# data[].attributes.body
1spain
2france
3london
4mẽico
5china
6rome
7russia
8canada
9itali
10moscow
11athens
12 japan
13madrid
14paris
15hungari
16tokyo
17germany
18brazil
----------

# data[].attributes.body
1 : Spain
2 : France
3 :London
4: Mexico
5 : China
6 : Rome
7 : Russia
8 : Canada
9 : Italy
10 : Moscow
11 :
12 : Japan
13 : Madrid
14 :Paris
15 :Hungary
16 :Tokyo
17 : Germany
18 : Brazil
----------------------

# data[].attributes.body
1. spain
2. france
3.london
4. mexico
5.china
6.rome
7.
8
9. italy
---------
1. russia
2 marid
3 fance
4 paris
5 london
6 italy
7 mexico
8 tokyo
9 china
10 japan

# data[].attributes.body
1 spain
2 france
3 london
4 mexico
5 China
6 rome
7 russia
8 canada

1 russia
2 MADRID
3 france
4 PARIS
5 LONDON
6 ITALY
7 MEXICO
8 TOKYO
9 CHINA
10 JAPAN

# data[].attributes.body
1. Spain
2. France
3. Lodon
4. Mexico
5. China
6. Rome
7. Russia
8. Canada
9. Italy
10. Moscow
11. Athens
12. Japan
13. Madrid
14. Paris
15. Hungary
16. Tokyo
17. Germany
18. Brazil
------------------
1 Russia
2 Madrid
3 France
4 Paris
5 London
6 Italy
7 Mexico
8 Tokyo
9 China
10 Japan

# data[].attributes.body
2. france
3.london
4. mexico
5 china
6. roma
7
8 canada
9 italy
10
11
12 japan
13
14 . paris
15 hungary
16
17

# data[].attributes.body
1 Spain
2 France
3 London
4 Mexico
5
6 Rome
7 Russia
8 Canada
9 Italy
10 Moscow
11
12 Japan
13 Madrid
14 Paris
15 Hungary
16 Tokyo
17 Germany
18 Brasil

# data[].attributes.body
1.Spain
2France
3. London
4. Mexico
8. Canada
9. Italy
5. China

# data[].attributes.body
Spain
Fance
London
Rome
Brazill
Italy
Mexico
Madeal

# data[].attributes.body
1. Spain
2. France
3. London
4. Mexico
5.
6. Roma
7.
8.
9. Italy
10.
11.
12.
13.
14.
15. Bungary
16. Tokyo
17. Germany
18. Brazil

# data[].attributes.body
1. Spain
2. France
3.lon don
4. Mexico
5.
6.
7.
8. Canada

.......
1 russia
2 madrid
3 france
4 paris
5 London
6 italy
7 mexico
8 tokyo
9 china
10 japan

# data[].attributes.body
Thúy Thảo
France
London
Italy
Brazil
Paris
Canada
Hungary
Madrid
Tokyo
---------------------
1 Russia

2
3 France
4 Paris
5 london
6italy
7 Mexico
8 china
9 Tokyo
10 japan

# data[].attributes.body
1

# data[].attributes.body
1. spain
2. france
3. london
4. mexico
5. china
6. rome
8. canada
9. italy

1. russia
2madrid
3. france
4. paris
5 london
6 italy
7 mexico
8 tokyo
9 china
10. japan

# data[].attributes.body
1. SPAIN
2. FRANCE
3. LONDON
4. MEXICO
5. CHINA
6. ROME
7. RUSSIA
8. CANADA
9. ITALY
10. MOSCOW
11. ATHENS
12. JAPAN
13. MADRID
14. PARIS
15. HUNGARY
16. TOKYO
17. GERMANY
18. BRAZIL
---------
1.
2
3
4
5
6
7
8
9
10

# data[].attributes.body
1 : Russia
2 : Madrid
3 : France
4 : Paris
5 : London
6 : Italy
7 : Mexico
8 : Tokyo
9 : China
10 : Japan

# data[].attributes.body
1 RUSSIA
2 MADRID
2 FRANCE
3 PARRIS
4 LONDON
5 ITALY
6 ROME
7 MEXICO
8 TOKYO
9 CHINA
10 JAPAN

# data[].attributes.body
1 Russia
2 Madrid
3 France
4 Paris
5 London
6 Italy
7 Mexico
8 Tokyo
9 China
10 Japan

# data[].attributes.body
1. Russia
2. Madrid
3. France
4. Paris
5. London
6. Italy
7. Mexico
8. Tokyo
9. China
10. japan

# data[].attributes.body
9 canada- 20 million
7 mexico, Russia- 21
6 UK- 25 million
10 Germany - 19 million
5. China- 31 million
4. Italy- 41 million
3. Spain- 50 million
2. US- 51 million
1. FRANCE- 75 million

# data[].attributes.body
russia
madrid
france
paris
london'
italy
mexico
tokyo
china
japan

# data[].attributes.body
a. 19 000
b. 18 milion
c. 30.5
d. 15
đúng 3

# data[].attributes.body
A 19000
B 18
C  30.5
D 15
DUNG 3

# data[].attributes.body
a 19000
b 80 million
c 30.5
d 15
4 điểm

# data[].attributes.body
A 19000
B 80 million
C 30.5 years
D 15 minutes

# data[].attributes.body
a, 19,000
b, 80 milion
c, 30.5
d, 15

# data[].attributes.body
a 19000
b 80
c13,5
d15
+3

# data[].attributes.body
a 19 000
b 80
c 30.5
d 15

# data[].attributes.body
A. 19.000
B. 18.000.000
C. 30.5
D. 15
+3
-----

# data[].attributes.body
a. nineteen thousand
b, eighty millions
c. thirty point five
d. fifteen

# data[].attributes.body
Thúy Thảo- listening 2
A 19
B 80
C 30
D 15
+4

# data[].attributes.body
a : 19.000
b : 18 million
c : 30.5
d : 15
+3

# data[].attributes.body
1
2
3
4
5
6
7
8
9
10

# data[].attributes.body
10 germany 19 million
9 canada 20 million
7 mexico 21 million
7 russia 21 millon
6 UK 25 million
5 china 31 million
4 italy 41 million
3 spain 48 million
2 US 51 million
1 France 75 million
FUll

# data[].attributes.body
1. France ( 75 milion)
2. United States (51 milion)
3. Spain (48 milion)
4.Italy (41 milion)
5. China ( 30 milion)
6. United Kingdom (25 milion)
7. Mexico and Russia (21milion)
8
9. Canada (20 milion)
10. Germany (19 milion)

# data[].attributes.body
1 FRANCE
2 THE US 51
3 SPAIN
4 ITALY 41
5 CHINA 31
6 THE UK 25
7  MEXICO AND RUSSIA 21
8
9 CANADA       20
10 GERMANY   19
sai 2

# data[].attributes.body
10. Germany - 19m
9. Canada - 20m
7. mexico - 21
7. russia - 21
6. U.K - 25m
5. China - 31
4. ITALY - 41
3. Japan - 48
2.U.S - 51
1. Fance - 75

# data[].attributes.body
1. FRANCE - 75M
2. US - 51M
3. SPAIN - 48M
4. ITALY - 41M
5. CHINA - 31M
6.U.K - 25M
7. RUSSIA - 21M
7. MEXICO - 21M
9. CANADA - 20M
10. GERMANY - 19M

# data[].attributes.body
1 germany
2 canada
3 mexico
4 russia
5 the united kingdom
6 china
7 italy
8 spain
9 the united states
10 frace

# data[].attributes.body
1 france- 75 millions
2 united states- 51 millions
3 spain- 48 millions
4 italy- 41 millions
5 china - 31 millions
6 united kingdom- 25 millions
7 mexico, russia - 21 millions
9  canada - 20 millions
10 germany - 19 millions

# data[].attributes.body
Thúy Thảo - 3
1 France 75
2 US 51

3 Spain 48
4 Italy 41
5 China 31
6 United Kingdom 25
7 Mexico/ Russia 21
9 Canada 20
10 Germany 19

# data[].attributes.body
10  Germany   19
9  Canada  20
7 Mexico  21
Russia   21
6  United of Kingdom   25
5 China  31
4 Italy  41
3 Japan  50
2 U.S  51
1 France 75

Sai 1 cau

# data[].attributes.body
1. France 75 million
2. U.S 51 milion
3. Spain
4. Italy 41 million
5. China 31 million
6. United Kingdom 25 milion
7. Mexico & Russia 21 million
8.
9. Canada 20 million
10. Germany 19 million

# data[].attributes.body
10 GERMANY - 19M
9 CANADA - 20M
7 MEXICO - 21M
7 RUSSIA -  21M
6 UNITED KINGDOM - 25M
5 CHINA- 31M
4 ITALY - 41M
3 SPAIN - 48M
2 UNITED STATES - 51M
1 FRANCE - 75M
DUNG 10