Overview

Dataset statistics

Number of variables7
Number of observations85
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.9 KiB
Average record size in memory58.6 B

Variable types

Text2
Categorical5

Dataset

Description남구 관내 광고를 위한 현수막 게첩을 할 수 있는 지정게시대 데이터로, 위치, 수수료, 게첩가능한 현수막 규격 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15116784/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
작동방식 is highly overall correlated with 제작규격High correlation
제작규격 is highly overall correlated with 작동방식High correlation
작동방식 is highly imbalanced (83.9%)Imbalance
제작규격 is highly imbalanced (83.9%)Imbalance

Reproduction

Analysis started2023-12-12 09:54:17.942048
Analysis finished2023-12-12 09:54:18.752173
Duration0.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

Distinct64
Distinct (%)75.3%
Missing0
Missing (%)0.0%
Memory size812.0 B
2023-12-12T18:54:18.941517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.7294118
Min length3

Characters and Unicode

Total characters317
Distinct characters13
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)52.9%

Sample

1st rowNN1
2nd rowNN1
3rd rowNN2
4th rowNN3
5th rowNN3
ValueCountFrequency (%)
nn15 3
 
3.5%
nn25 3
 
3.5%
nn11 2
 
2.4%
nn20 2
 
2.4%
nn1 2
 
2.4%
nn39 2
 
2.4%
nn37 2
 
2.4%
nn28 2
 
2.4%
nn23 2
 
2.4%
nn19 2
 
2.4%
Other values (54) 63
74.1%
2023-12-12T18:54:19.299406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 132
41.6%
1 37
 
11.7%
2 23
 
7.3%
3 22
 
6.9%
행 19
 
6.0%
정 19
 
6.0%
5 13
 
4.1%
4 13
 
4.1%
9 9
 
2.8%
7 8
 
2.5%
Other values (3) 22
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147
46.4%
Uppercase Letter 132
41.6%
Other Letter 38
 
12.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 37
25.2%
2 23
15.6%
3 22
15.0%
5 13
 
8.8%
4 13
 
8.8%
9 9
 
6.1%
7 8
 
5.4%
6 8
 
5.4%
0 7
 
4.8%
8 7
 
4.8%
Other Letter
ValueCountFrequency (%)
행 19
50.0%
정 19
50.0%
Uppercase Letter
ValueCountFrequency (%)
N 132
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 147
46.4%
Latin 132
41.6%
Hangul 38
 
12.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 37
25.2%
2 23
15.6%
3 22
15.0%
5 13
 
8.8%
4 13
 
8.8%
9 9
 
6.1%
7 8
 
5.4%
6 8
 
5.4%
0 7
 
4.8%
8 7
 
4.8%
Hangul
ValueCountFrequency (%)
행 19
50.0%
정 19
50.0%
Latin
ValueCountFrequency (%)
N 132
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 279
88.0%
Hangul 38
 
12.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 132
47.3%
1 37
 
13.3%
2 23
 
8.2%
3 22
 
7.9%
5 13
 
4.7%
4 13
 
4.7%
9 9
 
3.2%
7 8
 
2.9%
6 8
 
2.9%
0 7
 
2.5%
Hangul
ValueCountFrequency (%)
행 19
50.0%
정 19
50.0%

위치
Text

Distinct84
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size812.0 B
2023-12-12T18:54:19.701977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length11.305882
Min length4

Characters and Unicode

Total characters961
Distinct characters146
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

Unique83 ?
Unique (%)97.6%

Sample

1st row제2순환도로입구 화순방향(1)
2nd row제2순환도로입구 화순방향(2)
3rd row인성고 입구 효천역
4th row노대동 노인건강타운사거리 좌(1)
5th row노대동 노인건강타운사거리 좌(2)
ValueCountFrequency (%)
앞 11
 
5.3%
입구 8
 
3.8%
봉선 5
 
2.4%
삼거리 5
 
2.4%
진월동 4
 
1.9%
1 4
 
1.9%
사거리 4
 
1.9%
노대동 4
 
1.9%
노인건강타운사거리 4
 
1.9%
담벽 4
 
1.9%
Other values (115) 156
74.6%
2023-12-12T18:54:20.262552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
126
 
13.1%
( 44
 
4.6%
) 44
 
4.6%
2 30
 
3.1%
대 28
 
2.9%
1 27
 
2.8%
구 24
 
2.5%
입 18
 
1.9%
리 17
 
1.8%
거 16
 
1.7%
Other values (136) 587
61.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 667
69.4%
Space Separator 126
 
13.1%
Decimal Number 64
 
6.7%
Open Punctuation 44
 
4.6%
Close Punctuation 44
 
4.6%
Other Punctuation 6
 
0.6%
Uppercase Letter 6
 
0.6%
Dash Punctuation 2
 
0.2%
Math Symbol 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 28
 
4.2%
구 24
 
3.6%
입 18
 
2.7%
리 17
 
2.5%
거 16
 
2.4%
동 16
 
2.4%
앞 15
 
2.2%
진 14
 
2.1%
주 14
 
2.1%
지 13
 
1.9%
Other values (121) 492
73.8%
Decimal Number
ValueCountFrequency (%)
2 30
46.9%
1 27
42.2%
3 3
 
4.7%
9 2
 
3.1%
0 2
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
H 2
33.3%
L 2
33.3%
A 2
33.3%
Other Punctuation
ValueCountFrequency (%)
@ 4
66.7%
, 2
33.3%
Space Separator
ValueCountFrequency (%)
126
100.0%
Open Punctuation
ValueCountFrequency (%)
( 44
100.0%
Close Punctuation
ValueCountFrequency (%)
) 44
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
> 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 667
69.4%
Common 288
30.0%
Latin 6
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 28
 
4.2%
구 24
 
3.6%
입 18
 
2.7%
리 17
 
2.5%
거 16
 
2.4%
동 16
 
2.4%
앞 15
 
2.2%
진 14
 
2.1%
주 14
 
2.1%
지 13
 
1.9%
Other values (121) 492
73.8%
Common
ValueCountFrequency (%)
126
43.8%
( 44
 
15.3%
) 44
 
15.3%
2 30
 
10.4%
1 27
 
9.4%
@ 4
 
1.4%
3 3
 
1.0%
- 2
 
0.7%
> 2
 
0.7%
, 2
 
0.7%
Other values (2) 4
 
1.4%
Latin
ValueCountFrequency (%)
H 2
33.3%
L 2
33.3%
A 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 667
69.4%
ASCII 294
30.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
126
42.9%
( 44
 
15.0%
) 44
 
15.0%
2 30
 
10.2%
1 27
 
9.2%
@ 4
 
1.4%
3 3
 
1.0%
H 2
 
0.7%
- 2
 
0.7%
L 2
 
0.7%
Other values (5) 10
 
3.4%
Hangul
ValueCountFrequency (%)
대 28
 
4.2%
구 24
 
3.6%
입 18
 
2.7%
리 17
 
2.5%
거 16
 
2.4%
동 16
 
2.4%
앞 15
 
2.2%
진 14
 
2.1%
주 14
 
2.1%
지 13
 
1.9%
Other values (121) 492
73.8%

작동방식
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size812.0 B
반자동
83 
수동
 
2

Length

Max length3
Median length3
Mean length2.9764706
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
반자동 83
97.6%
수동 2
 
2.4%

Length

2023-12-12T18:54:20.426868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:54:20.542972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
반자동 83
97.6%
수동 2
 
2.4%

제작규격
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size812.0 B
5.7×0.7(M)
83 
5.5×0.7(M)
 
2

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5.7×0.7(M)
2nd row5.7×0.7(M)
3rd row5.7×0.7(M)
4th row5.7×0.7(M)
5th row5.7×0.7(M)

Common Values

ValueCountFrequency (%)
5.7×0.7(M) 83
97.6%
5.5×0.7(M) 2
 
2.4%

Length

2023-12-12T18:54:20.672336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:54:20.822609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5.7×0.7(m 83
97.6%
5.5×0.7(m 2
 
2.4%

부착면수
Categorical

Distinct5
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size812.0 B
5
34 
4
30 
3
12 
2
8 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.2%

Sample

1st row4
2nd row4
3rd row4
4th row4
5th row4

Common Values

ValueCountFrequency (%)
5 34
40.0%
4 30
35.3%
3 12
 
14.1%
2 8
 
9.4%
1 1
 
1.2%

Length

2023-12-12T18:54:20.938649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:54:21.051770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 34
40.0%
4 30
35.3%
3 12
 
14.1%
2 8
 
9.4%
1 1
 
1.2%

민원수수료
Categorical

Distinct3
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size812.0 B
27650
60 
공공, 행정용
19 
15000
 
6

Length

Max length7
Median length5
Mean length5.4470588
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row27650
2nd row27650
3rd row27650
4th row27650
5th row27650

Common Values

ValueCountFrequency (%)
27650 60
70.6%
공공, 행정용 19
 
22.4%
15000 6
 
7.1%

Length

2023-12-12T18:54:21.195386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:54:21.325590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
27650 60
57.7%
공공 19
 
18.3%
행정용 19
 
18.3%
15000 6
 
5.8%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size812.0 B
2023-07-04
85 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-07-04
2nd row2023-07-04
3rd row2023-07-04
4th row2023-07-04
5th row2023-07-04

Common Values

ValueCountFrequency (%)
2023-07-04 85
100.0%

Length

2023-12-12T18:54:21.470634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:54:21.553498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-07-04 85
100.0%

Correlations

2023-12-12T18:54:21.611964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호위치작동방식제작규격부착면수민원수수료
관리번호1.0000.9881.0001.0000.9980.982
위치0.9881.0001.0001.0001.0001.000
작동방식1.0001.0001.0000.9180.0000.000
제작규격1.0001.0000.9181.0000.0000.000
부착면수0.9981.0000.0000.0001.0000.451
민원수수료0.9821.0000.0000.0000.4511.000
2023-12-12T18:54:22.026484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부착면수작동방식제작규격민원수수료
부착면수1.0000.0000.0000.377
작동방식0.0001.0000.7400.000
제작규격0.0000.7401.0000.000
민원수수료0.3770.0000.0001.000
2023-12-12T18:54:22.127731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
작동방식제작규격부착면수민원수수료
작동방식1.0000.7400.0000.000
제작규격0.7401.0000.0000.000
부착면수0.0000.0001.0000.377
민원수수료0.0000.0000.3771.000

Missing values

2023-12-12T18:54:18.572740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:54:18.697285image/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

관리번호위치작동방식제작규격부착면수민원수수료데이터기준일자
0NN1제2순환도로입구 화순방향(1)반자동5.7×0.7(M)4276502023-07-04
1NN1제2순환도로입구 화순방향(2)반자동5.7×0.7(M)4276502023-07-04
2NN2인성고 입구 효천역반자동5.7×0.7(M)4276502023-07-04
3NN3노대동 노인건강타운사거리 좌(1)반자동5.7×0.7(M)4276502023-07-04
4NN3노대동 노인건강타운사거리 좌(2)반자동5.7×0.7(M)4276502023-07-04
5NN4방림모아 2단지 앞반자동5.7×0.7(M)4276502023-07-04
6NN5광주대입구 고가아래(1)반자동5.7×0.7(M)3276502023-07-04
7NN5광주대입구 고가아래(2)반자동5.7×0.7(M)3276502023-07-04
8NN6빅스포 건너편(1)반자동5.7×0.7(M)4276502023-07-04
9NN6빅스포 건너편(2)반자동5.7×0.7(M)4276502023-07-04
관리번호위치작동방식제작규격부착면수민원수수료데이터기준일자
75행정10금당중 입구 삼거리반자동5.7×0.7(M)2공공, 행정용2023-07-04
76행정11무진중학교 앞반자동5.7×0.7(M)5공공, 행정용2023-07-04
77행정12융프라우 보도면반자동5.7×0.7(M)5공공, 행정용2023-07-04
78행정13금호아파트 담장반자동5.7×0.7(M)5공공, 행정용2023-07-04
79행정14건강타운 앞반자동5.7×0.7(M)2공공, 행정용2023-07-04
80행정15방림터널반자동5.7×0.7(M)5공공, 행정용2023-07-04
81행정16봉선동 모아2차아파트 담벽반자동5.7×0.7(M)5공공, 행정용2023-07-04
82행정17진월동 현대1차아파트 담벽반자동5.7×0.7(M)5공공, 행정용2023-07-04
83행정18사직동 행정복지센터반자동5.7×0.7(M)5공공, 행정용2023-07-04
84행정19백운1동 행정복지센터반자동5.7×0.7(M)5공공, 행정용2023-07-04