Overview

Dataset statistics

Number of variables4
Number of observations147
Missing cells32
Missing cells (%)5.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.7 KiB
Average record size in memory32.9 B

Variable types

Text3
Categorical1

Dataset

Description진주시 식품위생업소별 신고현황 자료입니다. 업종(일반음식점, 휴게음식점, 식품판매업, 집단급식소, 즉석판매제조가공업 등 ) , 업소명, 소재지, 전화번호등의 정보를 제공합니다.
Author경상남도 진주시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15004470

Alerts

기준일자 has constant value ""Constant
전화번호 has 32 (21.8%) missing valuesMissing
업소명 has unique valuesUnique

Reproduction

Analysis started2023-12-11 01:03:16.038118
Analysis finished2023-12-11 01:03:16.500178
Duration0.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

UNIQUE 

Distinct147
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-11T10:03:16.687805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20
Mean length7.5578231
Min length2

Characters and Unicode

Total characters1111
Distinct characters268
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

Unique147 ?
Unique (%)100.0%

Sample

1st row영남제과
2nd row진주식품공업사
3rd row강남염업사
4th row설정제빙
5th row한보외식산업
ValueCountFrequency (%)
농업회사법인 5
 
3.0%
주식회사 4
 
2.4%
아미코젠(주 2
 
1.2%
영남제과 1
 
0.6%
에디슨커피 1
 
0.6%
주식회사(s&t 1
 
0.6%
foods 1
 
0.6%
어성초영농조합법인 1
 
0.6%
늘가람유통 1
 
0.6%
경상두부 1
 
0.6%
Other values (150) 150
89.3%
2023-12-11T10:03:17.090855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 56
 
5.0%
식 50
 
4.5%
품 40
 
3.6%
) 38
 
3.4%
( 38
 
3.4%
이 28
 
2.5%
농 28
 
2.5%
사 26
 
2.3%
진 21
 
1.9%
21
 
1.9%
Other values (258) 765
68.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 967
87.0%
Close Punctuation 38
 
3.4%
Open Punctuation 38
 
3.4%
Uppercase Letter 22
 
2.0%
Space Separator 21
 
1.9%
Lowercase Letter 18
 
1.6%
Decimal Number 5
 
0.5%
Other Punctuation 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 56
 
5.8%
식 50
 
5.2%
품 40
 
4.1%
이 28
 
2.9%
농 28
 
2.9%
사 26
 
2.7%
진 21
 
2.2%
회 21
 
2.2%
인 19
 
2.0%
업 19
 
2.0%
Other values (225) 659
68.1%
Uppercase Letter
ValueCountFrequency (%)
U 3
13.6%
O 3
13.6%
F 3
13.6%
S 3
13.6%
E 2
9.1%
L 1
 
4.5%
R 1
 
4.5%
D 1
 
4.5%
C 1
 
4.5%
T 1
 
4.5%
Other values (3) 3
13.6%
Lowercase Letter
ValueCountFrequency (%)
u 3
16.7%
s 3
16.7%
e 3
16.7%
a 2
11.1%
i 1
 
5.6%
o 1
 
5.6%
d 1
 
5.6%
r 1
 
5.6%
q 1
 
5.6%
t 1
 
5.6%
Decimal Number
ValueCountFrequency (%)
8 2
40.0%
2 1
20.0%
6 1
20.0%
0 1
20.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%
Space Separator
ValueCountFrequency (%)
21
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 967
87.0%
Common 104
 
9.4%
Latin 40
 
3.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 56
 
5.8%
식 50
 
5.2%
품 40
 
4.1%
이 28
 
2.9%
농 28
 
2.9%
사 26
 
2.7%
진 21
 
2.2%
회 21
 
2.2%
인 19
 
2.0%
업 19
 
2.0%
Other values (225) 659
68.1%
Latin
ValueCountFrequency (%)
U 3
 
7.5%
O 3
 
7.5%
F 3
 
7.5%
u 3
 
7.5%
s 3
 
7.5%
S 3
 
7.5%
e 3
 
7.5%
a 2
 
5.0%
E 2
 
5.0%
L 1
 
2.5%
Other values (14) 14
35.0%
Common
ValueCountFrequency (%)
) 38
36.5%
( 38
36.5%
21
20.2%
8 2
 
1.9%
2 1
 
1.0%
& 1
 
1.0%
- 1
 
1.0%
6 1
 
1.0%
0 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 967
87.0%
ASCII 144
 
13.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 56
 
5.8%
식 50
 
5.2%
품 40
 
4.1%
이 28
 
2.9%
농 28
 
2.9%
사 26
 
2.7%
진 21
 
2.2%
회 21
 
2.2%
인 19
 
2.0%
업 19
 
2.0%
Other values (225) 659
68.1%
ASCII
ValueCountFrequency (%)
) 38
26.4%
( 38
26.4%
21
14.6%
U 3
 
2.1%
O 3
 
2.1%
F 3
 
2.1%
u 3
 
2.1%
s 3
 
2.1%
S 3
 
2.1%
e 3
 
2.1%
Other values (23) 26
18.1%

소재지(도로명)
Text

Distinct146
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-11T10:03:17.479405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length38
Mean length29.44898
Min length19

Characters and Unicode

Total characters4329
Distinct characters159
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

Unique145 ?
Unique (%)98.6%

Sample

1st row경상남도 진주시 미천면 향양로 394
2nd row경상남도 진주시 솔밭로43번길 19 (상평동)
3rd row경상남도 진주시 남강로1385번길 7 (상대동)
4th row경상남도 진주시 돗골로 47 (상평동)
5th row경상남도 진주시 정촌면 화개천로54번길 33-38, 1층
ValueCountFrequency (%)
경상남도 147
 
17.0%
진주시 147
 
17.0%
1층 33
 
3.8%
문산읍 28
 
3.2%
월아산로 15
 
1.7%
대곡면 12
 
1.4%
991 11
 
1.3%
명석면 8
 
0.9%
월아산로950번길 7
 
0.8%
3층 7
 
0.8%
Other values (309) 449
52.0%
2023-12-11T10:03:18.013592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
717
 
16.6%
1 201
 
4.6%
상 170
 
3.9%
진 169
 
3.9%
남 157
 
3.6%
주 156
 
3.6%
경 150
 
3.5%
도 150
 
3.5%
시 148
 
3.4%
) 128
 
3.0%
Other values (149) 2183
50.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2479
57.3%
Decimal Number 742
 
17.1%
Space Separator 717
 
16.6%
Close Punctuation 128
 
3.0%
Open Punctuation 127
 
2.9%
Other Punctuation 86
 
2.0%
Dash Punctuation 36
 
0.8%
Uppercase Letter 14
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 170
 
6.9%
진 169
 
6.8%
남 157
 
6.3%
주 156
 
6.3%
경 150
 
6.1%
도 150
 
6.1%
시 148
 
6.0%
로 128
 
5.2%
동 111
 
4.5%
번 107
 
4.3%
Other values (127) 1033
41.7%
Decimal Number
ValueCountFrequency (%)
1 201
27.1%
2 93
12.5%
3 87
11.7%
0 66
 
8.9%
5 60
 
8.1%
9 59
 
8.0%
6 57
 
7.7%
4 54
 
7.3%
7 34
 
4.6%
8 31
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
A 4
28.6%
E 3
21.4%
B 3
21.4%
C 3
21.4%
F 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
, 81
94.2%
. 3
 
3.5%
: 2
 
2.3%
Space Separator
ValueCountFrequency (%)
717
100.0%
Close Punctuation
ValueCountFrequency (%)
) 128
100.0%
Open Punctuation
ValueCountFrequency (%)
( 127
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2479
57.3%
Common 1836
42.4%
Latin 14
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 170
 
6.9%
진 169
 
6.8%
남 157
 
6.3%
주 156
 
6.3%
경 150
 
6.1%
도 150
 
6.1%
시 148
 
6.0%
로 128
 
5.2%
동 111
 
4.5%
번 107
 
4.3%
Other values (127) 1033
41.7%
Common
ValueCountFrequency (%)
717
39.1%
1 201
 
10.9%
) 128
 
7.0%
( 127
 
6.9%
2 93
 
5.1%
3 87
 
4.7%
, 81
 
4.4%
0 66
 
3.6%
5 60
 
3.3%
9 59
 
3.2%
Other values (7) 217
 
11.8%
Latin
ValueCountFrequency (%)
A 4
28.6%
E 3
21.4%
B 3
21.4%
C 3
21.4%
F 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2479
57.3%
ASCII 1850
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
717
38.8%
1 201
 
10.9%
) 128
 
6.9%
( 127
 
6.9%
2 93
 
5.0%
3 87
 
4.7%
, 81
 
4.4%
0 66
 
3.6%
5 60
 
3.2%
9 59
 
3.2%
Other values (12) 231
 
12.5%
Hangul
ValueCountFrequency (%)
상 170
 
6.9%
진 169
 
6.8%
남 157
 
6.3%
주 156
 
6.3%
경 150
 
6.1%
도 150
 
6.1%
시 148
 
6.0%
로 128
 
5.2%
동 111
 
4.5%
번 107
 
4.3%
Other values (127) 1033
41.7%

전화번호
Text

MISSING 

Distinct113
Distinct (%)98.3%
Missing32
Missing (%)21.8%
Memory size1.3 KiB
2023-12-11T10:03:18.267609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.017391
Min length12

Characters and Unicode

Total characters1382
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

Unique111 ?
Unique (%)96.5%

Sample

1st row055-745-4648
2nd row055-752-3904
3rd row055-752-8266
4th row055-755-6700
5th row055-743-8383
ValueCountFrequency (%)
055-759-6161 2
 
1.7%
055-755-5355 2
 
1.7%
055-744-7976 1
 
0.9%
055-747-9595 1
 
0.9%
055-759-5288 1
 
0.9%
070-4197-9725 1
 
0.9%
055-757-8605 1
 
0.9%
055-759-9993 1
 
0.9%
055-756-1156 1
 
0.9%
055-758-4095 1
 
0.9%
Other values (103) 103
89.6%
2023-12-11T10:03:18.670340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 334
24.2%
- 230
16.6%
7 176
12.7%
0 175
12.7%
4 106
 
7.7%
6 80
 
5.8%
9 66
 
4.8%
1 59
 
4.3%
2 54
 
3.9%
8 54
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1152
83.4%
Dash Punctuation 230
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 334
29.0%
7 176
15.3%
0 175
15.2%
4 106
 
9.2%
6 80
 
6.9%
9 66
 
5.7%
1 59
 
5.1%
2 54
 
4.7%
8 54
 
4.7%
3 48
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 230
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1382
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 334
24.2%
- 230
16.6%
7 176
12.7%
0 175
12.7%
4 106
 
7.7%
6 80
 
5.8%
9 66
 
4.8%
1 59
 
4.3%
2 54
 
3.9%
8 54
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1382
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 334
24.2%
- 230
16.6%
7 176
12.7%
0 175
12.7%
4 106
 
7.7%
6 80
 
5.8%
9 66
 
4.8%
1 59
 
4.3%
2 54
 
3.9%
8 54
 
3.9%

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2017-03-15
147 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017-03-15
2nd row2017-03-15
3rd row2017-03-15
4th row2017-03-15
5th row2017-03-15

Common Values

ValueCountFrequency (%)
2017-03-15 147
100.0%

Length

2023-12-11T10:03:18.837448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T10:03:18.972039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017-03-15 147
100.0%

Missing values

2023-12-11T10:03:16.346577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T10:03:16.457302image/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

업소명소재지(도로명)전화번호기준일자
0영남제과경상남도 진주시 미천면 향양로 394055-745-46482017-03-15
1진주식품공업사경상남도 진주시 솔밭로43번길 19 (상평동)055-752-39042017-03-15
2강남염업사경상남도 진주시 남강로1385번길 7 (상대동)055-752-82662017-03-15
3설정제빙경상남도 진주시 돗골로 47 (상평동)055-755-67002017-03-15
4한보외식산업경상남도 진주시 정촌면 화개천로54번길 33-38, 1층055-743-83832017-03-15
5진주전통에나가한과경상남도 진주시 장대로43번길 10-3 (장대동)055-745-06442017-03-15
6봉봉종합식품경상남도 진주시 하대로129번길 10 (하대동)055-755-30482017-03-15
7설정식품(주)경상남도 진주시 남강로1367번길 14-8 (상대동)055-757-69902017-03-15
8큰들식품경상남도 진주시 신안들말길 36-6 (신안동,1층)055-741-61952017-03-15
9금대제과경상남도 진주시 문산읍 동부로609번길 20055-761-87442017-03-15
업소명소재지(도로명)전화번호기준일자
137농업회사법인주식회사제이비에프경상남도 진주시 집현면 진주성로751번길 33-11, 1,2층055-746-60792017-03-15
138새미찬방경상남도 진주시 집현면 진산로 703, 1층055-759-38022017-03-15
139농업회사법인 굼벵이농부(주)경상남도 진주시 명석면 광제산로 6, 1층<NA>2017-03-15
140(주)한보명가경상남도 진주시 대평면 한들길 33, 1호<NA>2017-03-15
141농업회사법인 예농(주)경상남도 진주시 문산읍 월아산로 991, 바이오산업진흥원 성장지원동 3층 305-2호055-744-79762017-03-15
142울루루 커피(ULURU COFFEE)경상남도 진주시 호탄길 30, 목천빌딩동 1층 (호탄동)<NA>2017-03-15
143아미코젠(주) 문산제2공장경상남도 진주시 문산읍 월아산로950번길 7-22055-759-61612017-03-15
144하애식품경상남도 진주시 돗골로161번길 22 (상대동)<NA>2017-03-15
145백세전복식품경상남도 진주시 비봉로 79 (상봉동)055-746-05662017-03-15
146오손도손건강이야기경상남도 진주시 진성면 동산길28번길 37<NA>2017-03-15