Overview

Dataset statistics

Number of variables4
Number of observations426
Missing cells1
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.9 KiB
Average record size in memory33.3 B

Variable types

Categorical2
Text2

Dataset

Description대륙별, 경제권별 포함국가 목록 데이터로서 우리나라와 무역하는 상대국을 대륙별로 분류하여 속하는 대륙권이 어느 곳인지 분류해놓은 데이터와 경제권별로 분류하여 속하는 경제권이 어느 곳인지 분류해 놓은 데이터 입니다.
Author관세청
URLhttps://www.data.go.kr/data/3040486/fileData.do

Alerts

기준연도(BASE_YY) has constant value ""Constant

Reproduction

Analysis started2024-03-14 16:49:00.648895
Analysis finished2024-03-14 16:49:01.437210
Duration0.79 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준연도(BASE_YY)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2023
426 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023
2nd row2023
3rd row2023
4th row2023
5th row2023

Common Values

ValueCountFrequency (%)
2023 426
100.0%

Length

2024-03-15T01:49:01.642371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T01:49:01.952922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023 426
100.0%

국가부호(CNTY_CD)
Text

Distinct258
Distinct (%)60.7%
Missing1
Missing (%)0.2%
Memory size3.5 KiB
2024-03-15T01:49:03.671720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters850
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

Unique174 ?
Unique (%)40.9%

Sample

1st rowAF
2nd rowAM
3rd rowAZ
4th rowBD
5th rowBN
ValueCountFrequency (%)
bn 5
 
1.2%
id 5
 
1.2%
ph 5
 
1.2%
vn 5
 
1.2%
my 5
 
1.2%
th 5
 
1.2%
sg 5
 
1.2%
de 4
 
0.9%
it 4
 
0.9%
mx 4
 
0.9%
Other values (248) 378
88.9%
2024-03-15T01:49:05.897697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
M 60
 
7.1%
S 54
 
6.4%
T 51
 
6.0%
A 47
 
5.5%
G 46
 
5.4%
E 43
 
5.1%
N 41
 
4.8%
C 40
 
4.7%
B 40
 
4.7%
I 39
 
4.6%
Other values (16) 389
45.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 850
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M 60
 
7.1%
S 54
 
6.4%
T 51
 
6.0%
A 47
 
5.5%
G 46
 
5.4%
E 43
 
5.1%
N 41
 
4.8%
C 40
 
4.7%
B 40
 
4.7%
I 39
 
4.6%
Other values (16) 389
45.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 850
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
M 60
 
7.1%
S 54
 
6.4%
T 51
 
6.0%
A 47
 
5.5%
G 46
 
5.4%
E 43
 
5.1%
N 41
 
4.8%
C 40
 
4.7%
B 40
 
4.7%
I 39
 
4.6%
Other values (16) 389
45.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 850
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
M 60
 
7.1%
S 54
 
6.4%
T 51
 
6.0%
A 47
 
5.5%
G 46
 
5.4%
E 43
 
5.1%
N 41
 
4.8%
C 40
 
4.7%
B 40
 
4.7%
I 39
 
4.6%
Other values (16) 389
45.8%

국가명(CNTY_NM)
Text

Distinct258
Distinct (%)60.6%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2024-03-15T01:49:07.591694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length4.2300469
Min length1

Characters and Unicode

Total characters1802
Distinct characters233
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique174 ?
Unique (%)40.8%

Sample

1st row아프카니스탄
2nd row아르메니아
3rd row아제르바이잔
4th row방글라데시
5th row브루나이
ValueCountFrequency (%)
군도 14
 
2.8%
아일랜드 9
 
1.8%
세인트 7
 
1.4%
태국 5
 
1.0%
브루나이 5
 
1.0%
네덜란드 5
 
1.0%
프랑스 5
 
1.0%
베트남 5
 
1.0%
싱가포르 5
 
1.0%
인도네시아 5
 
1.0%
Other values (276) 431
86.9%
2024-03-15T01:49:09.429035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 121
 
6.7%
70
 
3.9%
스 69
 
3.8%
리 59
 
3.3%
이 52
 
2.9%
르 46
 
2.6%
도 42
 
2.3%
드 40
 
2.2%
니 36
 
2.0%
라 34
 
1.9%
Other values (223) 1233
68.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1727
95.8%
Space Separator 70
 
3.9%
Other Punctuation 3
 
0.2%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 121
 
7.0%
스 69
 
4.0%
리 59
 
3.4%
이 52
 
3.0%
르 46
 
2.7%
도 42
 
2.4%
드 40
 
2.3%
니 36
 
2.1%
라 34
 
2.0%
트 33
 
1.9%
Other values (220) 1195
69.2%
Space Separator
ValueCountFrequency (%)
70
100.0%
Other Punctuation
ValueCountFrequency (%)
& 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1727
95.8%
Common 75
 
4.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 121
 
7.0%
스 69
 
4.0%
리 59
 
3.4%
이 52
 
3.0%
르 46
 
2.7%
도 42
 
2.4%
드 40
 
2.3%
니 36
 
2.1%
라 34
 
2.0%
트 33
 
1.9%
Other values (220) 1195
69.2%
Common
ValueCountFrequency (%)
70
93.3%
& 3
 
4.0%
- 2
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1727
95.8%
ASCII 75
 
4.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 121
 
7.0%
스 69
 
4.0%
리 59
 
3.4%
이 52
 
3.0%
르 46
 
2.7%
도 42
 
2.4%
드 40
 
2.3%
니 36
 
2.1%
라 34
 
2.0%
트 33
 
1.9%
Other values (220) 1195
69.2%
ASCII
ValueCountFrequency (%)
70
93.3%
& 3
 
4.0%
- 2
 
2.7%

대륙_경제권(CNTN_EBK_UNFC_CLSF_NM)
Categorical

Distinct20
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
유럽
58 
아프리카
56 
중남미
55 
아시아
34 
OECD
30 
Other values (15)
193 

Length

Max length8
Median length5
Mean length3.1220657
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row아시아
2nd row아시아
3rd row아시아
4th row아시아
5th row아시아

Common Values

ValueCountFrequency (%)
유럽 58
13.6%
아프리카 56
13.1%
중남미 55
12.9%
아시아 34
8.0%
OECD 30
 
7.0%
EU 27
 
6.3%
아셈 25
 
5.9%
중동 21
 
4.9%
APEC 21
 
4.9%
대양주 18
 
4.2%
Other values (10) 81
19.0%

Length

2024-03-15T01:49:09.854434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
유럽 58
13.6%
아프리카 56
13.1%
중남미 55
12.9%
아시아 34
8.0%
oecd 30
 
7.0%
eu 27
 
6.3%
아셈 25
 
5.9%
중동 21
 
4.9%
apec 21
 
4.9%
대양주 18
 
4.2%
Other values (10) 81
19.0%

Missing values

2024-03-15T01:49:00.970324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T01:49:01.311182image/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.

Sample

기준연도(BASE_YY)국가부호(CNTY_CD)국가명(CNTY_NM)대륙_경제권(CNTN_EBK_UNFC_CLSF_NM)
02023AF아프카니스탄아시아
12023AM아르메니아아시아
22023AZ아제르바이잔아시아
32023BD방글라데시아시아
42023BN브루나이아시아
52023BT부탄아시아
62023CN중국아시아
72023HK홍콩아시아
82023ID인도네시아아시아
92023IN인도아시아
기준연도(BASE_YY)국가부호(CNTY_CD)국가명(CNTY_NM)대륙_경제권(CNTN_EBK_UNFC_CLSF_NM)
4162023AR아르헨티나MERCOSUR
4172023BR브라질MERCOSUR
4182023PY파라과이MERCOSUR
4192023UY우루과이MERCOSUR
4202023AE아랍에미리트 연합GCC
4212023BH바레인GCC
4222023KW쿠웨이트GCC
4232023OM오만GCC
4242023QA카타르GCC
4252023SA사우디아라비아GCC