Overview

Dataset statistics

Number of variables4
Number of observations656
Missing cells19
Missing cells (%)0.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory20.6 KiB
Average record size in memory32.2 B

Variable types

Text2
Categorical2

Dataset

Description경기도 양주시 도시계획정보시스템(UPIS) 공간시설 현황으로 현황도형 관리번호, 라벨명, 도면번호, 현황도형 생성일 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15116439/fileData.do

Alerts

도면번호 has 19 (2.9%) missing valuesMissing
현황도형 관리번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 18:05:06.651299
Analysis finished2023-12-12 18:05:07.130887
Duration0.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

현황도형 관리번호
Text

UNIQUE 

Distinct656
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
2023-12-13T03:05:07.323137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters15744
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique656 ?
Unique (%)100.0%

Sample

1st row41630UQ153PS201706280793
2nd row41630UQ153PS201706280790
3rd row41630UQ153PS201706280788
4th row41630UQ153PS201706280786
5th row41630UQ153PS201706280785
ValueCountFrequency (%)
41630uq153ps201706280793 1
 
0.2%
41630uq153ps201609260566 1
 
0.2%
41630uq153ps201609261022 1
 
0.2%
41630uq153ps201810040682 1
 
0.2%
41630uq153ps201609260139 1
 
0.2%
41630uq153ps201609260210 1
 
0.2%
41630uq153ps201609260980 1
 
0.2%
41630uq153ps201909220725 1
 
0.2%
41630uq153ps201909220726 1
 
0.2%
41630uq153ps201609261032 1
 
0.2%
Other values (646) 646
98.5%
2023-12-13T03:05:07.706052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3020
19.2%
1 2383
15.1%
6 1678
10.7%
3 1622
10.3%
2 1497
9.5%
5 817
 
5.2%
4 812
 
5.2%
U 656
 
4.2%
Q 656
 
4.2%
P 656
 
4.2%
Other values (4) 1947
12.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13120
83.3%
Uppercase Letter 2624
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3020
23.0%
1 2383
18.2%
6 1678
12.8%
3 1622
12.4%
2 1497
11.4%
5 817
 
6.2%
4 812
 
6.2%
9 550
 
4.2%
7 427
 
3.3%
8 314
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
U 656
25.0%
Q 656
25.0%
P 656
25.0%
S 656
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13120
83.3%
Latin 2624
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3020
23.0%
1 2383
18.2%
6 1678
12.8%
3 1622
12.4%
2 1497
11.4%
5 817
 
6.2%
4 812
 
6.2%
9 550
 
4.2%
7 427
 
3.3%
8 314
 
2.4%
Latin
ValueCountFrequency (%)
U 656
25.0%
Q 656
25.0%
P 656
25.0%
S 656
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15744
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3020
19.2%
1 2383
15.1%
6 1678
10.7%
3 1622
10.3%
2 1497
9.5%
5 817
 
5.2%
4 812
 
5.2%
U 656
 
4.2%
Q 656
 
4.2%
P 656
 
4.2%
Other values (4) 1947
12.4%

라벨명
Categorical

Distinct33
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
완충녹지
195 
어린이공원
87 
경관녹지
85 
기타공원시설
74 
공공공지
54 
Other values (28)
161 

Length

Max length11
Median length4
Mean length4.6737805
Min length3

Unique

Unique11 ?
Unique (%)1.7%

Sample

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

Common Values

ValueCountFrequency (%)
완충녹지 195
29.7%
어린이공원 87
13.3%
경관녹지 85
13.0%
기타공원시설 74
 
11.3%
공공공지 54
 
8.2%
근린공원 43
 
6.6%
소공원 16
 
2.4%
기타녹지시설 13
 
2.0%
기타교통광장시설 12
 
1.8%
연결녹지 11
 
1.7%
Other values (23) 66
 
10.1%

Length

2023-12-13T03:05:08.232587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
완충녹지 195
29.0%
어린이공원 87
12.9%
경관녹지 85
12.6%
기타공원시설 74
 
11.0%
공공공지 54
 
8.0%
근린공원 43
 
6.4%
기타 17
 
2.5%
소공원 16
 
2.4%
기타녹지시설 13
 
1.9%
기타교통광장시설 12
 
1.8%
Other values (24) 77
 
11.4%

도면번호
Text

MISSING 

Distinct226
Distinct (%)35.5%
Missing19
Missing (%)2.9%
Memory size5.3 KiB
2023-12-13T03:05:08.591381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length2.3500785
Min length1

Characters and Unicode

Total characters1497
Distinct characters63
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique121 ?
Unique (%)19.0%

Sample

1st row27
2nd row25
3rd row24
4th row23
5th row22
ValueCountFrequency (%)
1 52
 
8.2%
2 34
 
5.3%
3 27
 
4.2%
고11 18
 
2.8%
고1 16
 
2.5%
4 15
 
2.4%
6 11
 
1.7%
8 10
 
1.6%
7 10
 
1.6%
9 9
 
1.4%
Other values (216) 435
68.3%
2023-12-13T03:05:09.127911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 295
19.7%
2 165
 
11.0%
3 115
 
7.7%
옥 75
 
5.0%
4 70
 
4.7%
) 65
 
4.3%
( 65
 
4.3%
고 59
 
3.9%
6 59
 
3.9%
5 58
 
3.9%
Other values (53) 471
31.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 959
64.1%
Other Letter 401
26.8%
Close Punctuation 65
 
4.3%
Open Punctuation 65
 
4.3%
Lowercase Letter 7
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
옥 75
18.7%
고 59
14.7%
암 27
 
6.7%
용 18
 
4.5%
공 18
 
4.5%
봉 14
 
3.5%
양 14
 
3.5%
지 14
 
3.5%
업 12
 
3.0%
완 12
 
3.0%
Other values (40) 138
34.4%
Decimal Number
ValueCountFrequency (%)
1 295
30.8%
2 165
17.2%
3 115
 
12.0%
4 70
 
7.3%
6 59
 
6.2%
5 58
 
6.0%
0 55
 
5.7%
7 55
 
5.7%
8 52
 
5.4%
9 35
 
3.6%
Close Punctuation
ValueCountFrequency (%)
) 65
100.0%
Open Punctuation
ValueCountFrequency (%)
( 65
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1089
72.7%
Hangul 401
 
26.8%
Latin 7
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
옥 75
18.7%
고 59
14.7%
암 27
 
6.7%
용 18
 
4.5%
공 18
 
4.5%
봉 14
 
3.5%
양 14
 
3.5%
지 14
 
3.5%
업 12
 
3.0%
완 12
 
3.0%
Other values (40) 138
34.4%
Common
ValueCountFrequency (%)
1 295
27.1%
2 165
15.2%
3 115
 
10.6%
4 70
 
6.4%
) 65
 
6.0%
( 65
 
6.0%
6 59
 
5.4%
5 58
 
5.3%
0 55
 
5.1%
7 55
 
5.1%
Other values (2) 87
 
8.0%
Latin
ValueCountFrequency (%)
a 7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1096
73.2%
Hangul 401
 
26.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 295
26.9%
2 165
15.1%
3 115
 
10.5%
4 70
 
6.4%
) 65
 
5.9%
( 65
 
5.9%
6 59
 
5.4%
5 58
 
5.3%
0 55
 
5.0%
7 55
 
5.0%
Other values (3) 94
 
8.6%
Hangul
ValueCountFrequency (%)
옥 75
18.7%
고 59
14.7%
암 27
 
6.7%
용 18
 
4.5%
공 18
 
4.5%
봉 14
 
3.5%
양 14
 
3.5%
지 14
 
3.5%
업 12
 
3.0%
완 12
 
3.0%
Other values (40) 138
34.4%

현황도형 생성일
Categorical

Distinct46
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
2015-10-01
168 
2023-03-30
117 
2017-06-28
51 
2018-10-10
42 
2018-10-04
31 
Other values (41)
247 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique9 ?
Unique (%)1.4%

Sample

1st row2023-03-30
2nd row2023-03-30
3rd row2023-03-30
4th row2023-03-30
5th row2023-03-30

Common Values

ValueCountFrequency (%)
2015-10-01 168
25.6%
2023-03-30 117
17.8%
2017-06-28 51
 
7.8%
2018-10-10 42
 
6.4%
2018-10-04 31
 
4.7%
2019-12-31 27
 
4.1%
2016-09-19 20
 
3.0%
2021-12-31 19
 
2.9%
2016-12-31 14
 
2.1%
2021-02-26 14
 
2.1%
Other values (36) 153
23.3%

Length

2023-12-13T03:05:09.306421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2015-10-01 168
25.6%
2023-03-30 117
17.8%
2017-06-28 51
 
7.8%
2018-10-10 42
 
6.4%
2018-10-04 31
 
4.7%
2019-12-31 27
 
4.1%
2016-09-19 20
 
3.0%
2021-12-31 19
 
2.9%
2016-12-31 14
 
2.1%
2021-02-26 14
 
2.1%
Other values (36) 153
23.3%

Correlations

2023-12-13T03:05:09.399112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
라벨명현황도형 생성일
라벨명1.0000.858
현황도형 생성일0.8581.000
2023-12-13T03:05:09.500925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
라벨명현황도형 생성일
라벨명1.0000.321
현황도형 생성일0.3211.000
2023-12-13T03:05:09.615427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
라벨명현황도형 생성일
라벨명1.0000.321
현황도형 생성일0.3211.000

Missing values

2023-12-13T03:05:06.973020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:05:07.086805image/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

현황도형 관리번호라벨명도면번호현황도형 생성일
041630UQ153PS201706280793공공공지272023-03-30
141630UQ153PS201706280790공공공지252023-03-30
241630UQ153PS201706280788공공공지242023-03-30
341630UQ153PS201706280786공공공지232023-03-30
441630UQ153PS201706280785공공공지222023-03-30
541630UQ153PS201706280782공공공지202023-03-30
641630UQ153PS201706280783공공공지192023-03-30
741630UQ153PS201706280781공공공지182023-03-30
841630UQ153PS201706280780공공공지162023-03-30
941630UQ153PS201706280778공공공지142023-03-30
현황도형 관리번호라벨명도면번호현황도형 생성일
64641630UQ153PS201609260586교통광장172022-05-23
64741630UQ153PS202007110001근린공원12022-05-23
64841630UQ153PS201609260946기타공원시설12022-05-23
64941630UQ153PS201609260584경관녹지72022-09-01
65041630UQ153PS201609261053어린이공원622022-09-01
65141630UQ153PS201801160008소공원덕정공업22022-09-01
65241630UQ153PS202203600001완충녹지(용암2)12022-09-29
65341630UQ153PS202203600004경관녹지(용암2)32022-09-29
65441630UQ153PS202203600006소공원(용암2)12022-09-29
65541630UQ153PS202204140001근린공원옥32022-09-29