Overview

Dataset statistics

Number of variables4
Number of observations33
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 KiB
Average record size in memory36.0 B

Variable types

Text4

Dataset

Description농림축산검역본부에 등록되어 있는 운영중인 수출입식물 방제업체 현황입니다.주소와 업체명이 있어 수출입 식물에 대한 훈증소독이 필요할 경우 파일을 확인하여 연락하실 수 있습니다.
URLhttps://www.data.go.kr/data/15102049/fileData.do

Alerts

업체명 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:54:13.554226
Analysis finished2023-12-12 05:54:14.021467
Duration0.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체명
Text

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2023-12-12T14:54:14.182277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length8.7878788
Min length5

Characters and Unicode

Total characters290
Distinct characters74
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)100.0%

Sample

1st row글로벌방제주식회사(광양지점)
2nd row주식회사 도원시스템즈
3rd row(주)영화기업사
4th row한국방역산업주식회사
5th row(주)신우티앤씨
ValueCountFrequency (%)
주식회사 6
 
15.4%
글로벌방제주식회사(광양지점 1
 
2.6%
글로벌방제주식회사 1
 
2.6%
신흥방역 1
 
2.6%
세림방역(주 1
 
2.6%
글로벌방제주식회사(부산지점 1
 
2.6%
국제에프티엘(주 1
 
2.6%
주)영진에프씨 1
 
2.6%
대림방역(주 1
 
2.6%
한국종합방제(주 1
 
2.6%
Other values (24) 24
61.5%
2023-12-12T14:54:14.584317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 32
 
11.0%
( 24
 
8.3%
) 24
 
8.3%
방 17
 
5.9%
역 12
 
4.1%
사 12
 
4.1%
식 11
 
3.8%
회 11
 
3.8%
제 7
 
2.4%
6
 
2.1%
Other values (64) 134
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 233
80.3%
Open Punctuation 24
 
8.3%
Close Punctuation 24
 
8.3%
Space Separator 6
 
2.1%
Uppercase Letter 3
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 32
 
13.7%
방 17
 
7.3%
역 12
 
5.2%
사 12
 
5.2%
식 11
 
4.7%
회 11
 
4.7%
제 7
 
3.0%
에 6
 
2.6%
씨 5
 
2.1%
산 5
 
2.1%
Other values (58) 115
49.4%
Uppercase Letter
ValueCountFrequency (%)
S 1
33.3%
C 1
33.3%
P 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 233
80.3%
Common 54
 
18.6%
Latin 3
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 32
 
13.7%
방 17
 
7.3%
역 12
 
5.2%
사 12
 
5.2%
식 11
 
4.7%
회 11
 
4.7%
제 7
 
3.0%
에 6
 
2.6%
씨 5
 
2.1%
산 5
 
2.1%
Other values (58) 115
49.4%
Common
ValueCountFrequency (%)
( 24
44.4%
) 24
44.4%
6
 
11.1%
Latin
ValueCountFrequency (%)
S 1
33.3%
C 1
33.3%
P 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 233
80.3%
ASCII 57
 
19.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 32
 
13.7%
방 17
 
7.3%
역 12
 
5.2%
사 12
 
5.2%
식 11
 
4.7%
회 11
 
4.7%
제 7
 
3.0%
에 6
 
2.6%
씨 5
 
2.1%
산 5
 
2.1%
Other values (58) 115
49.4%
ASCII
ValueCountFrequency (%)
( 24
42.1%
) 24
42.1%
6
 
10.5%
S 1
 
1.8%
C 1
 
1.8%
P 1
 
1.8%

주소
Text

Distinct32
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2023-12-12T14:54:14.939291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length35
Mean length25.242424
Min length16

Characters and Unicode

Total characters833
Distinct characters121
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

Unique31 ?
Unique (%)93.9%

Sample

1st row전라남도 광양시 항만7로 71-70 2층 201호
2nd row강원도 동해시 효자로 406-1 (쇄운동)
3rd row인천광역시 중구 신포로15번길 73
4th row부산광역시 강서구 화전산단2로 70-16
5th row인천광역시 중구 인항로 6 씨팰리스 A-805
ValueCountFrequency (%)
부산광역시 12
 
7.3%
인천광역시 10
 
6.1%
강서구 7
 
4.3%
중구 6
 
3.7%
동구 4
 
2.4%
남구 3
 
1.8%
2층 3
 
1.8%
광양시 3
 
1.8%
전라남도 3
 
1.8%
전라북도 2
 
1.2%
Other values (98) 111
67.7%
2023-12-12T14:54:15.529582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
151
 
18.1%
시 33
 
4.0%
3 29
 
3.5%
로 27
 
3.2%
광 27
 
3.2%
1 27
 
3.2%
구 26
 
3.1%
2 25
 
3.0%
역 23
 
2.8%
산 21
 
2.5%
Other values (111) 444
53.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 489
58.7%
Decimal Number 163
 
19.6%
Space Separator 151
 
18.1%
Dash Punctuation 9
 
1.1%
Close Punctuation 8
 
1.0%
Open Punctuation 8
 
1.0%
Other Punctuation 3
 
0.4%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 33
 
6.7%
로 27
 
5.5%
광 27
 
5.5%
구 26
 
5.3%
역 23
 
4.7%
산 21
 
4.3%
동 19
 
3.9%
길 18
 
3.7%
인 14
 
2.9%
번 13
 
2.7%
Other values (94) 268
54.8%
Decimal Number
ValueCountFrequency (%)
3 29
17.8%
1 27
16.6%
2 25
15.3%
7 17
10.4%
0 17
10.4%
5 13
8.0%
4 11
 
6.7%
9 10
 
6.1%
6 8
 
4.9%
8 6
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
151
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 489
58.7%
Common 342
41.1%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 33
 
6.7%
로 27
 
5.5%
광 27
 
5.5%
구 26
 
5.3%
역 23
 
4.7%
산 21
 
4.3%
동 19
 
3.9%
길 18
 
3.7%
인 14
 
2.9%
번 13
 
2.7%
Other values (94) 268
54.8%
Common
ValueCountFrequency (%)
151
44.2%
3 29
 
8.5%
1 27
 
7.9%
2 25
 
7.3%
7 17
 
5.0%
0 17
 
5.0%
5 13
 
3.8%
4 11
 
3.2%
9 10
 
2.9%
- 9
 
2.6%
Other values (5) 33
 
9.6%
Latin
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 489
58.7%
ASCII 344
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
151
43.9%
3 29
 
8.4%
1 27
 
7.8%
2 25
 
7.3%
7 17
 
4.9%
0 17
 
4.9%
5 13
 
3.8%
4 11
 
3.2%
9 10
 
2.9%
- 9
 
2.6%
Other values (7) 35
 
10.2%
Hangul
ValueCountFrequency (%)
시 33
 
6.7%
로 27
 
5.5%
광 27
 
5.5%
구 26
 
5.3%
역 23
 
4.7%
산 21
 
4.3%
동 19
 
3.9%
길 18
 
3.7%
인 14
 
2.9%
번 13
 
2.7%
Other values (94) 268
54.8%

전화번호
Text

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2023-12-12T14:54:15.768850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.030303
Min length12

Characters and Unicode

Total characters397
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

Unique33 ?
Unique (%)100.0%

Sample

1st row061-792-7891
2nd row033-252-0324
3rd row032-589-4403
4th row051-326-8871
5th row032-886-4417
ValueCountFrequency (%)
061-792-7891 1
 
3.0%
032-579-1346 1
 
3.0%
063-467-6154 1
 
3.0%
061-792-7890 1
 
3.0%
051-637-4648 1
 
3.0%
032-887-8114 1
 
3.0%
051-469-2149 1
 
3.0%
051-467-5477 1
 
3.0%
032-887-8111 1
 
3.0%
052-240-8370 1
 
3.0%
Other values (23) 23
69.7%
2023-12-12T14:54:16.133688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 66
16.6%
0 50
12.6%
1 41
10.3%
5 38
9.6%
6 33
8.3%
7 33
8.3%
2 32
8.1%
4 32
8.1%
8 31
7.8%
3 26
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 331
83.4%
Dash Punctuation 66
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 50
15.1%
1 41
12.4%
5 38
11.5%
6 33
10.0%
7 33
10.0%
2 32
9.7%
4 32
9.7%
8 31
9.4%
3 26
7.9%
9 15
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 66
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 397
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 66
16.6%
0 50
12.6%
1 41
10.3%
5 38
9.6%
6 33
8.3%
7 33
8.3%
2 32
8.1%
4 32
8.1%
8 31
7.8%
3 26
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 397
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 66
16.6%
0 50
12.6%
1 41
10.3%
5 38
9.6%
6 33
8.3%
7 33
8.3%
2 32
8.1%
4 32
8.1%
8 31
7.8%
3 26
 
6.5%

대표자명
Text

Distinct30
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size396.0 B
2023-12-12T14:54:16.339501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.1515152
Min length3

Characters and Unicode

Total characters104
Distinct characters55
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)84.8%

Sample

1st row이광형
2nd row김기익
3rd row정한종, 장청용
4th row김영환
5th row이성운
ValueCountFrequency (%)
이광형 3
 
8.8%
황현숙 2
 
5.9%
홍재희 1
 
2.9%
박재성 1
 
2.9%
송수연 1
 
2.9%
김채현 1
 
2.9%
노환덕 1
 
2.9%
박우진 1
 
2.9%
이돈홍 1
 
2.9%
윤영섭 1
 
2.9%
Other values (21) 21
61.8%
2023-12-12T14:54:16.758982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 7
 
6.7%
김 6
 
5.8%
형 4
 
3.8%
박 4
 
3.8%
성 4
 
3.8%
환 4
 
3.8%
용 3
 
2.9%
수 3
 
2.9%
광 3
 
2.9%
기 3
 
2.9%
Other values (45) 63
60.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 102
98.1%
Other Punctuation 1
 
1.0%
Space Separator 1
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 7
 
6.9%
김 6
 
5.9%
형 4
 
3.9%
박 4
 
3.9%
성 4
 
3.9%
환 4
 
3.9%
용 3
 
2.9%
수 3
 
2.9%
광 3
 
2.9%
기 3
 
2.9%
Other values (43) 61
59.8%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 102
98.1%
Common 2
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 7
 
6.9%
김 6
 
5.9%
형 4
 
3.9%
박 4
 
3.9%
성 4
 
3.9%
환 4
 
3.9%
용 3
 
2.9%
수 3
 
2.9%
광 3
 
2.9%
기 3
 
2.9%
Other values (43) 61
59.8%
Common
ValueCountFrequency (%)
, 1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 102
98.1%
ASCII 2
 
1.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 7
 
6.9%
김 6
 
5.9%
형 4
 
3.9%
박 4
 
3.9%
성 4
 
3.9%
환 4
 
3.9%
용 3
 
2.9%
수 3
 
2.9%
광 3
 
2.9%
기 3
 
2.9%
Other values (43) 61
59.8%
ASCII
ValueCountFrequency (%)
, 1
50.0%
1
50.0%

Correlations

2023-12-12T14:54:16.867607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업체명주소전화번호대표자명
업체명1.0001.0001.0001.000
주소1.0001.0001.0000.972
전화번호1.0001.0001.0001.000
대표자명1.0000.9721.0001.000

Missing values

2023-12-12T14:54:13.889855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:54:13.982409image/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

업체명주소전화번호대표자명
0글로벌방제주식회사(광양지점)전라남도 광양시 항만7로 71-70 2층 201호061-792-7891이광형
1주식회사 도원시스템즈강원도 동해시 효자로 406-1 (쇄운동)033-252-0324김기익
2(주)영화기업사인천광역시 중구 신포로15번길 73032-589-4403정한종, 장청용
3한국방역산업주식회사부산광역시 강서구 화전산단2로 70-16051-326-8871김영환
4(주)신우티앤씨인천광역시 중구 인항로 6 씨팰리스 A-805032-886-4417이성운
5대한티이씨(주)부산광역시 강서구 화전산단4로 39051-203-5719임기택
6주식회사 에코스캔부산광역시 금정구 중앙대로 2074 2층051-791-1661김민성
7아주종합방제(주)부산광역시 사하구 동매로 140-1051-465-6400황현숙
8주식회사 케이글로벌경상남도 창원시 진해구 신항8로 351051-717-2518임한규
9(주)명륜인천광역시 중구 신포로27번길 33 3층032-765-7600고동환
업체명주소전화번호대표자명
23대림방역(주)부산광역시 사하구 하신번영로 135 507호(신평동, 신평빌딩)051-466-4876황현숙
24글로벌방제주식회사울산광역시 남구 용연로 295-109052-240-8370이광형
25한국종합방제(주)인천광역시 중구 서해대로417번길 27-7032-887-8111이웅기
26(주)퍼시픽우진부산광역시 강서구 유통단지1로 76 13동 201호(건축자재판매단지)051-467-5477윤영섭
27주식회사 우리에프앤씨부산광역시 강서구 새진목길18번길 3051-469-2149이돈홍
28한국방역산업(주)인천광역시 중구 서해대로417번길 27-9032-887-8114박우진
29(주)대명에스앤피부산광역시 남구 우암로 75051-637-4648노환덕
30(유)대진방역전라남도 광양시 용지길 67-1061-792-7890김채현
31(유)대신방역산업전라북도 군산시 외항안길 295063-467-6154송수연
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