Overview

Dataset statistics

Number of variables3
Number of observations56
Missing cells3
Missing cells (%)1.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory26.3 B

Variable types

Text3

Dataset

Description동래구 관내 착한가격업소 현황에 대한 데이터로 상호(가게명), 도로명 주소, 업소 전화번호 등의 항목을 제공합니다.
Author부산광역시 동래구
URLhttps://www.data.go.kr/data/15011936/fileData.do

Alerts

전화번호 has 3 (5.4%) missing valuesMissing
상호 has unique valuesUnique

Reproduction

Analysis started2024-03-14 10:27:34.473815
Analysis finished2024-03-14 10:27:35.110483
Duration0.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호
Text

UNIQUE 

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size576.0 B
2024-03-14T19:27:35.924333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9.5
Mean length5.75
Min length3

Characters and Unicode

Total characters322
Distinct characters165
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)100.0%

Sample

1st row지지미용실
2nd row논두렁추어탕
3rd row희망통닭
4th row송화루
5th row만점숯불갈비
ValueCountFrequency (%)
지지미용실 1
 
1.6%
깜빠뉴베이커리 1
 
1.6%
하림오리마을 1
 
1.6%
하동녹차팥빙수 1
 
1.6%
원조본가산곰장어집 1
 
1.6%
선우이발원 1
 
1.6%
미남숯불구이 1
 
1.6%
먹을래싸갈래 1
 
1.6%
봉달이 1
 
1.6%
김밥 1
 
1.6%
Other values (53) 53
84.1%
2024-03-14T19:27:37.199147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 10
 
3.1%
이 10
 
3.1%
수 9
 
2.8%
미 7
 
2.2%
7
 
2.2%
집 6
 
1.9%
밥 5
 
1.6%
식 5
 
1.6%
원 5
 
1.6%
동 5
 
1.6%
Other values (155) 253
78.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 311
96.6%
Space Separator 7
 
2.2%
Close Punctuation 2
 
0.6%
Open Punctuation 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 10
 
3.2%
이 10
 
3.2%
수 9
 
2.9%
미 7
 
2.3%
집 6
 
1.9%
밥 5
 
1.6%
식 5
 
1.6%
원 5
 
1.6%
동 5
 
1.6%
지 4
 
1.3%
Other values (152) 245
78.8%
Space Separator
ValueCountFrequency (%)
7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 311
96.6%
Common 11
 
3.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 10
 
3.2%
이 10
 
3.2%
수 9
 
2.9%
미 7
 
2.3%
집 6
 
1.9%
밥 5
 
1.6%
식 5
 
1.6%
원 5
 
1.6%
동 5
 
1.6%
지 4
 
1.3%
Other values (152) 245
78.8%
Common
ValueCountFrequency (%)
7
63.6%
) 2
 
18.2%
( 2
 
18.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 311
96.6%
ASCII 11
 
3.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 10
 
3.2%
이 10
 
3.2%
수 9
 
2.9%
미 7
 
2.3%
집 6
 
1.9%
밥 5
 
1.6%
식 5
 
1.6%
원 5
 
1.6%
동 5
 
1.6%
지 4
 
1.3%
Other values (152) 245
78.8%
ASCII
ValueCountFrequency (%)
7
63.6%
) 2
 
18.2%
( 2
 
18.2%

도로명주소
Text

Distinct55
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size576.0 B
2024-03-14T19:27:38.153422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length30
Mean length25.785714
Min length21

Characters and Unicode

Total characters1444
Distinct characters65
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

Unique54 ?
Unique (%)96.4%

Sample

1st row부산광역시 동래구 금강공원로20번길 65(온천동)
2nd row부산광역시 동래구 명륜로139번길 42-5(명륜동)
3rd row부산광역시 동래구 명륜로98번길 94(낙민동)
4th row부산광역시 동래구 아시아드대로207번길 9(온천동)
5th row부산광역시 동래구 명륜로98번길 18(수안동)
ValueCountFrequency (%)
부산광역시 56
24.2%
동래구 56
24.2%
명륜로98번길 4
 
1.7%
아시아드대로 3
 
1.3%
명안로86번길 2
 
0.9%
17(명장동 2
 
0.9%
사직북로 2
 
0.9%
1층(명륜동 2
 
0.9%
삼성대길 2
 
0.9%
충렬대로359번길 2
 
0.9%
Other values (96) 100
43.3%
2024-03-14T19:27:39.355223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
175
 
12.1%
동 116
 
8.0%
시 61
 
4.2%
래 60
 
4.2%
부 56
 
3.9%
광 56
 
3.9%
역 56
 
3.9%
구 56
 
3.9%
산 56
 
3.9%
) 56
 
3.9%
Other values (55) 696
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 903
62.5%
Decimal Number 237
 
16.4%
Space Separator 175
 
12.1%
Close Punctuation 56
 
3.9%
Open Punctuation 56
 
3.9%
Dash Punctuation 10
 
0.7%
Other Punctuation 7
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 116
 
12.8%
시 61
 
6.8%
래 60
 
6.6%
부 56
 
6.2%
광 56
 
6.2%
역 56
 
6.2%
구 56
 
6.2%
산 56
 
6.2%
로 54
 
6.0%
길 39
 
4.3%
Other values (40) 293
32.4%
Decimal Number
ValueCountFrequency (%)
1 54
22.8%
2 39
16.5%
3 30
12.7%
4 26
11.0%
9 20
 
8.4%
8 18
 
7.6%
0 15
 
6.3%
6 15
 
6.3%
7 13
 
5.5%
5 7
 
3.0%
Space Separator
ValueCountFrequency (%)
175
100.0%
Close Punctuation
ValueCountFrequency (%)
) 56
100.0%
Open Punctuation
ValueCountFrequency (%)
( 56
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 903
62.5%
Common 541
37.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 116
 
12.8%
시 61
 
6.8%
래 60
 
6.6%
부 56
 
6.2%
광 56
 
6.2%
역 56
 
6.2%
구 56
 
6.2%
산 56
 
6.2%
로 54
 
6.0%
길 39
 
4.3%
Other values (40) 293
32.4%
Common
ValueCountFrequency (%)
175
32.3%
) 56
 
10.4%
( 56
 
10.4%
1 54
 
10.0%
2 39
 
7.2%
3 30
 
5.5%
4 26
 
4.8%
9 20
 
3.7%
8 18
 
3.3%
0 15
 
2.8%
Other values (5) 52
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 903
62.5%
ASCII 541
37.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
175
32.3%
) 56
 
10.4%
( 56
 
10.4%
1 54
 
10.0%
2 39
 
7.2%
3 30
 
5.5%
4 26
 
4.8%
9 20
 
3.7%
8 18
 
3.3%
0 15
 
2.8%
Other values (5) 52
 
9.6%
Hangul
ValueCountFrequency (%)
동 116
 
12.8%
시 61
 
6.8%
래 60
 
6.6%
부 56
 
6.2%
광 56
 
6.2%
역 56
 
6.2%
구 56
 
6.2%
산 56
 
6.2%
로 54
 
6.0%
길 39
 
4.3%
Other values (40) 293
32.4%

전화번호
Text

MISSING 

Distinct53
Distinct (%)100.0%
Missing3
Missing (%)5.4%
Memory size576.0 B
2024-03-14T19:27:40.207973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.018868
Min length12

Characters and Unicode

Total characters637
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

Unique53 ?
Unique (%)100.0%

Sample

1st row051-556-2298
2nd row051-553-5769
3rd row051-555-0073
4th row051-504-5415
5th row051-558-2240
ValueCountFrequency (%)
051-556-3070 1
 
1.9%
051-507-5278 1
 
1.9%
051-503-3639 1
 
1.9%
051-555-3358 1
 
1.9%
051-553-8377 1
 
1.9%
051-556-2804 1
 
1.9%
051-507-7668 1
 
1.9%
051-501-3134 1
 
1.9%
051-502-5757 1
 
1.9%
051-502-5759 1
 
1.9%
Other values (43) 43
81.1%
2024-03-14T19:27:41.562740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 161
25.3%
- 106
16.6%
0 91
14.3%
1 76
11.9%
3 35
 
5.5%
7 33
 
5.2%
2 30
 
4.7%
8 29
 
4.6%
6 28
 
4.4%
4 28
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 531
83.4%
Dash Punctuation 106
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 161
30.3%
0 91
17.1%
1 76
14.3%
3 35
 
6.6%
7 33
 
6.2%
2 30
 
5.6%
8 29
 
5.5%
6 28
 
5.3%
4 28
 
5.3%
9 20
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 106
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 637
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 161
25.3%
- 106
16.6%
0 91
14.3%
1 76
11.9%
3 35
 
5.5%
7 33
 
5.2%
2 30
 
4.7%
8 29
 
4.6%
6 28
 
4.4%
4 28
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 637
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 161
25.3%
- 106
16.6%
0 91
14.3%
1 76
11.9%
3 35
 
5.5%
7 33
 
5.2%
2 30
 
4.7%
8 29
 
4.6%
6 28
 
4.4%
4 28
 
4.4%

Correlations

2024-03-14T19:27:41.719191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상호도로명주소전화번호
상호1.0001.0001.000
도로명주소1.0001.0001.000
전화번호1.0001.0001.000

Missing values

2024-03-14T19:27:34.833462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T19:27:35.057409image/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

상호도로명주소전화번호
0지지미용실부산광역시 동래구 금강공원로20번길 65(온천동)051-556-2298
1논두렁추어탕부산광역시 동래구 명륜로139번길 42-5(명륜동)051-553-5769
2희망통닭부산광역시 동래구 명륜로98번길 94(낙민동)051-555-0073
3송화루부산광역시 동래구 아시아드대로207번길 9(온천동)051-504-5415
4만점숯불갈비부산광역시 동래구 명륜로98번길 18(수안동)051-558-2240
5은혜미용실부산광역시 동래구 수안로 33-4(수안동)051-558-1759
6이화한우소머리곰탕부산광역시 동래구 동래로148번길12(복천동)051-555-4718
7작은영토부산광역시 동래구 동래로 27-7(온천동)051-554-3516
8참뷔페부산광역시 동래구 명륜로112번가길 52, 1층(명륜동)051-552-2456
9하동각부산광역시 동래구 명륜로 130-6(명륜동)051-556-1081
상호도로명주소전화번호
46스시몬(몬스시)부산광역시 동래구 삼성대길 40, 1층(명륜동)051-553-0303
47진미 양푼이 촌국수부산광역시 동래구 사직북로47번길 30-2, 1층(사직동)070-4388-8540
48만나웰빙맛집부산광역시 동래구 충렬대로 306, 1층 103호(낙민동)051-781-3708
49다보랑김밥분식부산광역시 동래구 명륜로112번길 23(수안동)051-556-6678
50옛날 팥빙수부산광역시 동래구 아시아드대로 161(사직동)051-502-9440
51더멋진이발관부산광역시 동래구 여고로113번길 16(사직동)051-505-3988
52윤남성커트부산광역시 동래구 명서로 146, 1층(명장동)<NA>
53영일삼계탕부산광역시 동래구 사직로 64(사직동)051-507-6622
54깜빠뉴베이커리부산광역시 동래구 여고북로 163(온천동)051-506-0637
55대육자동차정비부산광역시 동래구 석사로 33(사직동)051-506-5554