Overview

Dataset statistics

Number of variables15
Number of observations5412
Missing cells2
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory655.5 KiB
Average record size in memory124.0 B

Variable types

Numeric4
Text5
Categorical5
DateTime1

Dataset

Description객체id,현황도형 관리번호,도형 대분류코드,도형 중분류코드,도형 소분류코드,도형 속성코드,도형 조서관리 코드,결정고시관리코드,라벨명,시군구코드,도면번호,집행상태코드 심볼,현황도형 생성일시,면적(도형),길이(도형)
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-21129/S/1/datasetView.do

Alerts

도형 속성코드 is highly overall correlated with 도형 대분류코드 and 2 other fieldsHigh correlation
도형 중분류코드 is highly overall correlated with 도형 대분류코드 and 2 other fieldsHigh correlation
도형 소분류코드 is highly overall correlated with 도형 중분류코드 and 1 other fieldsHigh correlation
면적(도형) is highly overall correlated with 길이(도형)High correlation
길이(도형) is highly overall correlated with 면적(도형)High correlation
도형 대분류코드 is highly overall correlated with 도형 중분류코드 and 1 other fieldsHigh correlation
도형 소분류코드 is highly imbalanced (89.4%)Imbalance
집행상태코드 심볼 is highly imbalanced (99.1%)Imbalance
시군구코드 is highly skewed (γ1 = 36.5160158)Skewed
면적(도형) is highly skewed (γ1 = 36.3647742)Skewed
길이(도형) is highly skewed (γ1 = 73.55911496)Skewed
객체id has unique valuesUnique

Reproduction

Analysis started2024-05-11 04:02:03.180247
Analysis finished2024-05-11 04:02:13.399011
Duration10.22 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

객체id
Real number (ℝ)

UNIQUE 

Distinct5412
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean234696.47
Minimum231975
Maximum237402
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size47.7 KiB
2024-05-11T04:02:13.627636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum231975
5-th percentile232261.55
Q1233343.75
median234696.5
Q3236049.25
95-th percentile237131.45
Maximum237402
Range5427
Interquartile range (IQR)2705.5

Descriptive statistics

Standard deviation1562.5054
Coefficient of variation (CV)0.0066575583
Kurtosis-1.1998415
Mean234696.47
Median Absolute Deviation (MAD)1353
Skewness-0.00011393449
Sum1.2701773 × 109
Variance2441423.2
MonotonicityNot monotonic
2024-05-11T04:02:14.137619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
236610 1
 
< 0.1%
236331 1
 
< 0.1%
236340 1
 
< 0.1%
236339 1
 
< 0.1%
236337 1
 
< 0.1%
236336 1
 
< 0.1%
236335 1
 
< 0.1%
236334 1
 
< 0.1%
236333 1
 
< 0.1%
236332 1
 
< 0.1%
Other values (5402) 5402
99.8%
ValueCountFrequency (%)
231975 1
< 0.1%
231976 1
< 0.1%
231977 1
< 0.1%
231978 1
< 0.1%
231979 1
< 0.1%
231980 1
< 0.1%
231981 1
< 0.1%
231982 1
< 0.1%
231983 1
< 0.1%
231984 1
< 0.1%
ValueCountFrequency (%)
237402 1
< 0.1%
237401 1
< 0.1%
237400 1
< 0.1%
237399 1
< 0.1%
237398 1
< 0.1%
237397 1
< 0.1%
237396 1
< 0.1%
237395 1
< 0.1%
237394 1
< 0.1%
237393 1
< 0.1%

현황도형 관리번호
Text

Distinct5411
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size42.4 KiB
2024-05-11T04:02:14.929754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters129888
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

Unique5410 ?
Unique (%)> 99.9%

Sample

1st row11000UQ153PS202011160001
2nd row11000UQ153PS202011160002
3rd row11590UQ153PS202404240001
4th row11000UQ153PS202404240001
5th row11500UQ153PS202404240001
ValueCountFrequency (%)
11380uq153ps202304130003 2
 
< 0.1%
11000uq153ps201912152225 1
 
< 0.1%
11000uq153ps201912153995 1
 
< 0.1%
11000uq153ps201912153994 1
 
< 0.1%
11000uq153ps201912150980 1
 
< 0.1%
11000uq153ps201912150979 1
 
< 0.1%
11000uq153ps201912152288 1
 
< 0.1%
11000uq153ps201912152579 1
 
< 0.1%
11000uq153ps201912153256 1
 
< 0.1%
11000uq153ps201912153737 1
 
< 0.1%
Other values (5401) 5401
99.8%
2024-05-11T04:02:16.293429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 32872
25.3%
0 27607
21.3%
2 14455
11.1%
5 11517
 
8.9%
3 8410
 
6.5%
9 5810
 
4.5%
U 5412
 
4.2%
Q 5412
 
4.2%
P 5412
 
4.2%
S 5412
 
4.2%
Other values (4) 7569
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 108240
83.3%
Uppercase Letter 21648
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 32872
30.4%
0 27607
25.5%
2 14455
13.4%
5 11517
 
10.6%
3 8410
 
7.8%
9 5810
 
5.4%
4 2614
 
2.4%
6 1686
 
1.6%
7 1655
 
1.5%
8 1614
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
U 5412
25.0%
Q 5412
25.0%
P 5412
25.0%
S 5412
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 108240
83.3%
Latin 21648
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 32872
30.4%
0 27607
25.5%
2 14455
13.4%
5 11517
 
10.6%
3 8410
 
7.8%
9 5810
 
5.4%
4 2614
 
2.4%
6 1686
 
1.6%
7 1655
 
1.5%
8 1614
 
1.5%
Latin
ValueCountFrequency (%)
U 5412
25.0%
Q 5412
25.0%
P 5412
25.0%
S 5412
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 129888
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 32872
25.3%
0 27607
21.3%
2 14455
11.1%
5 11517
 
8.9%
3 8410
 
6.5%
9 5810
 
4.5%
U 5412
 
4.2%
Q 5412
 
4.2%
P 5412
 
4.2%
S 5412
 
4.2%
Other values (4) 7569
 
5.8%

도형 대분류코드
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.4 KiB
UQT200
2732 
UQT300
1399 
UQT500
979 
UQT100
293 
UQT400
 
6
Other values (3)
 
3

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique3 ?
Unique (%)0.1%

Sample

1st rowUQT200
2nd rowUQT200
3rd rowUQT200
4th rowUQT200
5th rowUQT200

Common Values

ValueCountFrequency (%)
UQT200 2732
50.5%
UQT300 1399
25.8%
UQT500 979
 
18.1%
UQT100 293
 
5.4%
UQT400 6
 
0.1%
UQT290 1
 
< 0.1%
UQT110 1
 
< 0.1%
UQT220 1
 
< 0.1%

Length

2024-05-11T04:02:16.731538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:02:17.157974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
uqt200 2732
50.5%
uqt300 1399
25.8%
uqt500 979
 
18.1%
uqt100 293
 
5.4%
uqt400 6
 
0.1%
uqt290 1
 
< 0.1%
uqt110 1
 
< 0.1%
uqt220 1
 
< 0.1%

도형 중분류코드
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size42.4 KiB
UQT210
1062 
UQT510
888 
UQT205
613 
UQT220
543 
UQT310
495 
Other values (19)
1811 

Length

Max length6
Median length6
Mean length5.9981523
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUQT220
2nd rowUQT220
3rd rowUQT220
4th rowUQT220
5th rowUQT205

Common Values

ValueCountFrequency (%)
UQT210 1062
19.6%
UQT510 888
16.4%
UQT205 613
11.3%
UQT220 543
10.0%
UQT310 495
9.1%
UQT320 411
 
7.6%
UQT290 314
 
5.8%
UQT390 271
 
5.0%
UQT330 222
 
4.1%
UQT110 135
 
2.5%
Other values (14) 458
8.5%

Length

2024-05-11T04:02:17.678802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
uqt210 1062
19.6%
uqt510 888
16.4%
uqt205 613
11.3%
uqt220 543
10.0%
uqt310 495
9.1%
uqt320 411
 
7.6%
uqt290 314
 
5.8%
uqt390 271
 
5.0%
uqt330 222
 
4.1%
uqt110 135
 
2.5%
Other values (13) 456
8.4%

도형 소분류코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.4 KiB
5230 
UQT119
 
132
UQT129
 
44
UQT122
 
4
UQT111
 
2

Length

Max length6
Median length1
Mean length1.1681449
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
5230
96.6%
UQT119 132
 
2.4%
UQT129 44
 
0.8%
UQT122 4
 
0.1%
UQT111 2
 
< 0.1%

Length

2024-05-11T04:02:18.268010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:02:18.717068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
uqt119 132
72.5%
uqt129 44
 
24.2%
uqt122 4
 
2.2%
uqt111 2
 
1.1%

도형 속성코드
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size42.4 KiB
UQT210
1062 
UQT510
888 
UQT205
613 
UQT220
544 
UQT310
495 
Other values (19)
1810 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUQT220
2nd rowUQT220
3rd rowUQT220
4th rowUQT220
5th rowUQT205

Common Values

ValueCountFrequency (%)
UQT210 1062
19.6%
UQT510 888
16.4%
UQT205 613
11.3%
UQT220 544
10.1%
UQT310 495
9.1%
UQT320 411
 
7.6%
UQT290 315
 
5.8%
UQT390 271
 
5.0%
UQT330 222
 
4.1%
UQT119 135
 
2.5%
Other values (14) 456
8.4%

Length

2024-05-11T04:02:19.239301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
uqt210 1062
19.6%
uqt510 888
16.4%
uqt205 613
11.3%
uqt220 544
10.1%
uqt310 495
9.1%
uqt320 411
 
7.6%
uqt290 315
 
5.8%
uqt390 271
 
5.0%
uqt330 222
 
4.1%
uqt119 135
 
2.5%
Other values (14) 456
8.4%

도형 조서관리 코드
Text

Distinct4295
Distinct (%)79.4%
Missing0
Missing (%)0.0%
Memory size42.4 KiB
2024-05-11T04:02:19.893048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters108240
Distinct characters13
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

Unique4182 ?
Unique (%)77.3%

Sample

1st row11000URZ202011120001
2nd row11000URZ202011120001
3rd row11590URZ202103080005
4th row11000URZ202007210165
5th row11500URZ202404030002
ValueCountFrequency (%)
11000urz000000001531 846
 
15.6%
11230urz202008040051 28
 
0.5%
11230urz202008040054 14
 
0.3%
11230urz202008040053 14
 
0.3%
11710urz202010230082 13
 
0.2%
11710urz202010230083 13
 
0.2%
11000urz202001280144 7
 
0.1%
11710urz202010230001 7
 
0.1%
11560urz202008240002 7
 
0.1%
11000urz202207130011 7
 
0.1%
Other values (4285) 4456
82.3%
2024-05-11T04:02:21.038821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 38001
35.1%
1 20932
19.3%
2 9901
 
9.1%
U 5412
 
5.0%
R 5412
 
5.0%
Z 5412
 
5.0%
5 4424
 
4.1%
9 4278
 
4.0%
3 3716
 
3.4%
8 2774
 
2.6%
Other values (3) 7978
 
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 92004
85.0%
Uppercase Letter 16236
 
15.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 38001
41.3%
1 20932
22.8%
2 9901
 
10.8%
5 4424
 
4.8%
9 4278
 
4.6%
3 3716
 
4.0%
8 2774
 
3.0%
7 2717
 
3.0%
6 2683
 
2.9%
4 2578
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
U 5412
33.3%
R 5412
33.3%
Z 5412
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 92004
85.0%
Latin 16236
 
15.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 38001
41.3%
1 20932
22.8%
2 9901
 
10.8%
5 4424
 
4.8%
9 4278
 
4.6%
3 3716
 
4.0%
8 2774
 
3.0%
7 2717
 
3.0%
6 2683
 
2.9%
4 2578
 
2.8%
Latin
ValueCountFrequency (%)
U 5412
33.3%
R 5412
33.3%
Z 5412
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 108240
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 38001
35.1%
1 20932
19.3%
2 9901
 
9.1%
U 5412
 
5.0%
R 5412
 
5.0%
Z 5412
 
5.0%
5 4424
 
4.1%
9 4278
 
4.0%
3 3716
 
3.4%
8 2774
 
2.6%
Other values (3) 7978
 
7.4%

결정고시관리코드
Text

Distinct1980
Distinct (%)36.6%
Missing0
Missing (%)0.0%
Memory size42.4 KiB
2024-05-11T04:02:22.135365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length16.942166
Min length1

Characters and Unicode

Total characters91691
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1356 ?
Unique (%)25.1%

Sample

1st row11110NTC202011120005
2nd row11110NTC202011120005
3rd row11620NTC202403220002
4th row11650NTC202403280003
5th row11500NTC202404030004
ValueCountFrequency (%)
11000ntc199505205251 504
 
11.1%
11260ntc202112160004 81
 
1.8%
11000ntc202001280023 71
 
1.6%
11230ntc202008040003 56
 
1.2%
11000ntc202005250008 41
 
0.9%
11000ntc200912034179 40
 
0.9%
11000ntc202007210001 40
 
0.9%
11000ntc199401084285 38
 
0.8%
11000ntc201005134921 37
 
0.8%
11000ntc200909283894 36
 
0.8%
Other values (1969) 3597
79.2%
2024-05-11T04:02:23.936618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 28297
30.9%
1 17571
19.2%
2 10270
 
11.2%
N 4540
 
5.0%
T 4540
 
5.0%
C 4540
 
5.0%
5 4272
 
4.7%
9 3997
 
4.4%
3 2816
 
3.1%
7 2579
 
2.8%
Other values (7) 8269
 
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 77197
84.2%
Uppercase Letter 13623
 
14.9%
Space Separator 871
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 28297
36.7%
1 17571
22.8%
2 10270
 
13.3%
5 4272
 
5.5%
9 3997
 
5.2%
3 2816
 
3.6%
7 2579
 
3.3%
6 2512
 
3.3%
8 2512
 
3.3%
4 2371
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
N 4540
33.3%
T 4540
33.3%
C 4540
33.3%
U 1
 
< 0.1%
R 1
 
< 0.1%
Z 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
871
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 78068
85.1%
Latin 13623
 
14.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 28297
36.2%
1 17571
22.5%
2 10270
 
13.2%
5 4272
 
5.5%
9 3997
 
5.1%
3 2816
 
3.6%
7 2579
 
3.3%
6 2512
 
3.2%
8 2512
 
3.2%
4 2371
 
3.0%
Latin
ValueCountFrequency (%)
N 4540
33.3%
T 4540
33.3%
C 4540
33.3%
U 1
 
< 0.1%
R 1
 
< 0.1%
Z 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 91691
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 28297
30.9%
1 17571
19.2%
2 10270
 
11.2%
N 4540
 
5.0%
T 4540
 
5.0%
C 4540
 
5.0%
5 4272
 
4.7%
9 3997
 
4.4%
3 2816
 
3.1%
7 2579
 
2.8%
Other values (7) 8269
 
9.0%

라벨명
Text

Distinct1109
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Memory size42.4 KiB
2024-05-11T04:02:24.797692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length14
Mean length4.1079084
Min length1

Characters and Unicode

Total characters22232
Distinct characters418
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique923 ?
Unique (%)17.1%

Sample

1st row근린공원
2nd row근린공원
3rd row근린공원
4th row근린공원
5th row소공원
ValueCountFrequency (%)
공공공지 912
16.0%
공원 544
 
9.5%
녹지 488
 
8.5%
완충녹지 370
 
6.5%
소공원 329
 
5.8%
경관녹지 250
 
4.4%
근린공원 232
 
4.1%
기타 227
 
4.0%
공원시설 154
 
2.7%
연결녹지 127
 
2.2%
Other values (1117) 2084
36.5%
2024-05-11T04:02:26.306996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
공 5707
25.7%
원 2814
 
12.7%
지 2415
 
10.9%
녹 1396
 
6.3%
린 523
 
2.4%
충 383
 
1.7%
시 379
 
1.7%
완 374
 
1.7%
기 366
 
1.6%
소 360
 
1.6%
Other values (408) 7515
33.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21371
96.1%
Space Separator 305
 
1.4%
Decimal Number 271
 
1.2%
Open Punctuation 120
 
0.5%
Close Punctuation 120
 
0.5%
Dash Punctuation 22
 
0.1%
Uppercase Letter 12
 
0.1%
Other Number 6
 
< 0.1%
Other Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 5707
26.7%
원 2814
13.2%
지 2415
 
11.3%
녹 1396
 
6.5%
린 523
 
2.4%
충 383
 
1.8%
시 379
 
1.8%
완 374
 
1.8%
기 366
 
1.7%
소 360
 
1.7%
Other values (382) 6654
31.1%
Decimal Number
ValueCountFrequency (%)
1 89
32.8%
2 86
31.7%
3 36
13.3%
4 16
 
5.9%
5 12
 
4.4%
6 12
 
4.4%
7 8
 
3.0%
9 5
 
1.8%
8 4
 
1.5%
0 3
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
B 3
25.0%
C 3
25.0%
L 2
16.7%
I 2
16.7%
D 1
 
8.3%
A 1
 
8.3%
Other Number
ValueCountFrequency (%)
① 3
50.0%
② 2
33.3%
③ 1
 
16.7%
Other Punctuation
ValueCountFrequency (%)
, 2
40.0%
. 2
40.0%
？ 1
20.0%
Space Separator
ValueCountFrequency (%)
305
100.0%
Open Punctuation
ValueCountFrequency (%)
( 120
100.0%
Close Punctuation
ValueCountFrequency (%)
) 120
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21369
96.1%
Common 849
 
3.8%
Latin 12
 
0.1%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 5707
26.7%
원 2814
13.2%
지 2415
 
11.3%
녹 1396
 
6.5%
린 523
 
2.4%
충 383
 
1.8%
시 379
 
1.8%
완 374
 
1.8%
기 366
 
1.7%
소 360
 
1.7%
Other values (381) 6652
31.1%
Common
ValueCountFrequency (%)
305
35.9%
( 120
 
14.1%
) 120
 
14.1%
1 89
 
10.5%
2 86
 
10.1%
3 36
 
4.2%
- 22
 
2.6%
4 16
 
1.9%
5 12
 
1.4%
6 12
 
1.4%
Other values (10) 31
 
3.7%
Latin
ValueCountFrequency (%)
B 3
25.0%
C 3
25.0%
L 2
16.7%
I 2
16.7%
D 1
 
8.3%
A 1
 
8.3%
Han
ValueCountFrequency (%)
怨 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21369
96.1%
ASCII 854
 
3.8%
Enclosed Alphanum 6
 
< 0.1%
CJK 2
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
공 5707
26.7%
원 2814
13.2%
지 2415
 
11.3%
녹 1396
 
6.5%
린 523
 
2.4%
충 383
 
1.8%
시 379
 
1.8%
완 374
 
1.8%
기 366
 
1.7%
소 360
 
1.7%
Other values (381) 6652
31.1%
ASCII
ValueCountFrequency (%)
305
35.7%
( 120
 
14.1%
) 120
 
14.1%
1 89
 
10.4%
2 86
 
10.1%
3 36
 
4.2%
- 22
 
2.6%
4 16
 
1.9%
5 12
 
1.4%
6 12
 
1.4%
Other values (12) 36
 
4.2%
Enclosed Alphanum
ValueCountFrequency (%)
① 3
50.0%
② 2
33.3%
③ 1
 
16.7%
CJK
ValueCountFrequency (%)
怨 2
100.0%
None
ValueCountFrequency (%)
？ 1
100.0%

시군구코드
Real number (ℝ)

SKEWED 

Distinct27
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11121.962
Minimum11000
Maximum99999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size47.7 KiB
2024-05-11T04:02:26.902511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11000
5-th percentile11000
Q111000
median11000
Q311000
95-th percentile11530
Maximum99999
Range88999
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2422.5788
Coefficient of variation (CV)0.21781938
Kurtosis1337.6338
Mean11121.962
Median Absolute Deviation (MAD)0
Skewness36.516016
Sum60192056
Variance5868888.1
MonotonicityNot monotonic
2024-05-11T04:02:27.398957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
11000 4683
86.5%
11260 103
 
1.9%
11230 77
 
1.4%
11710 72
 
1.3%
11530 57
 
1.1%
11290 37
 
0.7%
11560 37
 
0.7%
11140 36
 
0.7%
11680 34
 
0.6%
11380 32
 
0.6%
Other values (17) 244
 
4.5%
ValueCountFrequency (%)
11000 4683
86.5%
11110 9
 
0.2%
11140 36
 
0.7%
11170 17
 
0.3%
11200 13
 
0.2%
11215 4
 
0.1%
11230 77
 
1.4%
11260 103
 
1.9%
11290 37
 
0.7%
11305 14
 
0.3%
ValueCountFrequency (%)
99999 4
 
0.1%
11740 16
 
0.3%
11710 72
1.3%
11680 34
0.6%
11650 21
 
0.4%
11620 12
 
0.2%
11590 31
0.6%
11560 37
0.7%
11545 12
 
0.2%
11530 57
1.1%

도면번호
Text

Distinct198
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size42.4 KiB
2024-05-11T04:02:28.006131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length1
Mean length1.1210273
Min length1

Characters and Unicode

Total characters6067
Distinct characters85
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique104 ?
Unique (%)1.9%

Sample

1st row
2nd row
3rd row299
4th row43
5th row1
ValueCountFrequency (%)
1 312
17.1%
2 172
 
9.4%
① 144
 
7.9%
3 112
 
6.1%
4 88
 
4.8%
② 72
 
3.9%
5 61
 
3.3%
6 50
 
2.7%
④ 43
 
2.4%
7 38
 
2.1%
Other values (181) 736
40.3%
2024-05-11T04:02:29.568430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3588
59.1%
1 556
 
9.2%
2 317
 
5.2%
3 233
 
3.8%
4 161
 
2.7%
① 146
 
2.4%
5 111
 
1.8%
6 92
 
1.5%
8 86
 
1.4%
7 75
 
1.2%
Other values (75) 702
 
11.6%

Most occurring categories

ValueCountFrequency (%)
Space Separator 3588
59.1%
Decimal Number 1748
28.8%
Other Number 388
 
6.4%
Other Letter 208
 
3.4%
Uppercase Letter 73
 
1.2%
Dash Punctuation 27
 
0.4%
Lowercase Letter 18
 
0.3%
Close Punctuation 7
 
0.1%
Open Punctuation 7
 
0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 26
12.5%
녹 25
12.0%
경 18
 
8.7%
완 15
 
7.2%
충 15
 
7.2%
공 15
 
7.2%
가 11
 
5.3%
서 10
 
4.8%
원 9
 
4.3%
관 7
 
3.4%
Other values (31) 57
27.4%
Other Number
ValueCountFrequency (%)
① 146
37.6%
② 72
18.6%
④ 43
 
11.1%
③ 37
 
9.5%
⑤ 27
 
7.0%
⑥ 14
 
3.6%
⑦ 14
 
3.6%
⑧ 12
 
3.1%
⑨ 9
 
2.3%
⑩ 7
 
1.8%
Other values (3) 7
 
1.8%
Decimal Number
ValueCountFrequency (%)
1 556
31.8%
2 317
18.1%
3 233
13.3%
4 161
 
9.2%
5 111
 
6.4%
6 92
 
5.3%
8 86
 
4.9%
7 75
 
4.3%
9 69
 
3.9%
0 48
 
2.7%
Lowercase Letter
ValueCountFrequency (%)
a 7
38.9%
e 2
 
11.1%
b 2
 
11.1%
d 2
 
11.1%
c 1
 
5.6%
v 1
 
5.6%
j 1
 
5.6%
k 1
 
5.6%
l 1
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
B 30
41.1%
C 15
20.5%
D 15
20.5%
A 11
 
15.1%
L 1
 
1.4%
E 1
 
1.4%
Space Separator
ValueCountFrequency (%)
3588
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Other Punctuation
ValueCountFrequency (%)
？ 2
100.0%
Other Symbol
ValueCountFrequency (%)
ⓒ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5768
95.1%
Hangul 208
 
3.4%
Latin 91
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 26
12.5%
녹 25
12.0%
경 18
 
8.7%
완 15
 
7.2%
충 15
 
7.2%
공 15
 
7.2%
가 11
 
5.3%
서 10
 
4.8%
원 9
 
4.3%
관 7
 
3.4%
Other values (31) 57
27.4%
Common
ValueCountFrequency (%)
3588
62.2%
1 556
 
9.6%
2 317
 
5.5%
3 233
 
4.0%
4 161
 
2.8%
① 146
 
2.5%
5 111
 
1.9%
6 92
 
1.6%
8 86
 
1.5%
7 75
 
1.3%
Other values (19) 403
 
7.0%
Latin
ValueCountFrequency (%)
B 30
33.0%
C 15
16.5%
D 15
16.5%
A 11
 
12.1%
a 7
 
7.7%
e 2
 
2.2%
b 2
 
2.2%
d 2
 
2.2%
L 1
 
1.1%
c 1
 
1.1%
Other values (5) 5
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5468
90.1%
Enclosed Alphanum 389
 
6.4%
Hangul 208
 
3.4%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3588
65.6%
1 556
 
10.2%
2 317
 
5.8%
3 233
 
4.3%
4 161
 
2.9%
5 111
 
2.0%
6 92
 
1.7%
8 86
 
1.6%
7 75
 
1.4%
9 69
 
1.3%
Other values (19) 180
 
3.3%
Enclosed Alphanum
ValueCountFrequency (%)
① 146
37.5%
② 72
18.5%
④ 43
 
11.1%
③ 37
 
9.5%
⑤ 27
 
6.9%
⑥ 14
 
3.6%
⑦ 14
 
3.6%
⑧ 12
 
3.1%
⑨ 9
 
2.3%
⑩ 7
 
1.8%
Other values (4) 8
 
2.1%
Hangul
ValueCountFrequency (%)
지 26
12.5%
녹 25
12.0%
경 18
 
8.7%
완 15
 
7.2%
충 15
 
7.2%
공 15
 
7.2%
가 11
 
5.3%
서 10
 
4.8%
원 9
 
4.3%
관 7
 
3.4%
Other values (31) 57
27.4%
None
ValueCountFrequency (%)
？ 2
100.0%

집행상태코드 심볼
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.4 KiB
EMA0009
5403 
 
4
EMA0001
 
3
EMA0003
 
1
EMA0002
 
1

Length

Max length7
Median length7
Mean length6.9955654
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowEMA0009
2nd rowEMA0009
3rd rowEMA0009
4th rowEMA0009
5th rowEMA0009

Common Values

ValueCountFrequency (%)
EMA0009 5403
99.8%
4
 
0.1%
EMA0001 3
 
0.1%
EMA0003 1
 
< 0.1%
EMA0002 1
 
< 0.1%

Length

2024-05-11T04:02:30.251726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:02:30.719170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ema0009 5403
99.9%
ema0001 3
 
0.1%
ema0003 1
 
< 0.1%
ema0002 1
 
< 0.1%

현황도형 생성일시
Date

Distinct323
Distinct (%)6.0%
Missing2
Missing (%)< 0.1%
Memory size42.4 KiB
Minimum1899-12-29 23:27:52
Maximum2024-04-24 00:00:00
2024-05-11T04:02:31.537416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:02:32.133897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

면적(도형)
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct5094
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22053.247
Minimum0
Maximum14391611
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size47.7 KiB
2024-05-11T04:02:32.740397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile96.103546
Q1549.15123
median1388.6682
Q33667.9081
95-th percentile45140.022
Maximum14391611
Range14391611
Interquartile range (IQR)3118.7569

Descriptive statistics

Standard deviation268961.6
Coefficient of variation (CV)12.196009
Kurtosis1674.1743
Mean22053.247
Median Absolute Deviation (MAD)1049.7386
Skewness36.364774
Sum1.1935217 × 108
Variance7.2340342 × 1010
MonotonicityNot monotonic
2024-05-11T04:02:33.323512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4362.464987 28
 
0.5%
552.53579892 14
 
0.3%
4467.16849299 14
 
0.3%
2720.22011257 14
 
0.3%
1565.0118379 13
 
0.2%
640.26156388 13
 
0.2%
4053.35687235 7
 
0.1%
1217.39575256 7
 
0.1%
71736.89979146 7
 
0.1%
45385.68320651 7
 
0.1%
Other values (5084) 5288
97.7%
ValueCountFrequency (%)
0.0 2
< 0.1%
0.5930746 1
< 0.1%
1.88346447 1
< 0.1%
2.79002863 1
< 0.1%
3.54648151 1
< 0.1%
3.7588296 1
< 0.1%
4.11551124 1
< 0.1%
4.28170486 1
< 0.1%
6.26752112 1
< 0.1%
6.52304724 1
< 0.1%
ValueCountFrequency (%)
14391610.7148 1
< 0.1%
6986987.80413 1
< 0.1%
5282220.53783 1
< 0.1%
5277570.77759 1
< 0.1%
5045749.99551 1
< 0.1%
3785015.44336 1
< 0.1%
2283126.26581 1
< 0.1%
2061049.19717 1
< 0.1%
1815871.14683 1
< 0.1%
1765533.43374 1
< 0.1%

길이(도형)
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct5094
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3193.9935
Minimum0
Maximum14391611
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size47.7 KiB
2024-05-11T04:02:34.298966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile49.264527
Q1123.64488
median194.03991
Q3392.35882
95-th percentile1861.3276
Maximum14391611
Range14391611
Interquartile range (IQR)268.71394

Descriptive statistics

Standard deviation195626.87
Coefficient of variation (CV)61.248361
Kurtosis5411.2949
Mean3193.9935
Median Absolute Deviation (MAD)99.675746
Skewness73.559115
Sum17285893
Variance3.8269872 × 1010
MonotonicityNot monotonic
2024-05-11T04:02:34.950332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
414.02100354 28
 
0.5%
107.98062549 14
 
0.3%
288.56876282 14
 
0.3%
221.6244974 14
 
0.3%
392.35882126 13
 
0.2%
260.69494971 13
 
0.2%
262.39632319 7
 
0.1%
236.26140938 7
 
0.1%
7127.17817706 7
 
0.1%
1365.93720235 7
 
0.1%
Other values (5084) 5288
97.7%
ValueCountFrequency (%)
0.0 2
< 0.1%
6.77533869 1
< 0.1%
7.88763328 1
< 0.1%
7.90109767 1
< 0.1%
10.0627413 1
< 0.1%
13.43266437 1
< 0.1%
15.5345743 1
< 0.1%
15.57017708 1
< 0.1%
15.62767186 1
< 0.1%
15.67772909 1
< 0.1%
ValueCountFrequency (%)
14391610.7148 1
< 0.1%
37363.0331391 1
< 0.1%
32311.4436343 1
< 0.1%
25131.58445593 1
< 0.1%
22421.40180116 1
< 0.1%
21546.0440218 1
< 0.1%
21238.8588654 1
< 0.1%
21056.2912089 1
< 0.1%
20414.5925528 1
< 0.1%
17545.3494674 1
< 0.1%

Interactions

2024-05-11T04:02:10.642086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:02:06.434645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:02:07.886554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:02:09.385401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:02:11.000689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:02:06.726605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:02:08.267003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:02:09.674321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:02:11.262403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:02:07.110534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:02:08.596308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:02:09.957407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:02:11.588915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:02:07.435411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:02:08.947663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:02:10.295815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T04:02:35.469442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
객체id도형 대분류코드도형 중분류코드도형 소분류코드도형 속성코드시군구코드집행상태코드 심볼면적(도형)길이(도형)
객체id1.0000.0800.1670.0880.1640.1180.0420.0140.000
도형 대분류코드0.0801.0000.9950.5620.9710.0000.0000.0000.000
도형 중분류코드0.1670.9951.0000.9011.0000.0000.0000.4080.181
도형 소분류코드0.0880.5620.9011.0000.9980.0000.0000.0000.000
도형 속성코드0.1640.9711.0000.9981.0000.0000.0000.4080.181
시군구코드0.1180.0000.0000.0000.0001.0000.0000.000NaN
집행상태코드 심볼0.0420.0000.0000.0000.0000.0001.0000.0000.000
면적(도형)0.0140.0000.4080.0000.4080.0000.0001.0001.000
길이(도형)0.0000.0000.1810.0000.181NaN0.0001.0001.000
2024-05-11T04:02:36.019370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
집행상태코드 심볼도형 속성코드도형 대분류코드도형 중분류코드도형 소분류코드
집행상태코드 심볼1.0000.0000.0000.0000.000
도형 속성코드0.0001.0000.7540.9550.995
도형 대분류코드0.0000.7541.0000.8840.388
도형 중분류코드0.0000.9550.8841.0000.703
도형 소분류코드0.0000.9950.3880.7031.000
2024-05-11T04:02:36.538343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
객체id시군구코드면적(도형)길이(도형)도형 대분류코드도형 중분류코드도형 소분류코드도형 속성코드집행상태코드 심볼
객체id1.000-0.0050.0260.0350.0380.0620.0370.0600.017
시군구코드-0.0051.0000.0840.1150.0000.0000.0000.0000.000
면적(도형)0.0260.0841.0000.9060.0000.1760.0000.1760.000
길이(도형)0.0350.1150.9061.0000.0000.1430.0000.1430.000
도형 대분류코드0.0380.0000.0000.0001.0000.8840.3880.7540.000
도형 중분류코드0.0620.0000.1760.1430.8841.0000.7030.9550.000
도형 소분류코드0.0370.0000.0000.0000.3880.7031.0000.9950.000
도형 속성코드0.0600.0000.1760.1430.7540.9550.9951.0000.000
집행상태코드 심볼0.0170.0000.0000.0000.0000.0000.0000.0001.000

Missing values

2024-05-11T04:02:12.086088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T04:02:12.876109image/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

객체id현황도형 관리번호도형 대분류코드도형 중분류코드도형 소분류코드도형 속성코드도형 조서관리 코드결정고시관리코드라벨명시군구코드도면번호집행상태코드 심볼현황도형 생성일시면적(도형)길이(도형)
023661011000UQ153PS202011160001UQT200UQT220UQT22011000URZ20201112000111110NTC202011120005근린공원11000EMA0009<NA>163544.1553256019.921452
123565111000UQ153PS202011160002UQT200UQT220UQT22011000URZ20201112000111110NTC202011120005근린공원11000EMA0009<NA>163544.1553256019.921452
223678211590UQ153PS202404240001UQT200UQT220UQT22011590URZ20210308000511620NTC202403220002근린공원11590299EMA00092024-04-24 00:00:00.0423862.14021815888.973328
323678111000UQ153PS202404240001UQT200UQT220UQT22011000URZ20200721016511650NTC202403280003근린공원1100043EMA00092024-04-24 00:00:00.0462892.02522412119.392834
423678011500UQ153PS202404240001UQT200UQT205UQT20511500URZ20240403000211500NTC202404030004소공원115001EMA00092024-04-24 00:00:00.0931.083251158.959764
523677611000UQ153PS202404230001UQT200UQT270UQT27011000URZ20240326000511000NTC202403260002문화공원11000AEMA00092024-04-23 00:00:00.06012.885992308.528503
623677911000UQ153PS202404230004UQT300UQT310UQT31011000URZ20240306000711000NTC202403060001완충녹지110003EMA00092024-04-23 00:00:00.021230.4309135033.740634
723677811000UQ153PS202404230003UQT100UQT119UQT11911000URZ20240306000611000NTC202403060001교통광장(양재I.C)1100049EMA00092024-04-23 00:00:00.0142426.1643462471.611474
823677711000UQ153PS202404230002UQT300UQT320UQT32011000URZ20240306000811000NTC202403060001경관녹지110001EMA00092024-04-23 00:00:00.01292.703736374.344239
923637211320UQ153PS202404180001UQT500UQT510UQT51011320URZ20230523000311320NTC202305230007공공공지11320EMA00092024-04-18 00:00:00.01855.137834544.550553
객체id현황도형 관리번호도형 대분류코드도형 중분류코드도형 소분류코드도형 속성코드도형 조서관리 코드결정고시관리코드라벨명시군구코드도면번호집행상태코드 심볼현황도형 생성일시면적(도형)길이(도형)
540223210911000UQ153PS201912153620UQT300UQT310UQT31011000URZ20070412400311000NTC200704120931녹지11000①EMA00092019-12-15 00:00:00.01338.87045284.838079
540323245311000UQ153PS201912152886UQT300UQT320UQT32011000URZ20060518541811000NTC200605180078녹지11000EMA00092019-12-15 00:00:00.0387.22105798.974405
540423245411000UQ153PS201912154292UQT500UQT510UQT51011000URZ20040705002211000NTC200407056543공공공지11000EMA00092019-12-15 00:00:00.0560.16198105.598501
540523245511000UQ153PS201912154294UQT500UQT510UQT51011000URZ19990803699411000NTC199908038905공공공지11000EMA00092019-12-15 00:00:00.03614.41731540.174193
540623245611000UQ153PS201912154295UQT500UQT510UQT51011000URZ20010915170311000NTC200109151314공공공지11000EMA00092019-12-15 00:00:00.0304.94154394.160118
540723246011000UQ153PS201912154296UQT500UQT510UQT51011000URZ19990323664811000NTC199903238621공공공지11000EMA00092019-12-15 00:00:00.0290.2026774.20947
540823246811000UQ153PS201912151269UQT200UQT210UQT21011000URZ20140717426311000NTC201407177263구룡공원11000EMA00092019-12-15 00:00:00.0934.690873120.918734
540923246911000UQ153PS201912151270UQT200UQT220UQT22011000URZ20100427729711000NTC201004274830공원110001EMA00092019-12-15 00:00:00.0108801.6490531363.852019
541023293211000UQ153PS202001130005UQT500UQT510UQT51011000URZ20191010105111000NTC201903071136공공공지1129088EMA00092019-05-22 00:00:00.01093.37927175.657494
541123601611000UQ153PS202401290012UQT300UQT310UQT31011650URZ20230816007711650NTC202309080003완충녹지116508EMA00091899-12-29 23:27:52.03817.649857890.838544