Overview

Dataset statistics

Number of variables7
Number of observations242
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.4 KiB
Average record size in memory56.5 B

Variable types

Categorical2
Text5

Dataset

Description한국무역보험공사 2019년 주요 수출국의 수출대금 결제기간 비중을 수입자 업종별로 구분해 제시한 파일 데이터 자료입니다.
Author한국무역보험공사
URLhttps://www.data.go.kr/data/15088877/fileData.do

Reproduction

Analysis started2023-12-11 22:45:41.711690
Analysis finished2023-12-11 22:45:42.306455
Duration0.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

수출국
Categorical

Distinct39
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
미국
 
15
중국
 
14
일본
 
11
인도
 
11
대만
 
10
Other values (34)
181 

Length

Max length9
Median length8
Mean length3.1239669
Min length2

Unique

Unique3 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
미국 15
 
6.2%
중국 14
 
5.8%
일본 11
 
4.5%
인도 11
 
4.5%
대만 10
 
4.1%
이탈리아 10
 
4.1%
태국 10
 
4.1%
싱가포르 9
 
3.7%
아랍에미리트 연합 9
 
3.7%
영국 9
 
3.7%
Other values (29) 134
55.4%

Length

2023-12-12T07:45:42.376731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
미국 15
 
6.0%
중국 14
 
5.6%
일본 11
 
4.4%
인도 11
 
4.4%
대만 10
 
4.0%
이탈리아 10
 
4.0%
태국 10
 
4.0%
호주 9
 
3.6%
영국 9
 
3.6%
연합 9
 
3.6%
Other values (30) 143
57.0%

수입자업종
Text

Distinct77
Distinct (%)31.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2023-12-12T07:45:42.580179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length21
Mean length16.508264
Min length6

Characters and Unicode

Total characters3995
Distinct characters161
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)15.7%

Sample

1st row액정 표시장치 제조업
2nd row전기용 기계.장비 및 관련 기자재 도매업
3rd row축전지 제조업
4th row그 외 기타 전자부품 제조업
5th row공작용 기계 및 장비 도매업
ValueCountFrequency (%)
및 147
 
12.2%
기타 119
 
9.9%
제조업 109
 
9.0%
도매업 101
 
8.4%
그 40
 
3.3%
외 40
 
3.3%
화학제품 37
 
3.1%
신품 34
 
2.8%
자동차 33
 
2.7%
화학물질 29
 
2.4%
Other values (128) 516
42.8%
2023-12-12T07:45:42.871757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
963
24.1%
업 254
 
6.4%
제 185
 
4.6%
기 177
 
4.4%
품 163
 
4.1%
및 147
 
3.7%
타 135
 
3.4%
매 133
 
3.3%
도 111
 
2.8%
조 110
 
2.8%
Other values (151) 1617
40.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2995
75.0%
Space Separator 963
 
24.1%
Other Punctuation 26
 
0.7%
Decimal Number 11
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 254
 
8.5%
제 185
 
6.2%
기 177
 
5.9%
품 163
 
5.4%
및 147
 
4.9%
타 135
 
4.5%
매 133
 
4.4%
도 111
 
3.7%
조 110
 
3.7%
화 69
 
2.3%
Other values (147) 1511
50.5%
Other Punctuation
ValueCountFrequency (%)
, 17
65.4%
. 9
34.6%
Space Separator
ValueCountFrequency (%)
963
100.0%
Decimal Number
ValueCountFrequency (%)
1 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2995
75.0%
Common 1000
 
25.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 254
 
8.5%
제 185
 
6.2%
기 177
 
5.9%
품 163
 
5.4%
및 147
 
4.9%
타 135
 
4.5%
매 133
 
4.4%
도 111
 
3.7%
조 110
 
3.7%
화 69
 
2.3%
Other values (147) 1511
50.5%
Common
ValueCountFrequency (%)
963
96.3%
, 17
 
1.7%
1 11
 
1.1%
. 9
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2991
74.9%
ASCII 1000
 
25.0%
Compat Jamo 4
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
963
96.3%
, 17
 
1.7%
1 11
 
1.1%
. 9
 
0.9%
Hangul
ValueCountFrequency (%)
업 254
 
8.5%
제 185
 
6.2%
기 177
 
5.9%
품 163
 
5.4%
및 147
 
4.9%
타 135
 
4.5%
매 133
 
4.4%
도 111
 
3.7%
조 110
 
3.7%
화 69
 
2.3%
Other values (146) 1507
50.4%
Compat Jamo
ValueCountFrequency (%)
ㆍ 4
100.0%

30일 이내
Text

Distinct65
Distinct (%)26.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2023-12-12T07:45:43.043926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.4876033
Min length2

Characters and Unicode

Total characters602
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)10.7%

Sample

1st row0%
2nd row6%
3rd row1%
4th row11%
5th row29%
ValueCountFrequency (%)
0 39
 
16.1%
1 19
 
7.9%
2 17
 
7.0%
7 11
 
4.5%
4 9
 
3.7%
13 9
 
3.7%
5 8
 
3.3%
3 8
 
3.3%
6 7
 
2.9%
21 7
 
2.9%
Other values (55) 108
44.6%
2023-12-12T07:45:43.367001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
% 242
40.2%
1 68
 
11.3%
0 58
 
9.6%
2 55
 
9.1%
3 44
 
7.3%
4 34
 
5.6%
6 28
 
4.7%
7 26
 
4.3%
5 21
 
3.5%
9 15
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 360
59.8%
Other Punctuation 242
40.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 68
18.9%
0 58
16.1%
2 55
15.3%
3 44
12.2%
4 34
9.4%
6 28
7.8%
7 26
 
7.2%
5 21
 
5.8%
9 15
 
4.2%
8 11
 
3.1%
Other Punctuation
ValueCountFrequency (%)
% 242
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 602
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
% 242
40.2%
1 68
 
11.3%
0 58
 
9.6%
2 55
 
9.1%
3 44
 
7.3%
4 34
 
5.6%
6 28
 
4.7%
7 26
 
4.3%
5 21
 
3.5%
9 15
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 602
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
% 242
40.2%
1 68
 
11.3%
0 58
 
9.6%
2 55
 
9.1%
3 44
 
7.3%
4 34
 
5.6%
6 28
 
4.7%
7 26
 
4.3%
5 21
 
3.5%
9 15
 
2.5%

31-60일
Text

Distinct75
Distinct (%)31.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2023-12-12T07:45:43.577122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.7231405
Min length2

Characters and Unicode

Total characters659
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)6.6%

Sample

1st row17%
2nd row21%
3rd row15%
4th row31%
5th row2%
ValueCountFrequency (%)
0 17
 
7.0%
3 11
 
4.5%
2 8
 
3.3%
7 8
 
3.3%
15 7
 
2.9%
31 7
 
2.9%
12 7
 
2.9%
27 7
 
2.9%
17 6
 
2.5%
1 5
 
2.1%
Other values (65) 159
65.7%
2023-12-12T07:45:43.878150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
% 242
36.7%
1 72
 
10.9%
2 59
 
9.0%
3 54
 
8.2%
4 43
 
6.5%
7 38
 
5.8%
5 38
 
5.8%
0 35
 
5.3%
9 30
 
4.6%
6 26
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 417
63.3%
Other Punctuation 242
36.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 72
17.3%
2 59
14.1%
3 54
12.9%
4 43
10.3%
7 38
9.1%
5 38
9.1%
0 35
8.4%
9 30
7.2%
6 26
 
6.2%
8 22
 
5.3%
Other Punctuation
ValueCountFrequency (%)
% 242
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 659
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
% 242
36.7%
1 72
 
10.9%
2 59
 
9.0%
3 54
 
8.2%
4 43
 
6.5%
7 38
 
5.8%
5 38
 
5.8%
0 35
 
5.3%
9 30
 
4.6%
6 26
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 659
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
% 242
36.7%
1 72
 
10.9%
2 59
 
9.0%
3 54
 
8.2%
4 43
 
6.5%
7 38
 
5.8%
5 38
 
5.8%
0 35
 
5.3%
9 30
 
4.6%
6 26
 
3.9%

61-90일
Text

Distinct77
Distinct (%)31.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2023-12-12T07:45:44.055021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.7272727
Min length2

Characters and Unicode

Total characters660
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)7.9%

Sample

1st row22%
2nd row36%
3rd row64%
4th row40%
5th row69%
ValueCountFrequency (%)
0 26
 
10.7%
4 8
 
3.3%
23 8
 
3.3%
14 8
 
3.3%
1 8
 
3.3%
20 6
 
2.5%
10 6
 
2.5%
26 6
 
2.5%
31 6
 
2.5%
5 5
 
2.1%
Other values (67) 155
64.0%
2023-12-12T07:45:44.378620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
% 242
36.7%
1 62
 
9.4%
2 61
 
9.2%
0 53
 
8.0%
4 53
 
8.0%
3 49
 
7.4%
6 41
 
6.2%
5 33
 
5.0%
7 29
 
4.4%
9 20
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 418
63.3%
Other Punctuation 242
36.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 62
14.8%
2 61
14.6%
0 53
12.7%
4 53
12.7%
3 49
11.7%
6 41
9.8%
5 33
7.9%
7 29
6.9%
9 20
 
4.8%
8 17
 
4.1%
Other Punctuation
ValueCountFrequency (%)
% 242
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 660
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
% 242
36.7%
1 62
 
9.4%
2 61
 
9.2%
0 53
 
8.0%
4 53
 
8.0%
3 49
 
7.4%
6 41
 
6.2%
5 33
 
5.0%
7 29
 
4.4%
9 20
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 660
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
% 242
36.7%
1 62
 
9.4%
2 61
 
9.2%
0 53
 
8.0%
4 53
 
8.0%
3 49
 
7.4%
6 41
 
6.2%
5 33
 
5.0%
7 29
 
4.4%
9 20
 
3.0%

91-120일
Text

Distinct59
Distinct (%)24.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2023-12-12T07:45:44.527033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.4256198
Min length2

Characters and Unicode

Total characters587
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)10.3%

Sample

1st row43%
2nd row28%
3rd row15%
4th row15%
5th row0%
ValueCountFrequency (%)
0 82
33.9%
1 14
 
5.8%
2 12
 
5.0%
17 7
 
2.9%
4 7
 
2.9%
15 6
 
2.5%
7 6
 
2.5%
3 5
 
2.1%
13 5
 
2.1%
10 5
 
2.1%
Other values (49) 93
38.4%
2023-12-12T07:45:44.821740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
% 242
41.2%
0 92
 
15.7%
1 56
 
9.5%
3 39
 
6.6%
2 38
 
6.5%
6 26
 
4.4%
5 25
 
4.3%
7 23
 
3.9%
4 20
 
3.4%
8 16
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 345
58.8%
Other Punctuation 242
41.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 92
26.7%
1 56
16.2%
3 39
11.3%
2 38
11.0%
6 26
 
7.5%
5 25
 
7.2%
7 23
 
6.7%
4 20
 
5.8%
8 16
 
4.6%
9 10
 
2.9%
Other Punctuation
ValueCountFrequency (%)
% 242
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 587
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
% 242
41.2%
0 92
 
15.7%
1 56
 
9.5%
3 39
 
6.6%
2 38
 
6.5%
6 26
 
4.4%
5 25
 
4.3%
7 23
 
3.9%
4 20
 
3.4%
8 16
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 587
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
% 242
41.2%
0 92
 
15.7%
1 56
 
9.5%
3 39
 
6.6%
2 38
 
6.5%
6 26
 
4.4%
5 25
 
4.3%
7 23
 
3.9%
4 20
 
3.4%
8 16
 
2.7%

120일 초과
Categorical

Distinct43
Distinct (%)17.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
0%
140 
1%
 
14
2%
 
13
3%
 
8
6%
 
6
Other values (38)
61 

Length

Max length3
Median length2
Mean length2.1942149
Min length2

Unique

Unique24 ?
Unique (%)9.9%

Sample

1st row18%
2nd row9%
3rd row6%
4th row3%
5th row0%

Common Values

ValueCountFrequency (%)
0% 140
57.9%
1% 14
 
5.8%
2% 13
 
5.4%
3% 8
 
3.3%
6% 6
 
2.5%
11% 6
 
2.5%
4% 4
 
1.7%
5% 3
 
1.2%
50% 3
 
1.2%
8% 3
 
1.2%
Other values (33) 42
 
17.4%

Length

2023-12-12T07:45:44.937724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 140
57.9%
1 14
 
5.8%
2 13
 
5.4%
3 8
 
3.3%
6 6
 
2.5%
11 6
 
2.5%
4 4
 
1.7%
5 3
 
1.2%
50 3
 
1.2%
8 3
 
1.2%
Other values (33) 42
 
17.4%

Correlations

2023-12-12T07:45:45.006563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수출국수입자업종30일 이내31-60일61-90일91-120일120일 초과
수출국1.0000.0000.0000.0000.6760.0000.000
수입자업종0.0001.0000.0000.8220.0000.8490.000
30일 이내0.0000.0001.0000.6830.0000.0000.000
31-60일0.0000.8220.6831.0000.0000.0000.000
61-90일0.6760.0000.0000.0001.0000.0000.000
91-120일0.0000.8490.0000.0000.0001.0000.367
120일 초과0.0000.0000.0000.0000.0000.3671.000
2023-12-12T07:45:45.094004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
120일 초과수출국
120일 초과1.0000.000
수출국0.0001.000
2023-12-12T07:45:45.159921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수출국120일 초과
수출국1.0000.000
120일 초과0.0001.000

Missing values

2023-12-12T07:45:42.172627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T07:45:42.268051image/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

수출국수입자업종30일 이내31-60일61-90일91-120일120일 초과
0중국액정 표시장치 제조업0%17%22%43%18%
1중국전기용 기계.장비 및 관련 기자재 도매업6%21%36%28%9%
2중국축전지 제조업1%15%64%15%6%
3중국그 외 기타 전자부품 제조업11%31%40%15%3%
4중국공작용 기계 및 장비 도매업29%2%69%0%0%
5중국동력식 수지공구 제조업0%56%19%14%11%
6중국기타 무선 통신장비 제조업2%3%71%23%0%
7중국승용차 및 기타 여객용 자동차 제조업0%12%6%82%0%
8중국합성수지 및 기타 플라스틱 물질 제조업22%44%30%4%0%
9중국컴퓨터 및 주변장치, 소프트웨어 도매업5%2%2%51%40%
수출국수입자업종30일 이내31-60일61-90일91-120일120일 초과
232호주기타 자동차 신품 부품 및 내장품 판매업2%29%64%0%4%
233호주기타 산업용 기계 및 장비 도매업21%44%34%0%2%
234호주전지 및 케이블 도매업0%43%3%27%27%
235호주전기용 기계.장비 및 관련 기자재 도매업20%19%31%29%1%
236호주기타 화학물질 및 화학제품 도매업49%35%8%7%0%
237호주건설ㆍ광업용 기계 및 장비 도매업20%20%18%7%34%
238호주1차 금속제품 도매업10%20%31%39%0%
239호주자동차 신품 타이어 및 튜브 판매업33%50%17%0%0%
240뉴질랜드자동차 신품 타이어 및 튜브 판매업1%99%0%0%0%
241뉴질랜드기타 화학물질 및 화학제품 도매업7%88%6%0%0%