Overview

Dataset statistics

Number of variables4
Number of observations181
Missing cells196
Missing cells (%)27.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.8 KiB
Average record size in memory32.7 B

Variable types

Text4

Dataset

Description경상남도 양산시의 사업장을 둔 식품제조가공업체 공공데이터 현황입니다. 사업장명, 소재지 주소, 전화번호, 식품의종류, 식품의유형 등을 확인할 수 있습니다.
Author경상남도 양산시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15021959

Alerts

지번주소 has 87 (48.1%) missing valuesMissing
전화번호 has 109 (60.2%) missing valuesMissing
업소명 has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:48:33.849266
Analysis finished2023-12-11 00:48:34.422334
Duration0.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

UNIQUE 

Distinct181
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-11T09:48:34.603480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length7.038674
Min length2

Characters and Unicode

Total characters1274
Distinct characters270
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

Unique181 ?
Unique (%)100.0%

Sample

1st row롯데칠성음료(주)
2nd row롯데제과(주)
3rd row(주)희창유업
4th row(주)진주햄
5th row오성식품
ValueCountFrequency (%)
주식회사 19
 
9.0%
제2공장 2
 
0.9%
주)희창유업 2
 
0.9%
주 2
 
0.9%
농업회사법인 2
 
0.9%
양인터네셔널 2
 
0.9%
푸드시스템 1
 
0.5%
승승푸드 1
 
0.5%
주)다정식품 1
 
0.5%
먹골 1
 
0.5%
Other values (179) 179
84.4%
2023-12-11T09:48:35.036077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 89
 
7.0%
( 70
 
5.5%
) 70
 
5.5%
식 62
 
4.9%
품 40
 
3.1%
31
 
2.4%
사 30
 
2.4%
드 29
 
2.3%
푸 27
 
2.1%
회 27
 
2.1%
Other values (260) 799
62.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1081
84.9%
Open Punctuation 70
 
5.5%
Close Punctuation 70
 
5.5%
Space Separator 31
 
2.4%
Uppercase Letter 14
 
1.1%
Decimal Number 7
 
0.5%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 89
 
8.2%
식 62
 
5.7%
품 40
 
3.7%
사 30
 
2.8%
드 29
 
2.7%
푸 27
 
2.5%
회 27
 
2.5%
산 24
 
2.2%
스 23
 
2.1%
에 20
 
1.9%
Other values (241) 710
65.7%
Uppercase Letter
ValueCountFrequency (%)
M 2
14.3%
S 2
14.3%
B 2
14.3%
W 1
7.1%
G 1
7.1%
D 1
7.1%
K 1
7.1%
J 1
7.1%
I 1
7.1%
F 1
7.1%
Decimal Number
ValueCountFrequency (%)
2 3
42.9%
0 2
28.6%
3 1
 
14.3%
1 1
 
14.3%
Open Punctuation
ValueCountFrequency (%)
( 70
100.0%
Close Punctuation
ValueCountFrequency (%)
) 70
100.0%
Space Separator
ValueCountFrequency (%)
31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1081
84.9%
Common 179
 
14.1%
Latin 14
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 89
 
8.2%
식 62
 
5.7%
품 40
 
3.7%
사 30
 
2.8%
드 29
 
2.7%
푸 27
 
2.5%
회 27
 
2.5%
산 24
 
2.2%
스 23
 
2.1%
에 20
 
1.9%
Other values (241) 710
65.7%
Latin
ValueCountFrequency (%)
M 2
14.3%
S 2
14.3%
B 2
14.3%
W 1
7.1%
G 1
7.1%
D 1
7.1%
K 1
7.1%
J 1
7.1%
I 1
7.1%
F 1
7.1%
Common
ValueCountFrequency (%)
( 70
39.1%
) 70
39.1%
31
17.3%
2 3
 
1.7%
0 2
 
1.1%
- 1
 
0.6%
3 1
 
0.6%
1 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1081
84.9%
ASCII 193
 
15.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 89
 
8.2%
식 62
 
5.7%
품 40
 
3.7%
사 30
 
2.8%
드 29
 
2.7%
푸 27
 
2.5%
회 27
 
2.5%
산 24
 
2.2%
스 23
 
2.1%
에 20
 
1.9%
Other values (241) 710
65.7%
ASCII
ValueCountFrequency (%)
( 70
36.3%
) 70
36.3%
31
16.1%
2 3
 
1.6%
M 2
 
1.0%
S 2
 
1.0%
B 2
 
1.0%
0 2
 
1.0%
W 1
 
0.5%
G 1
 
0.5%
Other values (9) 9
 
4.7%

도로명주소
Text

Distinct176
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-11T09:48:35.495963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length25
Mean length20.911602
Min length9

Characters and Unicode

Total characters3785
Distinct characters141
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

Unique172 ?
Unique (%)95.0%

Sample

1st row경상남도 양산시 북정공단1길 28 (북정동)
2nd row경상남도 양산시 양산대로 1158 (산막동)
3rd row경상남도 양산시 신기로 114 (북정동)
4th row경상남도 양산시 유산공단7길 39 (유산동)
5th row경상남도 양산시 중뫼길 36 (주남동)
ValueCountFrequency (%)
경상남도 180
20.9%
양산시 180
20.9%
상북면 23
 
2.7%
하북면 20
 
2.3%
동면 14
 
1.6%
물금읍 11
 
1.3%
어곡동 10
 
1.2%
주남동 9
 
1.0%
충렬로 9
 
1.0%
어실로 7
 
0.8%
Other values (272) 399
46.3%
2023-12-11T09:48:36.099730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
681
18.0%
산 229
 
6.1%
상 205
 
5.4%
남 202
 
5.3%
양 187
 
4.9%
경 180
 
4.8%
도 180
 
4.8%
시 180
 
4.8%
1 161
 
4.3%
길 98
 
2.6%
Other values (131) 1482
39.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2323
61.4%
Space Separator 681
 
18.0%
Decimal Number 588
 
15.5%
Open Punctuation 68
 
1.8%
Close Punctuation 67
 
1.8%
Dash Punctuation 47
 
1.2%
Uppercase Letter 7
 
0.2%
Math Symbol 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 229
 
9.9%
상 205
 
8.8%
남 202
 
8.7%
양 187
 
8.0%
경 180
 
7.7%
도 180
 
7.7%
시 180
 
7.7%
길 98
 
4.2%
동 95
 
4.1%
로 82
 
3.5%
Other values (108) 685
29.5%
Decimal Number
ValueCountFrequency (%)
1 161
27.4%
2 74
12.6%
3 73
12.4%
4 60
 
10.2%
5 46
 
7.8%
7 41
 
7.0%
8 37
 
6.3%
6 37
 
6.3%
0 32
 
5.4%
9 27
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
E 2
28.6%
R 1
14.3%
C 1
14.3%
A 1
14.3%
P 1
14.3%
L 1
14.3%
Math Symbol
ValueCountFrequency (%)
~ 2
50.0%
> 1
25.0%
< 1
25.0%
Space Separator
ValueCountFrequency (%)
681
100.0%
Open Punctuation
ValueCountFrequency (%)
( 68
100.0%
Close Punctuation
ValueCountFrequency (%)
) 67
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2323
61.4%
Common 1455
38.4%
Latin 7
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 229
 
9.9%
상 205
 
8.8%
남 202
 
8.7%
양 187
 
8.0%
경 180
 
7.7%
도 180
 
7.7%
시 180
 
7.7%
길 98
 
4.2%
동 95
 
4.1%
로 82
 
3.5%
Other values (108) 685
29.5%
Common
ValueCountFrequency (%)
681
46.8%
1 161
 
11.1%
2 74
 
5.1%
3 73
 
5.0%
( 68
 
4.7%
) 67
 
4.6%
4 60
 
4.1%
- 47
 
3.2%
5 46
 
3.2%
7 41
 
2.8%
Other values (7) 137
 
9.4%
Latin
ValueCountFrequency (%)
E 2
28.6%
R 1
14.3%
C 1
14.3%
A 1
14.3%
P 1
14.3%
L 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2323
61.4%
ASCII 1462
38.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
681
46.6%
1 161
 
11.0%
2 74
 
5.1%
3 73
 
5.0%
( 68
 
4.7%
) 67
 
4.6%
4 60
 
4.1%
- 47
 
3.2%
5 46
 
3.1%
7 41
 
2.8%
Other values (13) 144
 
9.8%
Hangul
ValueCountFrequency (%)
산 229
 
9.9%
상 205
 
8.8%
남 202
 
8.7%
양 187
 
8.0%
경 180
 
7.7%
도 180
 
7.7%
시 180
 
7.7%
길 98
 
4.2%
동 95
 
4.1%
로 82
 
3.5%
Other values (108) 685
29.5%

지번주소
Text

MISSING 

Distinct94
Distinct (%)100.0%
Missing87
Missing (%)48.1%
Memory size1.5 KiB
2023-12-11T09:48:36.485047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length27
Mean length20.329787
Min length9

Characters and Unicode

Total characters1911
Distinct characters92
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

Unique94 ?
Unique (%)100.0%

Sample

1st row경상남도 양산시 북정동 291
2nd row경상남도 양산시 산막동 511
3rd row경상남도 양산시 북정동 291-8
4th row경상남도 양산시 유산동 150
5th row경상남도 양산시 주남동 144
ValueCountFrequency (%)
경상남도 93
22.2%
양산시 93
22.2%
하북면 11
 
2.6%
상북면 11
 
2.6%
어곡동 10
 
2.4%
주남동 9
 
2.2%
소주동 6
 
1.4%
북정동 6
 
1.4%
원동면 5
 
1.2%
매곡동 4
 
1.0%
Other values (140) 170
40.7%
2023-12-11T09:48:37.038068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
416
21.8%
산 108
 
5.7%
상 105
 
5.5%
남 102
 
5.3%
시 93
 
4.9%
경 93
 
4.9%
양 93
 
4.9%
도 93
 
4.9%
1 75
 
3.9%
동 72
 
3.8%
Other values (82) 661
34.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1050
54.9%
Space Separator 416
 
21.8%
Decimal Number 367
 
19.2%
Dash Punctuation 65
 
3.4%
Uppercase Letter 7
 
0.4%
Math Symbol 4
 
0.2%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 108
10.3%
상 105
10.0%
남 102
9.7%
시 93
8.9%
경 93
8.9%
양 93
8.9%
도 93
8.9%
동 72
 
6.9%
리 32
 
3.0%
면 31
 
3.0%
Other values (59) 228
21.7%
Decimal Number
ValueCountFrequency (%)
1 75
20.4%
2 45
12.3%
4 42
11.4%
3 34
9.3%
5 33
9.0%
9 32
8.7%
8 32
8.7%
6 29
 
7.9%
0 26
 
7.1%
7 19
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
E 2
28.6%
L 1
14.3%
R 1
14.3%
P 1
14.3%
A 1
14.3%
C 1
14.3%
Math Symbol
ValueCountFrequency (%)
~ 2
50.0%
> 1
25.0%
< 1
25.0%
Space Separator
ValueCountFrequency (%)
416
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 65
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1050
54.9%
Common 854
44.7%
Latin 7
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 108
10.3%
상 105
10.0%
남 102
9.7%
시 93
8.9%
경 93
8.9%
양 93
8.9%
도 93
8.9%
동 72
 
6.9%
리 32
 
3.0%
면 31
 
3.0%
Other values (59) 228
21.7%
Common
ValueCountFrequency (%)
416
48.7%
1 75
 
8.8%
- 65
 
7.6%
2 45
 
5.3%
4 42
 
4.9%
3 34
 
4.0%
5 33
 
3.9%
9 32
 
3.7%
8 32
 
3.7%
6 29
 
3.4%
Other values (7) 51
 
6.0%
Latin
ValueCountFrequency (%)
E 2
28.6%
L 1
14.3%
R 1
14.3%
P 1
14.3%
A 1
14.3%
C 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1050
54.9%
ASCII 861
45.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
416
48.3%
1 75
 
8.7%
- 65
 
7.5%
2 45
 
5.2%
4 42
 
4.9%
3 34
 
3.9%
5 33
 
3.8%
9 32
 
3.7%
8 32
 
3.7%
6 29
 
3.4%
Other values (13) 58
 
6.7%
Hangul
ValueCountFrequency (%)
산 108
10.3%
상 105
10.0%
남 102
9.7%
시 93
8.9%
경 93
8.9%
양 93
8.9%
도 93
8.9%
동 72
 
6.9%
리 32
 
3.0%
면 31
 
3.0%
Other values (59) 228
21.7%

전화번호
Text

MISSING 

Distinct71
Distinct (%)98.6%
Missing109
Missing (%)60.2%
Memory size1.5 KiB
2023-12-11T09:48:37.294500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12
Min length9

Characters and Unicode

Total characters864
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

Unique70 ?
Unique (%)97.2%

Sample

1st row055-388-5580
2nd row055-370-6114
3rd row055-911-3112
4th row055-387-5001
5th row055-365-1286
ValueCountFrequency (%)
055-389-1001 2
 
2.8%
055-636-9735 1
 
1.4%
055-388-5580 1
 
1.4%
051-315-1657 1
 
1.4%
055-383-5413 1
 
1.4%
055-781-2230 1
 
1.4%
051-468-2675 1
 
1.4%
055-374-5569 1
 
1.4%
070-8274-5434 1
 
1.4%
055-384-0399 1
 
1.4%
Other values (61) 61
84.7%
2023-12-11T09:48:37.664380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 176
20.4%
- 143
16.6%
0 127
14.7%
3 95
11.0%
1 62
 
7.2%
7 60
 
6.9%
8 53
 
6.1%
6 50
 
5.8%
2 35
 
4.1%
4 32
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 721
83.4%
Dash Punctuation 143
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 176
24.4%
0 127
17.6%
3 95
13.2%
1 62
 
8.6%
7 60
 
8.3%
8 53
 
7.4%
6 50
 
6.9%
2 35
 
4.9%
4 32
 
4.4%
9 31
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 143
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 864
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 176
20.4%
- 143
16.6%
0 127
14.7%
3 95
11.0%
1 62
 
7.2%
7 60
 
6.9%
8 53
 
6.1%
6 50
 
5.8%
2 35
 
4.1%
4 32
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 864
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 176
20.4%
- 143
16.6%
0 127
14.7%
3 95
11.0%
1 62
 
7.2%
7 60
 
6.9%
8 53
 
6.1%
6 50
 
5.8%
2 35
 
4.1%
4 32
 
3.7%

Correlations

2023-12-11T09:48:37.775892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지번주소전화번호
지번주소1.0001.000
전화번호1.0001.000

Missing values

2023-12-11T09:48:34.206743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:48:34.295982image/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.
2023-12-11T09:48:34.374598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

업소명도로명주소지번주소전화번호
0롯데칠성음료(주)경상남도 양산시 북정공단1길 28 (북정동)경상남도 양산시 북정동 291055-388-5580
1롯데제과(주)경상남도 양산시 양산대로 1158 (산막동)경상남도 양산시 산막동 511055-370-6114
2(주)희창유업경상남도 양산시 신기로 114 (북정동)경상남도 양산시 북정동 291-8055-911-3112
3(주)진주햄경상남도 양산시 유산공단7길 39 (유산동)경상남도 양산시 유산동 150055-387-5001
4오성식품경상남도 양산시 중뫼길 36 (주남동)경상남도 양산시 주남동 144055-365-1286
5대륙식품(주)경상남도 양산시 동면 곡리1길 11경상남도 양산시 동면 석산리 680-12055-389-1700
6(주)엠에스씨(MSC)경상남도 양산시 소주회야로 45-73 (소주동)경상남도 양산시 소주동 439-13055-389-1001
7(주)동원식품경상남도 양산시 산막공단북8길 9-3 (호계동)경상남도 양산시 호계동 857-7055-383-3121
8대성식품경상남도 양산시 상북면 대석1길 64경상남도 양산시 상북면 대석리 524-3055-374-6000
9구포국수경상남도 양산시 원동면 원동로 1748경상남도 양산시 원동면 원리 251055-383-9917
업소명도로명주소지번주소전화번호
171올바롬경상남도 양산시 주남로 288<NA><NA>
172우리집수제차경상남도 양산시 하북면 백록로 124-1<NA><NA>
173(주)서부경건강이야기경상남도 양산시 명곡음지마을길 95<NA><NA>
174주식회사 양인터네셔널경상남도 양산시 주남로 288<NA><NA>
175(주)대진에프아이경상남도 양산시 주남로 288<NA><NA>
176제이와이스토리경상남도 양산시 명곡로 321<NA><NA>
177별미담경상남도 양산시 신명로 17<NA><NA>
178디에스(DS)푸드경상남도 양산시 명동7길 35 (명동)경상남도 양산시 명동 268-22070-4280-7110
179주식회사 청담경상남도 양산시 어실로 353-3 (어곡동)경상남도 양산시 어곡동 1129<NA>
180블루밍던 로스터리경상남도 양산시 물금읍 버들길 12<NA><NA>