Overview

Dataset statistics

Number of variables7
Number of observations200
Missing cells4
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.7 KiB
Average record size in memory59.7 B

Variable types

Text4
Categorical1
Numeric2

Dataset

Description2020년 12월 31일 기준으로 국가별 우리나라와 교류하는 무역 수출품, 수입품 등의 정보를 CSV파일로 제공합니다. (1회성 데이터로 업데이트 되지 않습니다.)
Author외교부
URLhttps://www.data.go.kr/data/15076560/fileData.do

Alerts

우리나라와의 무역 수출액(US달러(호주는 AU달러) is highly overall correlated with 우리나라와의 무역 수입액(US달러(호주는 AU달러)High correlation
우리나라와의 무역 수입액(US달러(호주는 AU달러) is highly overall correlated with 우리나라와의 무역 수출액(US달러(호주는 AU달러)High correlation
무역년도 is highly imbalanced (51.2%)Imbalance

Reproduction

Analysis started2023-12-12 08:05:15.944674
Analysis finished2023-12-12 08:05:17.566053
Duration1.62 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

국가
Text

Distinct193
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-12T17:05:17.863639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length3.98
Min length2

Characters and Unicode

Total characters796
Distinct characters181
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique186 ?
Unique (%)93.0%

Sample

1st row가나
2nd row가나
3rd row가봉
4th row가이아나
5th row감비아
ValueCountFrequency (%)
세인트 3
 
1.5%
가나 2
 
1.0%
말라위 2
 
1.0%
모리셔스 2
 
1.0%
마다가스카르 2
 
1.0%
르완다 2
 
1.0%
이란 2
 
1.0%
라이베리아 2
 
1.0%
중앙아프리카공화국 1
 
0.5%
아일랜드 1
 
0.5%
Other values (186) 186
90.7%
2023-12-12T17:05:18.401433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 56
 
7.0%
리 32
 
4.0%
스 30
 
3.8%
이 25
 
3.1%
르 24
 
3.0%
니 23
 
2.9%
라 22
 
2.8%
나 17
 
2.1%
바 15
 
1.9%
카 14
 
1.8%
Other values (171) 538
67.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 787
98.9%
Space Separator 5
 
0.6%
Uppercase Letter 2
 
0.3%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 56
 
7.1%
리 32
 
4.1%
스 30
 
3.8%
이 25
 
3.2%
르 24
 
3.0%
니 23
 
2.9%
라 22
 
2.8%
나 17
 
2.2%
바 15
 
1.9%
카 14
 
1.8%
Other values (166) 529
67.2%
Uppercase Letter
ValueCountFrequency (%)
R 1
50.0%
D 1
50.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 787
98.9%
Common 7
 
0.9%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 56
 
7.1%
리 32
 
4.1%
스 30
 
3.8%
이 25
 
3.2%
르 24
 
3.0%
니 23
 
2.9%
라 22
 
2.8%
나 17
 
2.2%
바 15
 
1.9%
카 14
 
1.8%
Other values (166) 529
67.2%
Common
ValueCountFrequency (%)
5
71.4%
) 1
 
14.3%
( 1
 
14.3%
Latin
ValueCountFrequency (%)
R 1
50.0%
D 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 787
98.9%
ASCII 9
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 56
 
7.1%
리 32
 
4.1%
스 30
 
3.8%
이 25
 
3.2%
르 24
 
3.0%
니 23
 
2.9%
라 22
 
2.8%
나 17
 
2.2%
바 15
 
1.9%
카 14
 
1.8%
Other values (166) 529
67.2%
ASCII
ValueCountFrequency (%)
5
55.6%
R 1
 
11.1%
) 1
 
11.1%
D 1
 
11.1%
( 1
 
11.1%

국가코드(ISO 2자리 코드)
Text

Distinct192
Distinct (%)96.5%
Missing1
Missing (%)0.5%
Memory size1.7 KiB
2023-12-12T17:05:18.865853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters398
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique185 ?
Unique (%)93.0%

Sample

1st rowGH
2nd rowGH
3rd rowGA
4th rowGY
5th rowGM
ValueCountFrequency (%)
gh 2
 
1.0%
rw 2
 
1.0%
mu 2
 
1.0%
mw 2
 
1.0%
mg 2
 
1.0%
ir 2
 
1.0%
lr 2
 
1.0%
cf 1
 
0.5%
it 1
 
0.5%
ie 1
 
0.5%
Other values (182) 182
91.5%
2023-12-12T17:05:19.361011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
M 33
 
8.3%
S 27
 
6.8%
G 25
 
6.3%
T 23
 
5.8%
C 21
 
5.3%
B 21
 
5.3%
A 21
 
5.3%
L 20
 
5.0%
R 20
 
5.0%
E 19
 
4.8%
Other values (16) 168
42.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 398
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M 33
 
8.3%
S 27
 
6.8%
G 25
 
6.3%
T 23
 
5.8%
C 21
 
5.3%
B 21
 
5.3%
A 21
 
5.3%
L 20
 
5.0%
R 20
 
5.0%
E 19
 
4.8%
Other values (16) 168
42.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 398
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
M 33
 
8.3%
S 27
 
6.8%
G 25
 
6.3%
T 23
 
5.8%
C 21
 
5.3%
B 21
 
5.3%
A 21
 
5.3%
L 20
 
5.0%
R 20
 
5.0%
E 19
 
4.8%
Other values (16) 168
42.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 398
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
M 33
 
8.3%
S 27
 
6.8%
G 25
 
6.3%
T 23
 
5.8%
C 21
 
5.3%
B 21
 
5.3%
A 21
 
5.3%
L 20
 
5.0%
R 20
 
5.0%
E 19
 
4.8%
Other values (16) 168
42.2%

수출품
Text

Distinct191
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-12T17:05:19.623197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length32
Mean length17.7
Min length2

Characters and Unicode

Total characters3540
Distinct characters189
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique184 ?
Unique (%)92.0%

Sample

1st row자동차, 합성수지, 기타섬유제품
2nd row자동차, 합성수지, 기타섬유제품
3rd row승용차, 컴퓨터 등
4th row기계류, 부품 등
5th rowTV, 어망, 자동차 등
ValueCountFrequency (%)
등 128
 
15.6%
자동차 80
 
9.8%
승용차 39
 
4.8%
합성수지 37
 
4.5%
및 23
 
2.8%
기계류 20
 
2.4%
자동차부품 18
 
2.2%
부품 17
 
2.1%
선박 15
 
1.8%
철강 15
 
1.8%
Other values (189) 428
52.2%
2023-12-12T17:05:19.975223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
621
17.5%
, 417
 
11.8%
차 165
 
4.7%
품 148
 
4.2%
기 134
 
3.8%
등 132
 
3.7%
자 128
 
3.6%
동 116
 
3.3%
제 79
 
2.2%
전 65
 
1.8%
Other values (179) 1535
43.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2489
70.3%
Space Separator 621
 
17.5%
Other Punctuation 422
 
11.9%
Uppercase Letter 8
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
차 165
 
6.6%
품 148
 
5.9%
기 134
 
5.4%
등 132
 
5.3%
자 128
 
5.1%
동 116
 
4.7%
제 79
 
3.2%
전 65
 
2.6%
유 56
 
2.2%
용 56
 
2.2%
Other values (172) 1410
56.6%
Other Punctuation
ValueCountFrequency (%)
, 417
98.8%
/ 3
 
0.7%
· 1
 
0.2%
. 1
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
T 4
50.0%
V 4
50.0%
Space Separator
ValueCountFrequency (%)
621
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2489
70.3%
Common 1043
29.5%
Latin 8
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
차 165
 
6.6%
품 148
 
5.9%
기 134
 
5.4%
등 132
 
5.3%
자 128
 
5.1%
동 116
 
4.7%
제 79
 
3.2%
전 65
 
2.6%
유 56
 
2.2%
용 56
 
2.2%
Other values (172) 1410
56.6%
Common
ValueCountFrequency (%)
621
59.5%
, 417
40.0%
/ 3
 
0.3%
· 1
 
0.1%
. 1
 
0.1%
Latin
ValueCountFrequency (%)
T 4
50.0%
V 4
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2489
70.3%
ASCII 1050
29.7%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
621
59.1%
, 417
39.7%
T 4
 
0.4%
V 4
 
0.4%
/ 3
 
0.3%
. 1
 
0.1%
Hangul
ValueCountFrequency (%)
차 165
 
6.6%
품 148
 
5.9%
기 134
 
5.4%
등 132
 
5.3%
자 128
 
5.1%
동 116
 
4.7%
제 79
 
3.2%
전 65
 
2.6%
유 56
 
2.2%
용 56
 
2.2%
Other values (172) 1410
56.6%
None
ValueCountFrequency (%)
· 1
100.0%

수입품
Text

Distinct188
Distinct (%)94.9%
Missing2
Missing (%)1.0%
Memory size1.7 KiB
2023-12-12T17:05:20.236422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length29
Mean length14.712121
Min length2

Characters and Unicode

Total characters2913
Distinct characters236
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique178 ?
Unique (%)89.9%

Sample

1st row건전지, 축전지, 동제품
2nd row건전지, 축전지, 동제품
3rd row원유, 금속광물 등
4th row목재류 등
5th row넙치, 기타 냉동어류 등
ValueCountFrequency (%)
등 133
 
17.8%
원유 22
 
2.9%
커피 18
 
2.4%
반도체 15
 
2.0%
의약품 15
 
2.0%
및 13
 
1.7%
어류 13
 
1.7%
동 12
 
1.6%
의류 11
 
1.5%
석유제품 9
 
1.2%
Other values (267) 488
65.2%
2023-12-12T17:05:20.668202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
551
 
18.9%
, 355
 
12.2%
등 133
 
4.6%
품 100
 
3.4%
기 78
 
2.7%
유 61
 
2.1%
류 57
 
2.0%
제 53
 
1.8%
동 48
 
1.6%
의 37
 
1.3%
Other values (226) 1440
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1983
68.1%
Space Separator 551
 
18.9%
Other Punctuation 359
 
12.3%
Uppercase Letter 12
 
0.4%
Decimal Number 3
 
0.1%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
등 133
 
6.7%
품 100
 
5.0%
기 78
 
3.9%
유 61
 
3.1%
류 57
 
2.9%
제 53
 
2.7%
동 48
 
2.4%
의 37
 
1.9%
물 37
 
1.9%
원 34
 
1.7%
Other values (210) 1345
67.8%
Other Punctuation
ValueCountFrequency (%)
, 355
98.9%
/ 1
 
0.3%
· 1
 
0.3%
% 1
 
0.3%
. 1
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
G 4
33.3%
L 4
33.3%
P 3
25.0%
N 1
 
8.3%
Decimal Number
ValueCountFrequency (%)
1 1
33.3%
0 1
33.3%
9 1
33.3%
Space Separator
ValueCountFrequency (%)
551
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1983
68.1%
Common 918
31.5%
Latin 12
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
등 133
 
6.7%
품 100
 
5.0%
기 78
 
3.9%
유 61
 
3.1%
류 57
 
2.9%
제 53
 
2.7%
동 48
 
2.4%
의 37
 
1.9%
물 37
 
1.9%
원 34
 
1.7%
Other values (210) 1345
67.8%
Common
ValueCountFrequency (%)
551
60.0%
, 355
38.7%
( 2
 
0.2%
) 2
 
0.2%
1 1
 
0.1%
/ 1
 
0.1%
- 1
 
0.1%
· 1
 
0.1%
% 1
 
0.1%
0 1
 
0.1%
Other values (2) 2
 
0.2%
Latin
ValueCountFrequency (%)
G 4
33.3%
L 4
33.3%
P 3
25.0%
N 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1983
68.1%
ASCII 929
31.9%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
551
59.3%
, 355
38.2%
G 4
 
0.4%
L 4
 
0.4%
P 3
 
0.3%
( 2
 
0.2%
) 2
 
0.2%
1 1
 
0.1%
/ 1
 
0.1%
N 1
 
0.1%
Other values (5) 5
 
0.5%
Hangul
ValueCountFrequency (%)
등 133
 
6.7%
품 100
 
5.0%
기 78
 
3.9%
유 61
 
3.1%
류 57
 
2.9%
제 53
 
2.7%
동 48
 
2.4%
의 37
 
1.9%
물 37
 
1.9%
원 34
 
1.7%
Other values (210) 1345
67.8%
None
ValueCountFrequency (%)
· 1
100.0%

무역년도
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2019
147 
2018
40 
2020
 
6
2017
 
6
<NA>
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row2020
2nd row2019
3rd row2019
4th row2019
5th row2019

Common Values

ValueCountFrequency (%)
2019 147
73.5%
2018 40
 
20.0%
2020 6
 
3.0%
2017 6
 
3.0%
<NA> 1
 
0.5%

Length

2023-12-12T17:05:20.828395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:05:20.964355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 147
73.5%
2018 40
 
20.0%
2020 6
 
3.0%
2017 6
 
3.0%
na 1
 
0.5%

우리나라와의 무역 수출액(US달러(호주는 AU달러)
Real number (ℝ)

HIGH CORRELATION 

Distinct185
Distinct (%)92.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4747119 × 109
Minimum38000
Maximum1.36 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-12T17:05:21.119485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum38000
5-th percentile1000000
Q117360000
median1.265 × 108
Q39.25 × 108
95-th percentile8.4145 × 109
Maximum1.36 × 1011
Range1.3599996 × 1011
Interquartile range (IQR)9.0764 × 108

Descriptive statistics

Standard deviation1.1665799 × 1010
Coefficient of variation (CV)4.7140029
Kurtosis94.257777
Mean2.4747119 × 109
Median Absolute Deviation (MAD)1.23135 × 108
Skewness9.1212869
Sum4.9494238 × 1011
Variance1.3609086 × 1020
MonotonicityNot monotonic
2023-12-12T17:05:21.274667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
70000000 3
 
1.5%
9030000 2
 
1.0%
1000000 2
 
1.0%
310000000 2
 
1.0%
30000000 2
 
1.0%
3800000 2
 
1.0%
1700000000 2
 
1.0%
1300000000 2
 
1.0%
17790000 2
 
1.0%
27000000 2
 
1.0%
Other values (175) 179
89.5%
ValueCountFrequency (%)
38000 1
0.5%
69000 1
0.5%
224000 1
0.5%
277000 1
0.5%
345000 1
0.5%
392000 1
0.5%
430000 1
0.5%
630000 1
0.5%
760000 1
0.5%
1000000 2
1.0%
ValueCountFrequency (%)
136000000000 1
0.5%
73340000000 1
0.5%
48200000000 1
0.5%
28410000000 1
0.5%
15100000000 1
0.5%
12800000000 1
0.5%
10900000000 1
0.5%
9600000000 1
0.5%
8800000000 1
0.5%
8690000000 1
0.5%

우리나라와의 무역 수입액(US달러(호주는 AU달러)
Real number (ℝ)

HIGH CORRELATION 

Distinct179
Distinct (%)89.9%
Missing1
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean2.4701044 × 109
Minimum5000
Maximum1.07 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-12T17:05:21.464969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5000
5-th percentile39800
Q15015000
median57000000
Q37 × 108
95-th percentile9.45 × 109
Maximum1.07 × 1011
Range1.07 × 1011
Interquartile range (IQR)6.94985 × 108

Descriptive statistics

Standard deviation9.8745509 × 109
Coefficient of variation (CV)3.9976248
Kurtosis71.695937
Mean2.4701044 × 109
Median Absolute Deviation (MAD)56842000
Skewness7.7970164
Sum4.9155078 × 1011
Variance9.7506755 × 1019
MonotonicityNot monotonic
2023-12-12T17:05:21.615538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5000000 3
 
1.5%
3000000 3
 
1.5%
39000000 3
 
1.5%
13000 2
 
1.0%
43000000 2
 
1.0%
20000000 2
 
1.0%
1200000000 2
 
1.0%
2700000000 2
 
1.0%
68000000 2
 
1.0%
17000000 2
 
1.0%
Other values (169) 176
88.0%
ValueCountFrequency (%)
5000 1
0.5%
10000 1
0.5%
13000 2
1.0%
14000 1
0.5%
17000 1
0.5%
20000 1
0.5%
25000 1
0.5%
35000 1
0.5%
38000 1
0.5%
40000 1
0.5%
ValueCountFrequency (%)
107000000000 1
0.5%
61880000000 1
0.5%
47580000000 1
0.5%
21814000000 1
0.5%
21100000000 1
0.5%
20700000000 1
0.5%
19940000000 1
0.5%
14550000000 1
0.5%
13040000000 1
0.5%
10800000000 1
0.5%

Interactions

2023-12-12T17:05:16.807334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:05:16.532760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:05:16.947649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:05:16.676811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:05:21.725464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
무역년도우리나라와의 무역 수출액(US달러(호주는 AU달러)우리나라와의 무역 수입액(US달러(호주는 AU달러)
무역년도1.0000.0000.000
우리나라와의 무역 수출액(US달러(호주는 AU달러)0.0001.0000.980
우리나라와의 무역 수입액(US달러(호주는 AU달러)0.0000.9801.000
2023-12-12T17:05:21.822688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우리나라와의 무역 수출액(US달러(호주는 AU달러)우리나라와의 무역 수입액(US달러(호주는 AU달러)무역년도
우리나라와의 무역 수출액(US달러(호주는 AU달러)1.0000.7800.000
우리나라와의 무역 수입액(US달러(호주는 AU달러)0.7801.0000.000
무역년도0.0000.0001.000

Missing values

2023-12-12T17:05:17.137569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:05:17.288973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-12T17:05:17.468508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

국가국가코드(ISO 2자리 코드)수출품수입품무역년도우리나라와의 무역 수출액(US달러(호주는 AU달러)우리나라와의 무역 수입액(US달러(호주는 AU달러)
0가나GH자동차, 합성수지, 기타섬유제품건전지, 축전지, 동제품202016900000031000000
1가나GH자동차, 합성수지, 기타섬유제품건전지, 축전지, 동제품201919100000043000000
2가봉GA승용차, 컴퓨터 등원유, 금속광물 등201910000000320000000
3가이아나GY기계류, 부품 등목재류 등201913000000115000000
4감비아GMTV, 어망, 자동차 등넙치, 기타 냉동어류 등201926000005590000
5과테말라GT섬유, 자동차 등광물, 커피 등201922200000064000000
6그레나다GD자동차, 플라스틱, 축전지 등전자부품, 코코넛 등2019272000014000
7그리스GR선박, 합성수지, 승용차, 석유화학연료나프타, 금속광물, 연초류20191640000000530000000
8기니GN석유화학제품, 수공구 등어류, 천연가스, 구리 등20182700000050000000
9기니비사우GW컨테이너, 화학제품 등어류제품 등201810000003000000
국가국가코드(ISO 2자리 코드)수출품수입품무역년도우리나라와의 무역 수출액(US달러(호주는 AU달러)우리나라와의 무역 수입액(US달러(호주는 AU달러)
190팔레스타인PS승용차, 화학기계석재, 올리브유20171020000001800000
191페루PE자동차, 합성수지, 기계류광물, 과일, 수산가공품20197440000002318000000
192포르투갈PT승용차, 합성수지, 아연도강판 등편직제의류, 타이어, 합성수지 등2019505000000287000000
193폴란드PL평판디스플레이, 자동차부품, 승용차 등도자기, 자동차부품, 의약품 등2018433000000680000000
194프랑스FR승용차, 축전지, 전기자동차, 집적회로반도체 등화장품, 가방, 의약품, 집적회로반도체 등201933170000005835000000
195피지FJ석유제품, 자동차, 어구참치, 고철, 생수20192300000005000000
196핀란드FI승용차, 전기자동차, 합성수지, 발전기 등기타정밀화학연료, 유선통신기기 부품, 발전기, 니켈괴 및 스크랩 등20193100000001120000000
197필리핀PH반도체, 석유제품, 자동차, 철강판반도체, 원유, 동 제품, 곡물, 컴퓨터, 평판디스플레이201984000000003700000000
198헝가리HU의약품, 컴퓨터, 자동차, 디스플레이자동차, 엔진, 자동차 부품20192500000000500000000
199호주AU석유제품, 자동차, 선박석탄, 철광석, 육류, 가스, 원유2018960000000020700000000