Overview

Dataset statistics

Number of variables4
Number of observations758
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)0.1%
Total size in memory23.8 KiB
Average record size in memory32.2 B

Variable types

Text4

Dataset

Description목재포장재에 대한 열처리업을 수행하고 있는 수출입목재 열처리업체 목록 입니다.
Author농림축산검역본부
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20220215000000001895

Alerts

Dataset has 1 (0.1%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-11 03:06:24.703108
Analysis finished2023-12-11 03:06:25.228091
Duration0.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체명
Text

Distinct729
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
2023-12-11T12:06:25.384871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length15
Mean length7.1873351
Min length2

Characters and Unicode

Total characters5448
Distinct characters283
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique702 ?
Unique (%)92.6%

Sample

1st row주식회사 진성
2nd row(주)뉴-그린
3rd row(주)신흥지엔티 평택공장
4th row대진산업(주)
5th row(주)송덕패키징
ValueCountFrequency (%)
주식회사 71
 
8.3%
주)한성목재 5
 
0.6%
주)성은글로벌 3
 
0.4%
한성수출포장 3
 
0.4%
명성수출포장 3
 
0.4%
금강수출포장 2
 
0.2%
대원수출포장 2
 
0.2%
주)일성수출포장 2
 
0.2%
한국수출포장 2
 
0.2%
수출포장 2
 
0.2%
Other values (734) 762
88.9%
2023-12-11T12:06:25.719231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 377
 
6.9%
장 322
 
5.9%
포 314
 
5.8%
( 292
 
5.4%
) 292
 
5.4%
수 249
 
4.6%
출 237
 
4.4%
재 191
 
3.5%
목 186
 
3.4%
산 106
 
1.9%
Other values (273) 2882
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4694
86.2%
Open Punctuation 292
 
5.4%
Close Punctuation 292
 
5.4%
Space Separator 99
 
1.8%
Other Symbol 30
 
0.6%
Uppercase Letter 30
 
0.6%
Lowercase Letter 5
 
0.1%
Other Punctuation 3
 
0.1%
Decimal Number 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 377
 
8.0%
장 322
 
6.9%
포 314
 
6.7%
수 249
 
5.3%
출 237
 
5.0%
재 191
 
4.1%
목 186
 
4.0%
산 106
 
2.3%
사 100
 
2.1%
업 96
 
2.0%
Other values (246) 2516
53.6%
Uppercase Letter
ValueCountFrequency (%)
S 5
16.7%
E 3
10.0%
G 3
10.0%
J 3
10.0%
K 2
 
6.7%
P 2
 
6.7%
B 2
 
6.7%
N 2
 
6.7%
D 2
 
6.7%
L 2
 
6.7%
Other values (4) 4
13.3%
Lowercase Letter
ValueCountFrequency (%)
m 1
20.0%
o 1
20.0%
g 1
20.0%
i 1
20.0%
s 1
20.0%
Other Punctuation
ValueCountFrequency (%)
& 2
66.7%
. 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 292
100.0%
Close Punctuation
ValueCountFrequency (%)
) 292
100.0%
Space Separator
ValueCountFrequency (%)
99
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 30
100.0%
Decimal Number
ValueCountFrequency (%)
2 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4724
86.7%
Common 689
 
12.6%
Latin 35
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 377
 
8.0%
장 322
 
6.8%
포 314
 
6.6%
수 249
 
5.3%
출 237
 
5.0%
재 191
 
4.0%
목 186
 
3.9%
산 106
 
2.2%
사 100
 
2.1%
업 96
 
2.0%
Other values (247) 2546
53.9%
Latin
ValueCountFrequency (%)
S 5
14.3%
E 3
 
8.6%
G 3
 
8.6%
J 3
 
8.6%
K 2
 
5.7%
P 2
 
5.7%
B 2
 
5.7%
N 2
 
5.7%
D 2
 
5.7%
L 2
 
5.7%
Other values (9) 9
25.7%
Common
ValueCountFrequency (%)
( 292
42.4%
) 292
42.4%
99
 
14.4%
2 2
 
0.3%
& 2
 
0.3%
- 1
 
0.1%
. 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4694
86.2%
ASCII 724
 
13.3%
None 30
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 377
 
8.0%
장 322
 
6.9%
포 314
 
6.7%
수 249
 
5.3%
출 237
 
5.0%
재 191
 
4.1%
목 186
 
4.0%
산 106
 
2.3%
사 100
 
2.1%
업 96
 
2.0%
Other values (246) 2516
53.6%
ASCII
ValueCountFrequency (%)
( 292
40.3%
) 292
40.3%
99
 
13.7%
S 5
 
0.7%
E 3
 
0.4%
G 3
 
0.4%
J 3
 
0.4%
2 2
 
0.3%
K 2
 
0.3%
P 2
 
0.3%
Other values (16) 21
 
2.9%
None
ValueCountFrequency (%)
㈜ 30
100.0%

주소
Text

Distinct751
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
2023-12-11T12:06:25.980451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length31
Mean length21.850923
Min length14

Characters and Unicode

Total characters16563
Distinct characters324
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

Unique744 ?
Unique (%)98.2%

Sample

1st row인천광역시 서구 북항로363번길 58
2nd row경기도 화성시 향남읍 토성로359번길 10
3rd row경기도 평택시 은실5길 90
4th row전라남도 여수시 율촌면 호산길 29-13
5th row경상북도 칠곡군 석적읍 중지3길 68
ValueCountFrequency (%)
경기도 186
 
5.1%
경상남도 160
 
4.4%
경상북도 89
 
2.4%
부산광역시 76
 
2.1%
김해시 70
 
1.9%
화성시 66
 
1.8%
강서구 64
 
1.7%
인천광역시 58
 
1.6%
충청남도 50
 
1.4%
서구 39
 
1.1%
Other values (1511) 2814
76.6%
2023-12-11T12:06:26.376429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2920
 
17.6%
시 699
 
4.2%
1 640
 
3.9%
도 593
 
3.6%
로 571
 
3.4%
경 469
 
2.8%
2 429
 
2.6%
길 409
 
2.5%
산 374
 
2.3%
3 370
 
2.2%
Other values (314) 9089
54.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10283
62.1%
Decimal Number 3085
 
18.6%
Space Separator 2920
 
17.6%
Dash Punctuation 253
 
1.5%
Other Punctuation 10
 
0.1%
Uppercase Letter 10
 
0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 699
 
6.8%
도 593
 
5.8%
로 571
 
5.6%
경 469
 
4.6%
길 409
 
4.0%
산 374
 
3.6%
면 367
 
3.6%
남 332
 
3.2%
구 293
 
2.8%
상 273
 
2.7%
Other values (292) 5903
57.4%
Decimal Number
ValueCountFrequency (%)
1 640
20.7%
2 429
13.9%
3 370
12.0%
4 273
8.8%
6 260
8.4%
7 241
 
7.8%
5 230
 
7.5%
8 228
 
7.4%
9 213
 
6.9%
0 201
 
6.5%
Uppercase Letter
ValueCountFrequency (%)
B 3
30.0%
D 2
20.0%
C 2
20.0%
L 2
20.0%
A 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 8
80.0%
. 1
 
10.0%
/ 1
 
10.0%
Space Separator
ValueCountFrequency (%)
2920
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 253
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10283
62.1%
Common 6270
37.9%
Latin 10
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 699
 
6.8%
도 593
 
5.8%
로 571
 
5.6%
경 469
 
4.6%
길 409
 
4.0%
산 374
 
3.6%
면 367
 
3.6%
남 332
 
3.2%
구 293
 
2.8%
상 273
 
2.7%
Other values (292) 5903
57.4%
Common
ValueCountFrequency (%)
2920
46.6%
1 640
 
10.2%
2 429
 
6.8%
3 370
 
5.9%
4 273
 
4.4%
6 260
 
4.1%
- 253
 
4.0%
7 241
 
3.8%
5 230
 
3.7%
8 228
 
3.6%
Other values (7) 426
 
6.8%
Latin
ValueCountFrequency (%)
B 3
30.0%
D 2
20.0%
C 2
20.0%
L 2
20.0%
A 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10283
62.1%
ASCII 6280
37.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2920
46.5%
1 640
 
10.2%
2 429
 
6.8%
3 370
 
5.9%
4 273
 
4.3%
6 260
 
4.1%
- 253
 
4.0%
7 241
 
3.8%
5 230
 
3.7%
8 228
 
3.6%
Other values (12) 436
 
6.9%
Hangul
ValueCountFrequency (%)
시 699
 
6.8%
도 593
 
5.8%
로 571
 
5.6%
경 469
 
4.6%
길 409
 
4.0%
산 374
 
3.6%
면 367
 
3.6%
남 332
 
3.2%
구 293
 
2.8%
상 273
 
2.7%
Other values (292) 5903
57.4%

전화번호
Text

Distinct739
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
2023-12-11T12:06:26.608884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.769129
Min length1

Characters and Unicode

Total characters8921
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

Unique734 ?
Unique (%)96.8%

Sample

1st row032-575-7600
2nd row031-354-3100
3rd row031-652-5451
4th row061-683-6363
5th row054-975-3242
ValueCountFrequency (%)
16
 
2.1%
061-683-9171 2
 
0.3%
041-641-2165 2
 
0.3%
031-354-3100 2
 
0.3%
062-945-8161 2
 
0.3%
055-716-1288 1
 
0.1%
055-342-8861 1
 
0.1%
055-385-3115 1
 
0.1%
031-508-0902 1
 
0.1%
055-586-5582 1
 
0.1%
Other values (729) 729
96.2%
2023-12-11T12:06:26.968221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1494
16.7%
0 1193
13.4%
5 1108
12.4%
3 950
10.6%
1 796
8.9%
2 705
7.9%
4 687
7.7%
6 543
 
6.1%
7 523
 
5.9%
8 487
 
5.5%
Other values (2) 435
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7426
83.2%
Dash Punctuation 1494
 
16.7%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1193
16.1%
5 1108
14.9%
3 950
12.8%
1 796
10.7%
2 705
9.5%
4 687
9.3%
6 543
7.3%
7 523
7.0%
8 487
6.6%
9 434
 
5.8%
Dash Punctuation
ValueCountFrequency (%)
- 1494
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8921
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1494
16.7%
0 1193
13.4%
5 1108
12.4%
3 950
10.6%
1 796
8.9%
2 705
7.9%
4 687
7.7%
6 543
 
6.1%
7 523
 
5.9%
8 487
 
5.5%
Other values (2) 435
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8921
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1494
16.7%
0 1193
13.4%
5 1108
12.4%
3 950
10.6%
1 796
8.9%
2 705
7.9%
4 687
7.7%
6 543
 
6.1%
7 523
 
5.9%
8 487
 
5.5%
Other values (2) 435
 
4.9%

대표자명
Text

Distinct722
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
2023-12-11T12:06:27.304459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length3
Mean length3.1266491
Min length2

Characters and Unicode

Total characters2370
Distinct characters204
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

Unique691 ?
Unique (%)91.2%

Sample

1st row홍진기
2nd row이윤기
3rd row구본재
4th row최대식
5th row이재필,이길희
ValueCountFrequency (%)
구민모 6
 
0.8%
이은학 3
 
0.4%
이대영 2
 
0.3%
이천호 2
 
0.3%
최진식 2
 
0.3%
정호영 2
 
0.3%
박재홍 2
 
0.3%
최성훈 2
 
0.3%
이상범 2
 
0.3%
이경호 2
 
0.3%
Other values (731) 756
96.8%
2023-12-11T12:06:27.748041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 143
 
6.0%
김 140
 
5.9%
정 79
 
3.3%
영 66
 
2.8%
박 55
 
2.3%
성 53
 
2.2%
수 44
 
1.9%
현 41
 
1.7%
종 38
 
1.6%
재 38
 
1.6%
Other values (194) 1673
70.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2319
97.8%
Space Separator 24
 
1.0%
Other Punctuation 16
 
0.7%
Uppercase Letter 9
 
0.4%
Decimal Number 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 143
 
6.2%
김 140
 
6.0%
정 79
 
3.4%
영 66
 
2.8%
박 55
 
2.4%
성 53
 
2.3%
수 44
 
1.9%
현 41
 
1.8%
종 38
 
1.6%
재 38
 
1.6%
Other values (184) 1622
69.9%
Uppercase Letter
ValueCountFrequency (%)
A 2
22.2%
N 2
22.2%
T 1
11.1%
R 1
11.1%
V 1
11.1%
K 1
11.1%
Y 1
11.1%
Space Separator
ValueCountFrequency (%)
24
100.0%
Other Punctuation
ValueCountFrequency (%)
, 16
100.0%
Decimal Number
ValueCountFrequency (%)
1 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2319
97.8%
Common 42
 
1.8%
Latin 9
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 143
 
6.2%
김 140
 
6.0%
정 79
 
3.4%
영 66
 
2.8%
박 55
 
2.4%
성 53
 
2.3%
수 44
 
1.9%
현 41
 
1.8%
종 38
 
1.6%
재 38
 
1.6%
Other values (184) 1622
69.9%
Latin
ValueCountFrequency (%)
A 2
22.2%
N 2
22.2%
T 1
11.1%
R 1
11.1%
V 1
11.1%
K 1
11.1%
Y 1
11.1%
Common
ValueCountFrequency (%)
24
57.1%
, 16
38.1%
1 2
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2319
97.8%
ASCII 51
 
2.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 143
 
6.2%
김 140
 
6.0%
정 79
 
3.4%
영 66
 
2.8%
박 55
 
2.4%
성 53
 
2.3%
수 44
 
1.9%
현 41
 
1.8%
종 38
 
1.6%
재 38
 
1.6%
Other values (184) 1622
69.9%
ASCII
ValueCountFrequency (%)
24
47.1%
, 16
31.4%
1 2
 
3.9%
A 2
 
3.9%
N 2
 
3.9%
T 1
 
2.0%
R 1
 
2.0%
V 1
 
2.0%
K 1
 
2.0%
Y 1
 
2.0%

Missing values

2023-12-11T12:06:25.128830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T12:06:25.199246image/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
0주식회사 진성인천광역시 서구 북항로363번길 58032-575-7600홍진기
1(주)뉴-그린경기도 화성시 향남읍 토성로359번길 10031-354-3100이윤기
2(주)신흥지엔티 평택공장경기도 평택시 은실5길 90031-652-5451구본재
3대진산업(주)전라남도 여수시 율촌면 호산길 29-13061-683-6363최대식
4(주)송덕패키징경상북도 칠곡군 석적읍 중지3길 68054-975-3242이재필,이길희
5(주)형진목재부산광역시 강서구 녹산산단381로86번길 14-21051-831-0748조희관
6(주)서울수출포장경기도 화성시 양감면 초록로 660031-352-8420임경빈
7㈜신영목재전라북도 군산시 외항로 1148063-464-9830김종환
8(주)한진수출포장경기도 안산시 단원구 번영1로 56031-497-0345공귀상
9(주)서경산업경기도 화성시 남양읍 무하로36번길 46031-357-8049홍사용
업체명주소전화번호대표자명
748진화기업경상남도 양산시 원동면 영포길 39055-364-3329이석현
749우진포장경기도 시흥시 군자로 260-진숙영
750(주)케이엠티엘에스충청남도 아산시 음봉면 월산로201번길 26-36041-543-5333방귀중
751(주)선용경상남도 김해시 주촌면 서부로1637번길 115-35055-343-0133강경훈
752주식회사 대성수출포장경상남도 김해시 진영읍 진영로 383055-346-7601최백수
753(주)에이스인팩경상북도 구미시 옥계2공단로5길 39054-461-8230양재호
754광신수출포장충청북도 옥천군 옥천읍 옥천동이로 231043-731-0295김중운
755자일자동차(주)인천광역시 부평구 부평대로 283 제6층 제에이-605호032-932-1320백병수
756대한수출포장 김해점경상남도 김해시 한림면 한림로515번길 151055-346-4320이승훈, 송경석
757(주)한제경상북도 고령군 개진면 양전공단길 171093592718박민규

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업체명주소전화번호대표자명# duplicates
0화성산업(주)전라남도 여수시 소라면 덕양로 377061-683-9171김철곤2