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 memory35.6 B

Variable types

Numeric1
Text2
Categorical1

Dataset

Description부산광역시_수영구_옥외광고업현황_20220125
Author부산광역시 수영구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3056020

Alerts

연번 has unique valuesUnique
상호 has unique valuesUnique

Reproduction

Analysis started2023-12-10 17:11:53.925460
Analysis finished2023-12-10 17:11:54.807684
Duration0.88 seconds
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 size591.0 B
2023-12-11T02:11:55.449840image/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
2023-12-11T02:11:55.781434image/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 size540.0 B
2023-12-11T02:11:56.337241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length5.3137255
Min length3

Characters and Unicode

Total characters271
Distinct characters108
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 row디자인제이투
2nd row현대후렘
3rd row싸인 디앤아이
4th row사인코아몰
5th row이조광고
ValueCountFrequency (%)
디자인제이투 1
 
1.9%
바라디자인 1
 
1.9%
백두광고사 1
 
1.9%
삼일디자인 1
 
1.9%
주)비트엘앤디 1
 
1.9%
간판공장 1
 
1.9%
공공디자인 1
 
1.9%
높은산 1
 
1.9%
대성기획 1
 
1.9%
동양기업 1
 
1.9%
Other values (44) 44
81.5%
2023-12-11T02:11:57.008428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
디 17
 
6.3%
광 14
 
5.2%
인 14
 
5.2%
고 13
 
4.8%
이 11
 
4.1%
자 11
 
4.1%
사 7
 
2.6%
기 7
 
2.6%
아 7
 
2.6%
획 6
 
2.2%
Other values (98) 164
60.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 257
94.8%
Close Punctuation 5
 
1.8%
Open Punctuation 5
 
1.8%
Space Separator 3
 
1.1%
Math Symbol 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
디 17
 
6.6%
광 14
 
5.4%
인 14
 
5.4%
고 13
 
5.1%
이 11
 
4.3%
자 11
 
4.3%
사 7
 
2.7%
기 7
 
2.7%
아 7
 
2.7%
획 6
 
2.3%
Other values (94) 150
58.4%
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 257
94.8%
Common 14
 
5.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
디 17
 
6.6%
광 14
 
5.4%
인 14
 
5.4%
고 13
 
5.1%
이 11
 
4.3%
자 11
 
4.3%
사 7
 
2.7%
기 7
 
2.7%
아 7
 
2.7%
획 6
 
2.3%
Other values (94) 150
58.4%
Common
ValueCountFrequency (%)
) 5
35.7%
( 5
35.7%
3
21.4%
+ 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 257
94.8%
ASCII 14
 
5.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
디 17
 
6.6%
광 14
 
5.4%
인 14
 
5.4%
고 13
 
5.1%
이 11
 
4.3%
자 11
 
4.3%
사 7
 
2.7%
기 7
 
2.7%
아 7
 
2.7%
획 6
 
2.3%
Other values (94) 150
58.4%
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 size540.0 B
망미1동
11 
남천1동
9 
수영동
8 
민락동
7 
광안1동
7 
Other values (4)
9 

Length

Max length4
Median length4
Mean length3.7058824
Min length3

Unique

Unique1 ?
Unique (%)2.0%

Sample

1st row수영동
2nd row망미2동
3rd row민락동
4th row광안1동
5th row남천1동

Common Values

ValueCountFrequency (%)
망미1동 11
21.6%
남천1동 9
17.6%
수영동 8
15.7%
민락동 7
13.7%
광안1동 7
13.7%
망미2동 3
 
5.9%
광안4동 3
 
5.9%
광안3동 2
 
3.9%
광안2동 1
 
2.0%

Length

2023-12-11T02:11:57.274810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:11:57.497987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
망미1동 11
21.6%
남천1동 9
17.6%
수영동 8
15.7%
민락동 7
13.7%
광안1동 7
13.7%
망미2동 3
 
5.9%
광안4동 3
 
5.9%
광안3동 2
 
3.9%
광안2동 1
 
2.0%

주소
Text

Distinct46
Distinct (%)90.2%
Missing0
Missing (%)0.0%
Memory size540.0 B
2023-12-11T02:11:58.012407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length33
Mean length26.862745
Min length22

Characters and Unicode

Total characters1370
Distinct characters68
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

Unique42 ?
Unique (%)82.4%

Sample

1st row부산광역시 수영구 수영로 759, 알파오피스텔 105호 (수영동)
2nd row부산광역시 수영구 좌수영로210번길 36 (망미동)
3rd row부산광역시 수영구 광남로 237-1, 1층 (민락동)
4th row부산광역시 수영구 감포로 47, 106호 (광안동, 부흥)
5th row부산광역시 수영구 수영로 405 (남천동)
ValueCountFrequency (%)
부산광역시 51
18.4%
수영구 51
18.4%
망미동 14
 
5.1%
광안동 13
 
4.7%
수영로 11
 
4.0%
남천동 9
 
3.2%
수영동 8
 
2.9%
감포로 7
 
2.5%
민락동 7
 
2.5%
1층 4
 
1.4%
Other values (82) 102
36.8%
2023-12-11T02:11:58.813899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
226
 
16.5%
수 82
 
6.0%
영 80
 
5.8%
광 68
 
5.0%
동 56
 
4.1%
구 55
 
4.0%
부 53
 
3.9%
산 53
 
3.9%
로 52
 
3.8%
역 51
 
3.7%
Other values (58) 594
43.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 811
59.2%
Space Separator 226
 
16.5%
Decimal Number 199
 
14.5%
Close Punctuation 51
 
3.7%
Open Punctuation 51
 
3.7%
Other Punctuation 19
 
1.4%
Dash Punctuation 13
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 82
 
10.1%
영 80
 
9.9%
광 68
 
8.4%
동 56
 
6.9%
구 55
 
6.8%
부 53
 
6.5%
산 53
 
6.5%
로 52
 
6.4%
역 51
 
6.3%
시 51
 
6.3%
Other values (43) 210
25.9%
Decimal Number
ValueCountFrequency (%)
1 39
19.6%
2 31
15.6%
4 22
11.1%
3 21
10.6%
0 21
10.6%
6 19
9.5%
5 16
8.0%
7 13
 
6.5%
9 9
 
4.5%
8 8
 
4.0%
Space Separator
ValueCountFrequency (%)
226
100.0%
Close Punctuation
ValueCountFrequency (%)
) 51
100.0%
Open Punctuation
ValueCountFrequency (%)
( 51
100.0%
Other Punctuation
ValueCountFrequency (%)
, 19
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 811
59.2%
Common 559
40.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 82
 
10.1%
영 80
 
9.9%
광 68
 
8.4%
동 56
 
6.9%
구 55
 
6.8%
부 53
 
6.5%
산 53
 
6.5%
로 52
 
6.4%
역 51
 
6.3%
시 51
 
6.3%
Other values (43) 210
25.9%
Common
ValueCountFrequency (%)
226
40.4%
) 51
 
9.1%
( 51
 
9.1%
1 39
 
7.0%
2 31
 
5.5%
4 22
 
3.9%
3 21
 
3.8%
0 21
 
3.8%
6 19
 
3.4%
, 19
 
3.4%
Other values (5) 59
 
10.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 811
59.2%
ASCII 559
40.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
226
40.4%
) 51
 
9.1%
( 51
 
9.1%
1 39
 
7.0%
2 31
 
5.5%
4 22
 
3.9%
3 21
 
3.8%
0 21
 
3.8%
6 19
 
3.4%
, 19
 
3.4%
Other values (5) 59
 
10.6%
Hangul
ValueCountFrequency (%)
수 82
 
10.1%
영 80
 
9.9%
광 68
 
8.4%
동 56
 
6.9%
구 55
 
6.8%
부 53
 
6.5%
산 53
 
6.5%
로 52
 
6.4%
역 51
 
6.3%
시 51
 
6.3%
Other values (43) 210
25.9%

Interactions

2023-12-11T02:11:54.358072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T02:11:58.976911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상호행정동주소
연번1.0001.0000.1400.639
상호1.0001.0001.0001.000
행정동0.1401.0001.0000.982
주소0.6391.0000.9821.000
2023-12-11T02:11:59.122495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번행정동
연번1.0000.139
행정동0.1391.000

Missing values

2023-12-11T02:11:54.603675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:11:54.745299image/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
01디자인제이투수영동부산광역시 수영구 수영로 759, 알파오피스텔 105호 (수영동)
12현대후렘망미2동부산광역시 수영구 좌수영로210번길 36 (망미동)
23싸인 디앤아이민락동부산광역시 수영구 광남로 237-1, 1층 (민락동)
34사인코아몰광안1동부산광역시 수영구 감포로 47, 106호 (광안동, 부흥)
45이조광고남천1동부산광역시 수영구 수영로 405 (남천동)
56디인사이트광안1동부산광역시 수영구 감포로 33, 5동 101호 (광안동, 화목)
67태극광고디자인남천1동부산광역시 수영구 황령산로8번길 22, 1층 (남천동)
78광역디자인민락동부산광역시 수영구 감포로 68 (민락동)
89티엘엔지니어링(주)민락동부산광역시 수영구 민락본동로 29-1 (민락동)
910서울광고광안4동부산광역시 수영구 수영로 505, 2층 (광안동)
연번상호행정동주소
4142스마트시스템수영동부산광역시 수영구 구락로 41-4 (수영동)
4243신영건설광고망미1동부산광역시 수영구 과정로 17 (망미동)
4344이수디자인민락동부산광역시 수영구 감포로 24 (민락동)
4445일창광고기획수영동부산광역시 수영구 망미번영로70번길 92 (수영동)
4546지아이디자인(주)광안1동부산광역시 수영구 수영로 648, 207호 (광안동, 광안동롯데골드로즈)
4647진홍아이디망미1동부산광역시 수영구 연수로310번길 23 (망미동)
4748프로젝트망미2동부산광역시 수영구 구락로 103-2 (망미동)
4849하나애드망미1동부산광역시 수영구 망미로8번길 51 (망미동)
4950한국디지텍남천1동부산광역시 수영구 수영로 460 (남천동)
5051홍익광고공사수영동부산광역시 수영구 망미번영로52번길 28 (수영동)