Overview

Dataset statistics

Number of variables4
Number of observations51
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory35.5 B

Variable types

Numeric1
Text2
Categorical1

Dataset

Description부산광역시 수영구 옥외광고업 현황 데이터로 연번, 상호명, 행정동, 소재지 주소(도로명주소) 정보를 제공하고 있다.
Author부산광역시 수영구
URLhttps://www.data.go.kr/data/3056020/fileData.do

Alerts

연번 has unique valuesUnique
상호 has unique valuesUnique

Reproduction

Analysis started2024-03-15 00:12:26.119802
Analysis finished2024-03-15 00:12:27.139807
Duration1.02 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26
Minimum1
Maximum51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size587.0 B
2024-03-15T09:12:27.363107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.5
Q113.5
median26
Q338.5
95-th percentile48.5
Maximum51
Range50
Interquartile range (IQR)25

Descriptive statistics

Standard deviation14.866069
Coefficient of variation (CV)0.57177187
Kurtosis-1.2
Mean26
Median Absolute Deviation (MAD)13
Skewness0
Sum1326
Variance221
MonotonicityStrictly increasing
2024-03-15T09:12:27.822276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
2.0%
2 1
 
2.0%
29 1
 
2.0%
30 1
 
2.0%
31 1
 
2.0%
32 1
 
2.0%
33 1
 
2.0%
34 1
 
2.0%
35 1
 
2.0%
36 1
 
2.0%
Other values (41) 41
80.4%
ValueCountFrequency (%)
1 1
2.0%
2 1
2.0%
3 1
2.0%
4 1
2.0%
5 1
2.0%
6 1
2.0%
7 1
2.0%
8 1
2.0%
9 1
2.0%
10 1
2.0%
ValueCountFrequency (%)
51 1
2.0%
50 1
2.0%
49 1
2.0%
48 1
2.0%
47 1
2.0%
46 1
2.0%
45 1
2.0%
44 1
2.0%
43 1
2.0%
42 1
2.0%

상호
Text

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size536.0 B
2024-03-15T09:12:28.726543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length5.2156863
Min length2

Characters and Unicode

Total characters266
Distinct characters110
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

Unique51 ?
Unique (%)100.0%

Sample

1st row애드리브
2nd row에이치디자인
3rd row신화광고사
4th row티엘엔지니어링(주)
5th row(주)가양
ValueCountFrequency (%)
애드리브 1
 
1.9%
동양기업 1
 
1.9%
미연사 1
 
1.9%
디자인 1
 
1.9%
다함 1
 
1.9%
예일디자인 1
 
1.9%
주)삼정 1
 
1.9%
비젼아트광고산업 1
 
1.9%
주)비트엘앤디 1
 
1.9%
간판공장 1
 
1.9%
Other values (44) 44
81.5%
2024-03-15T09:12:29.776297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
디 17
 
6.4%
인 13
 
4.9%
광 11
 
4.1%
이 11
 
4.1%
고 11
 
4.1%
자 10
 
3.8%
사 7
 
2.6%
트 6
 
2.3%
기 6
 
2.3%
드 6
 
2.3%
Other values (100) 168
63.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 252
94.7%
Close Punctuation 5
 
1.9%
Open Punctuation 5
 
1.9%
Space Separator 3
 
1.1%
Math Symbol 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
디 17
 
6.7%
인 13
 
5.2%
광 11
 
4.4%
이 11
 
4.4%
고 11
 
4.4%
자 10
 
4.0%
사 7
 
2.8%
트 6
 
2.4%
기 6
 
2.4%
드 6
 
2.4%
Other values (96) 154
61.1%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 252
94.7%
Common 14
 
5.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
디 17
 
6.7%
인 13
 
5.2%
광 11
 
4.4%
이 11
 
4.4%
고 11
 
4.4%
자 10
 
4.0%
사 7
 
2.8%
트 6
 
2.4%
기 6
 
2.4%
드 6
 
2.4%
Other values (96) 154
61.1%
Common
ValueCountFrequency (%)
) 5
35.7%
( 5
35.7%
3
21.4%
+ 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 252
94.7%
ASCII 14
 
5.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
디 17
 
6.7%
인 13
 
5.2%
광 11
 
4.4%
이 11
 
4.4%
고 11
 
4.4%
자 10
 
4.0%
사 7
 
2.8%
트 6
 
2.4%
기 6
 
2.4%
드 6
 
2.4%
Other values (96) 154
61.1%
ASCII
ValueCountFrequency (%)
) 5
35.7%
( 5
35.7%
3
21.4%
+ 1
 
7.1%

행정동
Categorical

Distinct9
Distinct (%)17.6%
Missing0
Missing (%)0.0%
Memory size536.0 B
망미1동
13 
수영동
8 
망미2동
7 
남천1동
7 
민락동
5 
Other values (4)
11 

Length

Max length4
Median length4
Mean length3.745098
Min length3

Unique

Unique2 ?
Unique (%)3.9%

Sample

1st row망미1동
2nd row망미2동
3rd row망미1동
4th row민락동
5th row남천1동

Common Values

ValueCountFrequency (%)
망미1동 13
25.5%
수영동 8
15.7%
망미2동 7
13.7%
남천1동 7
13.7%
민락동 5
 
9.8%
광안1동 5
 
9.8%
광안3동 4
 
7.8%
광안4동 1
 
2.0%
광안2동 1
 
2.0%

Length

2024-03-15T09:12:30.041627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T09:12:30.364488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
망미1동 13
25.5%
수영동 8
15.7%
망미2동 7
13.7%
남천1동 7
13.7%
민락동 5
 
9.8%
광안1동 5
 
9.8%
광안3동 4
 
7.8%
광안4동 1
 
2.0%
광안2동 1
 
2.0%

주소
Text

Distinct50
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size536.0 B
2024-03-15T09:12:31.409867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length31
Mean length26.882353
Min length22

Characters and Unicode

Total characters1371
Distinct characters67
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

Unique49 ?
Unique (%)96.1%

Sample

1st row부산광역시 수영구 과정로 19-2, 3층 (망미동)
2nd row부산광역시 수영구 수미로49번길 8-2, 1층 (망미동)
3rd row부산광역시 수영구 과정로41번길 53-1 (망미동)
4th row부산광역시 수영구 민락본동로 29-1 (민락동)
5th row부산광역시 수영구 수영로476번길 29, 3층 (남천동)
ValueCountFrequency (%)
부산광역시 51
18.6%
수영구 51
18.6%
망미동 20
 
7.3%
광안동 11
 
4.0%
수영로 9
 
3.3%
수영동 8
 
2.9%
남천동 7
 
2.6%
민락동 5
 
1.8%
구락로 5
 
1.8%
과정로 4
 
1.5%
Other values (87) 103
37.6%
2024-03-15T09:12:32.901317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
223
 
16.3%
수 81
 
5.9%
영 79
 
5.8%
광 65
 
4.7%
구 57
 
4.2%
동 55
 
4.0%
부 53
 
3.9%
산 52
 
3.8%
로 51
 
3.7%
( 51
 
3.7%
Other values (57) 604
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 813
59.3%
Space Separator 223
 
16.3%
Decimal Number 202
 
14.7%
Open Punctuation 51
 
3.7%
Close Punctuation 51
 
3.7%
Dash Punctuation 17
 
1.2%
Other Punctuation 14
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 81
 
10.0%
영 79
 
9.7%
광 65
 
8.0%
구 57
 
7.0%
동 55
 
6.8%
부 53
 
6.5%
산 52
 
6.4%
로 51
 
6.3%
시 51
 
6.3%
역 51
 
6.3%
Other values (42) 218
26.8%
Decimal Number
ValueCountFrequency (%)
1 42
20.8%
2 32
15.8%
4 21
10.4%
5 20
9.9%
0 19
9.4%
3 18
8.9%
6 16
 
7.9%
7 13
 
6.4%
9 11
 
5.4%
8 10
 
5.0%
Space Separator
ValueCountFrequency (%)
223
100.0%
Open Punctuation
ValueCountFrequency (%)
( 51
100.0%
Close Punctuation
ValueCountFrequency (%)
) 51
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 813
59.3%
Common 558
40.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 81
 
10.0%
영 79
 
9.7%
광 65
 
8.0%
구 57
 
7.0%
동 55
 
6.8%
부 53
 
6.5%
산 52
 
6.4%
로 51
 
6.3%
시 51
 
6.3%
역 51
 
6.3%
Other values (42) 218
26.8%
Common
ValueCountFrequency (%)
223
40.0%
( 51
 
9.1%
) 51
 
9.1%
1 42
 
7.5%
2 32
 
5.7%
4 21
 
3.8%
5 20
 
3.6%
0 19
 
3.4%
3 18
 
3.2%
- 17
 
3.0%
Other values (5) 64
 
11.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 813
59.3%
ASCII 558
40.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
223
40.0%
( 51
 
9.1%
) 51
 
9.1%
1 42
 
7.5%
2 32
 
5.7%
4 21
 
3.8%
5 20
 
3.6%
0 19
 
3.4%
3 18
 
3.2%
- 17
 
3.0%
Other values (5) 64
 
11.5%
Hangul
ValueCountFrequency (%)
수 81
 
10.0%
영 79
 
9.7%
광 65
 
8.0%
구 57
 
7.0%
동 55
 
6.8%
부 53
 
6.5%
산 52
 
6.4%
로 51
 
6.3%
시 51
 
6.3%
역 51
 
6.3%
Other values (42) 218
26.8%

Interactions

2024-03-15T09:12:26.422730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T09:12:33.406945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상호행정동주소
연번1.0001.0000.0000.945
상호1.0001.0001.0001.000
행정동0.0001.0001.0001.000
주소0.9451.0001.0001.000
2024-03-15T09:12:33.682141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번행정동
연번1.0000.000
행정동0.0001.000

Missing values

2024-03-15T09:12:26.742659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T09:12:27.028595image/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

연번상호행정동주소
01애드리브망미1동부산광역시 수영구 과정로 19-2, 3층 (망미동)
12에이치디자인망미2동부산광역시 수영구 수미로49번길 8-2, 1층 (망미동)
23신화광고사망미1동부산광역시 수영구 과정로41번길 53-1 (망미동)
34티엘엔지니어링(주)민락동부산광역시 수영구 민락본동로 29-1 (민락동)
45(주)가양남천1동부산광역시 수영구 수영로476번길 29, 3층 (남천동)
56하나애드망미1동부산광역시 수영구 망미로8번길 51 (망미동)
67(주)디케이부산경남센터광안3동부산광역시 수영구 수영로 685, 영동빌딩 4층 (광안동)
78명성디자인망미1동부산광역시 수영구 연수로336번길 46 (망미동)
89동양애드컴망미1동부산광역시 수영구 망미로 5-1 (망미동)
910마루기획광안1동부산광역시 수영구 수영로 630 (광안동)
연번상호행정동주소
4142백두광고사광안1동부산광역시 수영구 수영로618번길 13 (광안동)
4243삼일디자인광안3동부산광역시 수영구 광서로10번길 65 (광안동)
4344성경종합광고사민락동부산광역시 수영구 감포로 42-1 (민락동)
4445스마트시스템수영동부산광역시 수영구 구락로 41-4 (수영동)
4546이수디자인민락동부산광역시 수영구 감포로 24 (민락동)
4647일창광고기획수영동부산광역시 수영구 망미번영로70번길 92 (수영동)
4748진홍아이디망미1동부산광역시 수영구 연수로310번길 23 (망미동)
4849프로젝트망미2동부산광역시 수영구 구락로 103-2 (망미동)
4950한국디지텍남천1동부산광역시 수영구 수영로 460 (남천동)
5051홍익광고공사수영동부산광역시 수영구 망미번영로52번길 28 (수영동)