Overview

Dataset statistics

Number of variables6
Number of observations180
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.6 KiB
Average record size in memory48.7 B

Variable types

Text5
Categorical1

Dataset

Description경기도 양주시 도시계획정보시스템(UPIS) 방재시설 현황으로 현황도형 관리번호, 라벨명, 면적(도형), 면적(길이), 도면번호, 현황도형 생성일 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15115894/fileData.do

Alerts

현황도형 관리번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:00:27.799075
Analysis finished2023-12-12 20:00:28.200437
Duration0.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

현황도형 관리번호
Text

UNIQUE 

Distinct180
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-13T05:00:28.373078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters4320
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

Unique180 ?
Unique (%)100.0%

Sample

1st row41630UQ156PS201706280005
2nd row41630UQ156PS201706280013
3rd row41630UQ156PS202303290001
4th row41630UQ156PS201706280012
5th row41630UQ156PS201706280009
ValueCountFrequency (%)
41630uq156ps201706280005 1
 
0.6%
41630uq156ps201609260108 1
 
0.6%
41630uq156ps201609260189 1
 
0.6%
41630uq156ps201709290004 1
 
0.6%
41630uq156ps201709290005 1
 
0.6%
41630uq156ps201609260157 1
 
0.6%
41630uq156ps201609260177 1
 
0.6%
41630uq156ps201609260178 1
 
0.6%
41630uq156ps201609260179 1
 
0.6%
41630uq156ps201609260170 1
 
0.6%
Other values (170) 170
94.4%
2023-12-13T05:00:29.044522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 840
19.4%
6 696
16.1%
1 653
15.1%
2 476
11.0%
3 227
 
5.3%
5 218
 
5.0%
4 204
 
4.7%
9 189
 
4.4%
U 180
 
4.2%
Q 180
 
4.2%
Other values (4) 457
10.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3600
83.3%
Uppercase Letter 720
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 840
23.3%
6 696
19.3%
1 653
18.1%
2 476
13.2%
3 227
 
6.3%
5 218
 
6.1%
4 204
 
5.7%
9 189
 
5.2%
8 52
 
1.4%
7 45
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
U 180
25.0%
Q 180
25.0%
P 180
25.0%
S 180
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3600
83.3%
Latin 720
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 840
23.3%
6 696
19.3%
1 653
18.1%
2 476
13.2%
3 227
 
6.3%
5 218
 
6.1%
4 204
 
5.7%
9 189
 
5.2%
8 52
 
1.4%
7 45
 
1.2%
Latin
ValueCountFrequency (%)
U 180
25.0%
Q 180
25.0%
P 180
25.0%
S 180
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4320
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 840
19.4%
6 696
16.1%
1 653
15.1%
2 476
11.0%
3 227
 
5.3%
5 218
 
5.0%
4 204
 
4.7%
9 189
 
4.4%
U 180
 
4.2%
Q 180
 
4.2%
Other values (4) 457
10.6%

라벨명
Text

Distinct105
Distinct (%)58.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-13T05:00:29.364413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.6666667
Min length3

Characters and Unicode

Total characters660
Distinct characters131
Distinct categories2 ?
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 (%)52.8%

Sample

1st row유수지
2nd row마개미천
3rd row덕계천
4th row덕계천
5th row청담천
ValueCountFrequency (%)
소하천 31
 
17.2%
저류시설 18
 
10.0%
기타하천시설 16
 
8.9%
유수지 7
 
3.9%
중랑천 3
 
1.7%
과골천 2
 
1.1%
탑동천 2
 
1.1%
덕계천 2
 
1.1%
마개미천 2
 
1.1%
산북천 2
 
1.1%
Other values (95) 95
52.8%
2023-12-13T05:00:29.842543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
천 155
23.5%
하 49
 
7.4%
시 35
 
5.3%
설 34
 
5.2%
소 31
 
4.7%
기 19
 
2.9%
저 18
 
2.7%
류 18
 
2.7%
타 16
 
2.4%
골 12
 
1.8%
Other values (121) 273
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 644
97.6%
Decimal Number 16
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 155
24.1%
하 49
 
7.6%
시 35
 
5.4%
설 34
 
5.3%
소 31
 
4.8%
기 19
 
3.0%
저 18
 
2.8%
류 18
 
2.8%
타 16
 
2.5%
골 12
 
1.9%
Other values (118) 257
39.9%
Decimal Number
ValueCountFrequency (%)
1 8
50.0%
2 7
43.8%
3 1
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 644
97.6%
Common 16
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 155
24.1%
하 49
 
7.6%
시 35
 
5.4%
설 34
 
5.3%
소 31
 
4.8%
기 19
 
3.0%
저 18
 
2.8%
류 18
 
2.8%
타 16
 
2.5%
골 12
 
1.9%
Other values (118) 257
39.9%
Common
ValueCountFrequency (%)
1 8
50.0%
2 7
43.8%
3 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 644
97.6%
ASCII 16
 
2.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
천 155
24.1%
하 49
 
7.6%
시 35
 
5.4%
설 34
 
5.3%
소 31
 
4.8%
기 19
 
3.0%
저 18
 
2.8%
류 18
 
2.8%
타 16
 
2.5%
골 12
 
1.9%
Other values (118) 257
39.9%
ASCII
ValueCountFrequency (%)
1 8
50.0%
2 7
43.8%
3 1
 
6.2%

면적(도형)
Text

Distinct164
Distinct (%)91.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-13T05:00:30.134283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.338889
Min length1

Characters and Unicode

Total characters1861
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique162 ?
Unique (%)90.0%

Sample

1st row데이터 미집계
2nd row데이터 미집계
3rd row데이터 미집계
4th row데이터 미집계
5th row데이터 미집계
ValueCountFrequency (%)
데이터 15
 
7.7%
미집계 15
 
7.7%
0 3
 
1.5%
31669.22572 1
 
0.5%
8680.361436 1
 
0.5%
12261.11657 1
 
0.5%
144115.5688 1
 
0.5%
31930.24101 1
 
0.5%
8532.311546 1
 
0.5%
3156.492112 1
 
0.5%
Other values (155) 155
79.5%
2023-12-13T05:00:30.524237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 215
11.6%
6 181
9.7%
3 167
9.0%
5 165
8.9%
. 162
8.7%
2 159
8.5%
9 157
8.4%
7 143
7.7%
4 141
7.6%
8 140
7.5%
Other values (8) 231
12.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1594
85.7%
Other Punctuation 162
 
8.7%
Other Letter 90
 
4.8%
Space Separator 15
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 215
13.5%
6 181
11.4%
3 167
10.5%
5 165
10.4%
2 159
10.0%
9 157
9.8%
7 143
9.0%
4 141
8.8%
8 140
8.8%
0 126
7.9%
Other Letter
ValueCountFrequency (%)
이 15
16.7%
계 15
16.7%
집 15
16.7%
미 15
16.7%
터 15
16.7%
데 15
16.7%
Other Punctuation
ValueCountFrequency (%)
. 162
100.0%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1771
95.2%
Hangul 90
 
4.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 215
12.1%
6 181
10.2%
3 167
9.4%
5 165
9.3%
. 162
9.1%
2 159
9.0%
9 157
8.9%
7 143
8.1%
4 141
8.0%
8 140
7.9%
Other values (2) 141
8.0%
Hangul
ValueCountFrequency (%)
이 15
16.7%
계 15
16.7%
집 15
16.7%
미 15
16.7%
터 15
16.7%
데 15
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1771
95.2%
Hangul 90
 
4.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 215
12.1%
6 181
10.2%
3 167
9.4%
5 165
9.3%
. 162
9.1%
2 159
9.0%
9 157
8.9%
7 143
8.1%
4 141
8.0%
8 140
7.9%
Other values (2) 141
8.0%
Hangul
ValueCountFrequency (%)
이 15
16.7%
계 15
16.7%
집 15
16.7%
미 15
16.7%
터 15
16.7%
데 15
16.7%

길이(도형)
Text

Distinct164
Distinct (%)91.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-13T05:00:30.800926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.383333
Min length1

Characters and Unicode

Total characters1869
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique162 ?
Unique (%)90.0%

Sample

1st row데이터 미집계
2nd row데이터 미집계
3rd row데이터 미집계
4th row데이터 미집계
5th row데이터 미집계
ValueCountFrequency (%)
데이터 15
 
7.7%
미집계 15
 
7.7%
0 3
 
1.5%
3262.742205 1
 
0.5%
1580.405027 1
 
0.5%
1384.586553 1
 
0.5%
5562.963525 1
 
0.5%
2741.358862 1
 
0.5%
1464.427562 1
 
0.5%
534.9292571 1
 
0.5%
Other values (155) 155
79.5%
2023-12-13T05:00:31.237583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 200
10.7%
2 194
10.4%
5 177
9.5%
3 176
9.4%
4 170
9.1%
. 162
8.7%
9 144
7.7%
8 142
7.6%
6 139
7.4%
0 138
7.4%
Other values (8) 227
12.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1602
85.7%
Other Punctuation 162
 
8.7%
Other Letter 90
 
4.8%
Space Separator 15
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 200
12.5%
2 194
12.1%
5 177
11.0%
3 176
11.0%
4 170
10.6%
9 144
9.0%
8 142
8.9%
6 139
8.7%
0 138
8.6%
7 122
7.6%
Other Letter
ValueCountFrequency (%)
계 15
16.7%
이 15
16.7%
집 15
16.7%
미 15
16.7%
터 15
16.7%
데 15
16.7%
Other Punctuation
ValueCountFrequency (%)
. 162
100.0%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1779
95.2%
Hangul 90
 
4.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 200
11.2%
2 194
10.9%
5 177
9.9%
3 176
9.9%
4 170
9.6%
. 162
9.1%
9 144
8.1%
8 142
8.0%
6 139
7.8%
0 138
7.8%
Other values (2) 137
7.7%
Hangul
ValueCountFrequency (%)
계 15
16.7%
이 15
16.7%
집 15
16.7%
미 15
16.7%
터 15
16.7%
데 15
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1779
95.2%
Hangul 90
 
4.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 200
11.2%
2 194
10.9%
5 177
9.9%
3 176
9.9%
4 170
9.6%
. 162
9.1%
9 144
8.1%
8 142
8.0%
6 139
7.8%
0 138
7.8%
Other values (2) 137
7.7%
Hangul
ValueCountFrequency (%)
계 15
16.7%
이 15
16.7%
집 15
16.7%
미 15
16.7%
터 15
16.7%
데 15
16.7%

도면번호
Text

Distinct143
Distinct (%)79.4%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-13T05:00:31.565985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.0888889
Min length1

Characters and Unicode

Total characters376
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique131 ?
Unique (%)72.8%

Sample

1st row2
2nd row6
3rd row2
4th row2
5th row1
ValueCountFrequency (%)
지17 9
 
5.0%
1 8
 
4.4%
2 7
 
3.9%
4 5
 
2.8%
3 4
 
2.2%
5 4
 
2.2%
104 2
 
1.1%
9 2
 
1.1%
103 2
 
1.1%
6 2
 
1.1%
Other values (133) 135
75.0%
2023-12-13T05:00:32.047018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 90
23.9%
2 41
10.9%
7 30
 
8.0%
4 29
 
7.7%
3 28
 
7.4%
0 27
 
7.2%
5 27
 
7.2%
9 25
 
6.6%
8 24
 
6.4%
6 24
 
6.4%
Other values (7) 31
 
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 345
91.8%
Other Letter 29
 
7.7%
Open Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 90
26.1%
2 41
11.9%
7 30
 
8.7%
4 29
 
8.4%
3 28
 
8.1%
0 27
 
7.8%
5 27
 
7.8%
9 25
 
7.2%
8 24
 
7.0%
6 24
 
7.0%
Other Letter
ValueCountFrequency (%)
지 21
72.4%
옥 4
 
13.8%
고 2
 
6.9%
운 1
 
3.4%
암 1
 
3.4%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 347
92.3%
Hangul 29
 
7.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 90
25.9%
2 41
11.8%
7 30
 
8.6%
4 29
 
8.4%
3 28
 
8.1%
0 27
 
7.8%
5 27
 
7.8%
9 25
 
7.2%
8 24
 
6.9%
6 24
 
6.9%
Other values (2) 2
 
0.6%
Hangul
ValueCountFrequency (%)
지 21
72.4%
옥 4
 
13.8%
고 2
 
6.9%
운 1
 
3.4%
암 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 347
92.3%
Hangul 29
 
7.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 90
25.9%
2 41
11.8%
7 30
 
8.6%
4 29
 
8.4%
3 28
 
8.1%
0 27
 
7.8%
5 27
 
7.8%
9 25
 
7.2%
8 24
 
6.9%
6 24
 
6.9%
Other values (2) 2
 
0.6%
Hangul
ValueCountFrequency (%)
지 21
72.4%
옥 4
 
13.8%
고 2
 
6.9%
운 1
 
3.4%
암 1
 
3.4%

현황도형 생성일
Categorical

Distinct21
Distinct (%)11.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2020-04-03
96 
2016-09-20
19 
2019-03-14
15 
2023-03-29
10 
2015-10-01
 
7
Other values (16)
33 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique9 ?
Unique (%)5.0%

Sample

1st row2023-03-29
2nd row2023-03-30
3rd row2023-03-29
4th row2023-03-29
5th row2023-03-29

Common Values

ValueCountFrequency (%)
2020-04-03 96
53.3%
2016-09-20 19
 
10.6%
2019-03-14 15
 
8.3%
2023-03-29 10
 
5.6%
2015-10-01 7
 
3.9%
2018-10-10 6
 
3.3%
2019-09-22 6
 
3.3%
2023-03-30 3
 
1.7%
2021-12-31 3
 
1.7%
2019-03-26 2
 
1.1%
Other values (11) 13
 
7.2%

Length

2023-12-13T05:00:32.210801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-04-03 96
53.3%
2016-09-20 19
 
10.6%
2019-03-14 15
 
8.3%
2023-03-29 10
 
5.6%
2015-10-01 7
 
3.9%
2018-10-10 6
 
3.3%
2019-09-22 6
 
3.3%
2023-03-30 3
 
1.7%
2021-12-31 3
 
1.7%
2021-06-25 2
 
1.1%
Other values (11) 13
 
7.2%

Missing values

2023-12-13T05:00:28.039647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:00:28.153727image/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 관리번호라벨명면적(도형)길이(도형)도면번호현황도형 생성일
041630UQ156PS201706280005유수지데이터 미집계데이터 미집계22023-03-29
141630UQ156PS201706280013마개미천데이터 미집계데이터 미집계62023-03-30
241630UQ156PS202303290001덕계천데이터 미집계데이터 미집계22023-03-29
341630UQ156PS201706280012덕계천데이터 미집계데이터 미집계22023-03-29
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