Overview

Dataset statistics

Number of variables7
Number of observations714
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory39.9 KiB
Average record size in memory57.2 B

Variable types

Numeric1
Categorical3
DateTime1
Text2

Dataset

Description서울특별시 동작구 옥외광고물 허가 현황에는 허가구분, 광고물 종류, 허가 신고일, 업소명, 도로명주소의 데이터가 포함되어 있습니다.
Author서울특별시 동작구
URLhttps://www.data.go.kr/data/15100274/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
순번 is highly overall correlated with 구분High correlation
구분 is highly overall correlated with 순번High correlation
순번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 22:44:36.474356
Analysis finished2024-03-14 22:44:38.176921
Duration1.7 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct714
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean357.5
Minimum1
Maximum714
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.4 KiB
2024-03-15T07:44:38.380924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile36.65
Q1179.25
median357.5
Q3535.75
95-th percentile678.35
Maximum714
Range713
Interquartile range (IQR)356.5

Descriptive statistics

Standard deviation206.25833
Coefficient of variation (CV)0.57694639
Kurtosis-1.2
Mean357.5
Median Absolute Deviation (MAD)178.5
Skewness0
Sum255255
Variance42542.5
MonotonicityStrictly increasing
2024-03-15T07:44:38.762811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
492 1
 
0.1%
472 1
 
0.1%
473 1
 
0.1%
474 1
 
0.1%
475 1
 
0.1%
476 1
 
0.1%
477 1
 
0.1%
478 1
 
0.1%
479 1
 
0.1%
Other values (704) 704
98.6%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
714 1
0.1%
713 1
0.1%
712 1
0.1%
711 1
0.1%
710 1
0.1%
709 1
0.1%
708 1
0.1%
707 1
0.1%
706 1
0.1%
705 1
0.1%

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
허가
436 
신고
278 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
허가 436
61.1%
신고 278
38.9%

Length

2024-03-15T07:44:39.040080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T07:44:39.224075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
허가 436
61.1%
신고 278
38.9%

허가신고일
Date

Distinct320
Distinct (%)44.8%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
Minimum1993-02-06 00:00:00
Maximum2024-01-02 00:00:00
2024-03-15T07:44:39.429547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T07:44:39.682619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

광고물종류
Categorical

Distinct8
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
돌출간판
284 
벽면이용간판(가로형)
160 
공공시설물이용 광고물
122 
교통수단이용 광고물
86 
지주이용 간판
36 
Other values (3)
 
26

Length

Max length11
Median length10
Mean length7.7226891
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row벽면이용간판(세로형)
2nd row벽면이용간판(세로형)
3rd row벽면이용간판(가로형)
4th row벽면이용간판(세로형)
5th row옥상간판

Common Values

ValueCountFrequency (%)
돌출간판 284
39.8%
벽면이용간판(가로형) 160
22.4%
공공시설물이용 광고물 122
17.1%
교통수단이용 광고물 86
 
12.0%
지주이용 간판 36
 
5.0%
옥상간판 16
 
2.2%
벽면이용간판(세로형) 8
 
1.1%
현수막게시틀 2
 
0.3%

Length

2024-03-15T07:44:40.006739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T07:44:40.258466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
돌출간판 284
29.6%
광고물 208
21.7%
벽면이용간판(가로형 160
16.7%
공공시설물이용 122
12.7%
교통수단이용 86
 
9.0%
지주이용 36
 
3.8%
간판 36
 
3.8%
옥상간판 16
 
1.7%
벽면이용간판(세로형 8
 
0.8%
현수막게시틀 2
 
0.2%

업소명
Text

Distinct481
Distinct (%)67.4%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
2024-03-15T07:44:41.100330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length18
Mean length7.6666667
Min length2

Characters and Unicode

Total characters5474
Distinct characters487
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique438 ?
Unique (%)61.3%

Sample

1st row드림캐슬타워
2nd row드림캐슬타워
3rd row더클래식동작
4th row더클래식동작
5th row(주)대환애드
ValueCountFrequency (%)
주)농심 36
 
4.0%
파트너스 33
 
3.7%
주)인벤트 33
 
3.7%
제이씨데코코리아(주 30
 
3.3%
주식회사 25
 
2.8%
주)드웰링 21
 
2.3%
클레어폭스 17
 
1.9%
주)한성디자인기획 14
 
1.6%
주)클레어폭스 13
 
1.5%
주)모토브 12
 
1.3%
Other values (552) 662
73.9%
2024-03-15T07:44:42.185935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 286
 
5.2%
( 243
 
4.4%
) 242
 
4.4%
182
 
3.3%
스 143
 
2.6%
이 109
 
2.0%
트 96
 
1.8%
원 89
 
1.6%
사 77
 
1.4%
아 73
 
1.3%
Other values (477) 3934
71.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4697
85.8%
Open Punctuation 243
 
4.4%
Close Punctuation 242
 
4.4%
Space Separator 182
 
3.3%
Uppercase Letter 70
 
1.3%
Decimal Number 25
 
0.5%
Lowercase Letter 10
 
0.2%
Dash Punctuation 4
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 286
 
6.1%
스 143
 
3.0%
이 109
 
2.3%
트 96
 
2.0%
원 89
 
1.9%
사 77
 
1.6%
아 73
 
1.6%
코 71
 
1.5%
리 70
 
1.5%
인 63
 
1.3%
Other values (437) 3620
77.1%
Uppercase Letter
ValueCountFrequency (%)
C 8
 
11.4%
G 7
 
10.0%
S 7
 
10.0%
E 6
 
8.6%
K 5
 
7.1%
N 4
 
5.7%
H 3
 
4.3%
L 3
 
4.3%
R 3
 
4.3%
T 3
 
4.3%
Other values (11) 21
30.0%
Lowercase Letter
ValueCountFrequency (%)
b 2
20.0%
k 2
20.0%
l 1
10.0%
c 1
10.0%
p 1
10.0%
f 1
10.0%
e 1
10.0%
s 1
10.0%
Decimal Number
ValueCountFrequency (%)
3 7
28.0%
2 7
28.0%
5 4
16.0%
1 3
12.0%
6 2
 
8.0%
7 2
 
8.0%
Open Punctuation
ValueCountFrequency (%)
( 243
100.0%
Close Punctuation
ValueCountFrequency (%)
) 242
100.0%
Space Separator
ValueCountFrequency (%)
182
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4697
85.8%
Common 697
 
12.7%
Latin 80
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 286
 
6.1%
스 143
 
3.0%
이 109
 
2.3%
트 96
 
2.0%
원 89
 
1.9%
사 77
 
1.6%
아 73
 
1.6%
코 71
 
1.5%
리 70
 
1.5%
인 63
 
1.3%
Other values (437) 3620
77.1%
Latin
ValueCountFrequency (%)
C 8
 
10.0%
G 7
 
8.8%
S 7
 
8.8%
E 6
 
7.5%
K 5
 
6.2%
N 4
 
5.0%
H 3
 
3.8%
L 3
 
3.8%
R 3
 
3.8%
T 3
 
3.8%
Other values (19) 31
38.8%
Common
ValueCountFrequency (%)
( 243
34.9%
) 242
34.7%
182
26.1%
3 7
 
1.0%
2 7
 
1.0%
5 4
 
0.6%
- 4
 
0.6%
1 3
 
0.4%
6 2
 
0.3%
7 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4697
85.8%
ASCII 777
 
14.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 286
 
6.1%
스 143
 
3.0%
이 109
 
2.3%
트 96
 
2.0%
원 89
 
1.9%
사 77
 
1.6%
아 73
 
1.6%
코 71
 
1.5%
리 70
 
1.5%
인 63
 
1.3%
Other values (437) 3620
77.1%
ASCII
ValueCountFrequency (%)
( 243
31.3%
) 242
31.1%
182
23.4%
C 8
 
1.0%
3 7
 
0.9%
G 7
 
0.9%
S 7
 
0.9%
2 7
 
0.9%
E 6
 
0.8%
K 5
 
0.6%
Other values (30) 63
 
8.1%

도로명 주소
Text

Distinct504
Distinct (%)70.6%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
2024-03-15T07:44:43.089759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length41
Mean length29.014006
Min length19

Characters and Unicode

Total characters20716
Distinct characters306
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique405 ?
Unique (%)56.7%

Sample

1st row서울특별시 동작구 상도로 164 (상도동)
2nd row서울특별시 동작구 상도로 164 (상도동)
3rd row서울특별시 동작구 노량진로8길 55 (노량진동 더 클래식 동작)
4th row서울특별시 동작구 노량진로8길 55 (노량진동 더 클래식 동작)
5th row서울특별시 동작구 동작대로 13 (사당동)
ValueCountFrequency (%)
서울특별시 712
18.7%
동작구 711
18.7%
사당동 124
 
3.3%
노량진동 108
 
2.8%
신대방동 104
 
2.7%
노량진로 82
 
2.2%
대방동 73
 
1.9%
동작대로29길 68
 
1.8%
상도동 58
 
1.5%
여의대방로 55
 
1.4%
Other values (701) 1715
45.0%
2024-03-15T07:44:44.540171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3467
 
16.7%
동 1669
 
8.1%
작 919
 
4.4%
시 752
 
3.6%
서 738
 
3.6%
울 726
 
3.5%
구 724
 
3.5%
특 717
 
3.5%
별 717
 
3.5%
) 705
 
3.4%
Other values (296) 9582
46.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13177
63.6%
Space Separator 3467
 
16.7%
Decimal Number 2544
 
12.3%
Close Punctuation 705
 
3.4%
Open Punctuation 705
 
3.4%
Dash Punctuation 84
 
0.4%
Uppercase Letter 28
 
0.1%
Other Punctuation 5
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1669
 
12.7%
작 919
 
7.0%
시 752
 
5.7%
서 738
 
5.6%
울 726
 
5.5%
구 724
 
5.5%
특 717
 
5.4%
별 717
 
5.4%
로 665
 
5.0%
대 565
 
4.3%
Other values (269) 4985
37.8%
Decimal Number
ValueCountFrequency (%)
1 654
25.7%
2 459
18.0%
3 225
 
8.8%
5 224
 
8.8%
9 205
 
8.1%
0 179
 
7.0%
4 176
 
6.9%
6 176
 
6.9%
7 141
 
5.5%
8 105
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
C 6
21.4%
A 4
14.3%
S 4
14.3%
T 3
10.7%
V 3
10.7%
K 3
10.7%
B 2
 
7.1%
I 2
 
7.1%
Y 1
 
3.6%
Other Punctuation
ValueCountFrequency (%)
. 2
40.0%
/ 2
40.0%
? 1
20.0%
Space Separator
ValueCountFrequency (%)
3467
100.0%
Close Punctuation
ValueCountFrequency (%)
) 705
100.0%
Open Punctuation
ValueCountFrequency (%)
( 705
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 84
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13177
63.6%
Common 7510
36.3%
Latin 29
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1669
 
12.7%
작 919
 
7.0%
시 752
 
5.7%
서 738
 
5.6%
울 726
 
5.5%
구 724
 
5.5%
특 717
 
5.4%
별 717
 
5.4%
로 665
 
5.0%
대 565
 
4.3%
Other values (269) 4985
37.8%
Common
ValueCountFrequency (%)
3467
46.2%
) 705
 
9.4%
( 705
 
9.4%
1 654
 
8.7%
2 459
 
6.1%
3 225
 
3.0%
5 224
 
3.0%
9 205
 
2.7%
0 179
 
2.4%
4 176
 
2.3%
Other values (7) 511
 
6.8%
Latin
ValueCountFrequency (%)
C 6
20.7%
A 4
13.8%
S 4
13.8%
T 3
10.3%
V 3
10.3%
K 3
10.3%
B 2
 
6.9%
I 2
 
6.9%
e 1
 
3.4%
Y 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13177
63.6%
ASCII 7539
36.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3467
46.0%
) 705
 
9.4%
( 705
 
9.4%
1 654
 
8.7%
2 459
 
6.1%
3 225
 
3.0%
5 224
 
3.0%
9 205
 
2.7%
0 179
 
2.4%
4 176
 
2.3%
Other values (17) 540
 
7.2%
Hangul
ValueCountFrequency (%)
동 1669
 
12.7%
작 919
 
7.0%
시 752
 
5.7%
서 738
 
5.6%
울 726
 
5.5%
구 724
 
5.5%
특 717
 
5.4%
별 717
 
5.4%
로 665
 
5.0%
대 565
 
4.3%
Other values (269) 4985
37.8%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
2023-12-31
714 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-12-31
2nd row2023-12-31
3rd row2023-12-31
4th row2023-12-31
5th row2023-12-31

Common Values

ValueCountFrequency (%)
2023-12-31 714
100.0%

Length

2024-03-15T07:44:44.962328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T07:44:45.285722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-12-31 714
100.0%

Interactions

2024-03-15T07:44:37.287802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T07:44:45.472004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번구분광고물종류
순번1.0000.8690.505
구분0.8691.0000.575
광고물종류0.5050.5751.000
2024-03-15T07:44:45.714182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분광고물종류
구분1.0000.432
광고물종류0.4321.000
2024-03-15T07:44:45.946228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번구분광고물종류
순번1.0000.6990.269
구분0.6991.0000.432
광고물종류0.2690.4321.000

Missing values

2024-03-15T07:44:37.604221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T07:44:38.017007image/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

순번구분허가신고일광고물종류업소명도로명 주소데이터기준일자
01허가2020-12-02벽면이용간판(세로형)드림캐슬타워서울특별시 동작구 상도로 164 (상도동)2023-12-31
12허가2020-12-02벽면이용간판(세로형)드림캐슬타워서울특별시 동작구 상도로 164 (상도동)2023-12-31
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