Overview

Dataset statistics

Number of variables4
Number of observations325
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.3 KiB
Average record size in memory32.4 B

Variable types

Categorical1
Text3

Dataset

Description인천광역시 연수구 축산물위생업 현황으로써 사업장 명칭, 전화번호 등의 목록- 사업장명, 권리주체명, 소재지주소(지번), 소재지전화로 구분
Author인천광역시 연수구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15087374&srcSe=7661IVAWM27C61E190

Reproduction

Analysis started2024-01-28 17:06:07.298299
Analysis finished2024-01-28 17:06:07.819636
Duration0.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct8
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
식육판매업
130 
식육즉석판매가공업
106 
축산물유통전문판매업
39 
우유류판매업
38 
식육포장처리업
 
7
Other values (3)
 
5

Length

Max length10
Median length9
Mean length7.1230769
Min length5

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row식용란수집판매업
2nd row식용란수집판매업
3rd row식육부산물전문판매업
4th row식육부산물전문판매업
5th row식육즉석판매가공업

Common Values

ValueCountFrequency (%)
식육판매업 130
40.0%
식육즉석판매가공업 106
32.6%
축산물유통전문판매업 39
 
12.0%
우유류판매업 38
 
11.7%
식육포장처리업 7
 
2.2%
식용란수집판매업 2
 
0.6%
식육부산물전문판매업 2
 
0.6%
축산물수입판매업 1
 
0.3%

Length

2024-01-29T02:06:07.879629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:06:07.991630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식육판매업 130
40.0%
식육즉석판매가공업 106
32.6%
축산물유통전문판매업 39
 
12.0%
우유류판매업 38
 
11.7%
식육포장처리업 7
 
2.2%
식용란수집판매업 2
 
0.6%
식육부산물전문판매업 2
 
0.6%
축산물수입판매업 1
 
0.3%

사업장명칭
Text

Distinct303
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2024-01-29T02:06:08.210675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length15
Mean length7.6246154
Min length2

Characters and Unicode

Total characters2478
Distinct characters357
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique283 ?
Unique (%)87.1%

Sample

1st row충성계란
2nd row매일유업 송도청라대리점
3rd row(주) 탐라엘에스유통 송도점
4th row화톳불
5th row미남네 명품축산
ValueCountFrequency (%)
주식회사 14
 
2.9%
정육점 14
 
2.9%
송도점 10
 
2.1%
서울우유 6
 
1.2%
축산 6
 
1.2%
the 4
 
0.8%
연수점 4
 
0.8%
미트 4
 
0.8%
주)세계종합유통 3
 
0.6%
정육 3
 
0.6%
Other values (364) 418
86.0%
2024-01-29T02:06:08.540458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
163
 
6.6%
점 104
 
4.2%
주 72
 
2.9%
정 70
 
2.8%
( 67
 
2.7%
) 67
 
2.7%
육 62
 
2.5%
우 56
 
2.3%
축 48
 
1.9%
산 47
 
1.9%
Other values (347) 1722
69.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2060
83.1%
Space Separator 163
 
6.6%
Open Punctuation 67
 
2.7%
Close Punctuation 67
 
2.7%
Uppercase Letter 49
 
2.0%
Lowercase Letter 47
 
1.9%
Decimal Number 17
 
0.7%
Other Punctuation 7
 
0.3%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 104
 
5.0%
주 72
 
3.5%
정 70
 
3.4%
육 62
 
3.0%
우 56
 
2.7%
축 48
 
2.3%
산 47
 
2.3%
트 46
 
2.2%
도 46
 
2.2%
유 45
 
2.2%
Other values (299) 1464
71.1%
Uppercase Letter
ValueCountFrequency (%)
S 6
12.2%
A 4
 
8.2%
M 4
 
8.2%
F 4
 
8.2%
K 4
 
8.2%
H 4
 
8.2%
D 3
 
6.1%
O 3
 
6.1%
P 2
 
4.1%
L 2
 
4.1%
Other values (9) 13
26.5%
Lowercase Letter
ValueCountFrequency (%)
n 7
14.9%
i 7
14.9%
e 5
10.6%
a 5
10.6%
h 4
8.5%
t 4
8.5%
r 3
6.4%
g 3
6.4%
m 2
 
4.3%
o 2
 
4.3%
Other values (4) 5
10.6%
Decimal Number
ValueCountFrequency (%)
1 4
23.5%
4 3
17.6%
3 3
17.6%
0 2
11.8%
8 2
11.8%
9 1
 
5.9%
2 1
 
5.9%
5 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
& 3
42.9%
. 3
42.9%
· 1
 
14.3%
Space Separator
ValueCountFrequency (%)
163
100.0%
Open Punctuation
ValueCountFrequency (%)
( 67
100.0%
Close Punctuation
ValueCountFrequency (%)
) 67
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2058
83.1%
Common 322
 
13.0%
Latin 96
 
3.9%
Han 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 104
 
5.1%
주 72
 
3.5%
정 70
 
3.4%
육 62
 
3.0%
우 56
 
2.7%
축 48
 
2.3%
산 47
 
2.3%
트 46
 
2.2%
도 46
 
2.2%
유 45
 
2.2%
Other values (297) 1462
71.0%
Latin
ValueCountFrequency (%)
n 7
 
7.3%
i 7
 
7.3%
S 6
 
6.2%
e 5
 
5.2%
a 5
 
5.2%
A 4
 
4.2%
M 4
 
4.2%
h 4
 
4.2%
F 4
 
4.2%
K 4
 
4.2%
Other values (23) 46
47.9%
Common
ValueCountFrequency (%)
163
50.6%
( 67
20.8%
) 67
20.8%
1 4
 
1.2%
4 3
 
0.9%
& 3
 
0.9%
3 3
 
0.9%
. 3
 
0.9%
0 2
 
0.6%
8 2
 
0.6%
Other values (5) 5
 
1.6%
Han
ValueCountFrequency (%)
肉 1
50.0%
正 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2058
83.1%
ASCII 417
 
16.8%
CJK 2
 
0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
163
39.1%
( 67
16.1%
) 67
16.1%
n 7
 
1.7%
i 7
 
1.7%
S 6
 
1.4%
e 5
 
1.2%
a 5
 
1.2%
A 4
 
1.0%
M 4
 
1.0%
Other values (37) 82
19.7%
Hangul
ValueCountFrequency (%)
점 104
 
5.1%
주 72
 
3.5%
정 70
 
3.4%
육 62
 
3.0%
우 56
 
2.7%
축 48
 
2.3%
산 47
 
2.3%
트 46
 
2.2%
도 46
 
2.2%
유 45
 
2.2%
Other values (297) 1462
71.0%
CJK
ValueCountFrequency (%)
肉 1
50.0%
正 1
50.0%
None
ValueCountFrequency (%)
· 1
100.0%

권리주체명
Text

Distinct295
Distinct (%)90.8%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2024-01-29T02:06:08.762490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length3
Mean length4.72
Min length2

Characters and Unicode

Total characters1534
Distinct characters269
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique271 ?
Unique (%)83.4%

Sample

1st row김레오
2nd row이상삼
3rd row(주)탐라엘에스유통 송도점
4th row(주)화톳불
5th row김형렬
ValueCountFrequency (%)
주식회사 16
 
4.5%
dining 3
 
0.8%
안인호 3
 
0.8%
s.m 3
 
0.8%
주)덕용푸드시스템 3
 
0.8%
장정자 3
 
0.8%
주)세계종합유통 3
 
0.8%
롯데쇼핑(주 3
 
0.8%
최재분 2
 
0.6%
김재석 2
 
0.6%
Other values (300) 318
88.6%
2024-01-29T02:06:09.085720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 82
 
5.3%
이 61
 
4.0%
김 61
 
4.0%
( 59
 
3.8%
) 59
 
3.8%
34
 
2.2%
정 31
 
2.0%
박 29
 
1.9%
스 23
 
1.5%
영 23
 
1.5%
Other values (259) 1072
69.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1272
82.9%
Uppercase Letter 92
 
6.0%
Open Punctuation 59
 
3.8%
Close Punctuation 59
 
3.8%
Space Separator 34
 
2.2%
Lowercase Letter 15
 
1.0%
Other Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 82
 
6.4%
이 61
 
4.8%
김 61
 
4.8%
정 31
 
2.4%
박 29
 
2.3%
스 23
 
1.8%
영 23
 
1.8%
식 23
 
1.8%
미 22
 
1.7%
호 19
 
1.5%
Other values (232) 898
70.6%
Uppercase Letter
ValueCountFrequency (%)
A 10
10.9%
S 9
9.8%
O 8
 
8.7%
D 7
 
7.6%
N 7
 
7.6%
I 7
 
7.6%
E 6
 
6.5%
M 6
 
6.5%
Y 5
 
5.4%
R 5
 
5.4%
Other values (10) 22
23.9%
Lowercase Letter
ValueCountFrequency (%)
n 6
40.0%
i 6
40.0%
g 3
20.0%
Open Punctuation
ValueCountFrequency (%)
( 59
100.0%
Close Punctuation
ValueCountFrequency (%)
) 59
100.0%
Space Separator
ValueCountFrequency (%)
34
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1272
82.9%
Common 155
 
10.1%
Latin 107
 
7.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 82
 
6.4%
이 61
 
4.8%
김 61
 
4.8%
정 31
 
2.4%
박 29
 
2.3%
스 23
 
1.8%
영 23
 
1.8%
식 23
 
1.8%
미 22
 
1.7%
호 19
 
1.5%
Other values (232) 898
70.6%
Latin
ValueCountFrequency (%)
A 10
 
9.3%
S 9
 
8.4%
O 8
 
7.5%
D 7
 
6.5%
N 7
 
6.5%
I 7
 
6.5%
E 6
 
5.6%
n 6
 
5.6%
M 6
 
5.6%
i 6
 
5.6%
Other values (13) 35
32.7%
Common
ValueCountFrequency (%)
( 59
38.1%
) 59
38.1%
34
21.9%
. 3
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1272
82.9%
ASCII 262
 
17.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 82
 
6.4%
이 61
 
4.8%
김 61
 
4.8%
정 31
 
2.4%
박 29
 
2.3%
스 23
 
1.8%
영 23
 
1.8%
식 23
 
1.8%
미 22
 
1.7%
호 19
 
1.5%
Other values (232) 898
70.6%
ASCII
ValueCountFrequency (%)
( 59
22.5%
) 59
22.5%
34
13.0%
A 10
 
3.8%
S 9
 
3.4%
O 8
 
3.1%
D 7
 
2.7%
N 7
 
2.7%
I 7
 
2.7%
E 6
 
2.3%
Other values (17) 56
21.4%

소재지주소(지번)
Text

Distinct309
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2024-01-29T02:06:09.304816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length48
Mean length35.676923
Min length21

Characters and Unicode

Total characters11595
Distinct characters259
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

Unique296 ?
Unique (%)91.1%

Sample

1st row인천광역시 연수구 함박뫼로4번길 13-3, 101호 (청학동)
2nd row인천광역시 연수구 먼우금로251번길 36, 101호 (연수동)
3rd row인천광역시 연수구 해돋이로 107, H동 102호 (송도동, 송도 더샵 퍼스트월드)
4th row인천광역시 연수구 청량로109번길 79(옥련동)
5th row인천광역시 연수구 송도문화로28번길 28 (송도동)
ValueCountFrequency (%)
인천광역시 325
 
15.2%
연수구 325
 
15.2%
송도동 93
 
4.3%
연수동 58
 
2.7%
1층 53
 
2.5%
옥련동 51
 
2.4%
동춘동 37
 
1.7%
청학동 35
 
1.6%
송도 21
 
1.0%
101호 21
 
1.0%
Other values (596) 1124
52.4%
2024-01-29T02:06:09.647135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1827
 
15.8%
1 543
 
4.7%
동 447
 
3.9%
연 399
 
3.4%
수 399
 
3.4%
시 356
 
3.1%
인 351
 
3.0%
, 339
 
2.9%
천 335
 
2.9%
로 330
 
2.8%
Other values (249) 6269
54.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6787
58.5%
Decimal Number 1872
 
16.1%
Space Separator 1827
 
15.8%
Other Punctuation 341
 
2.9%
Open Punctuation 323
 
2.8%
Close Punctuation 323
 
2.8%
Uppercase Letter 58
 
0.5%
Dash Punctuation 55
 
0.5%
Lowercase Letter 8
 
0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 447
 
6.6%
연 399
 
5.9%
수 399
 
5.9%
시 356
 
5.2%
인 351
 
5.2%
천 335
 
4.9%
로 330
 
4.9%
광 326
 
4.8%
역 325
 
4.8%
구 325
 
4.8%
Other values (212) 3194
47.1%
Uppercase Letter
ValueCountFrequency (%)
B 15
25.9%
T 8
13.8%
A 7
12.1%
C 7
12.1%
D 4
 
6.9%
S 3
 
5.2%
R 3
 
5.2%
E 2
 
3.4%
M 2
 
3.4%
H 2
 
3.4%
Other values (4) 5
 
8.6%
Decimal Number
ValueCountFrequency (%)
1 543
29.0%
2 292
15.6%
0 234
12.5%
3 177
 
9.5%
6 124
 
6.6%
4 118
 
6.3%
5 118
 
6.3%
8 92
 
4.9%
9 89
 
4.8%
7 85
 
4.5%
Lowercase Letter
ValueCountFrequency (%)
e 3
37.5%
s 2
25.0%
a 1
 
12.5%
t 1
 
12.5%
m 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
, 339
99.4%
@ 1
 
0.3%
& 1
 
0.3%
Space Separator
ValueCountFrequency (%)
1827
100.0%
Open Punctuation
ValueCountFrequency (%)
( 323
100.0%
Close Punctuation
ValueCountFrequency (%)
) 323
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 55
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6787
58.5%
Common 4741
40.9%
Latin 67
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 447
 
6.6%
연 399
 
5.9%
수 399
 
5.9%
시 356
 
5.2%
인 351
 
5.2%
천 335
 
4.9%
로 330
 
4.9%
광 326
 
4.8%
역 325
 
4.8%
구 325
 
4.8%
Other values (212) 3194
47.1%
Latin
ValueCountFrequency (%)
B 15
22.4%
T 8
11.9%
A 7
10.4%
C 7
10.4%
D 4
 
6.0%
e 3
 
4.5%
S 3
 
4.5%
R 3
 
4.5%
E 2
 
3.0%
M 2
 
3.0%
Other values (10) 13
19.4%
Common
ValueCountFrequency (%)
1827
38.5%
1 543
 
11.5%
, 339
 
7.2%
( 323
 
6.8%
) 323
 
6.8%
2 292
 
6.2%
0 234
 
4.9%
3 177
 
3.7%
6 124
 
2.6%
4 118
 
2.5%
Other values (7) 441
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6787
58.5%
ASCII 4807
41.5%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1827
38.0%
1 543
 
11.3%
, 339
 
7.1%
( 323
 
6.7%
) 323
 
6.7%
2 292
 
6.1%
0 234
 
4.9%
3 177
 
3.7%
6 124
 
2.6%
4 118
 
2.5%
Other values (26) 507
 
10.5%
Hangul
ValueCountFrequency (%)
동 447
 
6.6%
연 399
 
5.9%
수 399
 
5.9%
시 356
 
5.2%
인 351
 
5.2%
천 335
 
4.9%
로 330
 
4.9%
광 326
 
4.8%
역 325
 
4.8%
구 325
 
4.8%
Other values (212) 3194
47.1%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

Missing values

2024-01-29T02:06:07.722687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-29T02:06:07.788338image/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

구분사업장명칭권리주체명소재지주소(지번)
0식용란수집판매업충성계란김레오인천광역시 연수구 함박뫼로4번길 13-3, 101호 (청학동)
1식용란수집판매업매일유업 송도청라대리점이상삼인천광역시 연수구 먼우금로251번길 36, 101호 (연수동)
2식육부산물전문판매업(주) 탐라엘에스유통 송도점(주)탐라엘에스유통 송도점인천광역시 연수구 해돋이로 107, H동 102호 (송도동, 송도 더샵 퍼스트월드)
3식육부산물전문판매업화톳불(주)화톳불인천광역시 연수구 청량로109번길 79(옥련동)
4식육즉석판매가공업미남네 명품축산김형렬인천광역시 연수구 송도문화로28번길 28 (송도동)
5식육즉석판매가공업푸르지오 유통강귀남인천광역시 연수구 벚꽃로 130-4, 푸루지오 2단지상가 101호 (연수동)
6식육즉석판매가공업해피트리이승인천광역시 연수구 원인재로 313 (연수동)
7식육즉석판매가공업(주)세계로유통 연수점양연주인천광역시 연수구 용담로 153 (연수동, 대동월드스포츠센타 지하)
8식육즉석판매가공업자연드림 송도점주식회사 쿱스토어경기인천광역시 연수구 하모니로36번길 17 (송도동)
9식육즉석판매가공업(주)빅토리월드(주)빅토리월드인천광역시 연수구 해돋이로120번길 16 (송도동)
구분사업장명칭권리주체명소재지주소(지번)
315축산물유통전문판매업(주)푸르웰(주)푸르웰인천광역시 연수구 센트럴로 263, 송도국제업무단지 C8-2블럭 업무복합시설 판매동 4층 (송도동)
316축산물유통전문판매업투란(TURAN)딜라프루즈인천광역시 연수구 함박로 80, 1층 (연수동)
317축산물유통전문판매업일조미트박진호인천광역시 연수구 컨벤시아대로 165, 포스코타워-송도 26층 브이439호 (송도동)
318축산물유통전문판매업로디팜(주)로디폼인천광역시 연수구 갯벌로 12, 미추홀타워 별관A동 422호 (송도동)
319축산물유통전문판매업주식회사 쇼엠커머스주식회사 쇼엠커머스인천광역시 연수구 한나루로158번길 5, 송도쇼핑 401호 (옥련동)
320축산물유통전문판매업백선생푸드 체인사업본부임승만인천광역시 연수구 컨벤시아대로 55, 2층 202(4엠)호 (송도동, 송도이안)
321축산물유통전문판매업(주)딜리셔스컬쳐(주)딜리셔스컬쳐인천광역시 연수구 함박뫼로12번길 13-1, 지층 (청학동)
322축산물유통전문판매업제주클래식(주)에이치아이제주클래식인천광역시 연수구 하모니로 124, 2층 205호 (송도동)
323축산물유통전문판매업주식회사 픽커스주식회사 픽커스인천광역시 연수구 송도과학로16번길 13-18, 송도건원테크노큐브 816호 (송도동)
324축산물유통전문판매업주식회사 담은푸드주식회사 담은푸드인천광역시 연수구 송도과학로 56, 송도테크노파크 BT센터 22층 2211호 (송도동)