Overview

Dataset statistics

Number of variables4
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 KiB
Average record size in memory36.4 B

Variable types

Text4

Dataset

Description전국에 수출입식물방제업 신고증을 받은 업체정보를 제공하는 서비스
Author농림축산검역본부
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20220214000000001887

Alerts

업체명 has unique valuesUnique
주소 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2023-12-11 03:11:06.079803
Analysis finished2023-12-11 03:11:06.480652
Duration0.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-11T12:11:06.657970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length10.5
Mean length8.5666667
Min length5

Characters and Unicode

Total characters257
Distinct characters72
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

Unique30 ?
Unique (%)100.0%

Sample

1st row평택당진방역(주)
2nd row국제에프티엘(주)
3rd row대한티이씨(주)
4th row(주)영화기업사
5th row인천훈증주식회사
ValueCountFrequency (%)
주식회사 2
 
6.2%
평택당진방역(주 1
 
3.1%
대림방역(주 1
 
3.1%
유)대신방역산업 1
 
3.1%
유)대진방역 1
 
3.1%
주)대명에스앤피 1
 
3.1%
주)해암산업 1
 
3.1%
한국방역산업주식회사 1
 
3.1%
경인방역(주 1
 
3.1%
세왕방역(주 1
 
3.1%
Other values (21) 21
65.6%
2023-12-11T12:11:07.153135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 28
 
10.9%
( 24
 
9.3%
) 24
 
9.3%
방 17
 
6.6%
역 11
 
4.3%
사 8
 
3.1%
식 8
 
3.1%
제 7
 
2.7%
회 7
 
2.7%
업 6
 
2.3%
Other values (62) 117
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 204
79.4%
Open Punctuation 24
 
9.3%
Close Punctuation 24
 
9.3%
Uppercase Letter 3
 
1.2%
Space Separator 2
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 28
 
13.7%
방 17
 
8.3%
역 11
 
5.4%
사 8
 
3.9%
식 8
 
3.9%
제 7
 
3.4%
회 7
 
3.4%
업 6
 
2.9%
씨 5
 
2.5%
대 5
 
2.5%
Other values (56) 102
50.0%
Uppercase Letter
ValueCountFrequency (%)
P 1
33.3%
C 1
33.3%
S 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 204
79.4%
Common 50
 
19.5%
Latin 3
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 28
 
13.7%
방 17
 
8.3%
역 11
 
5.4%
사 8
 
3.9%
식 8
 
3.9%
제 7
 
3.4%
회 7
 
3.4%
업 6
 
2.9%
씨 5
 
2.5%
대 5
 
2.5%
Other values (56) 102
50.0%
Common
ValueCountFrequency (%)
( 24
48.0%
) 24
48.0%
2
 
4.0%
Latin
ValueCountFrequency (%)
P 1
33.3%
C 1
33.3%
S 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 204
79.4%
ASCII 53
 
20.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 28
 
13.7%
방 17
 
8.3%
역 11
 
5.4%
사 8
 
3.9%
식 8
 
3.9%
제 7
 
3.4%
회 7
 
3.4%
업 6
 
2.9%
씨 5
 
2.5%
대 5
 
2.5%
Other values (56) 102
50.0%
ASCII
ValueCountFrequency (%)
( 24
45.3%
) 24
45.3%
2
 
3.8%
P 1
 
1.9%
C 1
 
1.9%
S 1
 
1.9%

주소
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-11T12:11:07.508291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length29
Mean length25.766667
Min length17

Characters and Unicode

Total characters773
Distinct characters113
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

Unique30 ?
Unique (%)100.0%

Sample

1st row경기도 평택시 포승읍 신영리 951 (평택당진항만내)
2nd row부산광역시 동구 중앙대로236번길 10 금호빌딩 501호
3rd row부산광역시 사하구 동매로9번길 20
4th row인천광역시 중구 신포로15번길 73
5th row인천광역시 동구 제물량로 351
ValueCountFrequency (%)
부산광역시 12
 
7.8%
인천광역시 8
 
5.2%
동구 5
 
3.3%
강서구 5
 
3.3%
중구 5
 
3.3%
경기도 3
 
2.0%
광양시 3
 
2.0%
전라남도 3
 
2.0%
사하구 3
 
2.0%
남구 3
 
2.0%
Other values (90) 103
67.3%
2023-12-11T12:11:08.092413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
145
 
18.8%
시 30
 
3.9%
1 26
 
3.4%
광 24
 
3.1%
구 23
 
3.0%
로 22
 
2.8%
역 21
 
2.7%
2 20
 
2.6%
3 20
 
2.6%
길 19
 
2.5%
Other values (103) 423
54.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 453
58.6%
Space Separator 145
 
18.8%
Decimal Number 142
 
18.4%
Dash Punctuation 9
 
1.2%
Close Punctuation 9
 
1.2%
Open Punctuation 9
 
1.2%
Other Punctuation 5
 
0.6%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 30
 
6.6%
광 24
 
5.3%
구 23
 
5.1%
로 22
 
4.9%
역 21
 
4.6%
길 19
 
4.2%
동 19
 
4.2%
산 18
 
4.0%
번 13
 
2.9%
부 12
 
2.6%
Other values (87) 252
55.6%
Decimal Number
ValueCountFrequency (%)
1 26
18.3%
2 20
14.1%
3 20
14.1%
7 18
12.7%
0 15
10.6%
5 13
9.2%
9 9
 
6.3%
4 9
 
6.3%
6 8
 
5.6%
8 4
 
2.8%
Space Separator
ValueCountFrequency (%)
145
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 453
58.6%
Common 319
41.3%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 30
 
6.6%
광 24
 
5.3%
구 23
 
5.1%
로 22
 
4.9%
역 21
 
4.6%
길 19
 
4.2%
동 19
 
4.2%
산 18
 
4.0%
번 13
 
2.9%
부 12
 
2.6%
Other values (87) 252
55.6%
Common
ValueCountFrequency (%)
145
45.5%
1 26
 
8.2%
2 20
 
6.3%
3 20
 
6.3%
7 18
 
5.6%
0 15
 
4.7%
5 13
 
4.1%
- 9
 
2.8%
) 9
 
2.8%
( 9
 
2.8%
Other values (5) 35
 
11.0%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 453
58.6%
ASCII 320
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
145
45.3%
1 26
 
8.1%
2 20
 
6.2%
3 20
 
6.2%
7 18
 
5.6%
0 15
 
4.7%
5 13
 
4.1%
- 9
 
2.8%
) 9
 
2.8%
( 9
 
2.8%
Other values (6) 36
 
11.2%
Hangul
ValueCountFrequency (%)
시 30
 
6.6%
광 24
 
5.3%
구 23
 
5.1%
로 22
 
4.9%
역 21
 
4.6%
길 19
 
4.2%
동 19
 
4.2%
산 18
 
4.0%
번 13
 
2.9%
부 12
 
2.6%
Other values (87) 252
55.6%

전화번호
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-11T12:11:08.379740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length12.666667
Min length9

Characters and Unicode

Total characters380
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row031) 6817288
2nd row051-462-8777-9
3rd row051-203-5719
4th row032-589-4403
5th row032-584-3802-3
ValueCountFrequency (%)
031 1
 
3.2%
051-466-4876-7 1
 
3.2%
063-467-6154-5 1
 
3.2%
061-792-7890 1
 
3.2%
051-637-4648 1
 
3.2%
054-274-7245 1
 
3.2%
051-326-8871-3 1
 
3.2%
032-579-1346 1
 
3.2%
032-588-1761-2 1
 
3.2%
032-765-7600 1
 
3.2%
Other values (21) 21
67.7%
2023-12-11T12:11:08.799882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 64
16.8%
0 46
12.1%
1 40
10.5%
5 34
8.9%
8 33
8.7%
6 31
8.2%
4 31
8.2%
7 30
7.9%
2 29
7.6%
3 23
 
6.1%
Other values (4) 19
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 311
81.8%
Dash Punctuation 64
 
16.8%
Close Punctuation 2
 
0.5%
Math Symbol 2
 
0.5%
Space Separator 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 46
14.8%
1 40
12.9%
5 34
10.9%
8 33
10.6%
6 31
10.0%
4 31
10.0%
7 30
9.6%
2 29
9.3%
3 23
7.4%
9 14
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 64
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 380
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 64
16.8%
0 46
12.1%
1 40
10.5%
5 34
8.9%
8 33
8.7%
6 31
8.2%
4 31
8.2%
7 30
7.9%
2 29
7.6%
3 23
 
6.1%
Other values (4) 19
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 380
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 64
16.8%
0 46
12.1%
1 40
10.5%
5 34
8.9%
8 33
8.7%
6 31
8.2%
4 31
8.2%
7 30
7.9%
2 29
7.6%
3 23
 
6.1%
Other values (4) 19
 
5.0%

대표자명
Text

Distinct26
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-11T12:11:08.995585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters90
Distinct characters51
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

Unique23 ?
Unique (%)76.7%

Sample

1st row홍재희
2nd row김호윤
3rd row임기택
4th row주창대
5th row홍재희
ValueCountFrequency (%)
이진우 3
 
10.0%
홍재희 2
 
6.7%
김호윤 2
 
6.7%
이성운 1
 
3.3%
박우진 1
 
3.3%
유인영 1
 
3.3%
김채현 1
 
3.3%
노환덕 1
 
3.3%
강인식 1
 
3.3%
박연진 1
 
3.3%
Other values (16) 16
53.3%
2023-12-11T12:11:09.340562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 8
 
8.9%
진 5
 
5.6%
우 4
 
4.4%
홍 4
 
4.4%
김 3
 
3.3%
호 3
 
3.3%
윤 3
 
3.3%
재 3
 
3.3%
희 3
 
3.3%
영 3
 
3.3%
Other values (41) 51
56.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 90
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 8
 
8.9%
진 5
 
5.6%
우 4
 
4.4%
홍 4
 
4.4%
김 3
 
3.3%
호 3
 
3.3%
윤 3
 
3.3%
재 3
 
3.3%
희 3
 
3.3%
영 3
 
3.3%
Other values (41) 51
56.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 90
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 8
 
8.9%
진 5
 
5.6%
우 4
 
4.4%
홍 4
 
4.4%
김 3
 
3.3%
호 3
 
3.3%
윤 3
 
3.3%
재 3
 
3.3%
희 3
 
3.3%
영 3
 
3.3%
Other values (41) 51
56.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 90
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 8
 
8.9%
진 5
 
5.6%
우 4
 
4.4%
홍 4
 
4.4%
김 3
 
3.3%
호 3
 
3.3%
윤 3
 
3.3%
재 3
 
3.3%
희 3
 
3.3%
영 3
 
3.3%
Other values (41) 51
56.7%

Correlations

2023-12-11T12:11:09.455474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업체명주소전화번호대표자명
업체명1.0001.0001.0001.000
주소1.0001.0001.0001.000
전화번호1.0001.0001.0001.000
대표자명1.0001.0001.0001.000

Missing values

2023-12-11T12:11:06.355941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T12:11:06.444818image/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
0평택당진방역(주)경기도 평택시 포승읍 신영리 951 (평택당진항만내)031) 6817288홍재희
1국제에프티엘(주)부산광역시 동구 중앙대로236번길 10 금호빌딩 501호051-462-8777-9김호윤
2대한티이씨(주)부산광역시 사하구 동매로9번길 20051-203-5719임기택
3(주)영화기업사인천광역시 중구 신포로15번길 73032-589-4403주창대
4인천훈증주식회사인천광역시 동구 제물량로 351032-584-3802-3홍재희
5글로벌방제주식회사울산광역시 남구 용연로 295-109052-240-8370이진우
6세림방역(주)경기도 평택시 포승읍 포승공단순환로 49031-686-5548문봉종
7(주)금호방역부산광역시 강서구 유통단지1로 76 12-301051-441-7800함영숙
8PCS(주)전라남도 광양시 중마용소4길 20061-903-1788용근식
9한국종합방제(주)인천광역시 중구 서해대로417번길 27-7032-887-8111~2이웅기
업체명주소전화번호대표자명
20아주종합방제(주)부산광역시 사하구 동매로 140-1051-465-6400안호제
21(주)명륜인천광역시 중구 신포로27번길 33 3층032-765-7600고도명
22세왕방역(주)인천광역시 동구 방축로 37번길 30, 331동 332호(송현동, 산업용품유통센타1동)032-588-1761-2전용성
23경인방역(주)인천광역시 동구 방축로 83번길 23 (송림동, 인천산업용품유통센타 편익비동 502호)032-579-1346이난희
24한국방역산업주식회사부산광역시 강서구 화전산단2로 70-16051-326-8871-3박연진
25(주)해암산업경상북도 포항시 북구 삼호로74번길 7054-274-7245강인식
26(주)대명에스앤피부산광역시 남구 우암로 75 (감만동)051-637-4648노환덕
27(유)대진방역전라남도 광양시 용지길 67-1 (태인동)061-792-7890김채현
28(유)대신방역산업전라북도 군산시 외항안길 295063-467-6154-5유인영
29한국방역써비스(주)전라북도 군산시 풍전4길 42063-465-0251-2염대환