Overview

Dataset statistics

Number of variables6
Number of observations121
Missing cells2
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.8 KiB
Average record size in memory49.1 B

Variable types

Text4
Categorical1
DateTime1

Dataset

Description경기도 양주시 도시계획정보시스템(UPIS) 교통시설 현황으로 현황도형 관리번호, 라벨명, 면적(도형), 길이(도형), 도면번호, 현황도형 생성일 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15115911/fileData.do

Alerts

도면번호 has 2 (1.7%) missing valuesMissing
현황도형 관리번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 06:23:11.932507
Analysis finished2023-12-12 06:23:12.360739
Duration0.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

현황도형 관리번호
Text

UNIQUE 

Distinct121
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T15:23:12.564378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters2904
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

Unique121 ?
Unique (%)100.0%

Sample

1st row41630UQ152PS202112310002
2nd row41630UQ152PS202112310003
3rd row41630UQ152PS202112310001
4th row41630UQ152PS201609260108
5th row41630UQ152PS201609260107
ValueCountFrequency (%)
41630uq152ps202112310002 1
 
0.8%
41630uq152ps201810100149 1
 
0.8%
41630uq152ps201609260134 1
 
0.8%
41630uq152ps201609260137 1
 
0.8%
41630uq152ps201609260141 1
 
0.8%
41630uq152ps201609260143 1
 
0.8%
41630uq152ps201612310001 1
 
0.8%
41630uq152ps201612310002 1
 
0.8%
41630uq152ps201703240111 1
 
0.8%
41630uq152ps201703240112 1
 
0.8%
Other values (111) 111
91.7%
2023-12-12T15:23:13.068678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 614
21.1%
1 469
16.2%
2 407
14.0%
6 313
10.8%
3 164
 
5.6%
4 147
 
5.1%
5 137
 
4.7%
U 121
 
4.2%
Q 121
 
4.2%
P 121
 
4.2%
Other values (4) 290
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2420
83.3%
Uppercase Letter 484
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 614
25.4%
1 469
19.4%
2 407
16.8%
6 313
12.9%
3 164
 
6.8%
4 147
 
6.1%
5 137
 
5.7%
9 97
 
4.0%
8 39
 
1.6%
7 33
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
U 121
25.0%
Q 121
25.0%
P 121
25.0%
S 121
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2420
83.3%
Latin 484
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 614
25.4%
1 469
19.4%
2 407
16.8%
6 313
12.9%
3 164
 
6.8%
4 147
 
6.1%
5 137
 
5.7%
9 97
 
4.0%
8 39
 
1.6%
7 33
 
1.4%
Latin
ValueCountFrequency (%)
U 121
25.0%
Q 121
25.0%
P 121
25.0%
S 121
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2904
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 614
21.1%
1 469
16.2%
2 407
14.0%
6 313
10.8%
3 164
 
5.6%
4 147
 
5.1%
5 137
 
4.7%
U 121
 
4.2%
Q 121
 
4.2%
P 121
 
4.2%
Other values (4) 290
10.0%

라벨명
Categorical

Distinct7
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
기타주차장시설
62 
노외주차장
45 
주차장
 
5
기타 주차장시설
 
4
일반철도
 
3
Other values (2)
 
2

Length

Max length12
Median length7
Mean length6.0661157
Min length3

Unique

Unique2 ?
Unique (%)1.7%

Sample

1st row노외주차장
2nd row노외주차
3rd row주차장
4th row기타주차장시설
5th row기타주차장시설

Common Values

ValueCountFrequency (%)
기타주차장시설 62
51.2%
노외주차장 45
37.2%
주차장 5
 
4.1%
기타 주차장시설 4
 
3.3%
일반철도 3
 
2.5%
노외주차 1
 
0.8%
도시철도(104정거장) 1
 
0.8%

Length

2023-12-12T15:23:13.278054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:23:13.469879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타주차장시설 62
49.6%
노외주차장 45
36.0%
주차장 5
 
4.0%
기타 4
 
3.2%
주차장시설 4
 
3.2%
일반철도 3
 
2.4%
노외주차 1
 
0.8%
도시철도(104정거장 1
 
0.8%

면적(도형)
Text

Distinct107
Distinct (%)88.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T15:23:13.851767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length9.8264463
Min length7

Characters and Unicode

Total characters1189
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

Unique106 ?
Unique (%)87.6%

Sample

1st row2331.25
2nd row966.0422267
3rd row2527.832611
4th row962.652803
5th row572.9371238
ValueCountFrequency (%)
데이터 15
 
11.0%
미집계 15
 
11.0%
677.964636 1
 
0.7%
530.7622285 1
 
0.7%
1364.24811 1
 
0.7%
2279.354991 1
 
0.7%
1533.851887 1
 
0.7%
3693.149203 1
 
0.7%
1594.203996 1
 
0.7%
963.4922735 1
 
0.7%
Other values (98) 98
72.1%
2023-12-12T15:23:14.369012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 121
10.2%
1 118
9.9%
. 106
8.9%
3 106
8.9%
2 100
8.4%
7 94
7.9%
9 92
7.7%
4 91
7.7%
8 87
7.3%
0 86
7.2%
Other values (8) 188
15.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 978
82.3%
Other Punctuation 106
 
8.9%
Other Letter 90
 
7.6%
Space Separator 15
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 121
12.4%
1 118
12.1%
3 106
10.8%
2 100
10.2%
7 94
9.6%
9 92
9.4%
4 91
9.3%
8 87
8.9%
0 86
8.8%
6 83
8.5%
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 (%)
. 106
100.0%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1099
92.4%
Hangul 90
 
7.6%

Most frequent character per script

Common
ValueCountFrequency (%)
5 121
11.0%
1 118
10.7%
. 106
9.6%
3 106
9.6%
2 100
9.1%
7 94
8.6%
9 92
8.4%
4 91
8.3%
8 87
7.9%
0 86
7.8%
Other values (2) 98
8.9%
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 1099
92.4%
Hangul 90
 
7.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 121
11.0%
1 118
10.7%
. 106
9.6%
3 106
9.6%
2 100
9.1%
7 94
8.6%
9 92
8.4%
4 91
8.3%
8 87
7.9%
0 86
7.8%
Other values (2) 98
8.9%
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

Distinct107
Distinct (%)88.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T15:23:14.771292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.413223
Min length7

Characters and Unicode

Total characters1260
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

Unique106 ?
Unique (%)87.6%

Sample

1st row198.3578644
2nd row135.8993269
3rd row207.6427284
4th row133.4169332
5th row96.53712155
ValueCountFrequency (%)
데이터 15
 
11.0%
미집계 15
 
11.0%
113.387306 1
 
0.7%
93.78195362 1
 
0.7%
150.0986638 1
 
0.7%
202.4504468 1
 
0.7%
175.969169 1
 
0.7%
255.949645 1
 
0.7%
158.8344087 1
 
0.7%
126.3658821 1
 
0.7%
Other values (98) 98
72.1%
2023-12-12T15:23:15.329901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 154
12.2%
2 118
9.4%
5 113
9.0%
9 107
8.5%
. 106
8.4%
7 106
8.4%
3 96
7.6%
8 94
7.5%
4 94
7.5%
6 92
7.3%
Other values (8) 180
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1049
83.3%
Other Punctuation 106
 
8.4%
Other Letter 90
 
7.1%
Space Separator 15
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 154
14.7%
2 118
11.2%
5 113
10.8%
9 107
10.2%
7 106
10.1%
3 96
9.2%
8 94
9.0%
4 94
9.0%
6 92
8.8%
0 75
7.1%
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 (%)
. 106
100.0%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1170
92.9%
Hangul 90
 
7.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 154
13.2%
2 118
10.1%
5 113
9.7%
9 107
9.1%
. 106
9.1%
7 106
9.1%
3 96
8.2%
8 94
8.0%
4 94
8.0%
6 92
7.9%
Other values (2) 90
7.7%
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 1170
92.9%
Hangul 90
 
7.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 154
13.2%
2 118
10.1%
5 113
9.7%
9 107
9.1%
. 106
9.1%
7 106
9.1%
3 96
8.2%
8 94
8.0%
4 94
8.0%
6 92
7.9%
Other values (2) 90
7.7%
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%

도면번호
Text

MISSING 

Distinct92
Distinct (%)77.3%
Missing2
Missing (%)1.7%
Memory size1.1 KiB
2023-12-12T15:23:15.646667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1260504
Min length1

Characters and Unicode

Total characters253
Distinct characters27
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

Unique77 ?
Unique (%)64.7%

Sample

1st row109
2nd row110
3rd row9
4th row105
5th row104
ValueCountFrequency (%)
1 11
 
9.2%
2 4
 
3.4%
9 3
 
2.5%
22 2
 
1.7%
4 2
 
1.7%
5 2
 
1.7%
3 2
 
1.7%
23 2
 
1.7%
24 2
 
1.7%
12 2
 
1.7%
Other values (82) 87
73.1%
2023-12-12T15:23:16.158780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 61
24.1%
2 33
13.0%
옥 25
9.9%
5 17
 
6.7%
4 15
 
5.9%
0 15
 
5.9%
8 14
 
5.5%
6 12
 
4.7%
3 12
 
4.7%
9 9
 
3.6%
Other values (17) 40
15.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 195
77.1%
Other Letter 56
 
22.1%
Open Punctuation 1
 
0.4%
Close Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
옥 25
44.6%
고 8
 
14.3%
주 6
 
10.7%
장 3
 
5.4%
차 3
 
5.4%
골 2
 
3.6%
삼 1
 
1.8%
곡 1
 
1.8%
부 1
 
1.8%
용 1
 
1.8%
Other values (5) 5
 
8.9%
Decimal Number
ValueCountFrequency (%)
1 61
31.3%
2 33
16.9%
5 17
 
8.7%
4 15
 
7.7%
0 15
 
7.7%
8 14
 
7.2%
6 12
 
6.2%
3 12
 
6.2%
9 9
 
4.6%
7 7
 
3.6%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 197
77.9%
Hangul 56
 
22.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
옥 25
44.6%
고 8
 
14.3%
주 6
 
10.7%
장 3
 
5.4%
차 3
 
5.4%
골 2
 
3.6%
삼 1
 
1.8%
곡 1
 
1.8%
부 1
 
1.8%
용 1
 
1.8%
Other values (5) 5
 
8.9%
Common
ValueCountFrequency (%)
1 61
31.0%
2 33
16.8%
5 17
 
8.6%
4 15
 
7.6%
0 15
 
7.6%
8 14
 
7.1%
6 12
 
6.1%
3 12
 
6.1%
9 9
 
4.6%
7 7
 
3.6%
Other values (2) 2
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 197
77.9%
Hangul 56
 
22.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 61
31.0%
2 33
16.8%
5 17
 
8.6%
4 15
 
7.6%
0 15
 
7.6%
8 14
 
7.1%
6 12
 
6.1%
3 12
 
6.1%
9 9
 
4.6%
7 7
 
3.6%
Other values (2) 2
 
1.0%
Hangul
ValueCountFrequency (%)
옥 25
44.6%
고 8
 
14.3%
주 6
 
10.7%
장 3
 
5.4%
차 3
 
5.4%
골 2
 
3.6%
삼 1
 
1.8%
곡 1
 
1.8%
부 1
 
1.8%
용 1
 
1.8%
Other values (5) 5
 
8.9%

현황도형 생성일
Date

Distinct23
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2015-10-01 00:00:00
Maximum2023-03-30 00:00:00
2023-12-12T15:23:16.302575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:23:16.457217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)

Correlations

2023-12-12T15:23:16.562465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
라벨명도면번호현황도형 생성일
라벨명1.0000.0000.901
도면번호0.0001.0000.000
현황도형 생성일0.9010.0001.000

Missing values

2023-12-12T15:23:12.177126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:23:12.311702image/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
041630UQ152PS202112310002노외주차장2331.25198.35786441092021-12-31
141630UQ152PS202112310003노외주차966.0422267135.89932691102021-12-31
241630UQ152PS202112310001주차장2527.832611207.642728492021-12-31
341630UQ152PS201609260108기타주차장시설962.652803133.41693321052015-10-01
441630UQ152PS201609260107기타주차장시설572.937123896.537121551042015-10-01
541630UQ152PS201609260106기타주차장시설480.11874589.505977411062015-10-01
641630UQ152PS201609260105기타주차장시설345.422388277.81903421812015-10-01
741630UQ152PS201609260104기타주차장시설793.0006682126.8425974982015-10-01
841630UQ152PS201609260103기타주차장시설410.481187683.61502454872015-10-01
941630UQ152PS201609260102기타주차장시설470.320483287.7183022882015-10-01
현황도형 관리번호라벨명면적(도형)길이(도형)도면번호현황도형 생성일
11141630UQ152PS201706280010노외주차장데이터 미집계데이터 미집계102023-03-30
11241630UQ152PS201609260121노외주차장데이터 미집계데이터 미집계132023-03-30
11341630UQ152PS201706280014노외주차장데이터 미집계데이터 미집계142023-03-30
11441630UQ152PS201706280015노외주차장데이터 미집계데이터 미집계152023-03-30
11541630UQ152PS201706280021노외주차장데이터 미집계데이터 미집계212023-03-30
11641630UQ152PS201706280022노외주차장데이터 미집계데이터 미집계222023-03-30
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