Overview

Dataset statistics

Number of variables3
Number of observations35
Missing cells3
Missing cells (%)2.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory968.0 B
Average record size in memory27.7 B

Variable types

Text3

Dataset

Description23년도 12월 기준 전라남도 내 천일염 가공업체(총 35개사)의 기업명, 주소, 연락처 등의 현황을 조회하실 수 있는 데이터입니다
Author전라남도
URLhttps://www.data.go.kr/data/15126545/fileData.do

Alerts

연락처 has 3 (8.6%) missing valuesMissing
가공기업명 has unique valuesUnique
주소 has unique valuesUnique

Reproduction

Analysis started2024-03-14 15:12:36.046811
Analysis finished2024-03-14 15:12:36.749125
Duration0.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

가공기업명
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size408.0 B
2024-03-15T00:12:37.422990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length11
Mean length7.7428571
Min length3

Characters and Unicode

Total characters271
Distinct characters111
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)100.0%

Sample

1st row농업회사법인 선한세상
2nd row바이오테크㈜
3rd row대한엽엄조합
4th row신안애
5th row에코솔트㈜
ValueCountFrequency (%)
농업회사법인 3
 
6.2%
영농조합법인 2
 
4.2%
갯벌 1
 
2.1%
목포신안군농협조합공동사업법인 1
 
2.1%
북신안농협 1
 
2.1%
6형제소금팩토리 1
 
2.1%
솔트앤그린푸드 1
 
2.1%
해여름 1
 
2.1%
신안보물섬 1
 
2.1%
솔트힐 1
 
2.1%
Other values (35) 35
72.9%
2024-03-15T00:12:38.720964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
농 14
 
5.2%
13
 
4.8%
신 10
 
3.7%
인 9
 
3.3%
법 9
 
3.3%
㈜ 9
 
3.3%
사 8
 
3.0%
안 8
 
3.0%
협 7
 
2.6%
업 7
 
2.6%
Other values (101) 177
65.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 238
87.8%
Space Separator 13
 
4.8%
Other Symbol 9
 
3.3%
Open Punctuation 4
 
1.5%
Close Punctuation 4
 
1.5%
Uppercase Letter 2
 
0.7%
Decimal Number 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
농 14
 
5.9%
신 10
 
4.2%
인 9
 
3.8%
법 9
 
3.8%
사 8
 
3.4%
안 8
 
3.4%
협 7
 
2.9%
업 7
 
2.9%
트 7
 
2.9%
회 6
 
2.5%
Other values (94) 153
64.3%
Uppercase Letter
ValueCountFrequency (%)
C 1
50.0%
J 1
50.0%
Space Separator
ValueCountFrequency (%)
13
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Decimal Number
ValueCountFrequency (%)
6 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 247
91.1%
Common 22
 
8.1%
Latin 2
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
농 14
 
5.7%
신 10
 
4.0%
인 9
 
3.6%
법 9
 
3.6%
㈜ 9
 
3.6%
사 8
 
3.2%
안 8
 
3.2%
협 7
 
2.8%
업 7
 
2.8%
트 7
 
2.8%
Other values (95) 159
64.4%
Common
ValueCountFrequency (%)
13
59.1%
( 4
 
18.2%
) 4
 
18.2%
6 1
 
4.5%
Latin
ValueCountFrequency (%)
C 1
50.0%
J 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 238
87.8%
ASCII 24
 
8.9%
None 9
 
3.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
농 14
 
5.9%
신 10
 
4.2%
인 9
 
3.8%
법 9
 
3.8%
사 8
 
3.4%
안 8
 
3.4%
협 7
 
2.9%
업 7
 
2.9%
트 7
 
2.9%
회 6
 
2.5%
Other values (94) 153
64.3%
ASCII
ValueCountFrequency (%)
13
54.2%
( 4
 
16.7%
) 4
 
16.7%
6 1
 
4.2%
C 1
 
4.2%
J 1
 
4.2%
None
ValueCountFrequency (%)
㈜ 9
100.0%

주소
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size408.0 B
2024-03-15T00:12:39.731228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length21.142857
Min length18

Characters and Unicode

Total characters740
Distinct characters92
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

Unique35 ?
Unique (%)100.0%

Sample

1st row전라남도 나주시 반남면 월량길 118-15
2nd row전라남도 목포시 연산동 1636-5
3rd row전라남도 목포시 고하대로 597번길 57
4th row전라남도 목포시 삼학로 75번길 10
5th row전라남도 무안군 몽탄면 몽탄공단길 35
ValueCountFrequency (%)
전라남도 35
20.1%
신안군 25
 
14.4%
지도읍 5
 
2.9%
도초면 5
 
2.9%
지도증도로 3
 
1.7%
임자면 3
 
1.7%
서남문로 3
 
1.7%
신의면 3
 
1.7%
비금면 3
 
1.7%
압해읍 3
 
1.7%
Other values (80) 86
49.4%
2024-03-15T00:12:41.164812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
139
18.8%
도 54
 
7.3%
남 39
 
5.3%
전 37
 
5.0%
라 36
 
4.9%
1 33
 
4.5%
군 30
 
4.1%
신 29
 
3.9%
안 28
 
3.8%
면 24
 
3.2%
Other values (82) 291
39.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 469
63.4%
Space Separator 139
 
18.8%
Decimal Number 118
 
15.9%
Dash Punctuation 14
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 54
 
11.5%
남 39
 
8.3%
전 37
 
7.9%
라 36
 
7.7%
군 30
 
6.4%
신 29
 
6.2%
안 28
 
6.0%
면 24
 
5.1%
길 21
 
4.5%
로 11
 
2.3%
Other values (70) 160
34.1%
Decimal Number
ValueCountFrequency (%)
1 33
28.0%
3 13
 
11.0%
5 13
 
11.0%
2 10
 
8.5%
4 10
 
8.5%
7 10
 
8.5%
0 9
 
7.6%
6 8
 
6.8%
8 7
 
5.9%
9 5
 
4.2%
Space Separator
ValueCountFrequency (%)
139
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 469
63.4%
Common 271
36.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 54
 
11.5%
남 39
 
8.3%
전 37
 
7.9%
라 36
 
7.7%
군 30
 
6.4%
신 29
 
6.2%
안 28
 
6.0%
면 24
 
5.1%
길 21
 
4.5%
로 11
 
2.3%
Other values (70) 160
34.1%
Common
ValueCountFrequency (%)
139
51.3%
1 33
 
12.2%
- 14
 
5.2%
3 13
 
4.8%
5 13
 
4.8%
2 10
 
3.7%
4 10
 
3.7%
7 10
 
3.7%
0 9
 
3.3%
6 8
 
3.0%
Other values (2) 12
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 469
63.4%
ASCII 271
36.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
139
51.3%
1 33
 
12.2%
- 14
 
5.2%
3 13
 
4.8%
5 13
 
4.8%
2 10
 
3.7%
4 10
 
3.7%
7 10
 
3.7%
0 9
 
3.3%
6 8
 
3.0%
Other values (2) 12
 
4.4%
Hangul
ValueCountFrequency (%)
도 54
 
11.5%
남 39
 
8.3%
전 37
 
7.9%
라 36
 
7.7%
군 30
 
6.4%
신 29
 
6.2%
안 28
 
6.0%
면 24
 
5.1%
길 21
 
4.5%
로 11
 
2.3%
Other values (70) 160
34.1%

연락처
Text

MISSING 

Distinct32
Distinct (%)100.0%
Missing3
Missing (%)8.6%
Memory size408.0 B
2024-03-15T00:12:41.998716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.9375
Min length9

Characters and Unicode

Total characters382
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

Unique32 ?
Unique (%)100.0%

Sample

1st row061-336-0388
2nd row061-278-0963
3rd row061-462-1400
4th row061-275-5224
5th row061-454-3303
ValueCountFrequency (%)
061-275-2981 1
 
3.1%
061-462-1400 1
 
3.1%
061-246-0057 1
 
3.1%
1899-6778 1
 
3.1%
061-262-2630 1
 
3.1%
02-3663-1599 1
 
3.1%
061-281-7766 1
 
3.1%
02-2282-0107 1
 
3.1%
061-275-0005 1
 
3.1%
061-246-4244 1
 
3.1%
Other values (22) 22
68.8%
2024-03-15T00:12:43.284706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 63
16.5%
0 62
16.2%
6 45
11.8%
2 45
11.8%
1 43
11.3%
7 30
7.9%
5 25
 
6.5%
3 24
 
6.3%
4 20
 
5.2%
8 17
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 319
83.5%
Dash Punctuation 63
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 62
19.4%
6 45
14.1%
2 45
14.1%
1 43
13.5%
7 30
9.4%
5 25
7.8%
3 24
 
7.5%
4 20
 
6.3%
8 17
 
5.3%
9 8
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 63
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 382
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 63
16.5%
0 62
16.2%
6 45
11.8%
2 45
11.8%
1 43
11.3%
7 30
7.9%
5 25
 
6.5%
3 24
 
6.3%
4 20
 
5.2%
8 17
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 382
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 63
16.5%
0 62
16.2%
6 45
11.8%
2 45
11.8%
1 43
11.3%
7 30
7.9%
5 25
 
6.5%
3 24
 
6.3%
4 20
 
5.2%
8 17
 
4.5%

Correlations

2024-03-15T00:12:43.542024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가공기업명주소연락처
가공기업명1.0001.0001.000
주소1.0001.0001.000
연락처1.0001.0001.000

Missing values

2024-03-15T00:12:36.408689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T00:12:36.652601image/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

가공기업명주소연락처
0농업회사법인 선한세상전라남도 나주시 반남면 월량길 118-15061-336-0388
1바이오테크㈜전라남도 목포시 연산동 1636-5061-278-0963
2대한엽엄조합전라남도 목포시 고하대로 597번길 57061-462-1400
3신안애전라남도 목포시 삼학로 75번길 10061-275-5224
4에코솔트㈜전라남도 무안군 몽탄면 몽탄공단길 35061-454-3303
5어업회사법인 케이솔트㈜전라남도 무안군 청계면 송현리 642-5061-452-8001
6하늘누리함초(미가식품)전라남도 순천시 별량면 송학리 143-21061-744-6484
7㈜태평소금전라남도 신안군 증도면 지도증도로 1083-4061-275-0370
8마하탑전라남도 신안군 임자면 전장포길 182061-275-0290
9영진그린식품㈜전라남도 신안군 지도읍 두류산길 91-41061-275-2330
가공기업명주소연락처
25손봉훈 갯벌 천일염전라남도 신안군 비금면 덕산리 1-2302-2282-0107
26목포신안군농협조합공동사업법인전라남도 신안군 압해읍 회룡길 51-113061-246-0057
27북신안농협전라남도 신안군 지도읍 지도증도로 1061-275-0005
28임자농협전라남도 신안군 임자면 진리길 7061-275-3018
29비금농협전라남도 신안군 비금면 서남문로 791061-275-5251
30도초농협전라남도 시안군 도초면 서남문로 1508061-275-2033
31남신안농협전라남도 신안군 하의면 곰실길 11-35061-275-3600
32압해농협(신장지점)전라남도 신안군 압해읍 압해로 368061-271-0502
33농업법인 삼손푸드㈜전라남도 장성군 북하면 궐전길 87061-392-4478
34㈜죽력원전라남도 화순군 한천면 산음길 161061-371-5777