Overview

Dataset statistics

Number of variables6
Number of observations33
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory53.0 B

Variable types

Numeric1
Text4
Categorical1

Dataset

Description위생관리상태등이 우수한 일반음식점의 위생 평가를 통해 모범음식점으로 지정 ․ 운영함으로써 위생환경개선과 서비스 수준 향상 도모하기 위한 예산군 관내 모범음식점 현황을 제공합니다.
Author충청남도 예산군
URLhttps://www.data.go.kr/data/15107788/fileData.do

Alerts

종류 is highly imbalanced (80.4%)Imbalance
연번 has unique valuesUnique
업 소 명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:34:06.017632
Analysis finished2023-12-12 21:34:06.658901
Duration0.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17
Minimum1
Maximum33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-13T06:34:06.722501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.6
Q19
median17
Q325
95-th percentile31.4
Maximum33
Range32
Interquartile range (IQR)16

Descriptive statistics

Standard deviation9.6695398
Coefficient of variation (CV)0.56879646
Kurtosis-1.2
Mean17
Median Absolute Deviation (MAD)8
Skewness0
Sum561
Variance93.5
MonotonicityStrictly increasing
2023-12-13T06:34:06.861954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
1 1
 
3.0%
26 1
 
3.0%
20 1
 
3.0%
21 1
 
3.0%
22 1
 
3.0%
23 1
 
3.0%
24 1
 
3.0%
25 1
 
3.0%
27 1
 
3.0%
2 1
 
3.0%
Other values (23) 23
69.7%
ValueCountFrequency (%)
1 1
3.0%
2 1
3.0%
3 1
3.0%
4 1
3.0%
5 1
3.0%
6 1
3.0%
7 1
3.0%
8 1
3.0%
9 1
3.0%
10 1
3.0%
ValueCountFrequency (%)
33 1
3.0%
32 1
3.0%
31 1
3.0%
30 1
3.0%
29 1
3.0%
28 1
3.0%
27 1
3.0%
26 1
3.0%
25 1
3.0%
24 1
3.0%

업 소 명
Text

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2023-12-13T06:34:07.131043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length14
Mean length6.6969697
Min length2

Characters and Unicode

Total characters221
Distinct characters120
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)100.0%

Sample

1st row153포인츠부대찌개예산점
2nd row고덕갈비
3rd row금강장어구이
4th row내가조선의한우다
5th row다루갈비
ValueCountFrequency (%)
153포인츠부대찌개예산점 1
 
3.0%
성일산채 1
 
3.0%
킹콩부대찌개(내포신도시점 1
 
3.0%
청암회관 1
 
3.0%
지돈가(지명영농조합법인 1
 
3.0%
자연식당 1
 
3.0%
임진강장어 1
 
3.0%
원조설악추어탕 1
 
3.0%
예산냉면갈비 1
 
3.0%
예산(대전방향)휴게소 1
 
3.0%
Other values (23) 23
69.7%
2023-12-13T06:34:07.520123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
당 7
 
3.2%
가 7
 
3.2%
산 7
 
3.2%
( 6
 
2.7%
식 6
 
2.7%
) 6
 
2.7%
어 5
 
2.3%
다 4
 
1.8%
비 4
 
1.8%
수 4
 
1.8%
Other values (110) 165
74.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 204
92.3%
Open Punctuation 6
 
2.7%
Close Punctuation 6
 
2.7%
Decimal Number 3
 
1.4%
Math Symbol 2
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
당 7
 
3.4%
가 7
 
3.4%
산 7
 
3.4%
식 6
 
2.9%
어 5
 
2.5%
다 4
 
2.0%
비 4
 
2.0%
수 4
 
2.0%
대 4
 
2.0%
예 4
 
2.0%
Other values (104) 152
74.5%
Decimal Number
ValueCountFrequency (%)
1 1
33.3%
3 1
33.3%
5 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 204
92.3%
Common 17
 
7.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
당 7
 
3.4%
가 7
 
3.4%
산 7
 
3.4%
식 6
 
2.9%
어 5
 
2.5%
다 4
 
2.0%
비 4
 
2.0%
수 4
 
2.0%
대 4
 
2.0%
예 4
 
2.0%
Other values (104) 152
74.5%
Common
ValueCountFrequency (%)
( 6
35.3%
) 6
35.3%
+ 2
 
11.8%
1 1
 
5.9%
3 1
 
5.9%
5 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 204
92.3%
ASCII 17
 
7.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
당 7
 
3.4%
가 7
 
3.4%
산 7
 
3.4%
식 6
 
2.9%
어 5
 
2.5%
다 4
 
2.0%
비 4
 
2.0%
수 4
 
2.0%
대 4
 
2.0%
예 4
 
2.0%
Other values (104) 152
74.5%
ASCII
ValueCountFrequency (%)
( 6
35.3%
) 6
35.3%
+ 2
 
11.8%
1 1
 
5.9%
3 1
 
5.9%
5 1
 
5.9%

대표자
Text

Distinct32
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2023-12-13T06:34:07.762477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters99
Distinct characters58
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)93.9%

Sample

1st row윤태구
2nd row이옥분
3rd row김상환
4th row강하나
5th row공병대
ValueCountFrequency (%)
윤태구 2
 
6.1%
이옥분 1
 
3.0%
이병일 1
 
3.0%
지경섭 1
 
3.0%
맹규재 1
 
3.0%
장대수 1
 
3.0%
조미숙 1
 
3.0%
조현구 1
 
3.0%
오인환 1
 
3.0%
차복자 1
 
3.0%
Other values (22) 22
66.7%
2023-12-13T06:34:08.125753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
조 8
 
8.1%
이 6
 
6.1%
윤 5
 
5.1%
자 4
 
4.0%
병 4
 
4.0%
정 3
 
3.0%
구 3
 
3.0%
김 3
 
3.0%
상 2
 
2.0%
현 2
 
2.0%
Other values (48) 59
59.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 99
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
조 8
 
8.1%
이 6
 
6.1%
윤 5
 
5.1%
자 4
 
4.0%
병 4
 
4.0%
정 3
 
3.0%
구 3
 
3.0%
김 3
 
3.0%
상 2
 
2.0%
현 2
 
2.0%
Other values (48) 59
59.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 99
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
조 8
 
8.1%
이 6
 
6.1%
윤 5
 
5.1%
자 4
 
4.0%
병 4
 
4.0%
정 3
 
3.0%
구 3
 
3.0%
김 3
 
3.0%
상 2
 
2.0%
현 2
 
2.0%
Other values (48) 59
59.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 99
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
조 8
 
8.1%
이 6
 
6.1%
윤 5
 
5.1%
자 4
 
4.0%
병 4
 
4.0%
정 3
 
3.0%
구 3
 
3.0%
김 3
 
3.0%
상 2
 
2.0%
현 2
 
2.0%
Other values (48) 59
59.6%

종류
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
한식
32 
분식
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)3.0%

Sample

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

Common Values

ValueCountFrequency (%)
한식 32
97.0%
분식 1
 
3.0%

Length

2023-12-13T06:34:08.287445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:34:08.435338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한식 32
97.0%
분식 1
 
3.0%

소 재 지
Text

Distinct32
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2023-12-13T06:34:08.701275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length15
Mean length12.969697
Min length10

Characters and Unicode

Total characters428
Distinct characters76
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)93.9%

Sample

1st row예산읍 금오대로 144
2nd row덕산면 덕산온천로 371-8
3rd row오가면 오가중앙로 125
4th row광시면 예당로 127-1
5th row예산읍 벚꽃로 100
ValueCountFrequency (%)
예산읍 10
 
9.9%
덕산면 9
 
8.9%
수덕사로 4
 
4.0%
오가면 3
 
3.0%
광시면 3
 
3.0%
벚꽃로 3
 
3.0%
당진영덕고속도로 2
 
2.0%
덕산온천로 2
 
2.0%
금오대로 2
 
2.0%
예당로 2
 
2.0%
Other values (57) 61
60.4%
2023-12-13T06:34:09.138105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
68
 
15.9%
로 29
 
6.8%
1 24
 
5.6%
산 23
 
5.4%
면 21
 
4.9%
덕 18
 
4.2%
예 13
 
3.0%
3 13
 
3.0%
2 13
 
3.0%
읍 12
 
2.8%
Other values (66) 194
45.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 245
57.2%
Decimal Number 108
25.2%
Space Separator 68
 
15.9%
Dash Punctuation 4
 
0.9%
Open Punctuation 1
 
0.2%
Other Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 29
 
11.8%
산 23
 
9.4%
면 21
 
8.6%
덕 18
 
7.3%
예 13
 
5.3%
읍 12
 
4.9%
길 9
 
3.7%
오 7
 
2.9%
사 6
 
2.4%
대 5
 
2.0%
Other values (51) 102
41.6%
Decimal Number
ValueCountFrequency (%)
1 24
22.2%
3 13
12.0%
2 13
12.0%
9 11
10.2%
4 10
9.3%
7 10
9.3%
0 9
 
8.3%
8 6
 
5.6%
5 6
 
5.6%
6 6
 
5.6%
Space Separator
ValueCountFrequency (%)
68
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 245
57.2%
Common 183
42.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 29
 
11.8%
산 23
 
9.4%
면 21
 
8.6%
덕 18
 
7.3%
예 13
 
5.3%
읍 12
 
4.9%
길 9
 
3.7%
오 7
 
2.9%
사 6
 
2.4%
대 5
 
2.0%
Other values (51) 102
41.6%
Common
ValueCountFrequency (%)
68
37.2%
1 24
 
13.1%
3 13
 
7.1%
2 13
 
7.1%
9 11
 
6.0%
4 10
 
5.5%
7 10
 
5.5%
0 9
 
4.9%
8 6
 
3.3%
5 6
 
3.3%
Other values (5) 13
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 245
57.2%
ASCII 183
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
68
37.2%
1 24
 
13.1%
3 13
 
7.1%
2 13
 
7.1%
9 11
 
6.0%
4 10
 
5.5%
7 10
 
5.5%
0 9
 
4.9%
8 6
 
3.3%
5 6
 
3.3%
Other values (5) 13
 
7.1%
Hangul
ValueCountFrequency (%)
로 29
 
11.8%
산 23
 
9.4%
면 21
 
8.6%
덕 18
 
7.3%
예 13
 
5.3%
읍 12
 
4.9%
길 9
 
3.7%
오 7
 
2.9%
사 6
 
2.4%
대 5
 
2.0%
Other values (51) 102
41.6%

주요음식
Text

Distinct25
Distinct (%)75.8%
Missing0
Missing (%)0.0%
Memory size396.0 B
2023-12-13T06:34:09.333447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length4.8181818
Min length2

Characters and Unicode

Total characters159
Distinct characters56
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row부대찌개
2nd row소갈비구이
3rd row장어구이
4th row한우생고기
5th row소,돼지갈비구이
ValueCountFrequency (%)
산채정식 4
 
12.1%
돼지갈비 3
 
9.1%
부대찌개 2
 
6.1%
장어구이 2
 
6.1%
한우생고기 2
 
6.1%
코다림조림 1
 
3.0%
소갈비 1
 
3.0%
한정식 1
 
3.0%
추어탕 1
 
3.0%
백반 1
 
3.0%
Other values (15) 15
45.5%
2023-12-13T06:34:09.677082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
탕 10
 
6.3%
, 8
 
5.0%
어 8
 
5.0%
갈 8
 
5.0%
비 8
 
5.0%
정 5
 
3.1%
식 5
 
3.1%
백 5
 
3.1%
기 5
 
3.1%
이 5
 
3.1%
Other values (46) 92
57.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 151
95.0%
Other Punctuation 8
 
5.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
탕 10
 
6.6%
어 8
 
5.3%
갈 8
 
5.3%
비 8
 
5.3%
정 5
 
3.3%
식 5
 
3.3%
백 5
 
3.3%
기 5
 
3.3%
이 5
 
3.3%
구 5
 
3.3%
Other values (45) 87
57.6%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 151
95.0%
Common 8
 
5.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
탕 10
 
6.6%
어 8
 
5.3%
갈 8
 
5.3%
비 8
 
5.3%
정 5
 
3.3%
식 5
 
3.3%
백 5
 
3.3%
기 5
 
3.3%
이 5
 
3.3%
구 5
 
3.3%
Other values (45) 87
57.6%
Common
ValueCountFrequency (%)
, 8
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 151
95.0%
ASCII 8
 
5.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
탕 10
 
6.6%
어 8
 
5.3%
갈 8
 
5.3%
비 8
 
5.3%
정 5
 
3.3%
식 5
 
3.3%
백 5
 
3.3%
기 5
 
3.3%
이 5
 
3.3%
구 5
 
3.3%
Other values (45) 87
57.6%
ASCII
ValueCountFrequency (%)
, 8
100.0%

Interactions

2023-12-13T06:34:06.381246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:34:09.772406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업 소 명대표자종류소 재 지주요음식
연번1.0001.0000.9490.0000.9320.694
업 소 명1.0001.0001.0001.0001.0001.000
대표자0.9491.0001.0001.0000.9920.974
종류0.0001.0001.0001.0001.0001.000
소 재 지0.9321.0000.9921.0001.0001.000
주요음식0.6941.0000.9741.0001.0001.000
2023-12-13T06:34:09.871923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번종류
연번1.0000.000
종류0.0001.000

Missing values

2023-12-13T06:34:06.497127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:34:06.618263image/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

연번업 소 명대표자종류소 재 지주요음식
01153포인츠부대찌개예산점윤태구한식예산읍 금오대로 144부대찌개
12고덕갈비이옥분한식덕산면 덕산온천로 371-8소갈비구이
23금강장어구이김상환한식오가면 오가중앙로 125장어구이
34내가조선의한우다강하나한식광시면 예당로 127-1한우생고기
45다루갈비공병대한식예산읍 벚꽃로 100소,돼지갈비구이
56대보건설(주)예산+(당진방향)휴게소(한식)정광식한식신양면 당진영덕고속도로 33백반,스넥
67두멍조금자한식덕산면 광천홍암길 83-5오리백숙,닭백숙
78뜨끈이식당윤병선한식덕산면 덕산온천로 331-6해장국
89맛나감자탕조인행한식예산읍 역전로140번길 22감자탕
910매일한우타운식당김동주한식광시면 예당로 155한우생고기
연번업 소 명대표자종류소 재 지주요음식
2324역탑리어죽차복자한식오가면 오가중앙로 60어죽,추어탕
2425예산(대전방향)휴게소오인환한식신양면 당진영덕고속도로 34백반
2526예산냉면갈비조현구한식예산읍 산성공원2길 19돼지갈비
2627원조설악추어탕조미숙한식예산읍 벚꽃로 211추어탕
2728임진강장어장대수한식광시면 충절로 2473장어구이
2829자연식당맹규재한식덕산면 수덕사로 978산채정식
2930지돈가(지명영농조합법인)지경섭한식예산읍 주안길 30돼지갈비
3031청암회관윤태구한식덕산면 옥계신토길 14한정식
3132킹콩부대찌개(내포신도시점)이병일한식삽교읍 청사로192번길 20 (106, 107)호부대찌개
3233태백산가든조현조한식대술면 충령사로 99생등심구이