Overview

Dataset statistics

Number of variables4
Number of observations31
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 KiB
Average record size in memory36.3 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
전화번호 has unique valuesUnique

Reproduction

Analysis started2023-12-11 03:10:35.218033
Analysis finished2023-12-11 03:10:35.743660
Duration0.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체명
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-11T12:10:35.935752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length10
Mean length8.5483871
Min length5

Characters and Unicode

Total characters265
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

Unique31 ?
Unique (%)100.0%

Sample

1st row대한티이씨(주)
2nd row(주)영화기업사
3rd row인천훈증주식회사
4th row글로벌방제주식회사
5th row세림방역(주)
ValueCountFrequency (%)
주식회사 2
 
6.1%
대한티이씨(주 1
 
3.0%
한국방역산업(주 1
 
3.0%
유)대신방역산업 1
 
3.0%
유)대진방역 1
 
3.0%
주)대명에스앤피 1
 
3.0%
주)해암산업 1
 
3.0%
한국방역산업주식회사 1
 
3.0%
경인방역(주 1
 
3.0%
세왕방역(주 1
 
3.0%
Other values (22) 22
66.7%
2023-12-11T12:10:36.371558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 28
 
10.6%
( 25
 
9.4%
) 25
 
9.4%
방 18
 
6.8%
역 11
 
4.2%
식 8
 
3.0%
제 8
 
3.0%
사 8
 
3.0%
회 7
 
2.6%
업 6
 
2.3%
Other values (62) 121
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 210
79.2%
Open Punctuation 25
 
9.4%
Close Punctuation 25
 
9.4%
Uppercase Letter 3
 
1.1%
Space Separator 2
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 28
 
13.3%
방 18
 
8.6%
역 11
 
5.2%
식 8
 
3.8%
제 8
 
3.8%
사 8
 
3.8%
회 7
 
3.3%
업 6
 
2.9%
한 5
 
2.4%
에 5
 
2.4%
Other values (56) 106
50.5%
Uppercase Letter
ValueCountFrequency (%)
S 1
33.3%
P 1
33.3%
C 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 210
79.2%
Common 52
 
19.6%
Latin 3
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 28
 
13.3%
방 18
 
8.6%
역 11
 
5.2%
식 8
 
3.8%
제 8
 
3.8%
사 8
 
3.8%
회 7
 
3.3%
업 6
 
2.9%
한 5
 
2.4%
에 5
 
2.4%
Other values (56) 106
50.5%
Common
ValueCountFrequency (%)
( 25
48.1%
) 25
48.1%
2
 
3.8%
Latin
ValueCountFrequency (%)
S 1
33.3%
P 1
33.3%
C 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 210
79.2%
ASCII 55
 
20.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 28
 
13.3%
방 18
 
8.6%
역 11
 
5.2%
식 8
 
3.8%
제 8
 
3.8%
사 8
 
3.8%
회 7
 
3.3%
업 6
 
2.9%
한 5
 
2.4%
에 5
 
2.4%
Other values (56) 106
50.5%
ASCII
ValueCountFrequency (%)
( 25
45.5%
) 25
45.5%
2
 
3.6%
S 1
 
1.8%
P 1
 
1.8%
C 1
 
1.8%

주소
Text

Distinct30
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-11T12:10:36.718318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length31
Mean length25.387097
Min length17

Characters and Unicode

Total characters787
Distinct characters111
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

Unique29 ?
Unique (%)93.5%

Sample

1st row부산광역시 사하구 동매로 120
2nd row인천광역시 중구 신포로15번길 73
3rd row인천광역시 동구 제물량로 351
4th row울산광역시 남구 용연로 295-109
5th row경기도 평택시 포승읍 포승공단순환로 49
ValueCountFrequency (%)
부산광역시 12
 
7.7%
인천광역시 8
 
5.1%
동구 5
 
3.2%
중구 5
 
3.2%
강서구 5
 
3.2%
남구 4
 
2.6%
사하구 3
 
1.9%
광양시 3
 
1.9%
전라남도 3
 
1.9%
경기도 3
 
1.9%
Other values (89) 105
67.3%
2023-12-11T12:10:37.284873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
149
 
18.9%
시 31
 
3.9%
1 27
 
3.4%
광 25
 
3.2%
구 24
 
3.0%
로 24
 
3.0%
역 22
 
2.8%
2 21
 
2.7%
3 21
 
2.7%
동 20
 
2.5%
Other values (101) 423
53.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 455
57.8%
Decimal Number 150
 
19.1%
Space Separator 149
 
18.9%
Dash Punctuation 11
 
1.4%
Open Punctuation 8
 
1.0%
Close Punctuation 8
 
1.0%
Other Punctuation 5
 
0.6%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 31
 
6.8%
광 25
 
5.5%
구 24
 
5.3%
로 24
 
5.3%
역 22
 
4.8%
동 20
 
4.4%
산 19
 
4.2%
길 18
 
4.0%
부 12
 
2.6%
번 12
 
2.6%
Other values (85) 248
54.5%
Decimal Number
ValueCountFrequency (%)
1 27
18.0%
2 21
14.0%
3 21
14.0%
7 19
12.7%
0 16
10.7%
5 15
10.0%
4 10
 
6.7%
9 9
 
6.0%
6 8
 
5.3%
8 4
 
2.7%
Space Separator
ValueCountFrequency (%)
149
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 455
57.8%
Common 331
42.1%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 31
 
6.8%
광 25
 
5.5%
구 24
 
5.3%
로 24
 
5.3%
역 22
 
4.8%
동 20
 
4.4%
산 19
 
4.2%
길 18
 
4.0%
부 12
 
2.6%
번 12
 
2.6%
Other values (85) 248
54.5%
Common
ValueCountFrequency (%)
149
45.0%
1 27
 
8.2%
2 21
 
6.3%
3 21
 
6.3%
7 19
 
5.7%
0 16
 
4.8%
5 15
 
4.5%
- 11
 
3.3%
4 10
 
3.0%
9 9
 
2.7%
Other values (5) 33
 
10.0%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 455
57.8%
ASCII 332
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
149
44.9%
1 27
 
8.1%
2 21
 
6.3%
3 21
 
6.3%
7 19
 
5.7%
0 16
 
4.8%
5 15
 
4.5%
- 11
 
3.3%
4 10
 
3.0%
9 9
 
2.7%
Other values (6) 34
 
10.2%
Hangul
ValueCountFrequency (%)
시 31
 
6.8%
광 25
 
5.5%
구 24
 
5.3%
로 24
 
5.3%
역 22
 
4.8%
동 20
 
4.4%
산 19
 
4.2%
길 18
 
4.0%
부 12
 
2.6%
번 12
 
2.6%
Other values (85) 248
54.5%

전화번호
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-11T12:10:37.563815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length12.645161
Min length9

Characters and Unicode

Total characters392
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

Unique31 ?
Unique (%)100.0%

Sample

1st row051-203-5719
2nd row032-589-4403
3rd row032-584-3802-3
4th row052-240-8370
5th row031-686-5548
ValueCountFrequency (%)
051-203-5719 1
 
3.1%
032-589-4403 1
 
3.1%
063-467-6154-5 1
 
3.1%
061-792-7890 1
 
3.1%
051-637-4648 1
 
3.1%
054-274-7245 1
 
3.1%
051-326-8871-3 1
 
3.1%
032-579-1346 1
 
3.1%
032-588-1761-2 1
 
3.1%
032-765-7600 1
 
3.1%
Other values (22) 22
68.8%
2023-12-11T12:10:38.000511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 65
16.6%
0 48
12.2%
5 42
10.7%
1 38
9.7%
8 34
8.7%
4 31
7.9%
2 30
7.7%
7 30
7.7%
6 30
7.7%
3 25
 
6.4%
Other values (4) 19
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 321
81.9%
Dash Punctuation 65
 
16.6%
Close Punctuation 3
 
0.8%
Math Symbol 2
 
0.5%
Space Separator 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 48
15.0%
5 42
13.1%
1 38
11.8%
8 34
10.6%
4 31
9.7%
2 30
9.3%
7 30
9.3%
6 30
9.3%
3 25
7.8%
9 13
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 65
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 392
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 65
16.6%
0 48
12.2%
5 42
10.7%
1 38
9.7%
8 34
8.7%
4 31
7.9%
2 30
7.7%
7 30
7.7%
6 30
7.7%
3 25
 
6.4%
Other values (4) 19
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 392
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 65
16.6%
0 48
12.2%
5 42
10.7%
1 38
9.7%
8 34
8.7%
4 31
7.9%
2 30
7.7%
7 30
7.7%
6 30
7.7%
3 25
 
6.4%
Other values (4) 19
 
4.8%

대표자명
Text

Distinct29
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-11T12:10:38.251637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters93
Distinct characters55
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

Unique28 ?
Unique (%)90.3%

Sample

1st row임기택
2nd row주창대
3rd row홍재희
4th row이진우
5th row문봉종
ValueCountFrequency (%)
이진우 3
 
9.7%
임기택 1
 
3.2%
박우진 1
 
3.2%
유인영 1
 
3.2%
김채현 1
 
3.2%
노환덕 1
 
3.2%
강인식 1
 
3.2%
박연진 1
 
3.2%
이난희 1
 
3.2%
전용성 1
 
3.2%
Other values (19) 19
61.3%
2023-12-11T12:10:38.634104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 9
 
9.7%
우 5
 
5.4%
진 5
 
5.4%
홍 4
 
4.3%
성 3
 
3.2%
영 3
 
3.2%
대 2
 
2.2%
박 2
 
2.2%
호 2
 
2.2%
김 2
 
2.2%
Other values (45) 56
60.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 93
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 9
 
9.7%
우 5
 
5.4%
진 5
 
5.4%
홍 4
 
4.3%
성 3
 
3.2%
영 3
 
3.2%
대 2
 
2.2%
박 2
 
2.2%
호 2
 
2.2%
김 2
 
2.2%
Other values (45) 56
60.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 93
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 9
 
9.7%
우 5
 
5.4%
진 5
 
5.4%
홍 4
 
4.3%
성 3
 
3.2%
영 3
 
3.2%
대 2
 
2.2%
박 2
 
2.2%
호 2
 
2.2%
김 2
 
2.2%
Other values (45) 56
60.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 93
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 9
 
9.7%
우 5
 
5.4%
진 5
 
5.4%
홍 4
 
4.3%
성 3
 
3.2%
영 3
 
3.2%
대 2
 
2.2%
박 2
 
2.2%
호 2
 
2.2%
김 2
 
2.2%
Other values (45) 56
60.2%

Correlations

2023-12-11T12:10:39.042524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업체명주소전화번호대표자명
업체명1.0001.0001.0001.000
주소1.0001.0001.0000.988
전화번호1.0001.0001.0001.000
대표자명1.0000.9881.0001.000

Missing values

2023-12-11T12:10:35.592503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T12:10:35.696338image/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
0대한티이씨(주)부산광역시 사하구 동매로 120051-203-5719임기택
1(주)영화기업사인천광역시 중구 신포로15번길 73032-589-4403주창대
2인천훈증주식회사인천광역시 동구 제물량로 351032-584-3802-3홍재희
3글로벌방제주식회사울산광역시 남구 용연로 295-109052-240-8370이진우
4세림방역(주)경기도 평택시 포승읍 포승공단순환로 49031-686-5548문봉종
5(주)금호방역부산광역시 강서구 유통단지1로 76 12-301051-441-7800함영숙
6국제에프티엘(주)부산광역시 동구 중앙대로236번길 10 금호빌딩 501호051-462-8777-9이성우
7PCS(주)전라남도 광양시 중마용소4길 20061-903-1788용근식
8한국종합방제(주)인천광역시 중구 서해대로417번길 27-7032-887-8111~2이웅기
9(주)퍼시픽우진부산광역시 강서구 유통단지1로 76 13동 201호(건축자재판매단지)051-467-5477윤영섭
업체명주소전화번호대표자명
21아주종합방제(주)부산광역시 사하구 동매로 140-1051-465-6400안호제
22(주)명륜인천광역시 중구 신포로27번길 33 3층032-765-7600고도명
23세왕방역(주)인천광역시 동구 방축로 37번길 30, 331동 332호(송현동, 산업용품유통센타1동)032-588-1761-2전용성
24경인방역(주)인천광역시 동구 방축로 83번길 23 (송림동, 인천산업용품유통센타 편익비동 502호)032-579-1346이난희
25한국방역산업주식회사부산광역시 강서구 화전산단2로 70-16051-326-8871-3박연진
26(주)해암산업경상북도 포항시 북구 삼호로74번길 7054-274-7245강인식
27(주)대명에스앤피부산광역시 남구 우암로 75 (감만동)051-637-4648노환덕
28(유)대진방역전라남도 광양시 용지길 67-1 (태인동)061-792-7890김채현
29(유)대신방역산업전라북도 군산시 외항안길 295063-467-6154-5유인영
30한국방역써비스(주)전라북도 군산시 풍전4길 42063-465-0251-2염대환