Overview

Dataset statistics

Number of variables6
Number of observations144
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.0 KiB
Average record size in memory49.9 B

Variable types

Numeric1
Text2
DateTime1
Categorical2

Dataset

Description「 옥외광고물등의 관리 및 옥외광고산업 진흥에 관한 법률」 에 의한 대전광역시 서구 관내에 있는 옥외광고업 등록 자료로 업소명, 주소 , 허가일, 영업상태 현황입니다.
URLhttps://www.data.go.kr/data/15061962/fileData.do

Alerts

상태 has constant value ""Constant
번호 is highly overall correlated with 기준일자High correlation
기준일자 is highly overall correlated with 번호High correlation
기준일자 is highly imbalanced (94.0%)Imbalance
번호 has unique valuesUnique
업소명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:33:17.519816
Analysis finished2023-12-12 09:33:18.209279
Duration0.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct144
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72.5
Minimum1
Maximum144
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T18:33:18.304667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.15
Q136.75
median72.5
Q3108.25
95-th percentile136.85
Maximum144
Range143
Interquartile range (IQR)71.5

Descriptive statistics

Standard deviation41.713307
Coefficient of variation (CV)0.57535596
Kurtosis-1.2
Mean72.5
Median Absolute Deviation (MAD)36
Skewness0
Sum10440
Variance1740
MonotonicityStrictly increasing
2023-12-12T18:33:18.488784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
74 1
 
0.7%
94 1
 
0.7%
95 1
 
0.7%
96 1
 
0.7%
97 1
 
0.7%
98 1
 
0.7%
99 1
 
0.7%
100 1
 
0.7%
101 1
 
0.7%
Other values (134) 134
93.1%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
144 1
0.7%
143 1
0.7%
142 1
0.7%
141 1
0.7%
140 1
0.7%
139 1
0.7%
138 1
0.7%
137 1
0.7%
136 1
0.7%
135 1
0.7%

업소명
Text

UNIQUE 

Distinct144
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-12T18:33:18.915465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length5.9513889
Min length3

Characters and Unicode

Total characters857
Distinct characters220
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique144 ?
Unique (%)100.0%

Sample

1st row영민사
2nd row성일광고
3rd row보성광고
4th row창작광고
5th row대성나염
ValueCountFrequency (%)
주식회사 6
 
3.6%
디자인 5
 
3.0%
광고기획 3
 
1.8%
사인팩토리(간판여기있다 1
 
0.6%
유엔그래픽 1
 
0.6%
간판의 1
 
0.6%
정석(fm 1
 
0.6%
sign 1
 
0.6%
숨 1
 
0.6%
인라이프 1
 
0.6%
Other values (146) 146
87.4%
2023-12-12T18:33:19.457785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 45
 
5.3%
광 44
 
5.1%
획 43
 
5.0%
고 40
 
4.7%
인 36
 
4.2%
디 31
 
3.6%
주 31
 
3.6%
자 27
 
3.2%
) 27
 
3.2%
( 26
 
3.0%
Other values (210) 507
59.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 760
88.7%
Close Punctuation 27
 
3.2%
Open Punctuation 26
 
3.0%
Space Separator 23
 
2.7%
Uppercase Letter 9
 
1.1%
Lowercase Letter 5
 
0.6%
Decimal Number 5
 
0.6%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 45
 
5.9%
광 44
 
5.8%
획 43
 
5.7%
고 40
 
5.3%
인 36
 
4.7%
디 31
 
4.1%
주 31
 
4.1%
자 27
 
3.6%
드 21
 
2.8%
이 18
 
2.4%
Other values (189) 424
55.8%
Uppercase Letter
ValueCountFrequency (%)
M 2
22.2%
F 1
11.1%
S 1
11.1%
R 1
11.1%
D 1
11.1%
G 1
11.1%
P 1
11.1%
Y 1
11.1%
Lowercase Letter
ValueCountFrequency (%)
g 2
40.0%
n 1
20.0%
i 1
20.0%
u 1
20.0%
Decimal Number
ValueCountFrequency (%)
1 2
40.0%
3 1
20.0%
5 1
20.0%
7 1
20.0%
Other Punctuation
ValueCountFrequency (%)
& 1
50.0%
. 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Space Separator
ValueCountFrequency (%)
23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 760
88.7%
Common 83
 
9.7%
Latin 14
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 45
 
5.9%
광 44
 
5.8%
획 43
 
5.7%
고 40
 
5.3%
인 36
 
4.7%
디 31
 
4.1%
주 31
 
4.1%
자 27
 
3.6%
드 21
 
2.8%
이 18
 
2.4%
Other values (189) 424
55.8%
Latin
ValueCountFrequency (%)
g 2
14.3%
M 2
14.3%
F 1
7.1%
S 1
7.1%
n 1
7.1%
R 1
7.1%
i 1
7.1%
u 1
7.1%
D 1
7.1%
G 1
7.1%
Other values (2) 2
14.3%
Common
ValueCountFrequency (%)
) 27
32.5%
( 26
31.3%
23
27.7%
1 2
 
2.4%
3 1
 
1.2%
5 1
 
1.2%
& 1
 
1.2%
7 1
 
1.2%
. 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 760
88.7%
ASCII 97
 
11.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 45
 
5.9%
광 44
 
5.8%
획 43
 
5.7%
고 40
 
5.3%
인 36
 
4.7%
디 31
 
4.1%
주 31
 
4.1%
자 27
 
3.6%
드 21
 
2.8%
이 18
 
2.4%
Other values (189) 424
55.8%
ASCII
ValueCountFrequency (%)
) 27
27.8%
( 26
26.8%
23
23.7%
g 2
 
2.1%
1 2
 
2.1%
M 2
 
2.1%
F 1
 
1.0%
S 1
 
1.0%
n 1
 
1.0%
R 1
 
1.0%
Other values (11) 11
11.3%

주소
Text

Distinct140
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-12T18:33:19.761299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length39
Mean length27.263889
Min length19

Characters and Unicode

Total characters3926
Distinct characters132
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique136 ?
Unique (%)94.4%

Sample

1st row대전광역시 서구 동서대로 1049 (내동)
2nd row대전광역시 서구 도솔로 101 (도마동,1층)
3rd row대전광역시 서구 도솔로 501 (용문동)
4th row대전광역시 서구 도산로167번길 76 (도마동)
5th row대전광역시 서구 변동로 33-1 (변동)
ValueCountFrequency (%)
대전광역시 144
 
17.7%
서구 144
 
17.7%
탄방동 21
 
2.6%
도마동 17
 
2.1%
1층 16
 
2.0%
변동 15
 
1.8%
월평동 14
 
1.7%
도솔로 12
 
1.5%
내동 11
 
1.4%
가장동 10
 
1.2%
Other values (259) 408
50.2%
2023-12-12T18:33:20.271548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
670
 
17.1%
1 173
 
4.4%
대 164
 
4.2%
동 164
 
4.2%
서 153
 
3.9%
광 147
 
3.7%
구 145
 
3.7%
역 144
 
3.7%
시 144
 
3.7%
) 144
 
3.7%
Other values (122) 1878
47.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2198
56.0%
Decimal Number 672
 
17.1%
Space Separator 670
 
17.1%
Close Punctuation 144
 
3.7%
Open Punctuation 144
 
3.7%
Other Punctuation 71
 
1.8%
Dash Punctuation 26
 
0.7%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 164
 
7.5%
동 164
 
7.5%
서 153
 
7.0%
광 147
 
6.7%
구 145
 
6.6%
역 144
 
6.6%
시 144
 
6.6%
전 144
 
6.6%
로 128
 
5.8%
길 69
 
3.1%
Other values (105) 796
36.2%
Decimal Number
ValueCountFrequency (%)
1 173
25.7%
2 90
13.4%
4 65
 
9.7%
3 63
 
9.4%
5 62
 
9.2%
0 56
 
8.3%
6 55
 
8.2%
9 38
 
5.7%
8 35
 
5.2%
7 35
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 70
98.6%
. 1
 
1.4%
Space Separator
ValueCountFrequency (%)
670
100.0%
Close Punctuation
ValueCountFrequency (%)
) 144
100.0%
Open Punctuation
ValueCountFrequency (%)
( 144
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2198
56.0%
Common 1727
44.0%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 164
 
7.5%
동 164
 
7.5%
서 153
 
7.0%
광 147
 
6.7%
구 145
 
6.6%
역 144
 
6.6%
시 144
 
6.6%
전 144
 
6.6%
로 128
 
5.8%
길 69
 
3.1%
Other values (105) 796
36.2%
Common
ValueCountFrequency (%)
670
38.8%
1 173
 
10.0%
) 144
 
8.3%
( 144
 
8.3%
2 90
 
5.2%
, 70
 
4.1%
4 65
 
3.8%
3 63
 
3.6%
5 62
 
3.6%
0 56
 
3.2%
Other values (6) 190
 
11.0%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2198
56.0%
ASCII 1728
44.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
670
38.8%
1 173
 
10.0%
) 144
 
8.3%
( 144
 
8.3%
2 90
 
5.2%
, 70
 
4.1%
4 65
 
3.8%
3 63
 
3.6%
5 62
 
3.6%
0 56
 
3.2%
Other values (7) 191
 
11.1%
Hangul
ValueCountFrequency (%)
대 164
 
7.5%
동 164
 
7.5%
서 153
 
7.0%
광 147
 
6.7%
구 145
 
6.6%
역 144
 
6.6%
시 144
 
6.6%
전 144
 
6.6%
로 128
 
5.8%
길 69
 
3.1%
Other values (105) 796
36.2%

허가일
Date

Distinct141
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum1986-02-27 00:00:00
Maximum2023-06-30 00:00:00
2023-12-12T18:33:20.473327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:33:20.694246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

상태
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
영업/정상
144 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row영업/정상
3rd row영업/정상
4th row영업/정상
5th row영업/정상

Common Values

ValueCountFrequency (%)
영업/정상 144
100.0%

Length

2023-12-12T18:33:20.871570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:33:21.006230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 144
100.0%

기준일자
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-07-17
143 
<NA>
 
1

Length

Max length10
Median length10
Mean length9.9583333
Min length4

Unique

Unique1 ?
Unique (%)0.7%

Sample

1st row2023-07-17
2nd row2023-07-17
3rd row2023-07-17
4th row2023-07-17
5th row2023-07-17

Common Values

ValueCountFrequency (%)
2023-07-17 143
99.3%
<NA> 1
 
0.7%

Length

2023-12-12T18:33:21.158776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:33:21.394486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-07-17 143
99.3%
na 1
 
0.7%

Interactions

2023-12-12T18:33:17.850691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:33:21.513540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호
번호1.000
2023-12-12T18:33:21.621301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호기준일자
번호1.0001.000
기준일자1.0001.000

Missing values

2023-12-12T18:33:18.011950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:33:18.155682image/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

번호업소명주소허가일상태기준일자
01영민사대전광역시 서구 동서대로 1049 (내동)1986-02-27영업/정상2023-07-17
12성일광고대전광역시 서구 도솔로 101 (도마동,1층)1991-06-13영업/정상2023-07-17
23보성광고대전광역시 서구 도솔로 501 (용문동)1991-11-26영업/정상2023-07-17
34창작광고대전광역시 서구 도산로167번길 76 (도마동)1993-06-22영업/정상2023-07-17
45대성나염대전광역시 서구 변동로 33-1 (변동)1994-10-31영업/정상2023-07-17
56국민광고기획대전광역시 서구 월평서로6번길 32, 1층 (월평동)1997-10-13영업/정상2023-07-17
67영일기획대전광역시 서구 도솔로 355 (괴정동)1997-11-03영업/정상2023-07-17
78한밭광고기획대전광역시 서구 계룡로326번길 135 (갈마동)1999-03-24영업/정상2023-07-17
89주식회사 탑대전광역시 서구 변동서로28번길 78-15, 가동 101호 (변동)1999-09-27영업/정상2023-07-17
910세인종합광고기획대전광역시 서구 계룡로339번길 8 (월평동)1999-10-05영업/정상2023-07-17
번호업소명주소허가일상태기준일자
134135주식회사 지구컴즈대전광역시 서구 둔산남로180번길 15, 3층 (탄방동)2023-01-13영업/정상2023-07-17
135136주식회사 룩스필대전광역시 서구 갈마로219번길 47, 위스퀘어빌딩 310호 (괴정동)2023-01-16영업/정상2023-07-17
136137모든광고기획대전광역시 서구 괴정로 180-2 (가장동)2023-03-06영업/정상2023-07-17
137138주식회사 공카대전광역시 서구 계룡로 566, 4층 401호 (괴정동)2023-03-16영업/정상2023-07-17
138139푸른광고기획대전광역시 서구 원도안로179번길 16-20 (도안동)2023-03-21영업/정상2023-07-17
139140(주)더모스트기획대전광역시 서구 원도안로179번길 37, 101호 (도안동)2023-03-29영업/정상2023-07-17
140141안광고기획대전광역시 서구 도마13길 7 (도마동)2023-05-01영업/정상2023-07-17
141142디자인존대전광역시 서구 도산로314번길 87 (가장동)2023-05-11영업/정상2023-07-17
142143주식회사 구광대전광역시 서구 유등로 403, 구광 (변동)2023-05-30영업/정상2023-07-17
143144디자인피디대전광역시 서구 도안동로 3, 리더스프라자에이 101호 (도안동)2023-06-30영업/정상<NA>