Overview

Dataset statistics

Number of variables5
Number of observations95
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.9 KiB
Average record size in memory42.4 B

Variable types

Text2
Categorical2
Boolean1

Dataset

Description경기도 의정부시 현수막게첨대 지정벽보판 현황으로 관리번호, 위치, 최대면수, 자동 고정여부, 관리부서 전화번호 등의 항목으로 구성되어 있습니다.
Author경기도 의정부시
URLhttps://www.data.go.kr/data/15017432/fileData.do

Alerts

관리부서전화번호 has constant value ""Constant
최대면수 is highly overall correlated with 자동여부High correlation
자동여부 is highly overall correlated with 최대면수High correlation
관리번호 has unique valuesUnique
위 치 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:31:42.910929
Analysis finished2023-12-12 05:31:43.313705
Duration0.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct95
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size892.0 B
2023-12-12T14:31:43.543316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.8526316
Min length5

Characters and Unicode

Total characters556
Distinct characters31
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)100.0%

Sample

1st row호원1동-1
2nd row호원1동-2
3rd row호원1동-3
4th row호원2동-1
5th row호원2동-2
ValueCountFrequency (%)
호원1동-1 1
 
1.1%
송산2동-5 1
 
1.1%
송산2동-2 1
 
1.1%
송산2동-1 1
 
1.1%
송산1동-10 1
 
1.1%
송산1동-9 1
 
1.1%
송산1동-8 1
 
1.1%
송산1동-7 1
 
1.1%
송산1동-6 1
 
1.1%
송산1동-5 1
 
1.1%
Other values (85) 85
89.5%
2023-12-12T14:31:43.945329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 95
17.1%
- 95
17.1%
1 59
10.6%
2 52
 
9.4%
송 24
 
4.3%
산 24
 
4.3%
신 19
 
3.4%
곡 19
 
3.4%
금 13
 
2.3%
자 13
 
2.3%
Other values (21) 143
25.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 288
51.8%
Decimal Number 173
31.1%
Dash Punctuation 95
 
17.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 95
33.0%
송 24
 
8.3%
산 24
 
8.3%
신 19
 
6.6%
곡 19
 
6.6%
금 13
 
4.5%
자 13
 
4.5%
양 12
 
4.2%
녹 12
 
4.2%
장 9
 
3.1%
Other values (10) 48
16.7%
Decimal Number
ValueCountFrequency (%)
1 59
34.1%
2 52
30.1%
3 13
 
7.5%
4 11
 
6.4%
5 9
 
5.2%
6 6
 
3.5%
7 6
 
3.5%
8 6
 
3.5%
9 6
 
3.5%
0 5
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 95
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 288
51.8%
Common 268
48.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 95
33.0%
송 24
 
8.3%
산 24
 
8.3%
신 19
 
6.6%
곡 19
 
6.6%
금 13
 
4.5%
자 13
 
4.5%
양 12
 
4.2%
녹 12
 
4.2%
장 9
 
3.1%
Other values (10) 48
16.7%
Common
ValueCountFrequency (%)
- 95
35.4%
1 59
22.0%
2 52
19.4%
3 13
 
4.9%
4 11
 
4.1%
5 9
 
3.4%
6 6
 
2.2%
7 6
 
2.2%
8 6
 
2.2%
9 6
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 288
51.8%
ASCII 268
48.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 95
33.0%
송 24
 
8.3%
산 24
 
8.3%
신 19
 
6.6%
곡 19
 
6.6%
금 13
 
4.5%
자 13
 
4.5%
양 12
 
4.2%
녹 12
 
4.2%
장 9
 
3.1%
Other values (10) 48
16.7%
ASCII
ValueCountFrequency (%)
- 95
35.4%
1 59
22.0%
2 52
19.4%
3 13
 
4.9%
4 11
 
4.1%
5 9
 
3.4%
6 6
 
2.2%
7 6
 
2.2%
8 6
 
2.2%
9 6
 
2.2%

위 치
Text

UNIQUE 

Distinct95
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size892.0 B
2023-12-12T14:31:44.157828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length29
Mean length24.347368
Min length16

Characters and Unicode

Total characters2313
Distinct characters161
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

Unique95 ?
Unique (%)100.0%

Sample

1st row경기도 의정부시 호원동 평화로 S커브 롯데아파트 앞
2nd row경기도 의정부시 호원동 평화로 S커브 서울방면 좌
3rd row경기도 의정부시 호원동 평화로 S커브 서울방면 우
4th row경기도 의정부시 호원동 동막교 앞
5th row경기도 의정부시 호원동 신도2차아파트 앞 좌
ValueCountFrequency (%)
경기도 95
18.6%
의정부시 95
18.6%
앞 36
 
7.0%
우 21
 
4.1%
좌 18
 
3.5%
삼거리 13
 
2.5%
자금동 13
 
2.5%
신곡동 11
 
2.1%
사거리 10
 
2.0%
녹양동 9
 
1.8%
Other values (104) 191
37.3%
2023-12-12T14:31:44.477125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
418
18.1%
부 112
 
4.8%
도 111
 
4.8%
의 107
 
4.6%
정 107
 
4.6%
경 98
 
4.2%
시 98
 
4.2%
기 97
 
4.2%
동 90
 
3.9%
앞 44
 
1.9%
Other values (151) 1031
44.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1788
77.3%
Space Separator 418
 
18.1%
Close Punctuation 31
 
1.3%
Open Punctuation 31
 
1.3%
Decimal Number 27
 
1.2%
Uppercase Letter 14
 
0.6%
Dash Punctuation 2
 
0.1%
Lowercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 112
 
6.3%
도 111
 
6.2%
의 107
 
6.0%
정 107
 
6.0%
경 98
 
5.5%
시 98
 
5.5%
기 97
 
5.4%
동 90
 
5.0%
앞 44
 
2.5%
리 37
 
2.1%
Other values (134) 887
49.6%
Decimal Number
ValueCountFrequency (%)
4 7
25.9%
2 5
18.5%
1 5
18.5%
3 3
11.1%
0 3
11.1%
6 3
11.1%
7 1
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
G 3
21.4%
P 3
21.4%
S 3
21.4%
L 3
21.4%
E 2
14.3%
Space Separator
ValueCountFrequency (%)
418
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1788
77.3%
Common 509
 
22.0%
Latin 16
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 112
 
6.3%
도 111
 
6.2%
의 107
 
6.0%
정 107
 
6.0%
경 98
 
5.5%
시 98
 
5.5%
기 97
 
5.4%
동 90
 
5.0%
앞 44
 
2.5%
리 37
 
2.1%
Other values (134) 887
49.6%
Common
ValueCountFrequency (%)
418
82.1%
) 31
 
6.1%
( 31
 
6.1%
4 7
 
1.4%
2 5
 
1.0%
1 5
 
1.0%
3 3
 
0.6%
0 3
 
0.6%
6 3
 
0.6%
- 2
 
0.4%
Latin
ValueCountFrequency (%)
G 3
18.8%
P 3
18.8%
S 3
18.8%
L 3
18.8%
E 2
12.5%
e 2
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1788
77.3%
ASCII 525
 
22.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
418
79.6%
) 31
 
5.9%
( 31
 
5.9%
4 7
 
1.3%
2 5
 
1.0%
1 5
 
1.0%
G 3
 
0.6%
P 3
 
0.6%
3 3
 
0.6%
0 3
 
0.6%
Other values (7) 16
 
3.0%
Hangul
ValueCountFrequency (%)
부 112
 
6.3%
도 111
 
6.2%
의 107
 
6.0%
정 107
 
6.0%
경 98
 
5.5%
시 98
 
5.5%
기 97
 
5.4%
동 90
 
5.0%
앞 44
 
2.5%
리 37
 
2.1%
Other values (134) 887
49.6%

최대면수
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size892.0 B
6
43 
5
32 
7
12 
8
7 
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st row5
2nd row5
3rd row6
4th row6
5th row5

Common Values

ValueCountFrequency (%)
6 43
45.3%
5 32
33.7%
7 12
 
12.6%
8 7
 
7.4%
4 1
 
1.1%

Length

2023-12-12T14:31:44.599651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:31:44.701710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
6 43
45.3%
5 32
33.7%
7 12
 
12.6%
8 7
 
7.4%
4 1
 
1.1%

자동여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size227.0 B
True
66 
False
29 
ValueCountFrequency (%)
True 66
69.5%
False 29
30.5%
2023-12-12T14:31:44.800610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

관리부서전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size892.0 B
031-828-4542
95 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row031-828-4542
2nd row031-828-4542
3rd row031-828-4542
4th row031-828-4542
5th row031-828-4542

Common Values

ValueCountFrequency (%)
031-828-4542 95
100.0%

Length

2023-12-12T14:31:44.897701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:31:44.973126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
031-828-4542 95
100.0%

Correlations

2023-12-12T14:31:45.021526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호위 치최대면수자동여부
관리번호1.0001.0001.0001.000
위 치1.0001.0001.0001.000
최대면수1.0001.0001.0000.561
자동여부1.0001.0000.5611.000
2023-12-12T14:31:45.101098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
자동여부최대면수
자동여부1.0000.667
최대면수0.6671.000
2023-12-12T14:31:45.166209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
최대면수자동여부
최대면수1.0000.667
자동여부0.6671.000

Missing values

2023-12-12T14:31:43.183546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:31:43.276806image/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

관리번호위 치최대면수자동여부관리부서전화번호
0호원1동-1경기도 의정부시 호원동 평화로 S커브 롯데아파트 앞5Y031-828-4542
1호원1동-2경기도 의정부시 호원동 평화로 S커브 서울방면 좌5Y031-828-4542
2호원1동-3경기도 의정부시 호원동 평화로 S커브 서울방면 우6Y031-828-4542
3호원2동-1경기도 의정부시 호원동 동막교 앞6Y031-828-4542
4호원2동-2경기도 의정부시 호원동 신도2차아파트 앞 좌5Y031-828-4542
5호원2동-3경기도 의정부시 호원동 신도2차아파트 앞 우5Y031-828-4542
6신곡1동-1경기도 의정부시 E1-LPG의정부충전소 앞 사거리 좌5Y031-828-4542
7신곡1동-2경기도 의정부시 E1-LPG의정부충전소 앞 사거리 우5Y031-828-4542
8호원2동-4경기도 의정부시 호원동 한승미메이드아파트 앞 좌7N031-828-4542
9호원2동-5경기도 의정부시 호원동 한승미메이드아파트 앞 우6N031-828-4542
관리번호위 치최대면수자동여부관리부서전화번호
85자금동-4경기도 의정부시 자금동 거성아파트 앞6Y031-828-4542
86자금동-5경기도 의정부시 자금동 홈플러스 대각선8N031-828-4542
87자금동-6경기도 의정부시 자금동 홈플러스 대각선 우5Y031-828-4542
88자금동-7경기도 의정부시 자금동 홈플러스 앞 좌7N031-828-4542
89자금동-8경기도 의정부시 자금동 홈플러스 앞 우5Y031-828-4542
90자금동-9경기도 의정부시 자금동 현대아이파크(부대방면)6Y031-828-4542
91자금동-10경기도 의정부시 자금동 현대아이파크(포천방면) 좌7N031-828-4542
92자금동-11경기도 의정부시 자금동 현대아이파크(포천방면) 우7Y031-828-4542
93자금동-12경기도 의정부시 자금동 현대아이파크(의정부방면)7N031-828-4542
94자금동-13경기도 의정부시 자금동 천보중학교 앞8N031-828-4542