46	760.5	86.0
73	73	1947	WEST	55.56	581.4	111.1
74	74	1948	WEST	49.56	662.3	130.6
75	75	1949	WEST	32.04	583.8	141.8
76	76	1950	WEST	32.24	635.2	136.7
77	77	1951	WEST	54.38	732.8	129.7
78	78	1952	WEST	71.78	864.1	145.5
79	79	1953	WEST	90.08	1193.5	174.8
80	80	1954	WEST	68.60	1188.9	213.5

str(e)

## 'data.frame':    80 obs. of  6 variables:
##  $ STT    : int  1 2 3 4 5 6 7 8 9 10 ...
##  $ Năm    : int  1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 ...
##  $ CÔNG.TY: chr  "GE" "GE" "GE" "GE" ...
##  $ Y      : num  33.1 45 77.2 44.6 48.1 74.4 113 91.9 61.3 56.8 ...
##  $ X2     : num  1171 2016 2803 2040 2256 ...
##  $ X3     : num  97.8 104.4 118 156.2 172.6 ...

is.na(e)

##         STT   Năm CÔNG.TY     Y    X2    X3
##  [1,] FALSE FALSE   FALSE FALSE FALSE FALSE
##  [2,] FALSE FALSE   FALSE FALSE FALSE FALSE
##  [3,] FALSE FALSE   FALSE FALSE FALSE FALSE
##  [4,] FALSE FALSE   FALSE FALSE FALSE FALSE
##  [5,] FALSE FALSE   FALSE FALSE FALSE FALSE
##  [6,] FALSE FALSE   FALSE FALSE FALSE FALSE
##  [7,] FALSE FALSE   FALSE FALSE FALSE FALSE
##  [8,] FALSE FALSE   FALSE FALSE FALSE FALSE
##  [9,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [10,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [11,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [12,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [13,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [14,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [15,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [16,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [17,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [18,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [19,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [20,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [21,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [22,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [23,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [24,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [25,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [26,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [27,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [28,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [29,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [30,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [31,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [32,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [33,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [34,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [35,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [36,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [37,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [38,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [39,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [40,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [41,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [42,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [43,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [44,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [45,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [46,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [47,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [48,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [49,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [50,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [51,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [52,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [53,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [54,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [55,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [56,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [57,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [58,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [59,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [60,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [61,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [62,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [63,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [64,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [65,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [66,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [67,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [68,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [69,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [70,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [71,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [72,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [73,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [74,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [75,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [76,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [77,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [78,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [79,] FALSE FALSE   FALSE FALSE FALSE FALSE
## [80,] FALSE FALSE   FALSE FALSE FALSE FALSE

sum(is.na(e))

## [1] 0

which(is.na(e))

## integer(0)

Rút trích dữ liệu

names(e) <- c('S', 'N', 'CT', 'Y', 'X2', 'X3')
e

S	N	CT	Y	X2	X3
1	1935	GE	33.10	1170.6	97.8
2	1936	GE	45.00	2015.8	104.4
3	1937	GE	77.20	2803.3	118.0
4	1938	GE	44.60	2039.7	156.2
5	1939	GE	48.10	2256.2	172.6
6	1940	GE	74.40	2132.2	186.6
7	1941	GE	113.00	1834.1	220.9
8	1942	GE	91.90	1588.0	287.8
9	1943	GE	61.30	1749.4	319.9
10	1944	GE	56.80	1687.2	321.3
11	1945	GE	93.60	2007.7	319.6
12	1946	GE	159.90	2208.3	346.0
13	1947	GE	147.20	1656.7	456.4
14	1948	GE	146.30	1604.4	543.4
15	1949	GE	98.30	1431.8	618.3
16	1950	GE	93.50	1610.5	647.4
17	1951	GE	135.20	1819.4	671.3
18	1952	GE	157.30	2079.7	726.1
19	1953	GE	179.50	2371.6	800.3
20	1954	GE	189.60	2759.9	888.9
21	1935	US	209.90	1362.4	53.8
22	1936	US	355.30	1807.1	50.5
23	1937	US	469.90	2673.3	118.1
24	1938	US	262.30	1801.9	260.2
25	1939	US	230.40	1957.3	312.7
26	1940	US	361.60	2202.9	254.2
27	1941	US	472.80	2380.5	261.4
28	1942	US	445.60	2168.6	298.7
29	1943	US	361.60	1985.1	301.8
30	1944	US	288.20	1813.9	279.1
31	1945	US	258.70	1850.2	213.8
32	1946	US	420.30	2067.7	232.6
33	1947	US	420.50	1796.3	264.8
34	1948	US	494.50	1625.8	306.9
35	1949	US	405.10	1667.0	351.1
36	1950	US	418.80	1677.4	357.8
37	1951	US	588.20	2289.5	341.1
38	1952	US	645.20	2159.4	444.2
39	1953	US	641.00	2031.3	623.6
40	1954	US	459.30	2115.5	669.7
41	1935	GM	317.60	3078.5	2.8
42	1936	GM	391.80	4661.7	52.6
43	1937	GM	410.60	5387.1	156.9
44	1938	GM	257.70	2792.2	209.2
45	1939	GM	330.80	4313.2	203.4
46	1940	GM	461.20	4643.9	207.2
47	1941	GM	512.00	4551.2	255.2
48	1942	GM	448.00	3244.1	303.7
49	1943	GM	499.60	4053.7	264.1
50	1944	GM	547.50	4379.3	201.6
51	1945	GM	561.20	4840.9	265.0
52	1946	GM	688.10	4900.0	402.0
53	1947	GM	568.90	3526.5	761.5
54	1948	GM	529.20	3245.7	922.4
55	1949	GM	555.10	3700.2	1020.1
56	1950	GM	642.90	3755.6	1099.0
57	1951	GM	755.90	4833.0	1207.7
58	1952	GM	891.20	4926.9	1430.5
59	1953	GM	1304.40	6241.7	1777.3
60	1954	GM	1486.70	5593.6	226.3
61	1935	WEST	12.93	191.5	1.8
62	1936	WEST	25.90	516.0	0.8
63	1937	WEST	35.05	729.0	7.4
64	1938	WEST	22.89	560.4	18.1
65	1939	WEST	18.84	519.9	23.5
66	1940	WEST	28.57	628.5	26.5
67	1941	WEST	48.51	537.1	36.2
68	1942	WEST	43.34	561.2	60.8
69	1943	WEST	37.02	617.2	84.4
70	1944	WEST	37.81	626.7	91.2
71	1945	WEST	39.27	737.2	92.4
72	1946	WEST	53.46	760.5	86.0
73	1947	WEST	55.56	581.4	111.1
74	1948	WEST	49.56	662.3	130.6
75	1949	WEST	32.04	583.8	141.8
76	1950	WEST	32.24	635.2	136.7
77	1951	WEST	54.38	732.8	129.7
78	1952	WEST	71.78	864.1	145.5
79	1953	WEST	90.08	1193.5	174.8
80	1954	WEST	68.60	1188.9	213.5

a1 <- e[10,4]
a1

## [1] 56.8

CT <- e$CT
CT

##  [1] "GE"   "GE"   "GE"   "GE"   "GE"   "GE"   "GE"   "GE"   "GE"   "GE"  
## [11] "GE"   "GE"   "GE"   "GE"   "GE"   "GE"   "GE"   "GE"   "GE"   "GE"  
## [21] "US"   "US"   "US"   "US"   "US"   "US"   "US"   "US"   "US"   "US"  
## [31] "US"   "US"   "US"   "US"   "US"   "US"   "US"   "US"   "US"   "US"  
## [41] "GM"   "GM"   "GM"   "GM"   "GM"   "GM"   "GM"   "GM"   "GM"   "GM"  
## [51] "GM"   "GM"   "GM"   "GM"   "GM"   "GM"   "GM"   "GM"   "GM"   "GM"  
## [61] "WEST" "WEST" "WEST" "WEST" "WEST" "WEST" "WEST" "WEST" "WEST" "WEST"
## [71] "WEST" "WEST" "WEST" "WEST" "WEST" "WEST" "WEST" "WEST" "WEST" "WEST"

a2 <- e[3,]
a2

	S	N	CT	Y	X2	X3
3	3	1937	GE	77.2	2803.3	118

a3 <- e[,c(1,4)]
a3

S	Y
1	33.10
2	45.00
3	77.20
4	44.60
5	48.10
6	74.40
7	113.00
8	91.90
9	61.30
10	56.80
11	93.60
12	159.90
13	147.20
14	146.30
15	98.30
16	93.50
17	135.20
18	157.30
19	179.50
20	189.60
21	209.90
22	355.30
23	469.90
24	262.30
25	230.40
26	361.60
27	472.80
28	445.60
29	361.60
30	288.20
31	258.70
32	420.30
33	420.50
34	494.50
35	405.10
36	418.80
37	588.20
38	645.20
39	641.00
40	459.30
41	317.60
42	391.80
43	410.60
44	257.70
45	330.80
46	461.20
47	512.00
48	448.00
49	499.60
50	547.50
51	561.20
52	688.10
53	568.90
54	529.20
55	555.10
56	642.90
57	755.90
58	891.20
59	1304.40
60	1486.70
61	12.93
62	25.90
63	35.05
64	22.89
65	18.84
66	28.57
67	48.51
68	43.34
69	37.02
70	37.81
71	39.27
72	53.46
73	55.56
74	49.56
75	32.04
76	32.24
77	54.38
78	71.78
79	90.08
80	68.60

a4 <- e[c(3,5,7,15,56),]
a4

	S	N	CT	Y	X2	X3
3	3	1937	GE	77.2	2803.3	118.0
5	5	1939	GE	48.1	2256.2	172.6
7	7	1941	GE	113.0	1834.1	220.9
15	15	1949	GE	98.3	1431.8	618.3
56	56	1950	GM	642.9	3755.6	1099.0

a5 <- e[e$Y <50 & e$X2 <=2000,]
a5

	S	N	CT	Y	X2	X3
1	1	1935	GE	33.10	1170.6	97.8
61	61	1935	WEST	12.93	191.5	1.8
62	62	1936	WEST	25.90	516.0	0.8
63	63	1937	WEST	35.05	729.0	7.4
64	64	1938	WEST	22.89	560.4	18.1
65	65	1939	WEST	18.84	519.9	23.5
66	66	1940	WEST	28.57	628.5	26.5
67	67	1941	WEST	48.51	537.1	36.2
68	68	1942	WEST	43.34	561.2	60.8
69	69	1943	WEST	37.02	617.2	84.4
70	70	1944	WEST	37.81	626.7	91.2
71	71	1945	WEST	39.27	737.2	92.4
74	74	1948	WEST	49.56	662.3	130.6
75	75	1949	WEST	32.04	583.8	141.8
76	76	1950	WEST	32.24	635.2	136.7

a5 <- e[e$CT =='WEST'| e$X3 >= 50,]
a5

	S	N	CT	Y	X2	X3
1	1	1935	GE	33.10	1170.6	97.8
2	2	1936	GE	45.00	2015.8	104.4
3	3	1937	GE	77.20	2803.3	118.0
4	4	1938	GE	44.60	2039.7	156.2
5	5	1939	GE	48.10	2256.2	172.6
6	6	1940	GE	74.40	2132.2	186.6
7	7	1941	GE	113.00	1834.1	220.9
8	8	1942	GE	91.90	1588.0	287.8
9	9	1943	GE	61.30	1749.4	319.9
10	10	1944	GE	56.80	1687.2	321.3
11	11	1945	GE	93.60	2007.7	319.6
12	12	1946	GE	159.90	2208.3	346.0
13	13	1947	GE	147.20	1656.7	456.4
14	14	1948	GE	146.30	1604.4	543.4
15	15	1949	GE	98.30	1431.8	618.3
16	16	1950	GE	93.50	1610.5	647.4
17	17	1951	GE	135.20	1819.4	671.3
18	18	1952	GE	157.30	2079.7	726.1
19	19	1953	GE	179.50	2371.6	800.3
20	20	1954	GE	189.60	2759.9	888.9
21	21	1935	US	209.90	1362.4	53.8
22	22	1936	US	355.30	1807.1	50.5
23	23	1937	US	469.90	2673.3	118.1
24	24	1938	US	262.30	1801.9	260.2
25	25	1939	US	230.40	1957.3	312.7
26	26	1940	US	361.60	2202.9	254.2
27	27	1941	US	472.80	2380.5	261.4
28	28	1942	US	445.60	2168.6	298.7
29	29	1943	US	361.60	1985.1	301.8
30	30	1944	US	288.20	1813.9	279.1
31	31	1945	US	258.70	1850.2	213.8
32	32	1946	US	420.30	2067.7	232.6
33	33	1947	US	420.50	1796.3	264.8
34	34	1948	US	494.50	1625.8	306.9
35	35	1949	US	405.10	1667.0	351.1
36	36	1950	US	418.80	1677.4	357.8
37	37	1951	US	588.20	2289.5	341.1
38	38	1952	US	645.20	2159.4	444.2
39	39	1953	US	641.00	2031.3	623.6
40	40	1954	US	459.30	2115.5	669.7
42	42	1936	GM	391.80	4661.7	52.6
43	43	1937	GM	410.60	5387.1	156.9
44	44	1938	GM	257.70	2792.2	209.2
45	45	1939	GM	330.80	4313.2	203.4
46	46	1940	GM	461.20	4643.9	207.2
47	47	1941	GM	512.00	4551.2	255.2
48	48	1942	GM	448.00	3244.1	303.7
49	49	1943	GM	499.60	4053.7	264.1
50	50	1944	GM	547.50	4379.3	201.6
51	51	1945	GM	561.20	4840.9	265.0
52	52	1946	GM	688.10	4900.0	402.0
53	53	1947	GM	568.90	3526.5	761.5
54	54	1948	GM	529.20	3245.7	922.4
55	55	1949	GM	555.10	3700.2	1020.1
56	56	1950	GM	642.90	3755.6	1099.0
57	57	1951	GM	755.90	4833.0	1207.7
58	58	1952	GM	891.20	4926.9	1430.5
59	59	1953	GM	1304.40	6241.7	1777.3
60	60	1954	GM	1486.70	5593.6	226.3
61	61	1935	WEST	12.93	191.5	1.8
62	62	1936	WEST	25.90	516.0	0.8
63	63	1937	WEST	35.05	729.0	7.4
64	64	1938	WEST	22.89	560.4	18.1
65	65	1939	WEST	18.84	519.9	23.5
66	66	1940	WEST	28.57	628.5	26.5
67	67	1941	WEST	48.51	537.1	36.2
68	68	1942	WEST	43.34	561.2	60.8
69	69	1943	WEST	37.02	617.2	84.4
70	70	1944	WEST	37.81	626.7	91.2
71	71	1945	WEST	39.27	737.2	92.4
72	72	1946	WEST	53.46	760.5	86.0
73	73	1947	WEST	55.56	581.4	111.1
74	74	1948	WEST	49.56	662.3	130.6
75	75	1949	WEST	32.04	583.8	141.8
76	76	1950	WEST	32.24	635.2	136.7
77	77	1951	WEST	54.38	732.8	129.7
78	78	1952	WEST	71.78	864.1	145.5
79	79	1953	WEST	90.08	1193.5	174.8
80	80	1954	WEST	68.60	1188.9	213.5

str(e)

## 'data.frame':    80 obs. of  6 variables:
##  $ S : int  1 2 3 4 5 6 7 8 9 10 ...
##  $ N : int  1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 ...
##  $ CT: chr  "GE" "GE" "GE" "GE" ...
##  $ Y : num  33.1 45 77.2 44.6 48.1 74.4 113 91.9 61.3 56.8 ...
##  $ X2: num  1171 2016 2803 2040 2256 ...
##  $ X3: num  97.8 104.4 118 156.2 172.6 ...

head(e,4)

S	N	CT	Y	X2	X3
1	1935	GE	33.1	1170.6	97.8
2	1936	GE	45.0	2015.8	104.4
3	1937	GE	77.2	2803.3	118.0
4	1938	GE	44.6	2039.7	156.2

tail(e,7)

	S	N	CT	Y	X2	X3
74	74	1948	WEST	49.56	662.3	130.6
75	75	1949	WEST	32.04	583.8	141.8
76	76	1950	WEST	32.24	635.2	136.7
77	77	1951	WEST	54.38	732.8	129.7
78	78	1952	WEST	71.78	864.1	145.5
79	79	1953	WEST	90.08	1193.5	174.8
80	80	1954	WEST	68.60	1188.9	213.5

a6 <- e[e$CT =='GE',]
a6

S	N	CT	Y	X2	X3
1	1935	GE	33.1	1170.6	97.8
2	1936	GE	45.0	2015.8	104.4
3	1937	GE	77.2	2803.3	118.0
4	1938	GE	44.6	2039.7	156.2
5	1939	GE	48.1	2256.2	172.6
6	1940	GE	74.4	2132.2	186.6
7	1941	GE	113.0	1834.1	220.9
8	1942	GE	91.9	1588.0	287.8
9	1943	GE	61.3	1749.4	319.9
10	1944	GE	56.8	1687.2	321.3
11	1945	GE	93.6	2007.7	319.6
12	1946	GE	159.9	2208.3	346.0
13	1947	GE	147.2	1656.7	456.4
14	1948	GE	146.3	1604.4	543.4
15	1949	GE	98.3	1431.8	618.3
16	1950	GE	93.5	1610.5	647.4
17	1951	GE	135.2	1819.4	671.3
18	1952	GE	157.3	2079.7	726.1
19	1953	GE	179.5	2371.6	800.3
20	1954	GE	189.6	2759.9	888.9

a7 <- e[5:20,]
a7

	S	N	CT	Y	X2	X3
5	5	1939	GE	48.1	2256.2	172.6
6	6	1940	GE	74.4	2132.2	186.6
7	7	1941	GE	113.0	1834.1	220.9
8	8	1942	GE	91.9	1588.0	287.8
9	9	1943	GE	61.3	1749.4	319.9
10	10	1944	GE	56.8	1687.2	321.3
11	11	1945	GE	93.6	2007.7	319.6
12	12	1946	GE	159.9	2208.3	346.0
13	13	1947	GE	147.2	1656.7	456.4
14	14	1948	GE	146.3	1604.4	543.4
15	15	1949	GE	98.3	1431.8	618.3
16	16	1950	GE	93.5	1610.5	647.4
17	17	1951	GE	135.2	1819.4	671.3
18	18	1952	GE	157.3	2079.7	726.1
19	19	1953	GE	179.5	2371.6	800.3
20	20	1954	GE	189.6	2759.9	888.9

a8 <- e[e$CT != 'WEST',]
a8

S	N	CT	Y	X2	X3
1	1935	GE	33.1	1170.6	97.8
2	1936	GE	45.0	2015.8	104.4
3	1937	GE	77.2	2803.3	118.0
4	1938	GE	44.6	2039.7	156.2
5	1939	GE	48.1	2256.2	172.6
6	1940	GE	74.4	2132.2	186.6
7	1941	GE	113.0	1834.1	220.9
8	1942	GE	91.9	1588.0	287.8
9	1943	GE	61.3	1749.4	319.9
10	1944	GE	56.8	1687.2	321.3
11	1945	GE	93.6	2007.7	319.6
12	1946	GE	159.9	2208.3	346.0
13	1947	GE	147.2	1656.7	456.4
14	1948	GE	146.3	1604.4	543.4
15	1949	GE	98.3	1431.8	618.3
16	1950	GE	93.5	1610.5	647.4
17	1951	GE	135.2	1819.4	671.3
18	1952	GE	157.3	2079.7	726.1
19	1953	GE	179.5	2371.6	800.3
20	1954	GE	189.6	2759.9	888.9
21	1935	US	209.9	1362.4	53.8
22	1936	US	355.3	1807.1	50.5
23	1937	US	469.9	2673.3	118.1
24	1938	US	262.3	1801.9	260.2
25	1939	US	230.4	1957.3	312.7
26	1940	US	361.6	2202.9	254.2
27	1941	US	472.8	2380.5	261.4
28	1942	US	445.6	2168.6	298.7
29	1943	US	361.6	1985.1	301.8
30	1944	US	288.2	1813.9	279.1
31	1945	US	258.7	1850.2	213.8
32	1946	US	420.3	2067.7	232.6
33	1947	US	420.5	1796.3	264.8
34	1948	US	494.5	1625.8	306.9
35	1949	US	405.1	1667.0	351.1
36	1950	US	418.8	1677.4	357.8
37	1951	US	588.2	2289.5	341.1
38	1952	US	645.2	2159.4	444.2
39	1953	US	641.0	2031.3	623.6
40	1954	US	459.3	2115.5	669.7
41	1935	GM	317.6	3078.5	2.8
42	1936	GM	391.8	4661.7	52.6
43	1937	GM	410.6	5387.1	156.9
44	1938	GM	257.7	2792.2	209.2
45	1939	GM	330.8	4313.2	203.4
46	1940	GM	461.2	4643.9	207.2
47	1941	GM	512.0	4551.2	255.2
48	1942	GM	448.0	3244.1	303.7
49	1943	GM	499.6	4053.7	264.1
50	1944	GM	547.5	4379.3	201.6
51	1945	GM	561.2	4840.9	265.0
52	1946	GM	688.1	4900.0	402.0
53	1947	GM	568.9	3526.5	761.5
54	1948	GM	529.2	3245.7	922.4
55	1949	GM	555.1	3700.2	1020.1
56	1950	GM	642.9	3755.6	1099.0
57	1951	GM	755.9	4833.0	1207.7
58	1952	GM	891.2	4926.9	1430.5
59	1953	GM	1304.4	6241.7	1777.3
60	1954	GM	1486.7	5593.6	226.3

library(tidyverse)

## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.5
## ✔ forcats   1.0.0     ✔ stringr   1.5.1
## ✔ lubridate 1.9.3     ✔ tibble    3.2.1
## ✔ purrr     1.0.2     ✔ tidyr     1.3.0
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

i <- iris
i1 <- filter(i,Sepal.Length >5|Species=='setosa')
i1

Sepal.Length	Sepal.Width	Petal.Length	Petal.Width	Species
5.1	3.5	1.4	0.2	setosa
4.9	3.0	1.4	0.2	setosa
4.7	3.2	1.3	0.2	setosa
4.6	3.1	1.5	0.2	setosa
5.0	3.6	1.4	0.2	setosa
5.4	3.9	1.7	0.4	setosa
4.6	3.4	1.4	0.3	setosa
5.0	3.4	1.5	0.2	setosa
4.4	2.9	1.4	0.2	setosa
4.9	3.1	1.5	0.1	setosa
5.4	3.7	1.5	0.2	setosa
4.8	3.4	1.6	0.2	setosa
4.8	3.0	1.4	0.1	setosa
4.3	3.0	1.1	0.1	setosa
5.8	4.0	1.2	0.2	setosa
5.7	4.4	1.5	0.4	setosa
5.4	3.9	1.3	0.4	setosa
5.1	3.5	1.4	0.3	setosa
5.7	3.8	1.7	0.3	setosa
5.1	3.8	1.5	0.3	setosa
5.4	3.4	1.7	0.2	setosa
5.1	3.7	1.5	0.4	setosa
4.6	3.6	1.0	0.2	setosa
5.1	3.3	1.7	0.5	setosa
4.8	3.4	1.9	0.2	setosa
5.0	3.0	1.6	0.2	setosa
5.0	3.4	1.6	0.4	setosa
5.2	3.5	1.5	0.2	setosa
5.2	3.4	1.4	0.2	setosa
4.7	3.2	1.6	0.2	setosa
4.8	3.1	1.6	0.2	setosa
5.4	3.4	1.5	0.4	setosa
5.2	4.1	1.5	0.1	setosa
5.5	4.2	1.4	0.2	setosa
4.9	3.1	1.5	0.2	setosa
5.0	3.2	1.2	0.2	setosa
5.5	3.5	1.3	0.2	setosa
4.9	3.6	1.4	0.1	setosa
4.4	3.0	1.3	0.2	setosa
5.1	3.4	1.5	0.2	setosa
5.0	3.5	1.3	0.3	setosa
4.5	2.3	1.3	0.3	setosa
4.4	3.2	1.3	0.2	setosa
5.0	3.5	1.6	0.6	setosa
5.1	3.8	1.9	0.4	setosa
4.8	3.0	1.4	0.3	setosa
5.1	3.8	1.6	0.2	setosa
4.6	3.2	1.4	0.2	setosa
5.3	3.7	1.5	0.2	setosa
5.0	3.3	1.4	0.2	setosa
7.0	3.2	4.7	1.4	versicolor
6.4	3.2	4.5	1.5	versicolor
6.9	3.1	4.9	1.5	versicolor
5.5	2.3	4.0	1.3	versicolor
6.5	2.8	4.6	1.5	versicolor
5.7	2.8	4.5	1.3	versicolor
6.3	3.3	4.7	1.6	versicolor
6.6	2.9	4.6	1.3	versicolor
5.2	2.7	3.9	1.4	versicolor
5.9	3.0	4.2	1.5	versicolor
6.0	2.2	4.0	1.0	versicolor
6.1	2.9	4.7	1.4	versicolor
5.6	2.9	3.6	1.3	versicolor
6.7	3.1	4.4	1.4	versicolor
5.6	3.0	4.5	1.5	versicolor
5.8	2.7	4.1	1.0	versicolor
6.2	2.2	4.5	1.5	versicolor
5.6	2.5	3.9	1.1	versicolor
5.9	3.2	4.8	1.8	versicolor
6.1	2.8	4.0	1.3	versicolor
6.3	2.5	4.9	1.5	versicolor
6.1	2.8	4.7	1.2	versicolor
6.4	2.9	4.3	1.3	versicolor
6.6	3.0	4.4	1.4	versicolor
6.8	2.8	4.8	1.4	versicolor
6.7	3.0	5.0	1.7	versicolor
6.0	2.9	4.5	1.5	versicolor
5.7	2.6	3.5	1.0	versicolor
5.5	2.4	3.8	1.1	versicolor
5.5	2.4	3.7	1.0	versicolor
5.8	2.7	3.9	1.2	versicolor
6.0	2.7	5.1	1.6	versicolor
5.4	3.0	4.5	1.5	versicolor
6.0	3.4	4.5	1.6	versicolor
6.7	3.1	4.7	1.5	versicolor
6.3	2.3	4.4	1.3	versicolor
5.6	3.0	4.1	1.3	versicolor
5.5	2.5	4.0	1.3	versicolor
5.5	2.6	4.4	1.2	versicolor
6.1	3.0	4.6	1.4	versicolor
5.8	2.6	4.0	1.2	versicolor
5.6	2.7	4.2	1.3	versicolor
5.7	3.0	4.2	1.2	versicolor
5.7	2.9	4.2	1.3	versicolor
6.2	2.9	4.3	1.3	versicolor
5.1	2.5	3.0	1.1	versicolor
5.7	2.8	4.1	1.3	versicolor
6.3	3.3	6.0	2.5	virginica
5.8	2.7	5.1	1.9	virginica
7.1	3.0	5.9	2.1	virginica
6.3	2.9	5.6	1.8	virginica
6.5	3.0	5.8	2.2	virginica
7.6	3.0	6.6	2.1	virginica
7.3	2.9	6.3	1.8	virginica
6.7	2.5	5.8	1.8	virginica
7.2	3.6	6.1	2.5	virginica
6.5	3.2	5.1	2.0	virginica
6.4	2.7	5.3	1.9	virginica
6.8	3.0	5.5	2.1	virginica
5.7	2.5	5.0	2.0	virginica
5.8	2.8	5.1	2.4	virginica
6.4	3.2	5.3	2.3	virginica
6.5	3.0	5.5	1.8	virginica
7.7	3.8	6.7	2.2	virginica
7.7	2.6	6.9	2.3	virginica
6.0	2.2	5.0	1.5	virginica
6.9	3.2	5.7	2.3	virginica
5.6	2.8	4.9	2.0	virginica
7.7	2.8	6.7	2.0	virginica
6.3	2.7	4.9	1.8	virginica
6.7	3.3	5.7	2.1	virginica
7.2	3.2	6.0	1.8	virginica
6.2	2.8	4.8	1.8	virginica
6.1	3.0	4.9	1.8	virginica
6.4	2.8	5.6	2.1	virginica
7.2	3.0	5.8	1.6	virginica
7.4	2.8	6.1	1.9	virginica
7.9	3.8	6.4	2.0	virginica
6.4	2.8	5.6	2.2	virginica
6.3	2.8	5.1	1.5	virginica
6.1	2.6	5.6	1.4	virginica
7.7	3.0	6.1	2.3	virginica
6.3	3.4	5.6	2.4	virginica
6.4	3.1	5.5	1.8	virginica
6.0	3.0	4.8	1.8	virginica
6.9	3.1	5.4	2.1	virginica
6.7	3.1	5.6	2.4	virginica
6.9	3.1	5.1	2.3	virginica
5.8	2.7	5.1	1.9	virginica
6.8	3.2	5.9	2.3	virginica
6.7	3.3	5.7	2.5	virginica
6.7	3.0	5.2	2.3	virginica
6.3	2.5	5.0	1.9	virginica
6.5	3.0	5.2	2.0	virginica
6.2	3.4	5.4	2.3	virginica
5.9	3.0	5.1	1.8	virginica

i2 <- i %>% filter(Petal.Width >= 1.5|Species == 'virginica')
i2

Sepal.Length	Sepal.Width	Petal.Length	Petal.Width	Species
6.4	3.2	4.5	1.5	versicolor
6.9	3.1	4.9	1.5	versicolor
6.5	2.8	4.6	1.5	versicolor
6.3	3.3	4.7	1.6	versicolor
5.9	3.0	4.2	1.5	versicolor
5.6	3.0	4.5	1.5	versicolor
6.2	2.2	4.5	1.5	versicolor
5.9	3.2	4.8	1.8	versicolor
6.3	2.5	4.9	1.5	versicolor
6.7	3.0	5.0	1.7	versicolor
6.0	2.9	4.5	1.5	versicolor
6.0	2.7	5.1	1.6	versicolor
5.4	3.0	4.5	1.5	versicolor
6.0	3.4	4.5	1.6	versicolor
6.7	3.1	4.7	1.5	versicolor
6.3	3.3	6.0	2.5	virginica
5.8	2.7	5.1	1.9	virginica
7.1	3.0	5.9	2.1	virginica
6.3	2.9	5.6	1.8	virginica
6.5	3.0	5.8	2.2	virginica
7.6	3.0	6.6	2.1	virginica
4.9	2.5	4.5	1.7	virginica
7.3	2.9	6.3	1.8	virginica
6.7	2.5	5.8	1.8	virginica
7.2	3.6	6.1	2.5	virginica
6.5	3.2	5.1	2.0	virginica
6.4	2.7	5.3	1.9	virginica
6.8	3.0	5.5	2.1	virginica
5.7	2.5	5.0	2.0	virginica
5.8	2.8	5.1	2.4	virginica
6.4	3.2	5.3	2.3	virginica
6.5	3.0	5.5	1.8	virginica
7.7	3.8	6.7	2.2	virginica
7.7	2.6	6.9	2.3	virginica
6.0	2.2	5.0	1.5	virginica
6.9	3.2	5.7	2.3	virginica
5.6	2.8	4.9	2.0	virginica
7.7	2.8	6.7	2.0	virginica
6.3	2.7	4.9	1.8	virginica
6.7	3.3	5.7	2.1	virginica
7.2	3.2	6.0	1.8	virginica
6.2	2.8	4.8	1.8	virginica
6.1	3.0	4.9	1.8	virginica
6.4	2.8	5.6	2.1	virginica
7.2	3.0	5.8	1.6	virginica
7.4	2.8	6.1	1.9	virginica
7.9	3.8	6.4	2.0	virginica
6.4	2.8	5.6	2.2	virginica
6.3	2.8	5.1	1.5	virginica
6.1	2.6	5.6	1.4	virginica
7.7	3.0	6.1	2.3	virginica
6.3	3.4	5.6	2.4	virginica
6.4	3.1	5.5	1.8	virginica
6.0	3.0	4.8	1.8	virginica
6.9	3.1	5.4	2.1	virginica
6.7	3.1	5.6	2.4	virginica
6.9	3.1	5.1	2.3	virginica
5.8	2.7	5.1	1.9	virginica
6.8	3.2	5.9	2.3	virginica
6.7	3.3	5.7	2.5	virginica
6.7	3.0	5.2	2.3	virginica
6.3	2.5	5.0	1.9	virginica
6.5	3.0	5.2	2.0	virginica
6.2	3.4	5.4	2.3	virginica
5.9	3.0	5.1	1.8	virginica

i3 <- i %>% select(Sepal.Length, Petal.Width, Species)
i3

Sepal.Length	Petal.Width	Species
5.1	0.2	setosa
4.9	0.2	setosa
4.7	0.2	setosa
4.6	0.2	setosa
5.0	0.2	setosa
5.4	0.4	setosa
4.6	0.3	setosa
5.0	0.2	setosa
4.4	0.2	setosa
4.9	0.1	setosa
5.4	0.2	setosa
4.8	0.2	setosa
4.8	0.1	setosa
4.3	0.1	setosa
5.8	0.2	setosa
5.7	0.4	setosa
5.4	0.4	setosa
5.1	0.3	setosa
5.7	0.3	setosa
5.1	0.3	setosa
5.4	0.2	setosa
5.1	0.4	setosa
4.6	0.2	setosa
5.1	0.5	setosa
4.8	0.2	setosa
5.0	0.2	setosa
5.0	0.4	setosa
5.2	0.2	setosa
5.2	0.2	setosa
4.7	0.2	setosa
4.8	0.2	setosa
5.4	0.4	setosa
5.2	0.1	setosa
5.5	0.2	setosa
4.9	0.2	setosa
5.0	0.2	setosa
5.5	0.2	setosa
4.9	0.1	setosa
4.4	0.2	setosa
5.1	0.2	setosa
5.0	0.3	setosa
4.5	0.3	setosa
4.4	0.2	setosa
5.0	0.6	setosa
5.1	0.4	setosa
4.8	0.3	setosa
5.1	0.2	setosa
4.6	0.2	setosa
5.3	0.2	setosa
5.0	0.2	setosa
7.0	1.4	versicolor
6.4	1.5	versicolor
6.9	1.5	versicolor
5.5	1.3	versicolor
6.5	1.5	versicolor
5.7	1.3	versicolor
6.3	1.6	versicolor
4.9	1.0	versicolor
6.6	1.3	versicolor
5.2	1.4	versicolor
5.0	1.0	versicolor
5.9	1.5	versicolor
6.0	1.0	versicolor
6.1	1.4	versicolor
5.6	1.3	versicolor
6.7	1.4	versicolor
5.6	1.5	versicolor
5.8	1.0	versicolor
6.2	1.5	versicolor
5.6	1.1	versicolor
5.9	1.8	versicolor
6.1	1.3	versicolor
6.3	1.5	versicolor
6.1	1.2	versicolor
6.4	1.3	versicolor
6.6	1.4	versicolor
6.8	1.4	versicolor
6.7	1.7	versicolor
6.0	1.5	versicolor
5.7	1.0	versicolor
5.5	1.1	versicolor
5.5	1.0	versicolor
5.8	1.2	versicolor
6.0	1.6	versicolor
5.4	1.5	versicolor
6.0	1.6	versicolor
6.7	1.5	versicolor
6.3	1.3	versicolor
5.6	1.3	versicolor
5.5	1.3	versicolor
5.5	1.2	versicolor
6.1	1.4	versicolor
5.8	1.2	versicolor
5.0	1.0	versicolor
5.6	1.3	versicolor
5.7	1.2	versicolor
5.7	1.3	versicolor
6.2	1.3	versicolor
5.1	1.1	versicolor
5.7	1.3	versicolor
6.3	2.5	virginica
5.8	1.9	virginica
7.1	2.1	virginica
6.3	1.8	virginica
6.5	2.2	virginica
7.6	2.1	virginica
4.9	1.7	virginica
7.3	1.8	virginica
6.7	1.8	virginica
7.2	2.5	virginica
6.5	2.0	virginica
6.4	1.9	virginica
6.8	2.1	virginica
5.7	2.0	virginica
5.8	2.4	virginica
6.4	2.3	virginica
6.5	1.8	virginica
7.7	2.2	virginica
7.7	2.3	virginica
6.0	1.5	virginica
6.9	2.3	virginica
5.6	2.0	virginica
7.7	2.0	virginica
6.3	1.8	virginica
6.7	2.1	virginica
7.2	1.8	virginica
6.2	1.8	virginica
6.1	1.8	virginica
6.4	2.1	virginica
7.2	1.6	virginica
7.4	1.9	virginica
7.9	2.0	virginica
6.4	2.2	virginica
6.3	1.5	virginica
6.1	1.4	virginica
7.7	2.3	virginica
6.3	2.4	virginica
6.4	1.8	virginica
6.0	1.8	virginica
6.9	2.1	virginica
6.7	2.4	virginica
6.9	2.3	virginica
5.8	1.9	virginica
6.8	2.3	virginica
6.7	2.5	virginica
6.7	2.3	virginica
6.3	1.9	virginica
6.5	2.0	virginica
6.2	2.3	virginica
5.9	1.8	virginica

i4 <- i %>% filter(Petal.Length <3| Species =='versicolor') %>% select(Sepal.Length,Petal.Width,Species)
i4

Sepal.Length	Petal.Width	Species
5.1	0.2	setosa
4.9	0.2	setosa
4.7	0.2	setosa
4.6	0.2	setosa
5.0	0.2	setosa
5.4	0.4	setosa
4.6	0.3	setosa
5.0	0.2	setosa
4.4	0.2	setosa
4.9	0.1	setosa
5.4	0.2	setosa
4.8	0.2	setosa
4.8	0.1	setosa
4.3	0.1	setosa
5.8	0.2	setosa
5.7	0.4	setosa
5.4	0.4	setosa
5.1	0.3	setosa
5.7	0.3	setosa
5.1	0.3	setosa
5.4	0.2	setosa
5.1	0.4	setosa
4.6	0.2	setosa
5.1	0.5	setosa
4.8	0.2	setosa
5.0	0.2	setosa
5.0	0.4	setosa
5.2	0.2	setosa
5.2	0.2	setosa
4.7	0.2	setosa
4.8	0.2	setosa
5.4	0.4	setosa
5.2	0.1	setosa
5.5	0.2	setosa
4.9	0.2	setosa
5.0	0.2	setosa
5.5	0.2	setosa
4.9	0.1	setosa
4.4	0.2	setosa
5.1	0.2	setosa
5.0	0.3	setosa
4.5	0.3	setosa
4.4	0.2	setosa
5.0	0.6	setosa
5.1	0.4	setosa
4.8	0.3	setosa
5.1	0.2	setosa
4.6	0.2	setosa
5.3	0.2	setosa
5.0	0.2	setosa
7.0	1.4	versicolor
6.4	1.5	versicolor
6.9	1.5	versicolor
5.5	1.3	versicolor
6.5	1.5	versicolor
5.7	1.3	versicolor
6.3	1.6	versicolor
4.9	1.0	versicolor
6.6	1.3	versicolor
5.2	1.4	versicolor
5.0	1.0	versicolor
5.9	1.5	versicolor
6.0	1.0	versicolor
6.1	1.4	versicolor
5.6	1.3	versicolor
6.7	1.4	versicolor
5.6	1.5	versicolor
5.8	1.0	versicolor
6.2	1.5	versicolor
5.6	1.1	versicolor
5.9	1.8	versicolor
6.1	1.3	versicolor
6.3	1.5	versicolor
6.1	1.2	versicolor
6.4	1.3	versicolor
6.6	1.4	versicolor
6.8	1.4	versicolor
6.7	1.7	versicolor
6.0	1.5	versicolor
5.7	1.0	versicolor
5.5	1.1	versicolor
5.5	1.0	versicolor
5.8	1.2	versicolor
6.0	1.6	versicolor
5.4	1.5	versicolor
6.0	1.6	versicolor
6.7	1.5	versicolor
6.3	1.3	versicolor
5.6	1.3	versicolor
5.5	1.3	versicolor
5.5	1.2	versicolor
6.1	1.4	versicolor
5.8	1.2	versicolor
5.0	1.0	versicolor
5.6	1.3	versicolor
5.7	1.2	versicolor
5.7	1.3	versicolor
6.2	1.3	versicolor
5.1	1.1	versicolor
5.7	1.3	versicolor

Tạo dữ liệu mới từ dữ liệu có sẵn

w <- women
tich <- w$height+w$weight
tich

##  [1] 173 176 180 184 188 192 196 200 205 209 214 219 224 230 236

sqrt = sqrt(tich)
sqrt

##  [1] 13.15295 13.26650 13.41641 13.56466 13.71131 13.85641 14.00000 14.14214
##  [9] 14.31782 14.45683 14.62874 14.79865 14.96663 15.16575 15.36229

w1 <- w %>% mutate(sqrt)
w1

height	weight	sqrt
58	115	13.15295
59	117	13.26650
60	120	13.41641
61	123	13.56466
62	126	13.71131
63	129	13.85641
64	132	14.00000
65	135	14.14214
66	139	14.31782
67	142	14.45683
68	146	14.62874
69	150	14.79865
70	154	14.96663
71	159	15.16575
72	164	15.36229

Lấy dữ liệu từ World Bank

library(WDI)
ind <- WDIsearch('Total reserves')
ind

	indicator	name
4340	DT.DOD.DSTC.IR.ZS	Short-term debt (% of total reserves)
6593	FI.RES.TOTL.CD	Total reserves (includes gold, current US$) \| \|6594 \|FI.RES.TOTL.CD.WB \|Total reserves including gold valued at London gold price (current US$)
6595	FI.RES.TOTL.CD.ZS	Total reserves includes gold (% of GDP)
6596	FI.RES.TOTL.DT.ZS	Total reserves (% of total external debt)
6597	FI.RES.TOTL.MO	Total reserves in months of imports
6598	FI.RES.TOTL.MO.WB	Total reserves in months of imports of goods and services
6599	FI.RES.XGLD.CD	Total reserves minus gold (current US$)
7408	FM.LBL.BMNY.IR.ZS	Broad money to total reserves ratio
7416	FM.LBL.MQMY.IR.ZS	Money and quasi money (M2) to total reserves ratio
17958	TOTRESV	Total Reserves

ind1 <- WDI(indicator = 'FI.RES.TOTL.MO', country = c('VN'), extra = T)
ind1

country	iso2c	iso3c	year	FI.RES.TOTL.MO	lastupdated	region	capital	longitude	latitude	income	lending
Viet Nam	VN	VNM	2022	2.641353	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	2021	3.686074	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	2020	3.978296	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	2019	3.366793	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	2018	2.529580	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	2017	2.462901	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	2016	2.223985	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	2015	1.850373	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	2014	2.536335	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	2013	2.146522	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	2012	2.487028	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	2011	1.417350	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	2010	1.620547	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	2009	2.574184	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	2008	3.214584	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	2007	4.075098	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	2006	3.224640	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	2005	2.653657	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	2004	2.442831	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	2003	2.694840	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	2002	2.213041	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	2001	2.355113	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	2000	2.264215	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1999	2.814992	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1998	1.680220	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1997	1.670657	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1996	1.620063	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1995	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1994	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1993	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1992	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1991	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1990	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1989	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1988	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1987	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1986	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1985	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1984	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1983	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1982	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1981	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1980	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1979	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1978	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1977	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1976	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1975	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1974	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1973	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1972	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1971	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1970	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1969	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1968	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1967	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1966	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1965	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1964	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1963	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1962	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1961	NA	2023-12-18	NA	NA	NA	NA	NA	NA
Viet Nam	VN	VNM	1960	NA	2023-12-18	NA	NA	NA	NA	NA	NA

se <- ind1 %>% select(year,FI.RES.TOTL.MO)
se

year	FI.RES.TOTL.MO
2022	2.641353
2021	3.686074
2020	3.978296
2019	3.366793
2018	2.529580
2017	2.462901
2016	2.223985
2015	1.850373
2014	2.536335
2013	2.146522
2012	2.487028
2011	1.417350
2010	1.620547
2009	2.574184
2008	3.214584
2007	4.075098
2006	3.224640
2005	2.653657
2004	2.442831
2003	2.694840
2002	2.213041
2001	2.355113
2000	2.264215
1999	2.814992
1998	1.680220
1997	1.670657
1996	1.620063
1995	NA
1994	NA
1993	NA
1992	NA
1991	NA
1990	NA
1989	NA
1988	NA
1987	NA
1986	NA
1985	NA
1984	NA
1983	NA
1982	NA
1981	NA
1980	NA
1979	NA
1978	NA
1977	NA
1976	NA
1975	NA
1974	NA
1973	NA
1972	NA
1971	NA
1970	NA
1969	NA
1968	NA
1967	NA
1966	NA
1965	NA
1964	NA
1963	NA
1962	NA
1961	NA
1960	NA

na <- na.omit(se)
na

year	FI.RES.TOTL.MO
2022	2.641353
2021	3.686074
2020	3.978296
2019	3.366793
2018	2.529580
2017	2.462901
2016	2.223985
2015	1.850373
2014	2.536335
2013	2.146522
2012	2.487028
2011	1.417350
2010	1.620547
2009	2.574184
2008	3.214584
2007	4.075098
2006	3.224640
2005	2.653657
2004	2.442831
2003	2.694840
2002	2.213041
2001	2.355113
2000	2.264215
1999	2.814992
1998	1.680220
1997	1.670657
1996	1.620063

names(na) <- c('year','DuTru')
na

year	DuTru
2022	2.641353
2021	3.686074
2020	3.978296
2019	3.366793
2018	2.529580
2017	2.462901
2016	2.223985
2015	1.850373
2014	2.536335
2013	2.146522
2012	2.487028
2011	1.417350
2010	1.620547
2009	2.574184
2008	3.214584
2007	4.075098
2006	3.224640
2005	2.653657
2004	2.442831
2003	2.694840
2002	2.213041
2001	2.355113
2000	2.264215
1999	2.814992
1998	1.680220
1997	1.670657
1996	1.620063

Nhiemvu2

Nguyễn Thúy Vy

NHIỆM VỤ 2.1

Đọc dữ liệu từ file csv

Sử dụng dữ liệu có sẵn trong R

Bộ dữ liệu “Data trong bài MP05 của Fulltight”

Rút trích dữ liệu

Tạo dữ liệu mới từ dữ liệu có sẵn

Lấy dữ liệu từ World Bank

NHIỆM VỤ 2.2

height	weight
58	115
59	117
60	120
61	123
62	126
63	129
64	132
65	135
66	139
67	142
68	146
69	150
70	154
71	159
72	164

height	weight
58	115
59	117
60	120
61	123
62	126
63	129
64	132
65	135
66	139
67	142
68	146
69	150
70	154
71	159
72	164

height	weight
58	115
59	117
60	120
61	123
62	126
63	129
64	132
65	135
66	139
67	142
68	146
69	150
70	154
71	159
72	164