Overview

Dataset statistics

Number of variables4
Number of observations53
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory34.5 B

Variable types

Categorical1
Text3

Dataset

Description해당 정보는 부산광역시 영도구 소재 이용업 현황에 대한 데이터로 업종, 업소명, 소재지, 전화번호 등의 항목을 제공합니다.
Author부산광역시 영도구
URLhttps://www.data.go.kr/data/15089297/fileData.do

Alerts

업종명 has constant value ""Constant
영업소 주소(도로명) has unique valuesUnique

Reproduction

Analysis started2024-04-17 09:56:36.578320
Analysis finished2024-04-17 09:56:36.909648
Duration0.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size556.0 B
이용업
53 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
이용업 53
100.0%

Length

2024-04-17T18:56:36.962422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:56:37.044376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
이용업 53
100.0%

업소명
Text

Distinct52
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size556.0 B
2024-04-17T18:56:37.235141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.7169811
Min length2

Characters and Unicode

Total characters197
Distinct characters100
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)96.2%

Sample

1st row긱스(geeks)
2nd row남성컷트
3rd row청춘컷트
4th rowJ남성컷트헤어
5th row퀸즈헤나 영도점
ValueCountFrequency (%)
삼거리 2
 
3.5%
대광 2
 
3.5%
청호 1
 
1.8%
별장 1
 
1.8%
중리 1
 
1.8%
삼형 1
 
1.8%
우정 1
 
1.8%
대양 1
 
1.8%
정일 1
 
1.8%
월드컵 1
 
1.8%
Other values (45) 45
78.9%
2024-04-17T18:56:37.557551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 13
 
6.6%
원 10
 
5.1%
용 10
 
5.1%
성 7
 
3.6%
청 5
 
2.5%
리 5
 
2.5%
남 5
 
2.5%
트 5
 
2.5%
대 5
 
2.5%
4
 
2.0%
Other values (90) 128
65.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 185
93.9%
Lowercase Letter 5
 
2.5%
Space Separator 4
 
2.0%
Open Punctuation 1
 
0.5%
Close Punctuation 1
 
0.5%
Uppercase Letter 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 13
 
7.0%
원 10
 
5.4%
용 10
 
5.4%
성 7
 
3.8%
청 5
 
2.7%
리 5
 
2.7%
남 5
 
2.7%
트 5
 
2.7%
대 5
 
2.7%
헤 4
 
2.2%
Other values (82) 116
62.7%
Lowercase Letter
ValueCountFrequency (%)
e 2
40.0%
s 1
20.0%
k 1
20.0%
g 1
20.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
J 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 185
93.9%
Common 6
 
3.0%
Latin 6
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 13
 
7.0%
원 10
 
5.4%
용 10
 
5.4%
성 7
 
3.8%
청 5
 
2.7%
리 5
 
2.7%
남 5
 
2.7%
트 5
 
2.7%
대 5
 
2.7%
헤 4
 
2.2%
Other values (82) 116
62.7%
Latin
ValueCountFrequency (%)
e 2
33.3%
s 1
16.7%
k 1
16.7%
g 1
16.7%
J 1
16.7%
Common
ValueCountFrequency (%)
4
66.7%
( 1
 
16.7%
) 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 185
93.9%
ASCII 12
 
6.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 13
 
7.0%
원 10
 
5.4%
용 10
 
5.4%
성 7
 
3.8%
청 5
 
2.7%
리 5
 
2.7%
남 5
 
2.7%
트 5
 
2.7%
대 5
 
2.7%
헤 4
 
2.2%
Other values (82) 116
62.7%
ASCII
ValueCountFrequency (%)
4
33.3%
e 2
16.7%
( 1
 
8.3%
) 1
 
8.3%
s 1
 
8.3%
k 1
 
8.3%
g 1
 
8.3%
J 1
 
8.3%

영업소 주소(도로명)
Text

UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size556.0 B
2024-04-17T18:56:37.821992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length42
Mean length27.264151
Min length18

Characters and Unicode

Total characters1445
Distinct characters86
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

Unique53 ?
Unique (%)100.0%

Sample

1st row부산광역시 영도구 영선대로 67 (영선동2가)
2nd row부산광역시 영도구 와치로 266, 1층 102호 (동삼동, 영도벽산비치타운)
3rd row부산광역시 영도구 남항로49번길 58, 1층 (영선동1가)
4th row부산광역시 영도구 절영로49번길 68 (영선동2가)
5th row부산광역시 영도구 절영로 555, 201호 (동삼동, 삼창파크맨션)
ValueCountFrequency (%)
부산광역시 53
18.5%
영도구 53
18.5%
동삼동 14
 
4.9%
청학동 12
 
4.2%
태종로 7
 
2.4%
1층 6
 
2.1%
하나길 4
 
1.4%
영선동3가 4
 
1.4%
봉래동5가 4
 
1.4%
절영로 3
 
1.0%
Other values (103) 127
44.3%
2024-04-17T18:56:38.202910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
234
 
16.2%
동 78
 
5.4%
영 76
 
5.3%
산 58
 
4.0%
부 54
 
3.7%
도 54
 
3.7%
광 53
 
3.7%
역 53
 
3.7%
시 53
 
3.7%
구 53
 
3.7%
Other values (76) 679
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 883
61.1%
Space Separator 234
 
16.2%
Decimal Number 204
 
14.1%
Close Punctuation 51
 
3.5%
Open Punctuation 51
 
3.5%
Other Punctuation 14
 
1.0%
Dash Punctuation 8
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 78
 
8.8%
영 76
 
8.6%
산 58
 
6.6%
부 54
 
6.1%
도 54
 
6.1%
광 53
 
6.0%
역 53
 
6.0%
시 53
 
6.0%
구 53
 
6.0%
로 42
 
4.8%
Other values (61) 309
35.0%
Decimal Number
ValueCountFrequency (%)
2 33
16.2%
1 33
16.2%
3 28
13.7%
5 22
10.8%
0 18
8.8%
4 15
7.4%
7 15
7.4%
8 14
6.9%
9 13
 
6.4%
6 13
 
6.4%
Space Separator
ValueCountFrequency (%)
234
100.0%
Close Punctuation
ValueCountFrequency (%)
) 51
100.0%
Open Punctuation
ValueCountFrequency (%)
( 51
100.0%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 883
61.1%
Common 562
38.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 78
 
8.8%
영 76
 
8.6%
산 58
 
6.6%
부 54
 
6.1%
도 54
 
6.1%
광 53
 
6.0%
역 53
 
6.0%
시 53
 
6.0%
구 53
 
6.0%
로 42
 
4.8%
Other values (61) 309
35.0%
Common
ValueCountFrequency (%)
234
41.6%
) 51
 
9.1%
( 51
 
9.1%
2 33
 
5.9%
1 33
 
5.9%
3 28
 
5.0%
5 22
 
3.9%
0 18
 
3.2%
4 15
 
2.7%
7 15
 
2.7%
Other values (5) 62
 
11.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 883
61.1%
ASCII 562
38.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
234
41.6%
) 51
 
9.1%
( 51
 
9.1%
2 33
 
5.9%
1 33
 
5.9%
3 28
 
5.0%
5 22
 
3.9%
0 18
 
3.2%
4 15
 
2.7%
7 15
 
2.7%
Other values (5) 62
 
11.0%
Hangul
ValueCountFrequency (%)
동 78
 
8.8%
영 76
 
8.6%
산 58
 
6.6%
부 54
 
6.1%
도 54
 
6.1%
광 53
 
6.0%
역 53
 
6.0%
시 53
 
6.0%
구 53
 
6.0%
로 42
 
4.8%
Other values (61) 309
35.0%

소재지전화
Text

Distinct45
Distinct (%)84.9%
Missing0
Missing (%)0.0%
Memory size556.0 B
2024-04-17T18:56:38.402230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.245283
Min length7

Characters and Unicode

Total characters596
Distinct characters18
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

Unique43 ?
Unique (%)81.1%

Sample

1st row051-946-6260
2nd row데이터 미집계
3rd row데이터 미집계
4th row데이터 미집계
5th row051-405-5490
ValueCountFrequency (%)
데이터 8
 
13.1%
미집계 8
 
13.1%
051-403-8098 2
 
3.3%
051-416-4397 1
 
1.6%
051-417-6541 1
 
1.6%
051-417-0329 1
 
1.6%
051-417-6472 1
 
1.6%
051-416-4894 1
 
1.6%
051-404-2528 1
 
1.6%
051-412-0150 1
 
1.6%
Other values (36) 36
59.0%
2024-04-17T18:56:38.724148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 95
15.9%
- 90
15.1%
0 79
13.3%
4 69
11.6%
5 62
10.4%
2 31
 
5.2%
6 29
 
4.9%
8 27
 
4.5%
7 24
 
4.0%
9 20
 
3.4%
Other values (8) 70
11.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 450
75.5%
Dash Punctuation 90
 
15.1%
Other Letter 48
 
8.1%
Space Separator 8
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 95
21.1%
0 79
17.6%
4 69
15.3%
5 62
13.8%
2 31
 
6.9%
6 29
 
6.4%
8 27
 
6.0%
7 24
 
5.3%
9 20
 
4.4%
3 14
 
3.1%
Other Letter
ValueCountFrequency (%)
계 8
16.7%
집 8
16.7%
이 8
16.7%
미 8
16.7%
터 8
16.7%
데 8
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 90
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 548
91.9%
Hangul 48
 
8.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 95
17.3%
- 90
16.4%
0 79
14.4%
4 69
12.6%
5 62
11.3%
2 31
 
5.7%
6 29
 
5.3%
8 27
 
4.9%
7 24
 
4.4%
9 20
 
3.6%
Other values (2) 22
 
4.0%
Hangul
ValueCountFrequency (%)
계 8
16.7%
집 8
16.7%
이 8
16.7%
미 8
16.7%
터 8
16.7%
데 8
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 548
91.9%
Hangul 48
 
8.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 95
17.3%
- 90
16.4%
0 79
14.4%
4 69
12.6%
5 62
11.3%
2 31
 
5.7%
6 29
 
5.3%
8 27
 
4.9%
7 24
 
4.4%
9 20
 
3.6%
Other values (2) 22
 
4.0%
Hangul
ValueCountFrequency (%)
계 8
16.7%
집 8
16.7%
이 8
16.7%
미 8
16.7%
터 8
16.7%
데 8
16.7%

Correlations

2024-04-17T18:56:38.811441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명영업소 주소(도로명)소재지전화
업소명1.0001.0000.984
영업소 주소(도로명)1.0001.0001.000
소재지전화0.9841.0001.000

Missing values

2024-04-17T18:56:36.807675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T18:56:36.874473image/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

업종명업소명영업소 주소(도로명)소재지전화
0이용업긱스(geeks)부산광역시 영도구 영선대로 67 (영선동2가)051-946-6260
1이용업남성컷트부산광역시 영도구 와치로 266, 1층 102호 (동삼동, 영도벽산비치타운)데이터 미집계
2이용업청춘컷트부산광역시 영도구 남항로49번길 58, 1층 (영선동1가)데이터 미집계
3이용업J남성컷트헤어부산광역시 영도구 절영로49번길 68 (영선동2가)데이터 미집계
4이용업퀸즈헤나 영도점부산광역시 영도구 절영로 555, 201호 (동삼동, 삼창파크맨션)051-405-5490
5이용업해사이용원부산광역시 영도구 상리로 7, 동삼그린힐아파트 상가 나동 1층 103호 (동삼동)데이터 미집계
6이용업대광 이발부산광역시 영도구 상리로 35 (동삼동)051-416-9656
7이용업엘샤론 코리아부산광역시 영도구 절영로13번길 35 (봉래동2가)051-996-2322
8이용업우리이용원부산광역시 영도구 태종로89번길 20 (대교동2가)데이터 미집계
9이용업봉래카트실부산광역시 영도구 대교로2번길 7, 봉래탕 내 3층 (봉래동3가)데이터 미집계
업종명업소명영업소 주소(도로명)소재지전화
43이용업장수부산광역시 영도구 동삼로81번길 28 (동삼동)051-405-5844
44이용업북청부산광역시 영도구 청학로 59-1 (청학동)051-416-6129
45이용업청자부산광역시 영도구 하나길 886 (봉래동5가)051-412-1998
46이용업멋장이부산광역시 영도구 태종로73번길 9 (대교동1가)051-412-6687
47이용업삼거리부산광역시 영도구 하나길 720 (봉래동4가)051-417-5213
48이용업아아부산광역시 영도구 청학동로 27-1 (청학동)051-416-4397
49이용업중앙부산광역시 영도구 동삼로 74-1 (동삼동)051-402-9252
50이용업희망이용원부산광역시 영도구 대교로2번길 14 (봉래동3가)051-417-6541
51이용업대광부산광역시 영도구 일산봉로 92 (청학동)051-403-8098
52이용업무궁화부산광역시 영도구 절영로93번길 25 (남항동2가)051-418-6197