Overview

Dataset statistics

Number of variables2
Number of observations485
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.7 KiB
Average record size in memory16.3 B

Variable types

Text2

Dataset

Description식품접객업소 및 집단급식소 시설의 위생적 개선과 서비스수준 향상을 도모하고 낭비적인 음식문화를 개선하는 등의 녹색 음식문화 조성에 기여한 대전광역시 모범음식점에 대한 업소명 및 소재지 정보입니다.
Author대전광역시
URLhttps://www.data.go.kr/data/15063351/fileData.do

Reproduction

Analysis started2023-12-12 03:14:28.791861
Analysis finished2023-12-12 03:14:29.366686
Duration0.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct476
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-12-12T12:14:29.793061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length16
Mean length6.2226804
Min length2

Characters and Unicode

Total characters3018
Distinct characters394
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

Unique468 ?
Unique (%)96.5%

Sample

1st row(주)가오종로상회
2nd row감골오리
3rd row강청골순대국밥
4th row경동오징어국수식당
5th row경성한우축산식당
ValueCountFrequency (%)
착한낙지 3
 
0.6%
토종칼국수 3
 
0.6%
진성아구찜 2
 
0.4%
정통춘천닭갈비 2
 
0.4%
완도수산 2
 
0.4%
대전본점 2
 
0.4%
오가네대구왕뽈떼기 2
 
0.4%
신촌설렁탕 2
 
0.4%
조마루감자탕 2
 
0.4%
보성이네생삼겹살전문점 1
 
0.2%
Other values (500) 500
96.0%
2023-12-12T12:14:30.504737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
98
 
3.2%
82
 
2.7%
74
 
2.5%
57
 
1.9%
47
 
1.6%
45
 
1.5%
44
 
1.5%
43
 
1.4%
42
 
1.4%
41
 
1.4%
Other values (384) 2445
81.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2918
96.7%
Space Separator 36
 
1.2%
Open Punctuation 21
 
0.7%
Close Punctuation 21
 
0.7%
Decimal Number 16
 
0.5%
Other Punctuation 4
 
0.1%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
98
 
3.4%
82
 
2.8%
74
 
2.5%
57
 
2.0%
47
 
1.6%
45
 
1.5%
44
 
1.5%
43
 
1.5%
42
 
1.4%
41
 
1.4%
Other values (373) 2345
80.4%
Decimal Number
ValueCountFrequency (%)
5 5
31.2%
0 5
31.2%
2 3
18.8%
3 2
 
12.5%
4 1
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
D 1
50.0%
Space Separator
ValueCountFrequency (%)
36
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2918
96.7%
Common 98
 
3.2%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
98
 
3.4%
82
 
2.8%
74
 
2.5%
57
 
2.0%
47
 
1.6%
45
 
1.5%
44
 
1.5%
43
 
1.5%
42
 
1.4%
41
 
1.4%
Other values (373) 2345
80.4%
Common
ValueCountFrequency (%)
36
36.7%
( 21
21.4%
) 21
21.4%
5 5
 
5.1%
0 5
 
5.1%
. 4
 
4.1%
2 3
 
3.1%
3 2
 
2.0%
4 1
 
1.0%
Latin
ValueCountFrequency (%)
K 1
50.0%
D 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2918
96.7%
ASCII 100
 
3.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
98
 
3.4%
82
 
2.8%
74
 
2.5%
57
 
2.0%
47
 
1.6%
45
 
1.5%
44
 
1.5%
43
 
1.5%
42
 
1.4%
41
 
1.4%
Other values (373) 2345
80.4%
ASCII
ValueCountFrequency (%)
36
36.0%
( 21
21.0%
) 21
21.0%
5 5
 
5.0%
0 5
 
5.0%
. 4
 
4.0%
2 3
 
3.0%
3 2
 
2.0%
4 1
 
1.0%
K 1
 
1.0%
Distinct482
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-12-12T12:14:30.972001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length43
Mean length29.063918
Min length19

Characters and Unicode

Total characters14096
Distinct characters207
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

Unique479 ?
Unique (%)98.8%

Sample

1st row대전광역시 동구 대전로 446, 301,302,303호 (가오동)
2nd row대전광역시 동구 대전로 896 (삼성동)
3rd row대전광역시 동구 옥천로 187, 101호 (판암동)
4th row대전광역시 동구 계족로 369 (성남동)
5th row대전광역시 동구 계족로140번길 150 (용운동)
ValueCountFrequency (%)
대전광역시 485
 
17.9%
서구 159
 
5.9%
유성구 102
 
3.8%
중구 95
 
3.5%
1층 91
 
3.4%
동구 69
 
2.5%
대덕구 60
 
2.2%
지상1층 39
 
1.4%
2층 31
 
1.1%
봉명동 26
 
1.0%
Other values (788) 1553
57.3%
2023-12-12T12:14:31.629631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2225
 
15.8%
1 734
 
5.2%
711
 
5.0%
616
 
4.4%
( 557
 
4.0%
) 557
 
4.0%
525
 
3.7%
495
 
3.5%
486
 
3.4%
485
 
3.4%
Other values (197) 6705
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7813
55.4%
Decimal Number 2422
 
17.2%
Space Separator 2225
 
15.8%
Open Punctuation 557
 
4.0%
Close Punctuation 557
 
4.0%
Other Punctuation 433
 
3.1%
Dash Punctuation 71
 
0.5%
Math Symbol 9
 
0.1%
Uppercase Letter 9
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
711
 
9.1%
616
 
7.9%
525
 
6.7%
495
 
6.3%
486
 
6.2%
485
 
6.2%
485
 
6.2%
479
 
6.1%
321
 
4.1%
231
 
3.0%
Other values (175) 2979
38.1%
Decimal Number
ValueCountFrequency (%)
1 734
30.3%
2 360
14.9%
3 222
 
9.2%
4 192
 
7.9%
5 180
 
7.4%
0 180
 
7.4%
7 158
 
6.5%
6 144
 
5.9%
8 130
 
5.4%
9 122
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
B 4
44.4%
C 2
22.2%
A 1
 
11.1%
E 1
 
11.1%
D 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
, 430
99.3%
. 3
 
0.7%
Space Separator
ValueCountFrequency (%)
2225
100.0%
Open Punctuation
ValueCountFrequency (%)
( 557
100.0%
Close Punctuation
ValueCountFrequency (%)
) 557
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 71
100.0%
Math Symbol
ValueCountFrequency (%)
~ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7813
55.4%
Common 6274
44.5%
Latin 9
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
711
 
9.1%
616
 
7.9%
525
 
6.7%
495
 
6.3%
486
 
6.2%
485
 
6.2%
485
 
6.2%
479
 
6.1%
321
 
4.1%
231
 
3.0%
Other values (175) 2979
38.1%
Common
ValueCountFrequency (%)
2225
35.5%
1 734
 
11.7%
( 557
 
8.9%
) 557
 
8.9%
, 430
 
6.9%
2 360
 
5.7%
3 222
 
3.5%
4 192
 
3.1%
5 180
 
2.9%
0 180
 
2.9%
Other values (7) 637
 
10.2%
Latin
ValueCountFrequency (%)
B 4
44.4%
C 2
22.2%
A 1
 
11.1%
E 1
 
11.1%
D 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7813
55.4%
ASCII 6283
44.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2225
35.4%
1 734
 
11.7%
( 557
 
8.9%
) 557
 
8.9%
, 430
 
6.8%
2 360
 
5.7%
3 222
 
3.5%
4 192
 
3.1%
5 180
 
2.9%
0 180
 
2.9%
Other values (12) 646
 
10.3%
Hangul
ValueCountFrequency (%)
711
 
9.1%
616
 
7.9%
525
 
6.7%
495
 
6.3%
486
 
6.2%
485
 
6.2%
485
 
6.2%
479
 
6.1%
321
 
4.1%
231
 
3.0%
Other values (175) 2979
38.1%

Missing values

2023-12-12T12:14:29.200614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:14:29.321297image/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
0(주)가오종로상회대전광역시 동구 대전로 446, 301,302,303호 (가오동)
1감골오리대전광역시 동구 대전로 896 (삼성동)
2강청골순대국밥대전광역시 동구 옥천로 187, 101호 (판암동)
3경동오징어국수식당대전광역시 동구 계족로 369 (성남동)
4경성한우축산식당대전광역시 동구 계족로140번길 150 (용운동)
5공주칼국수쭈꾸미구이대전광역시 동구 대전로 422-19 (가오동)
6금성삼계탕대전광역시 동구 선화로196번길 44 (중동)
7금촌한우정육식당대전광역시 동구 계족로 324 (성남동)
8대가밥상대전광역시 동구 대동천우안4길 14 (대동, 2층)
9대박한우집대전광역시 동구 계족로 426 (용전동)
업소명소재지
475다모아밥상대전광역시 대덕구 한밭대로 1027, 지하1층 (오정동)
476비빔국수전문점길갈대전광역시 대덕구 신탄진로567번길 2, 1층 (상서동)
477계족산염소맛집대전광역시 대덕구 송촌북로36번길 11, 2층 (송촌동)
478삼돈이대전광역시 대덕구 대덕대로 1554, 1층 (석봉동, 별관 )
479장동감나무보리밥대전광역시 대덕구 장동로 231 (장동)
480김연수소국밥막국수대전광역시 대덕구 대전로1370번길 13-14, 1-2층 (읍내동)
481딜리버리 팩토리 대전본점대전광역시 대덕구 송촌북로 1, 1층 (중리동)
482소도둑대전송촌점대전광역시 대덕구 송촌북로4번길 49, 1층 (송촌동, 101호)
483명품진한우대전광역시 대덕구 한밭대로1006번길 105, 2층 (오정동)
484샤브쌈주머니비래점대전광역시 대덕구 비래동로 20, 2층 (비래동)