Overview

Dataset statistics

Number of variables7
Number of observations74
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.2 KiB
Average record size in memory57.7 B

Variable types

Categorical3
Text4

Dataset

Description2023년 기준 해양오염방제 및 유창청소 업체 등록 현황에 관한 데이터로서 지방청,해경서,업체명,소재지,전화번호,팩스,구분 등의 항목을 제공합니다.
Author해양경찰청
URLhttps://www.data.go.kr/data/2632071/fileData.do

Alerts

지방청 is highly overall correlated with 해경서High correlation
해경서 is highly overall correlated with 지방청High correlation
업체명 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2024-03-14 21:00:33.439199
Analysis finished2024-03-14 21:00:34.837144
Duration1.4 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지방청
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size720.0 B
남해청
49 
서해청
13 
중부청
10 
동해청
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남해청 49
66.2%
서해청 13
 
17.6%
중부청 10
 
13.5%
동해청 2
 
2.7%

Length

2024-03-15T06:00:35.080016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T06:00:35.451682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남해청 49
66.2%
서해청 13
 
17.6%
중부청 10
 
13.5%
동해청 2
 
2.7%

해경서
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)13.5%
Missing0
Missing (%)0.0%
Memory size720.0 B
부산
37 
여수
12 
울산
10 
인천
5 
평택
4 
Other values (5)
6 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique4 ?
Unique (%)5.4%

Sample

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

Common Values

ValueCountFrequency (%)
부산 37
50.0%
여수 12
 
16.2%
울산 10
 
13.5%
인천 5
 
6.8%
평택 4
 
5.4%
포항 2
 
2.7%
태안 1
 
1.4%
목포 1
 
1.4%
통영 1
 
1.4%
창원 1
 
1.4%

Length

2024-03-15T06:00:35.864634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T06:00:36.245372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산 37
50.0%
여수 12
 
16.2%
울산 10
 
13.5%
인천 5
 
6.8%
평택 4
 
5.4%
포항 2
 
2.7%
태안 1
 
1.4%
목포 1
 
1.4%
통영 1
 
1.4%
창원 1
 
1.4%

업체명
Text

UNIQUE 

Distinct74
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size720.0 B
2024-03-15T06:00:37.561832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length7.0945946
Min length3

Characters and Unicode

Total characters525
Distinct characters118
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)100.0%

Sample

1st row(주)서해그린
2nd row송도항업(주)
3rd row주원환경(주)
4th row영화이앤알(주)
5th row(주)클린포트
ValueCountFrequency (%)
주)서해그린 1
 
1.4%
주)동승종합 1
 
1.4%
주)선화산업 1
 
1.4%
주)청해환경 1
 
1.4%
㈜태평양해양산업 1
 
1.4%
㈜청해쉽핑 1
 
1.4%
㈜부산마리타임 1
 
1.4%
주)인터오션마리타임 1
 
1.4%
주)월드환경 1
 
1.4%
주)마루산업 1
 
1.4%
Other values (64) 64
86.5%
2024-03-15T06:00:39.158504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 53
 
10.1%
) 53
 
10.1%
주 52
 
9.9%
경 21
 
4.0%
㈜ 20
 
3.8%
환 18
 
3.4%
린 17
 
3.2%
마 14
 
2.7%
업 11
 
2.1%
스 11
 
2.1%
Other values (108) 255
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 397
75.6%
Open Punctuation 53
 
10.1%
Close Punctuation 53
 
10.1%
Other Symbol 20
 
3.8%
Dash Punctuation 1
 
0.2%
Space Separator 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 52
 
13.1%
경 21
 
5.3%
환 18
 
4.5%
린 17
 
4.3%
마 14
 
3.5%
업 11
 
2.8%
스 11
 
2.8%
해 11
 
2.8%
산 8
 
2.0%
서 8
 
2.0%
Other values (103) 226
56.9%
Open Punctuation
ValueCountFrequency (%)
( 53
100.0%
Close Punctuation
ValueCountFrequency (%)
) 53
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 417
79.4%
Common 108
 
20.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 52
 
12.5%
경 21
 
5.0%
㈜ 20
 
4.8%
환 18
 
4.3%
린 17
 
4.1%
마 14
 
3.4%
업 11
 
2.6%
스 11
 
2.6%
해 11
 
2.6%
산 8
 
1.9%
Other values (104) 234
56.1%
Common
ValueCountFrequency (%)
( 53
49.1%
) 53
49.1%
- 1
 
0.9%
1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 397
75.6%
ASCII 108
 
20.6%
None 20
 
3.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 53
49.1%
) 53
49.1%
- 1
 
0.9%
1
 
0.9%
Hangul
ValueCountFrequency (%)
주 52
 
13.1%
경 21
 
5.3%
환 18
 
4.5%
린 17
 
4.3%
마 14
 
3.5%
업 11
 
2.8%
스 11
 
2.8%
해 11
 
2.8%
산 8
 
2.0%
서 8
 
2.0%
Other values (103) 226
56.9%
None
ValueCountFrequency (%)
㈜ 20
100.0%

소재지
Text

Distinct72
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size720.0 B
2024-03-15T06:00:40.278763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length32.5
Mean length24.675676
Min length14

Characters and Unicode

Total characters1826
Distinct characters157
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)94.6%

Sample

1st row인천시 중구 항동7가 27-54 화인통상빌딩 3층
2nd row인천시 중구 제물량로 189, 4층
3rd row인천시 중구 항동7가 27-211 유한빌딩 301-A호
4th row인천시 중구 신포로 23번길 49 중앙프라자 209
5th row인천시 중구 항동7가 58-7 씨사이드빌리지 502호
ValueCountFrequency (%)
부산시 35
 
8.8%
중구 20
 
5.0%
영도구 14
 
3.5%
전남 13
 
3.3%
울산시 10
 
2.5%
여수시 9
 
2.3%
남구 8
 
2.0%
중앙대로 6
 
1.5%
인천시 5
 
1.3%
포승읍 4
 
1.0%
Other values (218) 274
68.8%
2024-03-15T06:00:42.129770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
325
 
17.8%
시 77
 
4.2%
1 65
 
3.6%
산 58
 
3.2%
구 55
 
3.0%
2 54
 
3.0%
로 52
 
2.8%
동 47
 
2.6%
0 45
 
2.5%
4 42
 
2.3%
Other values (147) 1006
55.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 994
54.4%
Decimal Number 385
 
21.1%
Space Separator 325
 
17.8%
Other Punctuation 49
 
2.7%
Open Punctuation 24
 
1.3%
Close Punctuation 24
 
1.3%
Dash Punctuation 17
 
0.9%
Uppercase Letter 8
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 77
 
7.7%
산 58
 
5.8%
구 55
 
5.5%
로 52
 
5.2%
동 47
 
4.7%
부 40
 
4.0%
길 40
 
4.0%
중 36
 
3.6%
호 33
 
3.3%
번 28
 
2.8%
Other values (124) 528
53.1%
Decimal Number
ValueCountFrequency (%)
1 65
16.9%
2 54
14.0%
0 45
11.7%
4 42
10.9%
3 41
10.6%
5 36
9.4%
7 34
8.8%
6 28
7.3%
9 22
 
5.7%
8 18
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
B 2
25.0%
A 2
25.0%
T 1
12.5%
K 1
12.5%
O 1
12.5%
P 1
12.5%
Other Punctuation
ValueCountFrequency (%)
, 40
81.6%
? 8
 
16.3%
. 1
 
2.0%
Space Separator
ValueCountFrequency (%)
325
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 994
54.4%
Common 824
45.1%
Latin 8
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 77
 
7.7%
산 58
 
5.8%
구 55
 
5.5%
로 52
 
5.2%
동 47
 
4.7%
부 40
 
4.0%
길 40
 
4.0%
중 36
 
3.6%
호 33
 
3.3%
번 28
 
2.8%
Other values (124) 528
53.1%
Common
ValueCountFrequency (%)
325
39.4%
1 65
 
7.9%
2 54
 
6.6%
0 45
 
5.5%
4 42
 
5.1%
3 41
 
5.0%
, 40
 
4.9%
5 36
 
4.4%
7 34
 
4.1%
6 28
 
3.4%
Other values (7) 114
 
13.8%
Latin
ValueCountFrequency (%)
B 2
25.0%
A 2
25.0%
T 1
12.5%
K 1
12.5%
O 1
12.5%
P 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 994
54.4%
ASCII 832
45.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
325
39.1%
1 65
 
7.8%
2 54
 
6.5%
0 45
 
5.4%
4 42
 
5.0%
3 41
 
4.9%
, 40
 
4.8%
5 36
 
4.3%
7 34
 
4.1%
6 28
 
3.4%
Other values (13) 122
 
14.7%
Hangul
ValueCountFrequency (%)
시 77
 
7.7%
산 58
 
5.8%
구 55
 
5.5%
로 52
 
5.2%
동 47
 
4.7%
부 40
 
4.0%
길 40
 
4.0%
중 36
 
3.6%
호 33
 
3.3%
번 28
 
2.8%
Other values (124) 528
53.1%

전화번호
Text

UNIQUE 

Distinct74
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size720.0 B
2024-03-15T06:00:43.450293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.054054
Min length12

Characters and Unicode

Total characters892
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

Unique74 ?
Unique (%)100.0%

Sample

1st row032-882-4666
2nd row032-764-6668
3rd row032-888-3411
4th row070-8826-9150
5th row032-882-8279
ValueCountFrequency (%)
032-882-4666 1
 
1.4%
051-441-2027 1
 
1.4%
051-405-8500 1
 
1.4%
051-418-2272 1
 
1.4%
051-414-9303 1
 
1.4%
070-4122-5560 1
 
1.4%
051-246-8711 1
 
1.4%
070-7799-2234 1
 
1.4%
051-403-0702 1
 
1.4%
051-715-8915 1
 
1.4%
Other values (64) 64
86.5%
2024-03-15T06:00:44.794102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 148
16.6%
0 143
16.0%
1 110
12.3%
6 88
9.9%
5 87
9.8%
2 82
9.2%
4 67
7.5%
3 43
 
4.8%
8 43
 
4.8%
7 41
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 744
83.4%
Dash Punctuation 148
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 143
19.2%
1 110
14.8%
6 88
11.8%
5 87
11.7%
2 82
11.0%
4 67
9.0%
3 43
 
5.8%
8 43
 
5.8%
7 41
 
5.5%
9 40
 
5.4%
Dash Punctuation
ValueCountFrequency (%)
- 148
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 892
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 148
16.6%
0 143
16.0%
1 110
12.3%
6 88
9.9%
5 87
9.8%
2 82
9.2%
4 67
7.5%
3 43
 
4.8%
8 43
 
4.8%
7 41
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 892
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 148
16.6%
0 143
16.0%
1 110
12.3%
6 88
9.9%
5 87
9.8%
2 82
9.2%
4 67
7.5%
3 43
 
4.8%
8 43
 
4.8%
7 41
 
4.6%

팩스
Text

Distinct73
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size720.0 B
2024-03-15T06:00:45.714038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.027027
Min length11

Characters and Unicode

Total characters890
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)97.3%

Sample

1st row032-882-4999
2nd row032-764-6670
3rd row032-888-3153
4th row0504-182-9666
5th row032-883-8279
ValueCountFrequency (%)
052-716-0086 2
 
2.7%
032-882-4999 1
 
1.4%
051-403-0703 1
 
1.4%
051-405-7722 1
 
1.4%
051-418-2273 1
 
1.4%
051-413-0234 1
 
1.4%
051-442-5560 1
 
1.4%
051-246-8712 1
 
1.4%
051-462-2246 1
 
1.4%
051-715-8916 1
 
1.4%
Other values (63) 63
85.1%
2024-03-15T06:00:47.184305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 147
16.5%
0 129
14.5%
1 103
11.6%
2 91
10.2%
5 89
10.0%
6 83
9.3%
4 83
9.3%
3 54
 
6.1%
8 41
 
4.6%
7 40
 
4.5%
Other values (2) 30
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 742
83.4%
Dash Punctuation 147
 
16.5%
Space Separator 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 129
17.4%
1 103
13.9%
2 91
12.3%
5 89
12.0%
6 83
11.2%
4 83
11.2%
3 54
7.3%
8 41
 
5.5%
7 40
 
5.4%
9 29
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 147
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 890
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 147
16.5%
0 129
14.5%
1 103
11.6%
2 91
10.2%
5 89
10.0%
6 83
9.3%
4 83
9.3%
3 54
 
6.1%
8 41
 
4.6%
7 40
 
4.5%
Other values (2) 30
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 890
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 147
16.5%
0 129
14.5%
1 103
11.6%
2 91
10.2%
5 89
10.0%
6 83
9.3%
4 83
9.3%
3 54
 
6.1%
8 41
 
4.6%
7 40
 
4.5%
Other values (2) 30
 
3.4%

구분
Categorical

Distinct3
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size720.0 B
유 창
41 
겸 업
27 
방 제
6 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row유 창
2nd row유 창
3rd row유 창
4th row겸 업
5th row겸 업

Common Values

ValueCountFrequency (%)
유 창 41
55.4%
겸 업 27
36.5%
방 제 6
 
8.1%

Length

2024-03-15T06:00:47.469573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T06:00:47.769993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유 41
27.7%
창 41
27.7%
겸 27
18.2%
업 27
18.2%
방 6
 
4.1%
제 6
 
4.1%

Correlations

2024-03-15T06:00:47.981424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지방청해경서업체명소재지전화번호팩스구분
지방청1.0001.0001.0001.0001.0001.0000.269
해경서1.0001.0001.0001.0001.0001.0000.473
업체명1.0001.0001.0001.0001.0001.0001.000
소재지1.0001.0001.0001.0001.0001.0000.951
전화번호1.0001.0001.0001.0001.0001.0001.000
팩스1.0001.0001.0001.0001.0001.0000.865
구분0.2690.4731.0000.9511.0000.8651.000
2024-03-15T06:00:48.263753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지방청해경서구분
지방청1.0000.9560.255
해경서0.9561.0000.304
구분0.2550.3041.000
2024-03-15T06:00:48.501857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지방청해경서구분
지방청1.0000.9560.255
해경서0.9561.0000.304
구분0.2550.3041.000

Missing values

2024-03-15T06:00:34.273811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T06:00:34.695022image/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

지방청해경서업체명소재지전화번호팩스구분
0중부청인천(주)서해그린인천시 중구 항동7가 27-54 화인통상빌딩 3층032-882-4666032-882-4999유 창
1중부청인천송도항업(주)인천시 중구 제물량로 189, 4층032-764-6668032-764-6670유 창
2중부청인천주원환경(주)인천시 중구 항동7가 27-211 유한빌딩 301-A호032-888-3411032-888-3153유 창
3중부청인천영화이앤알(주)인천시 중구 신포로 23번길 49 중앙프라자 209070-8826-91500504-182-9666겸 업
4중부청인천(주)클린포트인천시 중구 항동7가 58-7 씨사이드빌리지 502호032-882-8279032-883-8279겸 업
5중부청평택㈜그린이앤씨경기 평택시 포승읍 평택항만길 86-54031-686-6796031-686-6798유 창
6중부청평택㈜서해환경경기 평택시 포승읍 내기새싹길 12-10, 가동 6호031-684-0551031-684-0552유 창
7중부청평택㈜씨앤경기 평택시 포승읍 평택항로 34-9031-683-8661031-683-8660유 창
8중부청평택㈜백두환경경기 평택시 포승읍 만석길 40-5, 2동070-8129-2389050-4132-2002유 창
9중부청태안우진해운(주)충남 서산시 대산읍 영좌동길 156 1층 102호041-681-9596041-681-9598겸 업
지방청해경서업체명소재지전화번호팩스구분
64남해청울산(주)골든씨울산시 남구 장생포동 249, 1703호052-261-2606052-2612607유 창
65남해청울산대한환경기술개발(주)울산시 남구 장생포고래로 179052-267-5152052-261-2227유 창
66남해청울산㈜블루엔텍울산시 남구 장생포고래로179번길 69052-000-0000052-716-0086유 창
67남해청울산글로벌마린서비스㈜울산시 울주군 온산읍 온산로 68052-238-0597052-238-0597방 제
68남해청울산㈜대상해운울산시 울주군 온산읍 처용산업 1길 57052-265-9517052-269-3323방 제
69남해청울산(주)한유마린서비스울산시 남구 장생포고래로255, 2층052-976-6500052-976-6565방 제
70남해청울산(주)우주환경울산시 남구장생포 고래로257-1052-227-3287052-227-3387겸 업
71남해청울산(주)블루코리아울산시 남구 장생포고래로179번길 69052-716-0085052-716-0086겸 업
72동해청포항(주)씨앤지경북 포항시 남구 동해안로 6262(해운센터 301호)054-274-2040054-278-2043겸 업
73동해청포항(주)블루씨경북 포항시 남구 청림서길 35번길 4-18054-278-8200054-278-4554겸 업