Overview

Dataset statistics

Number of variables5
Number of observations63
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory42.1 B

Variable types

Categorical1
Text3
DateTime1

Dataset

Description부산광역시영도구_착한가격업소정보_20230803
Author부산광역시 영도구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3038621

Alerts

데이터 기준일 has constant value ""Constant
업종 is highly imbalanced (50.5%)Imbalance
업소명 has unique valuesUnique
도로명주소 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:36:30.004344
Analysis finished2023-12-10 16:36:30.497309
Duration0.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종
Categorical

IMBALANCE 

Distinct6
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size636.0 B
식당
42 
이미용
17 
세탁소
 
1
목욕장
 
1
사진관
 
1

Length

Max length4
Median length2
Mean length2.3492063
Min length2

Unique

Unique4 ?
Unique (%)6.3%

Sample

1st row식당
2nd row이미용
3rd row이미용
4th row이미용
5th row이미용

Common Values

ValueCountFrequency (%)
식당 42
66.7%
이미용 17
27.0%
세탁소 1
 
1.6%
목욕장 1
 
1.6%
사진관 1
 
1.6%
체육시설 1
 
1.6%

Length

2023-12-11T01:36:30.578039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:36:30.713730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식당 42
66.7%
이미용 17
27.0%
세탁소 1
 
1.6%
목욕장 1
 
1.6%
사진관 1
 
1.6%
체육시설 1
 
1.6%

업소명
Text

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size636.0 B
2023-12-11T01:36:30.951317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length10
Mean length5.1587302
Min length1

Characters and Unicode

Total characters325
Distinct characters167
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)100.0%

Sample

1st row함흥보쌈
2nd row김선임헤어샵
3rd row효정헤어
4th row리라헤어라인
5th row오고파미용실
ValueCountFrequency (%)
함흥보쌈 1
 
1.5%
희망이용원 1
 
1.5%
외양간혜림 1
 
1.5%
대성이용원 1
 
1.5%
아아이용원 1
 
1.5%
부산갈매기 1
 
1.5%
영도해장국집 1
 
1.5%
양푼이국수 1
 
1.5%
고기밥상 1
 
1.5%
연창돼지국밥 1
 
1.5%
Other values (56) 56
84.8%
2023-12-11T01:36:31.392653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 11
 
3.4%
국 9
 
2.8%
어 9
 
2.8%
장 8
 
2.5%
기 7
 
2.2%
용 7
 
2.2%
식 6
 
1.8%
수 6
 
1.8%
영 6
 
1.8%
미 5
 
1.5%
Other values (157) 251
77.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 318
97.8%
Space Separator 3
 
0.9%
Other Punctuation 2
 
0.6%
Close Punctuation 1
 
0.3%
Open Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 11
 
3.5%
국 9
 
2.8%
어 9
 
2.8%
장 8
 
2.5%
기 7
 
2.2%
용 7
 
2.2%
식 6
 
1.9%
수 6
 
1.9%
영 6
 
1.9%
미 5
 
1.6%
Other values (152) 244
76.7%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
· 1
50.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 318
97.8%
Common 7
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 11
 
3.5%
국 9
 
2.8%
어 9
 
2.8%
장 8
 
2.5%
기 7
 
2.2%
용 7
 
2.2%
식 6
 
1.9%
수 6
 
1.9%
영 6
 
1.9%
미 5
 
1.6%
Other values (152) 244
76.7%
Common
ValueCountFrequency (%)
3
42.9%
) 1
 
14.3%
( 1
 
14.3%
, 1
 
14.3%
· 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 318
97.8%
ASCII 6
 
1.8%
None 1
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 11
 
3.5%
국 9
 
2.8%
어 9
 
2.8%
장 8
 
2.5%
기 7
 
2.2%
용 7
 
2.2%
식 6
 
1.9%
수 6
 
1.9%
영 6
 
1.9%
미 5
 
1.6%
Other values (152) 244
76.7%
ASCII
ValueCountFrequency (%)
3
50.0%
) 1
 
16.7%
( 1
 
16.7%
, 1
 
16.7%
None
ValueCountFrequency (%)
· 1
100.0%

도로명주소
Text

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size636.0 B
2023-12-11T01:36:31.735480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length30
Mean length17.428571
Min length11

Characters and Unicode

Total characters1098
Distinct characters75
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

Unique63 ?
Unique (%)100.0%

Sample

1st row남항로 42 (영선동2가)
2nd row번영1길 14 (봉래동4가)
3rd row꿈나무길 254 (영선동3가)
4th row번영길 57 (신선동1가)
5th row절영로101번길 17 (영선동3가)
ValueCountFrequency (%)
동삼동 11
 
5.7%
남항동1가 7
 
3.6%
남항로 6
 
3.1%
상가동 6
 
3.1%
태종로 5
 
2.6%
꿈나무길 4
 
2.1%
절영로 4
 
2.1%
봉래동3가 4
 
2.1%
청학동 4
 
2.1%
영선동2가 3
 
1.6%
Other values (113) 139
72.0%
2023-12-11T01:36:32.157923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
132
 
12.0%
동 102
 
9.3%
( 63
 
5.7%
) 63
 
5.7%
로 55
 
5.0%
1 54
 
4.9%
2 47
 
4.3%
가 45
 
4.1%
3 32
 
2.9%
길 31
 
2.8%
Other values (65) 474
43.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 564
51.4%
Decimal Number 249
22.7%
Space Separator 132
 
12.0%
Open Punctuation 63
 
5.7%
Close Punctuation 63
 
5.7%
Other Punctuation 21
 
1.9%
Dash Punctuation 6
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 102
18.1%
로 55
 
9.8%
가 45
 
8.0%
길 31
 
5.5%
삼 28
 
5.0%
영 27
 
4.8%
번 25
 
4.4%
남 24
 
4.3%
항 24
 
4.3%
선 15
 
2.7%
Other values (50) 188
33.3%
Decimal Number
ValueCountFrequency (%)
1 54
21.7%
2 47
18.9%
3 32
12.9%
4 25
10.0%
6 18
 
7.2%
5 17
 
6.8%
0 16
 
6.4%
9 15
 
6.0%
7 14
 
5.6%
8 11
 
4.4%
Space Separator
ValueCountFrequency (%)
132
100.0%
Open Punctuation
ValueCountFrequency (%)
( 63
100.0%
Close Punctuation
ValueCountFrequency (%)
) 63
100.0%
Other Punctuation
ValueCountFrequency (%)
, 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 564
51.4%
Common 534
48.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 102
18.1%
로 55
 
9.8%
가 45
 
8.0%
길 31
 
5.5%
삼 28
 
5.0%
영 27
 
4.8%
번 25
 
4.4%
남 24
 
4.3%
항 24
 
4.3%
선 15
 
2.7%
Other values (50) 188
33.3%
Common
ValueCountFrequency (%)
132
24.7%
( 63
11.8%
) 63
11.8%
1 54
10.1%
2 47
 
8.8%
3 32
 
6.0%
4 25
 
4.7%
, 21
 
3.9%
6 18
 
3.4%
5 17
 
3.2%
Other values (5) 62
11.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 564
51.4%
ASCII 534
48.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
132
24.7%
( 63
11.8%
) 63
11.8%
1 54
10.1%
2 47
 
8.8%
3 32
 
6.0%
4 25
 
4.7%
, 21
 
3.9%
6 18
 
3.4%
5 17
 
3.2%
Other values (5) 62
11.6%
Hangul
ValueCountFrequency (%)
동 102
18.1%
로 55
 
9.8%
가 45
 
8.0%
길 31
 
5.5%
삼 28
 
5.0%
영 27
 
4.8%
번 25
 
4.4%
남 24
 
4.3%
항 24
 
4.3%
선 15
 
2.7%
Other values (50) 188
33.3%

연락처
Text

Distinct58
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Memory size636.0 B
2023-12-11T01:36:32.388075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.222222
Min length2

Characters and Unicode

Total characters707
Distinct characters13
Distinct categories3 ?
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 (%)88.9%

Sample

1st row051-416-2342
2nd row051-415-3588
3rd row051-416-3450
4th row051-414-8586
5th row051-413-5031
ValueCountFrequency (%)
없음 5
 
7.9%
051-413-3799 2
 
3.2%
051-417-8885 1
 
1.6%
051-418-6683 1
 
1.6%
051-404-0855 1
 
1.6%
051-404-1850 1
 
1.6%
051-416-8716 1
 
1.6%
051-418-7080 1
 
1.6%
051-417-6472 1
 
1.6%
051-416-4397 1
 
1.6%
Other values (48) 48
76.2%
2023-12-11T01:36:32.753373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 116
16.4%
1 110
15.6%
0 101
14.3%
5 93
13.2%
4 82
11.6%
3 43
 
6.1%
7 37
 
5.2%
8 31
 
4.4%
9 29
 
4.1%
2 28
 
4.0%
Other values (3) 37
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 581
82.2%
Dash Punctuation 116
 
16.4%
Other Letter 10
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 110
18.9%
0 101
17.4%
5 93
16.0%
4 82
14.1%
3 43
 
7.4%
7 37
 
6.4%
8 31
 
5.3%
9 29
 
5.0%
2 28
 
4.8%
6 27
 
4.6%
Other Letter
ValueCountFrequency (%)
없 5
50.0%
음 5
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 116
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 697
98.6%
Hangul 10
 
1.4%

Most frequent character per script

Common
ValueCountFrequency (%)
- 116
16.6%
1 110
15.8%
0 101
14.5%
5 93
13.3%
4 82
11.8%
3 43
 
6.2%
7 37
 
5.3%
8 31
 
4.4%
9 29
 
4.2%
2 28
 
4.0%
Hangul
ValueCountFrequency (%)
없 5
50.0%
음 5
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 697
98.6%
Hangul 10
 
1.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 116
16.6%
1 110
15.8%
0 101
14.5%
5 93
13.3%
4 82
11.8%
3 43
 
6.2%
7 37
 
5.3%
8 31
 
4.4%
9 29
 
4.2%
2 28
 
4.0%
Hangul
ValueCountFrequency (%)
없 5
50.0%
음 5
50.0%

데이터 기준일
Date

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size636.0 B
Minimum2023-08-03 00:00:00
Maximum2023-08-03 00:00:00
2023-12-11T01:36:32.892472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:36:33.006232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-11T01:36:33.115613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종업소명도로명주소연락처
업종1.0001.0001.0000.991
업소명1.0001.0001.0001.000
도로명주소1.0001.0001.0001.000
연락처0.9911.0001.0001.000

Missing values

2023-12-11T01:36:30.329647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:36:30.440809image/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

업종업소명도로명주소연락처데이터 기준일
0식당함흥보쌈남항로 42 (영선동2가)051-416-23422023-08-03
1이미용김선임헤어샵번영1길 14 (봉래동4가)051-415-35882023-08-03
2이미용효정헤어꿈나무길 254 (영선동3가)051-416-34502023-08-03
3이미용리라헤어라인번영길 57 (신선동1가)051-414-85862023-08-03
4이미용오고파미용실절영로101번길 17 (영선동3가)051-413-50312023-08-03
5식당영선불고기절영로35번길 69 (영선동1가)051-416-75702023-08-03
6식당티모아절영로13번길 25, 상가동 (봉래동2가, 대화아파트)051-415-35842023-08-03
7식당영선꼼장어·바다장어태종로89번길 13 (대교동2가)051-412-92902023-08-03
8식당금성갈비탕남항로 35-2 (남항동1가)051-416-55532023-08-03
9식당부영식당태종로113번길 23 (봉래동3가)051-416-74632023-08-03
업종업소명도로명주소연락처데이터 기준일
53식당동규분식남항로19번길 1(남항동1가)051-418-68692023-08-03
54식당동방밀면꿈나무길 239(영선동2가)051-416-95922023-08-03
55식당마이퍼주는집동삼로 120(동삼동)051-403-62332023-08-03
56식당영도할매국수, 과일 (영도시니어클럽)절영로101번길 18(영선동3가)051-413-72722023-08-03
57식당옛날한우곰탕태종로 744, 5층(동삼동)051-405-08012023-08-03
58식당오늘도달다절영로 551-1, 삼창파크타운상가 2층(동삼동)051-515-25402023-08-03
59식당초량화진갈비삼겹살영선대로 59(영선동3가)051-418-66832023-08-03
60식당국제하이포크중리로 24 (동삼동)051-405-89892023-08-03
61이미용머리치장청학동로 50(청학동)없음2023-08-03
62이미용정성희칼라공간태종로 132, 1층(봉래동3가)없음2023-08-03