Overview

Dataset statistics

Number of variables4
Number of observations113
Missing cells39
Missing cells (%)8.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 KiB
Average record size in memory33.2 B

Variable types

Categorical1
Text3

Dataset

Description부산광역시사상구_식품제조가공업현황_20230619
Author부산광역시 사상구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15001775

Alerts

업종 has constant value ""Constant
소재지전화 has 39 (34.5%) missing valuesMissing
업소명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:41:58.945468
Analysis finished2023-12-10 16:41:59.584210
Duration0.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
식품제조가공업
113 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row식품제조가공업
2nd row식품제조가공업
3rd row식품제조가공업
4th row식품제조가공업
5th row식품제조가공업

Common Values

ValueCountFrequency (%)
식품제조가공업 113
100.0%

Length

2023-12-11T01:41:59.694398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:41:59.802649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 113
100.0%

업소명
Text

UNIQUE 

Distinct113
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-11T01:42:00.051928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length4
Mean length5.9734513
Min length2

Characters and Unicode

Total characters675
Distinct characters194
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

Unique113 ?
Unique (%)100.0%

Sample

1st row(주)농심
2nd row삼성식품
3rd row한동냉장
4th row대우통상
5th row부전식품
ValueCountFrequency (%)
주식회사 6
 
4.6%
주)농심 1
 
0.8%
장수생명 1
 
0.8%
천정 1
 
0.8%
국제에프씨 1
 
0.8%
로스터스 1
 
0.8%
커피픽 1
 
0.8%
주)케이푸드아이엔지 1
 
0.8%
커피랑 1
 
0.8%
가향푸드 1
 
0.8%
Other values (115) 115
88.5%
2023-12-11T01:42:00.561845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 39
 
5.8%
품 33
 
4.9%
주 25
 
3.7%
( 24
 
3.6%
) 24
 
3.6%
산 17
 
2.5%
17
 
2.5%
이 14
 
2.1%
에 14
 
2.1%
회 13
 
1.9%
Other values (184) 455
67.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 580
85.9%
Open Punctuation 24
 
3.6%
Close Punctuation 24
 
3.6%
Uppercase Letter 21
 
3.1%
Space Separator 17
 
2.5%
Decimal Number 8
 
1.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 39
 
6.7%
품 33
 
5.7%
주 25
 
4.3%
산 17
 
2.9%
이 14
 
2.4%
에 14
 
2.4%
회 13
 
2.2%
사 12
 
2.1%
스 12
 
2.1%
성 12
 
2.1%
Other values (164) 389
67.1%
Uppercase Letter
ValueCountFrequency (%)
S 5
23.8%
A 4
19.0%
B 3
14.3%
Y 2
 
9.5%
L 2
 
9.5%
Z 1
 
4.8%
K 1
 
4.8%
D 1
 
4.8%
F 1
 
4.8%
C 1
 
4.8%
Decimal Number
ValueCountFrequency (%)
1 3
37.5%
5 1
 
12.5%
0 1
 
12.5%
9 1
 
12.5%
8 1
 
12.5%
3 1
 
12.5%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Space Separator
ValueCountFrequency (%)
17
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 580
85.9%
Common 74
 
11.0%
Latin 21
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 39
 
6.7%
품 33
 
5.7%
주 25
 
4.3%
산 17
 
2.9%
이 14
 
2.4%
에 14
 
2.4%
회 13
 
2.2%
사 12
 
2.1%
스 12
 
2.1%
성 12
 
2.1%
Other values (164) 389
67.1%
Common
ValueCountFrequency (%)
( 24
32.4%
) 24
32.4%
17
23.0%
1 3
 
4.1%
5 1
 
1.4%
& 1
 
1.4%
0 1
 
1.4%
9 1
 
1.4%
8 1
 
1.4%
3 1
 
1.4%
Latin
ValueCountFrequency (%)
S 5
23.8%
A 4
19.0%
B 3
14.3%
Y 2
 
9.5%
L 2
 
9.5%
Z 1
 
4.8%
K 1
 
4.8%
D 1
 
4.8%
F 1
 
4.8%
C 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 580
85.9%
ASCII 95
 
14.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 39
 
6.7%
품 33
 
5.7%
주 25
 
4.3%
산 17
 
2.9%
이 14
 
2.4%
에 14
 
2.4%
회 13
 
2.2%
사 12
 
2.1%
스 12
 
2.1%
성 12
 
2.1%
Other values (164) 389
67.1%
ASCII
ValueCountFrequency (%)
( 24
25.3%
) 24
25.3%
17
17.9%
S 5
 
5.3%
A 4
 
4.2%
B 3
 
3.2%
1 3
 
3.2%
Y 2
 
2.1%
L 2
 
2.1%
Z 1
 
1.1%
Other values (10) 10
10.5%

소재지전화
Text

MISSING 

Distinct74
Distinct (%)100.0%
Missing39
Missing (%)34.5%
Memory size1.0 KiB
2023-12-11T01:42:00.871464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters1036
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

Unique74 ?
Unique (%)100.0%

Sample

1st row051 -366 -5300
2nd row 051- 323-9797
3rd row 051- 324-5575
4th row 051- 325-6870
5th row 051- 819-4846
ValueCountFrequency (%)
051 65
36.9%
304 3
 
1.7%
7100 2
 
1.1%
314 2
 
1.1%
311 2
 
1.1%
301 2
 
1.1%
317 2
 
1.1%
321 2
 
1.1%
304-4477 1
 
0.6%
203 1
 
0.6%
Other values (94) 94
53.4%
2023-12-11T01:42:01.364689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 148
14.3%
144
13.9%
1 136
13.1%
0 130
12.5%
5 114
11.0%
3 108
10.4%
2 53
 
5.1%
4 47
 
4.5%
8 45
 
4.3%
9 40
 
3.9%
Other values (2) 71
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 744
71.8%
Dash Punctuation 148
 
14.3%
Space Separator 144
 
13.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 136
18.3%
0 130
17.5%
5 114
15.3%
3 108
14.5%
2 53
 
7.1%
4 47
 
6.3%
8 45
 
6.0%
9 40
 
5.4%
7 38
 
5.1%
6 33
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 148
100.0%
Space Separator
ValueCountFrequency (%)
144
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1036
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 148
14.3%
144
13.9%
1 136
13.1%
0 130
12.5%
5 114
11.0%
3 108
10.4%
2 53
 
5.1%
4 47
 
4.5%
8 45
 
4.3%
9 40
 
3.9%
Other values (2) 71
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1036
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 148
14.3%
144
13.9%
1 136
13.1%
0 130
12.5%
5 114
11.0%
3 108
10.4%
2 53
 
5.1%
4 47
 
4.5%
8 45
 
4.3%
9 40
 
3.9%
Other values (2) 71
6.9%

소재지(도로명)
Text

Distinct107
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-11T01:42:01.796597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length43
Mean length31.362832
Min length22

Characters and Unicode

Total characters3544
Distinct characters112
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique106 ?
Unique (%)93.8%

Sample

1st row부산광역시 사상구 사상로455번길 46 (모라동)
2nd row부산광역시 사상구 새벽시장로46번길 3-3 (감전동)
3rd row부산광역시 사상구 새벽시장로 20 (감전동)
4th row부산광역시 사상구 새벽로 141 (감전동)
5th row부산광역시 사상구 사상로386번길 38-21 (덕포동)
ValueCountFrequency (%)
부산광역시 113
 
16.5%
사상구 113
 
16.5%
엄궁동 26
 
3.8%
1층 20
 
2.9%
감전동 18
 
2.6%
2층 18
 
2.6%
11 16
 
2.3%
모라동 14
 
2.0%
삼락동 14
 
2.0%
덕포동 14
 
2.0%
Other values (204) 318
46.5%
2023-12-11T01:42:02.449592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
650
 
18.3%
동 153
 
4.3%
시 150
 
4.2%
1 143
 
4.0%
산 143
 
4.0%
상 137
 
3.9%
사 134
 
3.8%
부 118
 
3.3%
) 116
 
3.3%
( 116
 
3.3%
Other values (102) 1684
47.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2081
58.7%
Space Separator 650
 
18.3%
Decimal Number 554
 
15.6%
Close Punctuation 117
 
3.3%
Open Punctuation 117
 
3.3%
Dash Punctuation 11
 
0.3%
Math Symbol 8
 
0.2%
Uppercase Letter 5
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 153
 
7.4%
시 150
 
7.2%
산 143
 
6.9%
상 137
 
6.6%
사 134
 
6.4%
부 118
 
5.7%
광 114
 
5.5%
구 114
 
5.5%
로 114
 
5.5%
역 113
 
5.4%
Other values (80) 791
38.0%
Decimal Number
ValueCountFrequency (%)
1 143
25.8%
2 79
14.3%
3 72
13.0%
4 55
 
9.9%
9 44
 
7.9%
0 39
 
7.0%
5 38
 
6.9%
6 35
 
6.3%
7 25
 
4.5%
8 24
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
B 2
40.0%
C 1
20.0%
Y 1
20.0%
A 1
20.0%
Close Punctuation
ValueCountFrequency (%)
) 116
99.1%
] 1
 
0.9%
Open Punctuation
ValueCountFrequency (%)
( 116
99.1%
[ 1
 
0.9%
Space Separator
ValueCountFrequency (%)
650
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%
Other Punctuation
ValueCountFrequency (%)
* 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2081
58.7%
Common 1458
41.1%
Latin 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 153
 
7.4%
시 150
 
7.2%
산 143
 
6.9%
상 137
 
6.6%
사 134
 
6.4%
부 118
 
5.7%
광 114
 
5.5%
구 114
 
5.5%
로 114
 
5.5%
역 113
 
5.4%
Other values (80) 791
38.0%
Common
ValueCountFrequency (%)
650
44.6%
1 143
 
9.8%
) 116
 
8.0%
( 116
 
8.0%
2 79
 
5.4%
3 72
 
4.9%
4 55
 
3.8%
9 44
 
3.0%
0 39
 
2.7%
5 38
 
2.6%
Other values (8) 106
 
7.3%
Latin
ValueCountFrequency (%)
B 2
40.0%
C 1
20.0%
Y 1
20.0%
A 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2081
58.7%
ASCII 1463
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
650
44.4%
1 143
 
9.8%
) 116
 
7.9%
( 116
 
7.9%
2 79
 
5.4%
3 72
 
4.9%
4 55
 
3.8%
9 44
 
3.0%
0 39
 
2.7%
5 38
 
2.6%
Other values (12) 111
 
7.6%
Hangul
ValueCountFrequency (%)
동 153
 
7.4%
시 150
 
7.2%
산 143
 
6.9%
상 137
 
6.6%
사 134
 
6.4%
부 118
 
5.7%
광 114
 
5.5%
구 114
 
5.5%
로 114
 
5.5%
역 113
 
5.4%
Other values (80) 791
38.0%

Missing values

2023-12-11T01:41:59.452474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:41:59.550877image/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

업종업소명소재지전화소재지(도로명)
0식품제조가공업(주)농심051 -366 -5300부산광역시 사상구 사상로455번길 46 (모라동)
1식품제조가공업삼성식품051- 323-9797부산광역시 사상구 새벽시장로46번길 3-3 (감전동)
2식품제조가공업한동냉장051- 324-5575부산광역시 사상구 새벽시장로 20 (감전동)
3식품제조가공업대우통상051- 325-6870부산광역시 사상구 새벽로 141 (감전동)
4식품제조가공업부전식품051- 819-4846부산광역시 사상구 사상로386번길 38-21 (덕포동)
5식품제조가공업광신식품051 -334 -7686부산광역시 사상구 모덕로96번길 60 (덕포동)
6식품제조가공업신라에스지(주)부산공장051- 302-3813부산광역시 사상구 낙동대로 1414 (삼락동)
7식품제조가공업진일식품051 -304 -2985부산광역시 사상구 모라로6번길 13-12 (삼락동)
8식품제조가공업제일식품051- 301-3269부산광역시 사상구 낙동대로1348번길 54 (삼락동)
9식품제조가공업서울제분051-311 -5930부산광역시 사상구 가야대로104번길 36 (학장동)
업종업소명소재지전화소재지(도로명)
103식품제조가공업카르도<NA>부산광역시 사상구 사상로374번길 31 (덕포동)
104식품제조가공업(주)공오일 제조<NA>부산광역시 사상구 사상로 157 1층 (괘법동)
105식품제조가공업(주)원코프<NA>부산광역시 사상구 대동로 127 2층 일부호 (학장동)
106식품제조가공업피에이치푸드<NA>부산광역시 사상구 새벽시장로 80 (감전동)
107식품제조가공업브뤼트<NA>부산광역시 사상구 백양대로700번길 13 덕포청구아파트 105동 2층 206호 (덕포동)
108식품제조가공업레이지 데이(LAZY DAY)<NA>부산광역시 사상구 운산로 22 괘법2차한신아파트 상가12동 2층 203호 (괘법동)
109식품제조가공업(주)하고자비<NA>부산광역시 사상구 낙동대로1330번길 72 2층 (삼락동)
110식품제조가공업성지식품051 -522 -6777부산광역시 사상구 사상로469번길 9 1~2층 (모라동)
111식품제조가공업버거15<NA>부산광역시 사상구 대동로64번길 36 삼성타워아파트 상가동 1층 101호 (엄궁동)
112식품제조가공업동백에프앤비<NA>부산광역시 사상구 사상로 475-14 1층 (모라동)