Overview

Dataset statistics

Number of variables10
Number of observations197
Missing cells240
Missing cells (%)12.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.9 KiB
Average record size in memory82.7 B

Variable types

Text8
Numeric2

Dataset

Description외교부 홈페이지에 공개 중인 각 국가별 약황 정보 중 우리나라와의 관계 정보를 CSV 형식으로 제공 합니다.(데이터 업데이트 주기: 12개월, 실시간 정보는 동명의 API 참고)
Author외교부
URLhttps://www.data.go.kr/data/15076562/fileData.do

Alerts

수출액 is highly overall correlated with 수입액High correlation
수입액 is highly overall correlated with 수출액High correlation
공관현황 has 34 (17.3%) missing valuesMissing
투자현황 has 55 (27.9%) missing valuesMissing
교민현황 has 14 (7.1%) missing valuesMissing
공적개발원조(ODA)현황 has 129 (65.5%) missing valuesMissing
수출액 has 3 (1.5%) missing valuesMissing
수입액 has 4 (2.0%) missing valuesMissing
한글 국가명 has unique valuesUnique
영문 국가명 has unique valuesUnique

Reproduction

Analysis started2024-04-17 17:35:29.791346
Analysis finished2024-04-17 17:35:31.008626
Duration1.22 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

한글 국가명
Text

UNIQUE 

Distinct197
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-04-18T02:35:31.223126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.964467
Min length2

Characters and Unicode

Total characters781
Distinct characters180
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

Unique197 ?
Unique (%)100.0%

Sample

1st row가나
2nd row가봉
3rd row가이아나
4th row감비아
5th row과테말라
ValueCountFrequency (%)
가나 1
 
0.5%
슬로베니아 1
 
0.5%
오스트리아 1
 
0.5%
온두라스 1
 
0.5%
요르단 1
 
0.5%
우간다 1
 
0.5%
우루과이 1
 
0.5%
우즈베키스탄 1
 
0.5%
우크라이나 1
 
0.5%
이라크 1
 
0.5%
Other values (187) 187
94.9%
2024-04-18T02:35:31.578471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 55
 
7.0%
리 31
 
4.0%
스 28
 
3.6%
니 24
 
3.1%
르 24
 
3.1%
이 23
 
2.9%
라 20
 
2.6%
바 16
 
2.0%
나 16
 
2.0%
도 14
 
1.8%
Other values (170) 530
67.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 781
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 55
 
7.0%
리 31
 
4.0%
스 28
 
3.6%
니 24
 
3.1%
르 24
 
3.1%
이 23
 
2.9%
라 20
 
2.6%
바 16
 
2.0%
나 16
 
2.0%
도 14
 
1.8%
Other values (170) 530
67.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 781
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 55
 
7.0%
리 31
 
4.0%
스 28
 
3.6%
니 24
 
3.1%
르 24
 
3.1%
이 23
 
2.9%
라 20
 
2.6%
바 16
 
2.0%
나 16
 
2.0%
도 14
 
1.8%
Other values (170) 530
67.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 781
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 55
 
7.0%
리 31
 
4.0%
스 28
 
3.6%
니 24
 
3.1%
르 24
 
3.1%
이 23
 
2.9%
라 20
 
2.6%
바 16
 
2.0%
나 16
 
2.0%
도 14
 
1.8%
Other values (170) 530
67.9%

영문 국가명
Text

UNIQUE 

Distinct197
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-04-18T02:35:31.814174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length26
Mean length8.5380711
Min length3

Characters and Unicode

Total characters1682
Distinct characters59
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique197 ?
Unique (%)100.0%

Sample

1st rowGhana
2nd rowGabon
3rd rowGuyana
4th rowGambia
5th rowGuatemala
ValueCountFrequency (%)
republic 5
 
2.0%
5
 
2.0%
of 4
 
1.6%
united 3
 
1.2%
st 3
 
1.2%
guinea 3
 
1.2%
islands 3
 
1.2%
states 2
 
0.8%
sudan 2
 
0.8%
south 2
 
0.8%
Other values (217) 219
87.3%
2024-04-18T02:35:32.151438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 249
14.8%
i 149
 
8.9%
n 125
 
7.4%
e 117
 
7.0%
o 90
 
5.4%
r 90
 
5.4%
u 66
 
3.9%
t 64
 
3.8%
l 58
 
3.4%
s 57
 
3.4%
Other values (49) 617
36.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1364
81.1%
Uppercase Letter 251
 
14.9%
Space Separator 54
 
3.2%
Other Punctuation 9
 
0.5%
Dash Punctuation 4
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 249
18.3%
i 149
10.9%
n 125
9.2%
e 117
 
8.6%
o 90
 
6.6%
r 90
 
6.6%
u 66
 
4.8%
t 64
 
4.7%
l 58
 
4.3%
s 57
 
4.2%
Other values (19) 299
21.9%
Uppercase Letter
ValueCountFrequency (%)
S 29
 
11.6%
M 20
 
8.0%
C 20
 
8.0%
B 19
 
7.6%
A 17
 
6.8%
G 15
 
6.0%
T 15
 
6.0%
N 14
 
5.6%
L 13
 
5.2%
P 12
 
4.8%
Other values (14) 77
30.7%
Other Punctuation
ValueCountFrequency (%)
& 3
33.3%
. 3
33.3%
: 2
22.2%
' 1
 
11.1%
Space Separator
ValueCountFrequency (%)
54
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1615
96.0%
Common 67
 
4.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 249
15.4%
i 149
 
9.2%
n 125
 
7.7%
e 117
 
7.2%
o 90
 
5.6%
r 90
 
5.6%
u 66
 
4.1%
t 64
 
4.0%
l 58
 
3.6%
s 57
 
3.5%
Other values (43) 550
34.1%
Common
ValueCountFrequency (%)
54
80.6%
- 4
 
6.0%
& 3
 
4.5%
. 3
 
4.5%
: 2
 
3.0%
' 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1679
99.8%
None 3
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 249
14.8%
i 149
 
8.9%
n 125
 
7.4%
e 117
 
7.0%
o 90
 
5.4%
r 90
 
5.4%
u 66
 
3.9%
t 64
 
3.8%
l 58
 
3.5%
s 57
 
3.4%
Other values (46) 614
36.6%
None
ValueCountFrequency (%)
â 1
33.3%
é 1
33.3%
ô 1
33.3%

국가코드(ISO 2자리)
Text

Distinct196
Distinct (%)100.0%
Missing1
Missing (%)0.5%
Memory size1.7 KiB
2024-04-18T02:35:32.470221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters392
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

Unique196 ?
Unique (%)100.0%

Sample

1st rowGH
2nd rowGA
3rd rowGY
4th rowGM
5th rowGT
ValueCountFrequency (%)
gh 1
 
0.5%
si 1
 
0.5%
at 1
 
0.5%
hn 1
 
0.5%
jo 1
 
0.5%
ug 1
 
0.5%
uy 1
 
0.5%
uz 1
 
0.5%
ua 1
 
0.5%
iq 1
 
0.5%
Other values (186) 186
94.9%
2024-04-18T02:35:32.867549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
M 30
 
7.7%
S 27
 
6.9%
T 24
 
6.1%
G 23
 
5.9%
A 22
 
5.6%
C 21
 
5.4%
B 21
 
5.4%
N 19
 
4.8%
E 19
 
4.8%
L 19
 
4.8%
Other values (16) 167
42.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 392
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M 30
 
7.7%
S 27
 
6.9%
T 24
 
6.1%
G 23
 
5.9%
A 22
 
5.6%
C 21
 
5.4%
B 21
 
5.4%
N 19
 
4.8%
E 19
 
4.8%
L 19
 
4.8%
Other values (16) 167
42.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 392
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
M 30
 
7.7%
S 27
 
6.9%
T 24
 
6.1%
G 23
 
5.9%
A 22
 
5.6%
C 21
 
5.4%
B 21
 
5.4%
N 19
 
4.8%
E 19
 
4.8%
L 19
 
4.8%
Other values (16) 167
42.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 392
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
M 30
 
7.7%
S 27
 
6.9%
T 24
 
6.1%
G 23
 
5.9%
A 22
 
5.6%
C 21
 
5.4%
B 21
 
5.4%
N 19
 
4.8%
E 19
 
4.8%
L 19
 
4.8%
Other values (16) 167
42.6%

외교관계
Text

Distinct195
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-04-18T02:35:33.107799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length217
Median length167
Mean length34.086294
Min length8

Characters and Unicode

Total characters6715
Distinct characters303
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique193 ?
Unique (%)98.0%

Sample

1st row1977.11.14. 수교
2nd row1962.10.01. 수교
3rd row1968.06.13. 수교일자1966.05.26. 독립과 동시에 우리나라 승인1986.09.30. 최광수-Jackson 양국 외교장관 회담2018.03.19. 이낙연 총리-Granger 대통령 회담
4th row1965.04.21. 수교
5th row1962.10.24. 수교
ValueCountFrequency (%)
수교 73
 
7.6%
외교관계 53
 
5.5%
수립 39
 
4.1%
수교일자 33
 
3.4%
대사관 18
 
1.9%
개설 17
 
1.8%
주한 11
 
1.1%
상주대사관 11
 
1.1%
대사 8
 
0.8%
대사급 7
 
0.7%
Other values (604) 692
71.9%
2024-04-18T02:35:33.453701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 897
 
13.4%
769
 
11.5%
1 584
 
8.7%
0 461
 
6.9%
9 423
 
6.3%
2 295
 
4.4%
교 219
 
3.3%
수 216
 
3.2%
6 150
 
2.2%
관 146
 
2.2%
Other values (293) 2555
38.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2475
36.9%
Other Letter 2319
34.5%
Other Punctuation 930
 
13.8%
Space Separator 769
 
11.5%
Lowercase Letter 94
 
1.4%
Close Punctuation 40
 
0.6%
Open Punctuation 40
 
0.6%
Uppercase Letter 24
 
0.4%
Dash Punctuation 15
 
0.2%
Final Punctuation 4
 
0.1%
Other values (2) 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 219
 
9.4%
수 216
 
9.3%
관 146
 
6.3%
대 110
 
4.7%
사 101
 
4.4%
주 88
 
3.8%
립 65
 
2.8%
계 63
 
2.7%
외 57
 
2.5%
설 56
 
2.4%
Other values (233) 1198
51.7%
Lowercase Letter
ValueCountFrequency (%)
r 15
16.0%
a 13
13.8%
i 11
11.7%
n 9
9.6%
e 9
9.6%
y 5
 
5.3%
t 5
 
5.3%
k 4
 
4.3%
u 3
 
3.2%
o 3
 
3.2%
Other values (10) 17
18.1%
Uppercase Letter
ValueCountFrequency (%)
R 3
12.5%
B 3
12.5%
P 3
12.5%
S 2
8.3%
K 2
8.3%
A 2
8.3%
J 2
8.3%
C 1
 
4.2%
G 1
 
4.2%
T 1
 
4.2%
Other values (4) 4
16.7%
Decimal Number
ValueCountFrequency (%)
1 584
23.6%
0 461
18.6%
9 423
17.1%
2 295
11.9%
6 150
 
6.1%
8 126
 
5.1%
7 125
 
5.1%
3 121
 
4.9%
5 107
 
4.3%
4 83
 
3.4%
Other Punctuation
ValueCountFrequency (%)
. 897
96.5%
' 12
 
1.3%
, 10
 
1.1%
· 4
 
0.4%
: 3
 
0.3%
※ 3
 
0.3%
* 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 39
97.5%
」 1
 
2.5%
Open Punctuation
ValueCountFrequency (%)
( 39
97.5%
「 1
 
2.5%
Space Separator
ValueCountFrequency (%)
769
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 4
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4278
63.7%
Hangul 2319
34.5%
Latin 118
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 219
 
9.4%
수 216
 
9.3%
관 146
 
6.3%
대 110
 
4.7%
사 101
 
4.4%
주 88
 
3.8%
립 65
 
2.8%
계 63
 
2.7%
외 57
 
2.5%
설 56
 
2.4%
Other values (233) 1198
51.7%
Latin
ValueCountFrequency (%)
r 15
 
12.7%
a 13
 
11.0%
i 11
 
9.3%
n 9
 
7.6%
e 9
 
7.6%
y 5
 
4.2%
t 5
 
4.2%
k 4
 
3.4%
u 3
 
2.5%
R 3
 
2.5%
Other values (24) 41
34.7%
Common
ValueCountFrequency (%)
. 897
21.0%
769
18.0%
1 584
13.7%
0 461
10.8%
9 423
9.9%
2 295
 
6.9%
6 150
 
3.5%
8 126
 
2.9%
7 125
 
2.9%
3 121
 
2.8%
Other values (16) 327
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4378
65.2%
Hangul 2319
34.5%
Punctuation 11
 
0.2%
None 7
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 897
20.5%
769
17.6%
1 584
13.3%
0 461
10.5%
9 423
9.7%
2 295
 
6.7%
6 150
 
3.4%
8 126
 
2.9%
7 125
 
2.9%
3 121
 
2.8%
Other values (43) 427
9.8%
Hangul
ValueCountFrequency (%)
교 219
 
9.4%
수 216
 
9.3%
관 146
 
6.3%
대 110
 
4.7%
사 101
 
4.4%
주 88
 
3.8%
립 65
 
2.8%
계 63
 
2.7%
외 57
 
2.5%
설 56
 
2.4%
Other values (233) 1198
51.7%
None
ValueCountFrequency (%)
· 4
57.1%
」 1
 
14.3%
「 1
 
14.3%
š 1
 
14.3%
Punctuation
ValueCountFrequency (%)
’ 4
36.4%
‘ 4
36.4%
※ 3
27.3%

공관현황
Text

MISSING 

Distinct163
Distinct (%)100.0%
Missing34
Missing (%)17.3%
Memory size1.7 KiB
2024-04-18T02:35:33.616355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length218
Median length115
Mean length85.453988
Min length12

Characters and Unicode

Total characters13929
Distinct characters450
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique163 ?
Unique (%)100.0%

Sample

1st row아국 : 상주공관('78.5.4)※ 임정택 대사('20.12.1 . 신임장 제정, '21.11. 부임)상대국 : 상주공관('99.11.8)※ 카리스 오베체비-램프티 즈웨네스(Charis Obetsebi-Lamptey Zwennes) ('21.5.27 아그레망 부여, 7.21 부임)
2nd row* 아국 : '73.5. 설치, 신송범 대사('23.1월 부임)* 상대국 : '75.6. 설치, 카를로스 빅터 붕구(Carlos Victor Boungou) 대사('11.11.25. 신임장 제정, 현재 주한외교단장 겸 주한아프리카외교단장)
3rd row* 아국 : 주세네갈(대) 겸임 - 주감비아명예영사 : Muhammed Jah('16.1 임명)* 상대국 : 주중국감비아(대) 겸임
4th row- 1974.09 주과테말라 상주대사관 개설- 1977.10 주한 과테말라 대사관 개설- 2023.01 천준호 대사 부임
5th row- 1999.02. 주트리니다드토바고 대사관 폐쇄로 주베네수엘라 대사관 관할 편입- 2007.10. 주트리니다드토바고 대사관 겸임
ValueCountFrequency (%)
408
 
15.7%
부임 117
 
4.5%
대사 103
 
4.0%
개설 81
 
3.1%
겸임 57
 
2.2%
대사관 50
 
1.9%
주한 49
 
1.9%
※ 25
 
1.0%
우리측 25
 
1.0%
설치 22
 
0.8%
Other values (1217) 1654
63.8%
2024-04-18T02:35:33.891895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2522
 
18.1%
. 573
 
4.1%
대 542
 
3.9%
사 492
 
3.5%
2 476
 
3.4%
1 438
 
3.1%
주 397
 
2.9%
0 383
 
2.7%
임 289
 
2.1%
( 284
 
2.0%
Other values (440) 7533
54.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5938
42.6%
Space Separator 2522
18.1%
Decimal Number 2018
 
14.5%
Lowercase Letter 1198
 
8.6%
Other Punctuation 1064
 
7.6%
Uppercase Letter 291
 
2.1%
Open Punctuation 284
 
2.0%
Close Punctuation 282
 
2.0%
Dash Punctuation 266
 
1.9%
Initial Punctuation 28
 
0.2%
Other values (4) 38
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 542
 
9.1%
사 492
 
8.3%
주 397
 
6.7%
임 289
 
4.9%
관 270
 
4.5%
부 157
 
2.6%
한 154
 
2.6%
설 146
 
2.5%
아 124
 
2.1%
국 123
 
2.1%
Other values (351) 3244
54.6%
Lowercase Letter
ValueCountFrequency (%)
a 164
13.7%
e 119
 
9.9%
i 111
 
9.3%
o 96
 
8.0%
r 93
 
7.8%
n 92
 
7.7%
s 69
 
5.8%
l 52
 
4.3%
t 51
 
4.3%
u 45
 
3.8%
Other values (25) 306
25.5%
Uppercase Letter
ValueCountFrequency (%)
A 33
 
11.3%
M 25
 
8.6%
S 20
 
6.9%
D 18
 
6.2%
E 15
 
5.2%
C 15
 
5.2%
B 15
 
5.2%
P 14
 
4.8%
I 13
 
4.5%
T 13
 
4.5%
Other values (15) 110
37.8%
Decimal Number
ValueCountFrequency (%)
2 476
23.6%
1 438
21.7%
0 383
19.0%
9 218
10.8%
3 116
 
5.7%
7 107
 
5.3%
8 101
 
5.0%
6 81
 
4.0%
5 56
 
2.8%
4 42
 
2.1%
Other Punctuation
ValueCountFrequency (%)
. 573
53.9%
: 209
 
19.6%
' 90
 
8.5%
※ 62
 
5.8%
* 61
 
5.7%
, 47
 
4.4%
/ 20
 
1.9%
· 1
 
0.1%
& 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 13
92.9%
∼ 1
 
7.1%
Space Separator
ValueCountFrequency (%)
2522
100.0%
Open Punctuation
ValueCountFrequency (%)
( 284
100.0%
Close Punctuation
ValueCountFrequency (%)
) 282
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 266
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 28
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 18
100.0%
Control
ValueCountFrequency (%)
4
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6500
46.7%
Hangul 5934
42.6%
Latin 1489
 
10.7%
Han 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 542
 
9.1%
사 492
 
8.3%
주 397
 
6.7%
임 289
 
4.9%
관 270
 
4.6%
부 157
 
2.6%
한 154
 
2.6%
설 146
 
2.5%
아 124
 
2.1%
국 123
 
2.1%
Other values (348) 3240
54.6%
Latin
ValueCountFrequency (%)
a 164
 
11.0%
e 119
 
8.0%
i 111
 
7.5%
o 96
 
6.4%
r 93
 
6.2%
n 92
 
6.2%
s 69
 
4.6%
l 52
 
3.5%
t 51
 
3.4%
u 45
 
3.0%
Other values (50) 597
40.1%
Common
ValueCountFrequency (%)
2522
38.8%
. 573
 
8.8%
2 476
 
7.3%
1 438
 
6.7%
0 383
 
5.9%
( 284
 
4.4%
) 282
 
4.3%
- 266
 
4.1%
9 218
 
3.4%
: 209
 
3.2%
Other values (18) 849
 
13.1%
Han
ValueCountFrequency (%)
現 3
50.0%
前 1
 
16.7%
日 1
 
16.7%
駐 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7862
56.4%
Hangul 5932
42.6%
Punctuation 108
 
0.8%
None 20
 
0.1%
CJK 6
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2522
32.1%
. 573
 
7.3%
2 476
 
6.1%
1 438
 
5.6%
0 383
 
4.9%
( 284
 
3.6%
) 282
 
3.6%
- 266
 
3.4%
9 218
 
2.8%
: 209
 
2.7%
Other values (61) 2211
28.1%
Hangul
ValueCountFrequency (%)
대 542
 
9.1%
사 492
 
8.3%
주 397
 
6.7%
임 289
 
4.9%
관 270
 
4.6%
부 157
 
2.6%
한 154
 
2.6%
설 146
 
2.5%
아 124
 
2.1%
국 123
 
2.1%
Other values (347) 3238
54.6%
Punctuation
ValueCountFrequency (%)
※ 62
57.4%
‘ 28
25.9%
’ 18
 
16.7%
None
ValueCountFrequency (%)
á 4
20.0%
č 3
15.0%
㈜ 2
10.0%
š 1
 
5.0%
· 1
 
5.0%
ü 1
 
5.0%
Š 1
 
5.0%
ã 1
 
5.0%
ð 1
 
5.0%
í 1
 
5.0%
Other values (4) 4
20.0%
CJK
ValueCountFrequency (%)
現 3
50.0%
前 1
 
16.7%
日 1
 
16.7%
駐 1
 
16.7%
Math Operators
ValueCountFrequency (%)
∼ 1
100.0%

투자현황
Text

MISSING 

Distinct141
Distinct (%)99.3%
Missing55
Missing (%)27.9%
Memory size1.7 KiB
2024-04-18T02:35:34.054741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length184
Median length83
Mean length56.549296
Min length2

Characters and Unicode

Total characters8030
Distinct characters280
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique140 ?
Unique (%)98.6%

Sample

1st row45건, 1.37억달러('21월말 누계, 수출입은행)
2nd row2건, 9백만 불('21 누계, 수출입은행)
3rd row약 150개 업체 진출(주로 섬유, 봉제업)
4th row* (한국수출입은행) - 對한 투자 : 11백만불(9건, '22년 누계) - 對그리스 투자 : 13백만불(20건, '22년 누계)
5th row11건, 170만불('21 누계, 수출입은행)
ValueCountFrequency (%)
354
23.7%
누계 93
 
6.2%
수출입은행 37
 
2.5%
투자 32
 
2.1%
신고기준 31
 
2.1%
기준 29
 
1.9%
한국 21
 
1.4%
대 21
 
1.4%
對한 20
 
1.3%
등 19
 
1.3%
Other values (585) 838
56.1%
2024-04-18T02:35:34.560807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1422
 
17.7%
2 471
 
5.9%
, 285
 
3.5%
) 268
 
3.3%
( 268
 
3.3%
1 242
 
3.0%
불 195
 
2.4%
0 193
 
2.4%
- 187
 
2.3%
: 186
 
2.3%
Other values (270) 4313
53.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3326
41.4%
Decimal Number 1505
18.7%
Space Separator 1422
17.7%
Other Punctuation 802
 
10.0%
Close Punctuation 268
 
3.3%
Open Punctuation 268
 
3.3%
Dash Punctuation 187
 
2.3%
Math Symbol 77
 
1.0%
Uppercase Letter 71
 
0.9%
Lowercase Letter 62
 
0.8%
Other values (4) 42
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
불 195
 
5.9%
자 165
 
5.0%
누 132
 
4.0%
계 125
 
3.8%
한 119
 
3.6%
억 110
 
3.3%
기 109
 
3.3%
만 107
 
3.2%
건 106
 
3.2%
투 102
 
3.1%
Other values (206) 2056
61.8%
Uppercase Letter
ValueCountFrequency (%)
L 14
19.7%
G 14
19.7%
S 7
9.9%
K 4
 
5.6%
I 4
 
5.6%
D 4
 
5.6%
A 3
 
4.2%
C 3
 
4.2%
N 3
 
4.2%
B 2
 
2.8%
Other values (10) 13
18.3%
Lowercase Letter
ValueCountFrequency (%)
o 10
16.1%
e 9
14.5%
t 9
14.5%
r 8
12.9%
l 4
 
6.5%
s 4
 
6.5%
i 4
 
6.5%
k 3
 
4.8%
a 3
 
4.8%
n 2
 
3.2%
Other values (5) 6
9.7%
Decimal Number
ValueCountFrequency (%)
2 471
31.3%
1 242
16.1%
0 193
12.8%
3 102
 
6.8%
4 100
 
6.6%
6 96
 
6.4%
8 85
 
5.6%
9 79
 
5.2%
5 79
 
5.2%
7 58
 
3.9%
Other Punctuation
ValueCountFrequency (%)
, 285
35.5%
: 186
23.2%
. 184
22.9%
' 69
 
8.6%
* 50
 
6.2%
/ 20
 
2.5%
※ 8
 
1.0%
Math Symbol
ValueCountFrequency (%)
~ 45
58.4%
→ 16
 
20.8%
> 14
 
18.2%
⟶ 2
 
2.6%
Space Separator
ValueCountFrequency (%)
1422
100.0%
Close Punctuation
ValueCountFrequency (%)
) 268
100.0%
Open Punctuation
ValueCountFrequency (%)
( 268
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 187
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 20
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 13
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 6
100.0%
Format
ValueCountFrequency (%)
​ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4571
56.9%
Hangul 3223
40.1%
Latin 133
 
1.7%
Han 103
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
불 195
 
6.1%
자 165
 
5.1%
누 132
 
4.1%
계 125
 
3.9%
한 119
 
3.7%
억 110
 
3.4%
기 109
 
3.4%
만 107
 
3.3%
건 106
 
3.3%
투 102
 
3.2%
Other values (204) 1953
60.6%
Latin
ValueCountFrequency (%)
L 14
 
10.5%
G 14
 
10.5%
o 10
 
7.5%
e 9
 
6.8%
t 9
 
6.8%
r 8
 
6.0%
S 7
 
5.3%
K 4
 
3.0%
I 4
 
3.0%
l 4
 
3.0%
Other values (25) 50
37.6%
Common
ValueCountFrequency (%)
1422
31.1%
2 471
 
10.3%
, 285
 
6.2%
) 268
 
5.9%
( 268
 
5.9%
1 242
 
5.3%
0 193
 
4.2%
- 187
 
4.1%
: 186
 
4.1%
. 184
 
4.0%
Other values (19) 865
18.9%
Han
ValueCountFrequency (%)
對 100
97.1%
韓 3
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4649
57.9%
Hangul 3223
40.1%
CJK 103
 
1.3%
Punctuation 37
 
0.5%
Arrows 16
 
0.2%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1422
30.6%
2 471
 
10.1%
, 285
 
6.1%
) 268
 
5.8%
( 268
 
5.8%
1 242
 
5.2%
0 193
 
4.2%
- 187
 
4.0%
: 186
 
4.0%
. 184
 
4.0%
Other values (48) 943
20.3%
Hangul
ValueCountFrequency (%)
불 195
 
6.1%
자 165
 
5.1%
누 132
 
4.1%
계 125
 
3.9%
한 119
 
3.7%
억 110
 
3.4%
기 109
 
3.4%
만 107
 
3.3%
건 106
 
3.3%
투 102
 
3.2%
Other values (204) 1953
60.6%
CJK
ValueCountFrequency (%)
對 100
97.1%
韓 3
 
2.9%
Punctuation
ValueCountFrequency (%)
‘ 20
54.1%
※ 8
 
21.6%
’ 6
 
16.2%
​ 3
 
8.1%
Arrows
ValueCountFrequency (%)
→ 16
100.0%
None
ValueCountFrequency (%)
⟶ 2
100.0%

교민현황
Text

MISSING 

Distinct182
Distinct (%)99.5%
Missing14
Missing (%)7.1%
Memory size1.7 KiB
2024-04-18T02:35:34.732004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length126
Median length68
Mean length22.57377
Min length2

Characters and Unicode

Total characters4131
Distinct characters208
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique181 ?
Unique (%)98.9%

Sample

1st row약 436명('22.2월)
2nd row약 61여명(‘22)
3rd row한인 체류자수(2023)：4명
4th row39 명('21)
5th row약 5,629명
ValueCountFrequency (%)
95
 
13.5%
약 39
 
5.5%
내 23
 
3.3%
외교부 16
 
2.3%
2023 13
 
1.8%
한국인 13
 
1.8%
한국 11
 
1.6%
기준 9
 
1.3%
2021 8
 
1.1%
※외교부 6
 
0.9%
Other values (411) 470
66.9%
2024-04-18T02:35:35.039127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
532
 
12.9%
2 486
 
11.8%
0 238
 
5.8%
명 232
 
5.6%
1 222
 
5.4%
( 217
 
5.3%
) 216
 
5.2%
, 126
 
3.1%
3 119
 
2.9%
5 74
 
1.8%
Other values (198) 1669
40.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1419
34.4%
Other Letter 1309
31.7%
Space Separator 532
 
12.9%
Other Punctuation 354
 
8.6%
Open Punctuation 217
 
5.3%
Close Punctuation 216
 
5.2%
Dash Punctuation 60
 
1.5%
Uppercase Letter 8
 
0.2%
Initial Punctuation 7
 
0.2%
Final Punctuation 6
 
0.1%
Other values (3) 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
명 232
 
17.7%
외 57
 
4.4%
국 52
 
4.0%
인 48
 
3.7%
약 46
 
3.5%
부 38
 
2.9%
교 36
 
2.8%
월 34
 
2.6%
재 34
 
2.6%
포 29
 
2.2%
Other values (164) 703
53.7%
Decimal Number
ValueCountFrequency (%)
2 486
34.2%
0 238
16.8%
1 222
15.6%
3 119
 
8.4%
5 74
 
5.2%
4 71
 
5.0%
6 65
 
4.6%
8 52
 
3.7%
7 48
 
3.4%
9 44
 
3.1%
Other Punctuation
ValueCountFrequency (%)
, 126
35.6%
. 69
19.5%
: 67
18.9%
' 65
18.4%
※ 13
 
3.7%
* 9
 
2.5%
· 2
 
0.6%
% 2
 
0.6%
： 1
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
L 2
25.0%
I 2
25.0%
U 1
12.5%
F 1
12.5%
N 1
12.5%
G 1
12.5%
Space Separator
ValueCountFrequency (%)
532
100.0%
Open Punctuation
ValueCountFrequency (%)
( 217
100.0%
Close Punctuation
ValueCountFrequency (%)
) 216
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 60
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 7
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 6
100.0%
Format
ValueCountFrequency (%)
​ 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2814
68.1%
Hangul 1308
31.7%
Latin 8
 
0.2%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
명 232
 
17.7%
외 57
 
4.4%
국 52
 
4.0%
인 48
 
3.7%
약 46
 
3.5%
부 38
 
2.9%
교 36
 
2.8%
월 34
 
2.6%
재 34
 
2.6%
포 29
 
2.2%
Other values (163) 702
53.7%
Common
ValueCountFrequency (%)
532
18.9%
2 486
17.3%
0 238
8.5%
1 222
7.9%
( 217
7.7%
) 216
7.7%
, 126
 
4.5%
3 119
 
4.2%
5 74
 
2.6%
4 71
 
2.5%
Other values (18) 513
18.2%
Latin
ValueCountFrequency (%)
L 2
25.0%
I 2
25.0%
U 1
12.5%
F 1
12.5%
N 1
12.5%
G 1
12.5%
Han
ValueCountFrequency (%)
內 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2792
67.6%
Hangul 1308
31.7%
Punctuation 27
 
0.7%
None 3
 
0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
532
19.1%
2 486
17.4%
0 238
8.5%
1 222
8.0%
( 217
7.8%
) 216
7.7%
, 126
 
4.5%
3 119
 
4.3%
5 74
 
2.7%
4 71
 
2.5%
Other values (18) 491
17.6%
Hangul
ValueCountFrequency (%)
명 232
 
17.7%
외 57
 
4.4%
국 52
 
4.0%
인 48
 
3.7%
약 46
 
3.5%
부 38
 
2.9%
교 36
 
2.8%
월 34
 
2.6%
재 34
 
2.6%
포 29
 
2.2%
Other values (163) 702
53.7%
Punctuation
ValueCountFrequency (%)
※ 13
48.1%
‘ 7
25.9%
’ 6
22.2%
​ 1
 
3.7%
None
ValueCountFrequency (%)
· 2
66.7%
： 1
33.3%
CJK
ValueCountFrequency (%)
內 1
100.0%

공적개발원조(ODA)현황
Text

MISSING 

Distinct68
Distinct (%)100.0%
Missing129
Missing (%)65.5%
Memory size1.7 KiB
2024-04-18T02:35:35.254342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length332
Median length50.5
Mean length39.014706
Min length13

Characters and Unicode

Total characters2653
Distinct characters201
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)100.0%

Sample

1st row 2.75억달러('87-'20, OECD)(무상) 1.24억달러 / (유상) 1.85억달러
2nd row423만 불(2010-2021)
3rd row584만불('94-'21)
4th row697만불('87~19)
5th row196만불('87-'19)
ValueCountFrequency (%)
58
 
13.4%
누계 12
 
2.8%
oecd 11
 
2.5%
※외교부 10
 
2.3%
누적액 10
 
2.3%
원조현황 10
 
2.3%
지원 9
 
2.1%
무상원조 8
 
1.8%
dac 6
 
1.4%
무상 5
 
1.2%
Other values (250) 295
68.0%
2024-04-18T02:35:35.586676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
392
 
14.8%
2 167
 
6.3%
1 161
 
6.1%
0 116
 
4.4%
- 101
 
3.8%
불 83
 
3.1%
만 79
 
3.0%
. 77
 
2.9%
9 75
 
2.8%
' 74
 
2.8%
Other values (191) 1328
50.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 851
32.1%
Decimal Number 783
29.5%
Space Separator 392
14.8%
Other Punctuation 247
 
9.3%
Uppercase Letter 109
 
4.1%
Dash Punctuation 101
 
3.8%
Open Punctuation 73
 
2.8%
Close Punctuation 73
 
2.8%
Currency Symbol 8
 
0.3%
Math Symbol 6
 
0.2%
Other values (4) 10
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
불 83
 
9.8%
만 79
 
9.3%
원 49
 
5.8%
지 36
 
4.2%
조 24
 
2.8%
누 23
 
2.7%
상 22
 
2.6%
억 21
 
2.5%
백 19
 
2.2%
무 18
 
2.1%
Other values (147) 477
56.1%
Uppercase Letter
ValueCountFrequency (%)
D 25
22.9%
C 22
20.2%
E 16
14.7%
O 16
14.7%
A 10
 
9.2%
P 4
 
3.7%
R 4
 
3.7%
F 4
 
3.7%
T 3
 
2.8%
W 2
 
1.8%
Other values (3) 3
 
2.8%
Decimal Number
ValueCountFrequency (%)
2 167
21.3%
1 161
20.6%
0 116
14.8%
9 75
9.6%
8 68
8.7%
7 59
 
7.5%
6 37
 
4.7%
4 35
 
4.5%
5 33
 
4.2%
3 32
 
4.1%
Other Punctuation
ValueCountFrequency (%)
. 77
31.2%
' 74
30.0%
, 50
20.2%
: 22
 
8.9%
※ 11
 
4.5%
/ 7
 
2.8%
* 3
 
1.2%
· 3
 
1.2%
Lowercase Letter
ValueCountFrequency (%)
e 1
25.0%
r 1
25.0%
o 1
25.0%
a 1
25.0%
Space Separator
ValueCountFrequency (%)
392
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 101
100.0%
Open Punctuation
ValueCountFrequency (%)
( 73
100.0%
Close Punctuation
ValueCountFrequency (%)
) 73
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 8
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 3
100.0%
Format
ValueCountFrequency (%)
​ 2
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1689
63.7%
Hangul 850
32.0%
Latin 113
 
4.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
불 83
 
9.8%
만 79
 
9.3%
원 49
 
5.8%
지 36
 
4.2%
조 24
 
2.8%
누 23
 
2.7%
상 22
 
2.6%
억 21
 
2.5%
백 19
 
2.2%
무 18
 
2.1%
Other values (146) 476
56.0%
Common
ValueCountFrequency (%)
392
23.2%
2 167
9.9%
1 161
9.5%
0 116
 
6.9%
- 101
 
6.0%
. 77
 
4.6%
9 75
 
4.4%
' 74
 
4.4%
( 73
 
4.3%
) 73
 
4.3%
Other values (17) 380
22.5%
Latin
ValueCountFrequency (%)
D 25
22.1%
C 22
19.5%
E 16
14.2%
O 16
14.2%
A 10
 
8.8%
P 4
 
3.5%
R 4
 
3.5%
F 4
 
3.5%
T 3
 
2.7%
W 2
 
1.8%
Other values (7) 7
 
6.2%
Han
ValueCountFrequency (%)
州 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1782
67.2%
Hangul 850
32.0%
Punctuation 17
 
0.6%
None 3
 
0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
392
22.0%
2 167
 
9.4%
1 161
 
9.0%
0 116
 
6.5%
- 101
 
5.7%
. 77
 
4.3%
9 75
 
4.2%
' 74
 
4.2%
( 73
 
4.1%
) 73
 
4.1%
Other values (29) 473
26.5%
Hangul
ValueCountFrequency (%)
불 83
 
9.8%
만 79
 
9.3%
원 49
 
5.8%
지 36
 
4.2%
조 24
 
2.8%
누 23
 
2.7%
상 22
 
2.6%
억 21
 
2.5%
백 19
 
2.2%
무 18
 
2.1%
Other values (146) 476
56.0%
Punctuation
ValueCountFrequency (%)
※ 11
64.7%
‘ 3
 
17.6%
​ 2
 
11.8%
’ 1
 
5.9%
None
ValueCountFrequency (%)
· 3
100.0%
CJK
ValueCountFrequency (%)
州 1
100.0%

수출액
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct181
Distinct (%)93.3%
Missing3
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean8.2992684 × 109
Minimum3000
Maximum4.597 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-18T02:35:35.696807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000
5-th percentile1262821.8
Q113827500
median1.37 × 108
Q39.89 × 108
95-th percentile1.6706 × 1010
Maximum4.597 × 1011
Range4.597 × 1011
Interquartile range (IQR)9.751725 × 108

Descriptive statistics

Standard deviation4.8311746 × 1010
Coefficient of variation (CV)5.8212054
Kurtosis77.497217
Mean8.2992684 × 109
Median Absolute Deviation (MAD)1.333 × 108
Skewness8.5981625
Sum1.6100581 × 1012
Variance2.3340248 × 1021
MonotonicityNot monotonic
2024-04-18T02:35:35.800943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
140000000 3
 
1.5%
350000000 2
 
1.0%
18760000000 2
 
1.0%
230000000 2
 
1.0%
10000000 2
 
1.0%
45000000 2
 
1.0%
210000000 2
 
1.0%
183000000 2
 
1.0%
3200000000 2
 
1.0%
90000000 2
 
1.0%
Other values (171) 173
87.8%
(Missing) 3
 
1.5%
ValueCountFrequency (%)
3000 1
0.5%
105178 1
0.5%
230000 1
0.5%
248000 1
0.5%
259000 1
0.5%
311000 1
0.5%
430000 1
0.5%
676000 1
0.5%
730000 1
0.5%
1082348 1
0.5%
ValueCountFrequency (%)
459700000000 1
0.5%
456100000000 1
0.5%
124830000000 1
0.5%
109800000000 1
0.5%
97500000000 1
0.5%
60960000000 1
0.5%
29020000000 1
0.5%
26198000000 1
0.5%
18760000000 2
1.0%
15600000000 1
0.5%

수입액
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct173
Distinct (%)89.6%
Missing4
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean1.1568159 × 1010
Minimum1000
Maximum8.006 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-18T02:35:35.902734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile85200
Q14000000
median72000000
Q31 × 109
95-th percentile2.4848 × 1010
Maximum8.006 × 1011
Range8.006 × 1011
Interquartile range (IQR)9.96 × 108

Descriptive statistics

Standard deviation7.5837646 × 1010
Coefficient of variation (CV)6.5557232
Kurtosis89.456044
Mean1.1568159 × 1010
Median Absolute Deviation (MAD)71718000
Skewness9.3210708
Sum2.2326546 × 1012
Variance5.7513485 × 1021
MonotonicityNot monotonic
2024-04-18T02:35:36.026464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000000 4
 
2.0%
1000000 4
 
2.0%
10000000 3
 
1.5%
14000000 3
 
1.5%
1030000 2
 
1.0%
4000000 2
 
1.0%
120000000 2
 
1.0%
57000000 2
 
1.0%
100000000 2
 
1.0%
7000000 2
 
1.0%
Other values (163) 167
84.8%
(Missing) 4
 
2.0%
ValueCountFrequency (%)
1000 1
0.5%
5000 1
0.5%
6000 1
0.5%
13000 1
0.5%
23000 2
1.0%
33000 1
0.5%
35198 1
0.5%
42000 1
0.5%
63000 1
0.5%
100000 1
0.5%
ValueCountFrequency (%)
800600000000 1
0.5%
664200000000 1
0.5%
142850000000 1
0.5%
104400000000 1
0.5%
81800000000 1
0.5%
47660000000 1
0.5%
44910000000 1
0.5%
41600000000 1
0.5%
28274000000 1
0.5%
26720000000 1
0.5%

Interactions

2024-04-18T02:35:30.574844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:35:30.447877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:35:30.641864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:35:30.509176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-18T02:35:36.099251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공적개발원조(ODA)현황수출액수입액
공적개발원조(ODA)현황1.000NaNNaN
수출액NaN1.0000.981
수입액NaN0.9811.000
2024-04-18T02:35:36.165818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수출액수입액
수출액1.0000.824
수입액0.8241.000

Missing values

2024-04-18T02:35:30.741139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-18T02:35:30.846716image/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.
2024-04-18T02:35:30.943280image/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

한글 국가명영문 국가명국가코드(ISO 2자리)외교관계공관현황투자현황교민현황공적개발원조(ODA)현황수출액수입액
0가나GhanaGH1977.11.14. 수교아국 : 상주공관('78.5.4)※ 임정택 대사('20.12.1 . 신임장 제정, '21.11. 부임)상대국 : 상주공관('99.11.8)※ 카리스 오베체비-램프티 즈웨네스(Charis Obetsebi-Lamptey Zwennes) ('21.5.27 아그레망 부여, 7.21 부임)45건, 1.37억달러('21월말 누계, 수출입은행)약 436명('22.2월)2.75억달러('87-'20, OECD)(무상) 1.24억달러 / (유상) 1.85억달러27400000033000000
1가봉GabonGA1962.10.01. 수교* 아국 : '73.5. 설치, 신송범 대사('23.1월 부임)* 상대국 : '75.6. 설치, 카를로스 빅터 붕구(Carlos Victor Boungou) 대사('11.11.25. 신임장 제정, 현재 주한외교단장 겸 주한아프리카외교단장)2건, 9백만 불('21 누계, 수출입은행)약 61여명(‘22)423만 불(2010-2021)8000000602000000
2가이아나GuyanaGY1968.06.13. 수교일자1966.05.26. 독립과 동시에 우리나라 승인1986.09.30. 최광수-Jackson 양국 외교장관 회담2018.03.19. 이낙연 총리-Granger 대통령 회담<NA><NA>한인 체류자수(2023)：4명<NA>130000001150000
3감비아GambiaGM1965.04.21. 수교* 아국 : 주세네갈(대) 겸임 - 주감비아명예영사 : Muhammed Jah('16.1 임명)* 상대국 : 주중국감비아(대) 겸임<NA>39 명('21)584만불('94-'21)40000005000000
4과테말라GuatemalaGT1962.10.24. 수교- 1974.09 주과테말라 상주대사관 개설- 1977.10 주한 과테말라 대사관 개설- 2023.01 천준호 대사 부임약 150개 업체 진출(주로 섬유, 봉제업)약 5,629명<NA>323000000131000000
5교황청VaticanVA1947.08. 교황사절 Patrick Byrne 신부 한국 파견(동 신부는 한국전쟁중 납북되어 순교되었고, 주교로 추서)1963.12. 외교관계 수립(공사급)1966.09. 대사급 외교관계 격상<NA><NA><NA><NA><NA><NA>
6그레나다GrenadaGD1974.08.01. 수교1979.03. 관계 동결(좌익 쿠데타 성공후 인민혁명정부 수립)1984.05. 관계 정상화- 1999.02. 주트리니다드토바고 대사관 폐쇄로 주베네수엘라 대사관 관할 편입- 2007.10. 주트리니다드토바고 대사관 겸임<NA>73명(2022.12월)<NA>277000023000
7그리스GreeceGR1961.04.05. 수교일자* 공관장 : 이정일 대사(2021.06.) - ※ 주한그리스대사 : 에카테리니 루파스(Ekaterini Loupas, 2021.11.)* (한국수출입은행) - 對한 투자 : 11백만불(9건, '22년 누계) - 對그리스 투자 : 13백만불(20건, '22년 누계)- 동포현황 : 301명 (2023)<NA>1230000000900000000
8기니GuineaGN2006.08.28. 수교아 국 : 주세네갈(대)겸임(김지준 대사)상대국 : 주일본(대)겸임※ 주기니명예영사 : Ibrahima Kassus DIOUBATE(‘08.5.12 최초임명)11건, 170만불('21 누계, 수출입은행)46명('21)697만불('87~19)3400000053000000
9기니비사우Guinea-BissauGW1983.12.22. 수교아국 : 주세네갈(대)겸임상대국 : 주중국(대)겸임2건, 50.2만불('19 누계, 수출입은행)22명('22): 기니비사우 내 한국인196만불('87-'19)20000001000000
한글 국가명영문 국가명국가코드(ISO 2자리)외교관계공관현황투자현황교민현황공적개발원조(ODA)현황수출액수입액
187팔레스타인PalestinePS없음 (유엔결의로 확인된 팔레스타인의 합법적 권리 존중)1995.11. 우리 외교관의 ‘팔’ 관료 접촉 허용1996.08. ‘팔’ 자치정부 발급여권 인정 및 동 여권상 비자발급 허용2005.06. 일반 대표부 관계 수립2014.08. 주팔레스타인 대표사무소 상주근무 개시<NA><NA>약 31명('20)- 07.12 팔레스타인 원조공여국회의(파리)시 2천만불 무상원조 서약(2008-2010)- 14.07 가자사태 관련 1백만불 인도적 지원- 14.10 가자재건 국제회의시 1,200만불 지원 공약- 16년 난민지원 95만불- 17년 난민지원 100만불- 18년 난민지원, 의료센터지원 등 140만불- 19년 교육 및 식량지원 100만불- 20년 코로나19 현물지원 등 120만불- 21년 이-팔 충돌 직후 UNRWA 100만불39960000940000
188페루PeruPE1963.04.01. 수교일자o 공관 창설 - 1971.8.1. 주페 상주대사관 개설 - 1980.2.4. 주한 상주대사관 개설o 現 대사 - 주페 : 최종욱 대사(2023.6.25. 부임, 제17대) - 주한 : Paul Fernando Duclos Parodi 대사 (2023.2.28. 부임, 제11대)* (2022, 수출입은행) - 총누계투자 : 61.96억$(신고기준) - 지상사 : LG전자, 삼성전자, 포스코대우 등 - 자원개발업체 : SK에너지, 석유공사 등약 1,230명(2023) - 의류·원단 수입 판매, 중고차 판매, 수산업 등 종사<NA>7780000002850000000
189포르투갈PortugalPT1961.04.15. 수립1975.06. 주포르투갈대사관 개설1988.08. 주한포르투갈대사관 개설주포르투갈 대사 : 조영무 대사(2022.03 부임, 19대)주한 대사 : 수자나 바스 파투(Susana Vaz Patto) 대사(2022.02 부임, 10대)對포르투갈 투자 : 84건, 4억 1,100만 불(수출입은행, ~2021. 누계, 신고기준)對한국 투자 : 30건, 5억 500만불(산업통상자원부, ~2021. 누계, 신고기준)265명(2021)<NA>744000000449000000
190폴란드PolandPL1989.11. 수립1989.11. 주폴란드 대사관 개설1990.01. 주한 대사관 개설임훈민 제14대 대사(2021.12. 부임)피오트르 오스타셰프스키(Piotr Ostaszewski) 주한 폴란드대사 (2017.09. 부임)* (2022.12월, 신고기준 누계 / 산업통상자원부, 수출입은행) - 對폴 : 61.23억불 - 對한 : 7.2억불2,635명(2021년 기준)<NA>78610000001090000000
191프랑스FranceFR1886.06.04. 외교관계 수립1949.02.15. 국교재수립2004. 21세기 포괄적 동반자관계 수립- 주프랑스대사: 최재철 대사 (’22.12. 부임, '23.1.13 신임장 제정)- 주한프랑스대사 : 필립 르포르(Philippe Lefort, '19.11월 신임장 제정)(누계, 신고기준) - 대불 : 805건, 67.54억불(1968~2021, 수출입은행) - 대한 : 1,230건, 89.86억불(1962~2021, 산업통상자원부)- 재불한인 총수 : 25,417명('21, 입양인 포함)<NA>456100000000664200000000
192피지FijiFJ1971.01.30. 수교일자- 한국측 : 상주 대사관 설치 (1980.12.)- 피지측 : 상주 대사관 설치 (2012.7.) *2020.12. 코로나19로 폐쇄(주일본대사관이 겸임)對피지 : 1.08억불 (1984.-2021. 누계신고액)약 1,189명 (2021.)- 원조현황 : 50.72만불(1989.-2021. 누적액) ※외교부17600000021000000
193핀란드FinlandFI1973.08.24. 수립1973.08.24. 주핀란드대사관 개설1978.11.01. 주한 핀란드대사관 개설주핀란드 대사 : 김정하 대사(2023.1. 부임)주한 핀란드 대사 : 페카 멧초(Pekka Metso) 대사(2020.08. 부임, 2021.02.17. 신임장 제정)* (누계, 신고 기준) - 對핀란드 투자 : 55건, 1.42억 불(수출입은행, ~2021) - 對한국 투자 : 121건, 3.5억불(산업통상자원부, ~2021)850명(2021)<NA>531000000882000000
194필리핀PhilippinesPH1949.03. 공사급 수교1954.01.19. 주마닐라 공사관 개설1958.02.01. 대사급 수교(대사관으로 승격)2015.03.17. 주세부 분관 개설- 이상화 주필리핀 대사(2023.6. 부임)- Maria Theresa B. Dizon-de Vega 주한 필리핀대사(2021.7. 부임)(신고 기준) - 대 필리핀 : 146건, 1.4억 $(한국수출입은행, 2022년) - 대 한국 : 7건, 60만 $(산업통상자원부, 2023년)필리핀 내 한국인 : 25,485명(재외동포청, 2023)한국 내 필리핀인 : 64,055명(법무부, 2023)11.2억 $(1987~2022 누계, 총지출 기준, OECD)- 무상원조 : 4.7억 $- 유상원조 : 6.5억 $90100000004640000000
195헝가리HungaryHU1989.02.01. 대사급 외교관계 수립- 홍규덕 제14대 주헝가리 대사(2023.1월 부임)- 이슈트반 세르더헤이(István Szerdahelyi)) 제8대 주한대사 (2022.9월 부임)* 투자 누계(2022년, 수출입은행/산업통상부) - 對헝: 49억불(SK온, 삼성SDI, 한국타이어 등) - 對한: 5.4억불4,544명(2021)<NA>6160000000790000000
196호주AustraliaAU1961.10.30. 수교일자<NA>* (총 누적, 신고기준) (2020.) - 對호주 투자 : 168.8억불 (누적) - 對한국 투자 : 48.6억불 (누적)158,103명 (2021) ※ 외교부<NA>1876000000044910000000