Overview

Dataset statistics

Number of variables13
Number of observations3476
Missing cells7768
Missing cells (%)17.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory366.7 KiB
Average record size in memory108.0 B

Variable types

Text6
Categorical1
Numeric4
Boolean1
DateTime1

Dataset

Description민방위 대피시설별 대피가능 인원
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=6T98794V0223GQQ9O1P421644027&infSeq=1

Alerts

정제WGS84위도 is highly overall correlated with 개방여부High correlation
시설면적 is highly overall correlated with 수용인원수High correlation
수용인원수 is highly overall correlated with 시설면적High correlation
개방여부 is highly overall correlated with 정제WGS84위도High correlation
시설구분명 is highly imbalanced (83.4%)Imbalance
개방여부 is highly imbalanced (68.6%)Imbalance
정제도로명주소 has 1581 (45.5%) missing valuesMissing
정제지번주소 has 1578 (45.4%) missing valuesMissing
정제WGS84위도 has 1589 (45.7%) missing valuesMissing
정제WGS84경도 has 1589 (45.7%) missing valuesMissing
관련정보 has 488 (14.0%) missing valuesMissing
관리기관전화번호 has 943 (27.1%) missing valuesMissing
수용인원수 has 56 (1.6%) zerosZeros

Reproduction

Analysis started2024-05-03 19:17:22.243476
Analysis finished2024-05-03 19:17:31.715323
Duration9.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

Distinct3401
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
2024-05-03T19:17:32.294719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length36
Mean length15.160817
Min length2

Characters and Unicode

Total characters52699
Distinct characters549
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3343 ?
Unique (%)96.2%

Sample

1st row목동초등학교
2nd row북면우체국
3rd row태광아파트(101동)(지하1층주차장)
4th row태광아파트(102동)(지하1층주차장)
5th row대현빌라트(지하 1층 주차장)
ValueCountFrequency (%)
지하주차장 1584
 
18.0%
1층 570
 
6.5%
지하 220
 
2.5%
주차장 134
 
1.5%
아파트 127
 
1.4%
동의 124
 
1.4%
모든 103
 
1.2%
앞 68
 
0.8%
지하1층 59
 
0.7%
전체(지하 42
 
0.5%
Other values (3639) 5771
65.6%
2024-05-03T19:17:33.914675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5336
 
10.1%
지 3437
 
6.5%
하 2356
 
4.5%
차 2302
 
4.4%
아 2288
 
4.3%
주 2276
 
4.3%
트 2144
 
4.1%
파 2109
 
4.0%
장 2002
 
3.8%
1 1858
 
3.5%
Other values (539) 26591
50.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 40922
77.7%
Space Separator 5336
 
10.1%
Decimal Number 4524
 
8.6%
Open Punctuation 539
 
1.0%
Close Punctuation 535
 
1.0%
Other Punctuation 392
 
0.7%
Uppercase Letter 223
 
0.4%
Math Symbol 159
 
0.3%
Lowercase Letter 40
 
0.1%
Dash Punctuation 28
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 3437
 
8.4%
하 2356
 
5.8%
차 2302
 
5.6%
아 2288
 
5.6%
주 2276
 
5.6%
트 2144
 
5.2%
파 2109
 
5.2%
장 2002
 
4.9%
동 1330
 
3.3%
단 903
 
2.2%
Other values (489) 19775
48.3%
Uppercase Letter
ValueCountFrequency (%)
K 28
12.6%
L 28
12.6%
C 26
11.7%
A 20
9.0%
H 19
8.5%
S 19
8.5%
T 18
8.1%
B 15
6.7%
G 14
6.3%
I 6
 
2.7%
Other values (12) 30
13.5%
Decimal Number
ValueCountFrequency (%)
1 1858
41.1%
2 815
18.0%
0 583
 
12.9%
3 397
 
8.8%
4 202
 
4.5%
5 201
 
4.4%
6 140
 
3.1%
7 129
 
2.9%
8 104
 
2.3%
9 95
 
2.1%
Other Punctuation
ValueCountFrequency (%)
, 356
90.8%
. 23
 
5.9%
· 5
 
1.3%
/ 5
 
1.3%
& 1
 
0.3%
? 1
 
0.3%
@ 1
 
0.3%
Lowercase Letter
ValueCountFrequency (%)
e 32
80.0%
s 3
 
7.5%
k 2
 
5.0%
c 2
 
5.0%
i 1
 
2.5%
Space Separator
ValueCountFrequency (%)
5336
100.0%
Open Punctuation
ValueCountFrequency (%)
( 539
100.0%
Close Punctuation
ValueCountFrequency (%)
) 535
100.0%
Math Symbol
ValueCountFrequency (%)
~ 159
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 40923
77.7%
Common 11513
 
21.8%
Latin 263
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 3437
 
8.4%
하 2356
 
5.8%
차 2302
 
5.6%
아 2288
 
5.6%
주 2276
 
5.6%
트 2144
 
5.2%
파 2109
 
5.2%
장 2002
 
4.9%
동 1330
 
3.3%
단 903
 
2.2%
Other values (490) 19776
48.3%
Latin
ValueCountFrequency (%)
e 32
12.2%
K 28
10.6%
L 28
10.6%
C 26
9.9%
A 20
7.6%
H 19
7.2%
S 19
7.2%
T 18
6.8%
B 15
 
5.7%
G 14
 
5.3%
Other values (17) 44
16.7%
Common
ValueCountFrequency (%)
5336
46.3%
1 1858
 
16.1%
2 815
 
7.1%
0 583
 
5.1%
( 539
 
4.7%
) 535
 
4.6%
3 397
 
3.4%
, 356
 
3.1%
4 202
 
1.8%
5 201
 
1.7%
Other values (12) 691
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 40922
77.7%
ASCII 11771
 
22.3%
None 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5336
45.3%
1 1858
 
15.8%
2 815
 
6.9%
0 583
 
5.0%
( 539
 
4.6%
) 535
 
4.5%
3 397
 
3.4%
, 356
 
3.0%
4 202
 
1.7%
5 201
 
1.7%
Other values (38) 949
 
8.1%
Hangul
ValueCountFrequency (%)
지 3437
 
8.4%
하 2356
 
5.8%
차 2302
 
5.6%
아 2288
 
5.6%
주 2276
 
5.6%
트 2144
 
5.2%
파 2109
 
5.2%
장 2002
 
4.9%
동 1330
 
3.3%
단 903
 
2.2%
Other values (489) 19775
48.3%
None
ValueCountFrequency (%)
· 5
83.3%
㈜ 1
 
16.7%

시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
공공용
3391 
정부지원
 
85

Length

Max length4
Median length3
Mean length3.0244534
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공용 3391
97.6%
정부지원 85
 
2.4%

Length

2024-05-03T19:17:34.470682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T19:17:34.897283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공용 3391
97.6%
정부지원 85
 
2.4%

정제도로명주소
Text

MISSING 

Distinct1751
Distinct (%)92.4%
Missing1581
Missing (%)45.5%
Memory size27.3 KiB
2024-05-03T19:17:35.520081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length44
Mean length29.326121
Min length13

Characters and Unicode

Total characters55573
Distinct characters434
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1666 ?
Unique (%)87.9%

Sample

1st row경기도 고양시 일산서구 송포로 10 (대화동, 대화마을9단지)
2nd row경기도 고양시 일산서구 고양대로255번길 46 (대화동, 대화마을10단지아파트)
3rd row경기도 고양시 일산서구 산현로 34 (일산동, 동문1차아파트)
4th row경기도 고양시 일산서구 탄중로 523 (일산동, 에이스11차아파트)
5th row경기도 고양시 일산서구 산현로92번길 20 (일산동)
ValueCountFrequency (%)
경기도 1895
 
17.1%
고양시 411
 
3.7%
수원시 280
 
2.5%
용인시 265
 
2.4%
성남시 264
 
2.4%
김포시 246
 
2.2%
덕양구 163
 
1.5%
분당구 139
 
1.3%
일산서구 132
 
1.2%
기흥구 120
 
1.1%
Other values (2623) 7149
64.6%
2024-05-03T19:17:36.753418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9169
 
16.5%
기 2077
 
3.7%
도 1983
 
3.6%
시 1981
 
3.6%
경 1976
 
3.6%
로 1880
 
3.4%
1 1526
 
2.7%
동 1373
 
2.5%
구 1282
 
2.3%
( 1179
 
2.1%
Other values (424) 31147
56.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 35782
64.4%
Space Separator 9169
 
16.5%
Decimal Number 7060
 
12.7%
Open Punctuation 1179
 
2.1%
Close Punctuation 1179
 
2.1%
Other Punctuation 920
 
1.7%
Dash Punctuation 221
 
0.4%
Uppercase Letter 45
 
0.1%
Lowercase Letter 15
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 2077
 
5.8%
도 1983
 
5.5%
시 1981
 
5.5%
경 1976
 
5.5%
로 1880
 
5.3%
동 1373
 
3.8%
구 1282
 
3.6%
아 810
 
2.3%
양 796
 
2.2%
트 751
 
2.1%
Other values (380) 20873
58.3%
Uppercase Letter
ValueCountFrequency (%)
I 9
20.0%
A 4
 
8.9%
S 4
 
8.9%
E 4
 
8.9%
L 3
 
6.7%
G 3
 
6.7%
K 2
 
4.4%
P 2
 
4.4%
U 2
 
4.4%
D 2
 
4.4%
Other values (7) 10
22.2%
Decimal Number
ValueCountFrequency (%)
1 1526
21.6%
2 1036
14.7%
3 781
11.1%
5 615
8.7%
6 572
 
8.1%
4 572
 
8.1%
0 563
 
8.0%
7 509
 
7.2%
8 454
 
6.4%
9 432
 
6.1%
Lowercase Letter
ValueCountFrequency (%)
e 6
40.0%
a 3
20.0%
s 1
 
6.7%
t 1
 
6.7%
r 1
 
6.7%
n 1
 
6.7%
l 1
 
6.7%
c 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 912
99.1%
? 7
 
0.8%
. 1
 
0.1%
Space Separator
ValueCountFrequency (%)
9169
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1179
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1179
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 221
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35782
64.4%
Common 19730
35.5%
Latin 61
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 2077
 
5.8%
도 1983
 
5.5%
시 1981
 
5.5%
경 1976
 
5.5%
로 1880
 
5.3%
동 1373
 
3.8%
구 1282
 
3.6%
아 810
 
2.3%
양 796
 
2.2%
트 751
 
2.1%
Other values (380) 20873
58.3%
Latin
ValueCountFrequency (%)
I 9
14.8%
e 6
 
9.8%
A 4
 
6.6%
S 4
 
6.6%
E 4
 
6.6%
L 3
 
4.9%
G 3
 
4.9%
a 3
 
4.9%
K 2
 
3.3%
P 2
 
3.3%
Other values (16) 21
34.4%
Common
ValueCountFrequency (%)
9169
46.5%
1 1526
 
7.7%
( 1179
 
6.0%
) 1179
 
6.0%
2 1036
 
5.3%
, 912
 
4.6%
3 781
 
4.0%
5 615
 
3.1%
6 572
 
2.9%
4 572
 
2.9%
Other values (8) 2189
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35782
64.4%
ASCII 19790
35.6%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9169
46.3%
1 1526
 
7.7%
( 1179
 
6.0%
) 1179
 
6.0%
2 1036
 
5.2%
, 912
 
4.6%
3 781
 
3.9%
5 615
 
3.1%
6 572
 
2.9%
4 572
 
2.9%
Other values (33) 2249
 
11.4%
Hangul
ValueCountFrequency (%)
기 2077
 
5.8%
도 1983
 
5.5%
시 1981
 
5.5%
경 1976
 
5.5%
로 1880
 
5.3%
동 1373
 
3.8%
구 1282
 
3.6%
아 810
 
2.3%
양 796
 
2.2%
트 751
 
2.1%
Other values (380) 20873
58.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

정제지번주소
Text

MISSING 

Distinct1747
Distinct (%)92.0%
Missing1578
Missing (%)45.4%
Memory size27.3 KiB
2024-05-03T19:17:37.447436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length36
Mean length26.346154
Min length16

Characters and Unicode

Total characters50005
Distinct characters419
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1660 ?
Unique (%)87.5%

Sample

1st row경기도 고양시 일산서구 대화동 2582번지
2nd row경기도 고양시 일산서구 대화동 2580번지
3rd row경기도 고양시 일산서구 일산동 1694번지
4th row경기도 고양시 일산서구 일산동 2019번지
5th row경기도 고양시 일산서구 일산동 1997번지
ValueCountFrequency (%)
경기도 1898
 
18.5%
고양시 411
 
4.0%
수원시 280
 
2.7%
용인시 265
 
2.6%
성남시 265
 
2.6%
김포시 246
 
2.4%
덕양구 163
 
1.6%
분당구 139
 
1.4%
일산서구 132
 
1.3%
기흥구 124
 
1.2%
Other values (2672) 6309
61.7%
2024-05-03T19:17:39.110107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8353
 
16.7%
기 2065
 
4.1%
지 2022
 
4.0%
시 1989
 
4.0%
도 1980
 
4.0%
동 1971
 
3.9%
경 1932
 
3.9%
번 1691
 
3.4%
1 1357
 
2.7%
구 1281
 
2.6%
Other values (409) 25364
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 34090
68.2%
Space Separator 8353
 
16.7%
Decimal Number 6959
 
13.9%
Dash Punctuation 452
 
0.9%
Uppercase Letter 78
 
0.2%
Other Punctuation 33
 
0.1%
Close Punctuation 17
 
< 0.1%
Open Punctuation 17
 
< 0.1%
Lowercase Letter 5
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 2065
 
6.1%
지 2022
 
5.9%
시 1989
 
5.8%
도 1980
 
5.8%
동 1971
 
5.8%
경 1932
 
5.7%
번 1691
 
5.0%
구 1281
 
3.8%
아 808
 
2.4%
양 778
 
2.3%
Other values (371) 17573
51.5%
Uppercase Letter
ValueCountFrequency (%)
I 12
15.4%
K 9
11.5%
S 8
10.3%
L 6
 
7.7%
C 5
 
6.4%
A 5
 
6.4%
G 5
 
6.4%
W 4
 
5.1%
T 4
 
5.1%
E 4
 
5.1%
Other values (9) 16
20.5%
Decimal Number
ValueCountFrequency (%)
1 1357
19.5%
2 800
11.5%
3 687
9.9%
5 656
9.4%
6 616
8.9%
7 608
8.7%
4 601
8.6%
8 586
8.4%
0 546
7.8%
9 502
 
7.2%
Other Punctuation
ValueCountFrequency (%)
. 13
39.4%
, 13
39.4%
? 7
21.2%
Space Separator
ValueCountFrequency (%)
8353
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 452
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 5
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 34090
68.2%
Common 15831
31.7%
Latin 84
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 2065
 
6.1%
지 2022
 
5.9%
시 1989
 
5.8%
도 1980
 
5.8%
동 1971
 
5.8%
경 1932
 
5.7%
번 1691
 
5.0%
구 1281
 
3.8%
아 808
 
2.4%
양 778
 
2.3%
Other values (371) 17573
51.5%
Latin
ValueCountFrequency (%)
I 12
14.3%
K 9
10.7%
S 8
 
9.5%
L 6
 
7.1%
C 5
 
6.0%
A 5
 
6.0%
G 5
 
6.0%
e 5
 
6.0%
W 4
 
4.8%
T 4
 
4.8%
Other values (11) 21
25.0%
Common
ValueCountFrequency (%)
8353
52.8%
1 1357
 
8.6%
2 800
 
5.1%
3 687
 
4.3%
5 656
 
4.1%
6 616
 
3.9%
7 608
 
3.8%
4 601
 
3.8%
8 586
 
3.7%
0 546
 
3.4%
Other values (7) 1021
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 34090
68.2%
ASCII 15914
31.8%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8353
52.5%
1 1357
 
8.5%
2 800
 
5.0%
3 687
 
4.3%
5 656
 
4.1%
6 616
 
3.9%
7 608
 
3.8%
4 601
 
3.8%
8 586
 
3.7%
0 546
 
3.4%
Other values (27) 1104
 
6.9%
Hangul
ValueCountFrequency (%)
기 2065
 
6.1%
지 2022
 
5.9%
시 1989
 
5.8%
도 1980
 
5.8%
동 1971
 
5.8%
경 1932
 
5.7%
번 1691
 
5.0%
구 1281
 
3.8%
아 808
 
2.4%
양 778
 
2.3%
Other values (371) 17573
51.5%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

정제WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1812
Distinct (%)96.0%
Missing1589
Missing (%)45.7%
Infinite0
Infinite (%)0.0%
Mean37.435258
Minimum37.113659
Maximum37.761956
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.7 KiB
2024-05-03T19:17:39.710319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.113659
5-th percentile37.246499
Q137.296185
median37.385231
Q337.624039
95-th percentile37.723305
Maximum37.761956
Range0.64829753
Interquartile range (IQR)0.32785348

Descriptive statistics

Standard deviation0.1629348
Coefficient of variation (CV)0.0043524422
Kurtosis-1.0356851
Mean37.435258
Median Absolute Deviation (MAD)0.09708929
Skewness0.58547889
Sum70640.332
Variance0.026547749
MonotonicityNot monotonic
2024-05-03T19:17:40.174441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.30148663 10
 
0.3%
37.6421846 6
 
0.2%
37.30632759 4
 
0.1%
37.6367151 4
 
0.1%
37.6435216 4
 
0.1%
37.6487178 4
 
0.1%
37.365458465 4
 
0.1%
37.6467741 4
 
0.1%
37.41292932 3
 
0.1%
37.30451968 3
 
0.1%
Other values (1802) 1841
53.0%
(Missing) 1589
45.7%
ValueCountFrequency (%)
37.1136586689 1
< 0.1%
37.1144827 1
< 0.1%
37.1145553431 1
< 0.1%
37.1156765351 1
< 0.1%
37.1186557 1
< 0.1%
37.1224303009 1
< 0.1%
37.1391709037 1
< 0.1%
37.1411233252 1
< 0.1%
37.1436791354 1
< 0.1%
37.1473680492 1
< 0.1%
ValueCountFrequency (%)
37.7619562 1
< 0.1%
37.7619215 1
< 0.1%
37.7604793 1
< 0.1%
37.7604602 1
< 0.1%
37.760417 1
< 0.1%
37.7603324 1
< 0.1%
37.7598025 1
< 0.1%
37.7579447 1
< 0.1%
37.7571911 1
< 0.1%
37.7567505 1
< 0.1%

정제WGS84경도
Real number (ℝ)

MISSING 

Distinct1737
Distinct (%)92.1%
Missing1589
Missing (%)45.7%
Infinite0
Infinite (%)0.0%
Mean126.99086
Minimum126.50222
Maximum127.63057
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.7 KiB
2024-05-03T19:17:40.735473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.50222
5-th percentile126.66568
Q1126.79543
median127.03839
Q3127.12657
95-th percentile127.30669
Maximum127.63057
Range1.1283507
Interquartile range (IQR)0.33113627

Descriptive statistics

Standard deviation0.20845218
Coefficient of variation (CV)0.0016414738
Kurtosis-0.46952687
Mean126.99086
Median Absolute Deviation (MAD)0.1504832
Skewness0.075546366
Sum239631.76
Variance0.04345231
MonotonicityNot monotonic
2024-05-03T19:17:41.253393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9941413 10
 
0.3%
126.6686043 6
 
0.2%
126.8359524 6
 
0.2%
126.6237007 5
 
0.1%
126.724445 5
 
0.1%
126.6018142 5
 
0.1%
126.7188089 5
 
0.1%
126.8321462 4
 
0.1%
127.245873725 4
 
0.1%
126.7246268 4
 
0.1%
Other values (1727) 1833
52.7%
(Missing) 1589
45.7%
ValueCountFrequency (%)
126.502221 1
< 0.1%
126.504612 1
< 0.1%
126.5275047 1
< 0.1%
126.5298507 1
< 0.1%
126.5462177 1
< 0.1%
126.553159 1
< 0.1%
126.5593239 1
< 0.1%
126.563226 1
< 0.1%
126.5828456 1
< 0.1%
126.5834693 1
< 0.1%
ValueCountFrequency (%)
127.6305717 1
< 0.1%
127.6288204735 1
< 0.1%
127.6180430495 1
< 0.1%
127.6169703123 1
< 0.1%
127.6150378799 1
< 0.1%
127.599306385 1
< 0.1%
127.5149949519 2
0.1%
127.4983500155 1
< 0.1%
127.4941038337 1
< 0.1%
127.4936968475 1
< 0.1%

시설면적
Real number (ℝ)

HIGH CORRELATION 

Distinct3021
Distinct (%)86.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10934.749
Minimum31
Maximum243000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.7 KiB
2024-05-03T19:17:41.691332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31
5-th percentile293
Q11880
median5610
Q313362.75
95-th percentile37941
Maximum243000
Range242969
Interquartile range (IQR)11482.75

Descriptive statistics

Standard deviation16471.191
Coefficient of variation (CV)1.5063163
Kurtosis38.331385
Mean10934.749
Median Absolute Deviation (MAD)4368.5
Skewness4.7569529
Sum38009187
Variance2.7130012 × 108
MonotonicityNot monotonic
2024-05-03T19:17:42.222753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
660.0 15
 
0.4%
330.0 11
 
0.3%
165.0 9
 
0.3%
990.0 8
 
0.2%
264.0 8
 
0.2%
200.0 7
 
0.2%
2645.0 6
 
0.2%
1200.0 6
 
0.2%
133.0 5
 
0.1%
198.0 5
 
0.1%
Other values (3011) 3396
97.7%
ValueCountFrequency (%)
31.0 1
< 0.1%
38.0 1
< 0.1%
50.0 1
< 0.1%
55.0 1
< 0.1%
65.0 1
< 0.1%
66.0 1
< 0.1%
67.0 1
< 0.1%
69.0 1
< 0.1%
71.0 2
0.1%
72.0 1
< 0.1%
ValueCountFrequency (%)
243000.0 1
< 0.1%
220239.0 1
< 0.1%
187681.0 1
< 0.1%
178867.0 1
< 0.1%
161227.0 1
< 0.1%
155236.0 1
< 0.1%
150574.0 1
< 0.1%
134078.0 1
< 0.1%
126910.0 1
< 0.1%
126849.0 1
< 0.1%

수용인원수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct2986
Distinct (%)85.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12397.341
Minimum0
Maximum294545
Zeros56
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size30.7 KiB
2024-05-03T19:17:42.652038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile209
Q12020.75
median6363
Q314830.5
95-th percentile43603
Maximum294545
Range294545
Interquartile range (IQR)12809.75

Descriptive statistics

Standard deviation19276.91
Coefficient of variation (CV)1.5549229
Kurtosis44.286939
Mean12397.341
Median Absolute Deviation (MAD)4949
Skewness5.1272879
Sum43093159
Variance3.7159927 × 108
MonotonicityNot monotonic
2024-05-03T19:17:43.169927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 56
 
1.6%
400 13
 
0.4%
800 13
 
0.4%
1200 7
 
0.2%
320 7
 
0.2%
3206 7
 
0.2%
200 6
 
0.2%
93 5
 
0.1%
480 5
 
0.1%
6932 5
 
0.1%
Other values (2976) 3352
96.4%
ValueCountFrequency (%)
0 56
1.6%
38 1
 
< 0.1%
46 1
 
< 0.1%
61 1
 
< 0.1%
67 1
 
< 0.1%
69 4
 
0.1%
70 1
 
< 0.1%
80 2
 
0.1%
81 2
 
0.1%
84 2
 
0.1%
ValueCountFrequency (%)
294545 1
< 0.1%
266956 1
< 0.1%
227492 1
< 0.1%
216808 1
< 0.1%
195426 1
< 0.1%
188165 1
< 0.1%
182513 1
< 0.1%
162518 1
< 0.1%
153830 1
< 0.1%
153756 1
< 0.1%

개방여부
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
True
3279 
False
 
197
ValueCountFrequency (%)
True 3279
94.3%
False 197
 
5.7%
2024-05-03T19:17:43.564276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

관련정보
Text

MISSING 

Distinct77
Distinct (%)2.6%
Missing488
Missing (%)14.0%
Memory size27.3 KiB
2024-05-03T19:17:43.959271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length3
Mean length3.9919679
Min length2

Characters and Unicode

Total characters11928
Distinct characters99
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)1.1%

Sample

1st row지하주차장
2nd row지하주차장
3rd row지하주차장
4th row지하주차장
5th row지하주차장
ValueCountFrequency (%)
주차장 1216
38.7%
지하주차장 902
28.7%
주거시설 281
 
8.9%
주자창 252
 
8.0%
아파트 111
 
3.5%
지하시설 26
 
0.8%
체육시설 26
 
0.8%
공동작업장 22
 
0.7%
등 22
 
0.7%
관공서 21
 
0.7%
Other values (67) 265
 
8.4%
2024-05-03T19:17:44.844312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 2652
22.2%
장 2173
18.2%
차 2120
17.8%
지 978
 
8.2%
하 973
 
8.2%
시 402
 
3.4%
설 401
 
3.4%
거 281
 
2.4%
창 275
 
2.3%
자 253
 
2.1%
Other values (89) 1420
11.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11724
98.3%
Space Separator 156
 
1.3%
Other Punctuation 24
 
0.2%
Open Punctuation 12
 
0.1%
Close Punctuation 12
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 2652
22.6%
장 2173
18.5%
차 2120
18.1%
지 978
 
8.3%
하 973
 
8.3%
시 402
 
3.4%
설 401
 
3.4%
거 281
 
2.4%
창 275
 
2.3%
자 253
 
2.2%
Other values (85) 1216
10.4%
Space Separator
ValueCountFrequency (%)
156
100.0%
Other Punctuation
ValueCountFrequency (%)
, 24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11724
98.3%
Common 204
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 2652
22.6%
장 2173
18.5%
차 2120
18.1%
지 978
 
8.3%
하 973
 
8.3%
시 402
 
3.4%
설 401
 
3.4%
거 281
 
2.4%
창 275
 
2.3%
자 253
 
2.2%
Other values (85) 1216
10.4%
Common
ValueCountFrequency (%)
156
76.5%
, 24
 
11.8%
( 12
 
5.9%
) 12
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11724
98.3%
ASCII 204
 
1.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 2652
22.6%
장 2173
18.5%
차 2120
18.1%
지 978
 
8.3%
하 973
 
8.3%
시 402
 
3.4%
설 401
 
3.4%
거 281
 
2.4%
창 275
 
2.3%
자 253
 
2.2%
Other values (85) 1216
10.4%
ASCII
ValueCountFrequency (%)
156
76.5%
, 24
 
11.8%
( 12
 
5.9%
) 12
 
5.9%

관리기관전화번호
Text

MISSING 

Distinct506
Distinct (%)20.0%
Missing943
Missing (%)27.1%
Memory size27.3 KiB
2024-05-03T19:17:45.668441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.194236
Min length11

Characters and Unicode

Total characters30888
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique325 ?
Unique (%)12.8%

Sample

1st row031-8075-7921
2nd row031-8075-7921
3rd row031-8075-7703
4th row031-8075-7703
5th row031-8075-7703
ValueCountFrequency (%)
031-228-2164 280
 
11.1%
031-481-2164 155
 
6.1%
031-760-4612 103
 
4.1%
031-828-4984 103
 
4.1%
031-8024-4943 97
 
3.8%
031-345-2913 87
 
3.4%
031-390-0314 79
 
3.1%
031-550-2166 56
 
2.2%
031-678-2982 49
 
1.9%
031-8075-5849 26
 
1.0%
Other values (496) 1498
59.1%
2024-05-03T19:17:47.184173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 5066
16.4%
0 4091
13.2%
3 3923
12.7%
1 3812
12.3%
8 2802
9.1%
2 2604
8.4%
4 2500
8.1%
6 1844
 
6.0%
7 1666
 
5.4%
9 1322
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 25822
83.6%
Dash Punctuation 5066
 
16.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4091
15.8%
3 3923
15.2%
1 3812
14.8%
8 2802
10.9%
2 2604
10.1%
4 2500
9.7%
6 1844
7.1%
7 1666
6.5%
9 1322
 
5.1%
5 1258
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 5066
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30888
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 5066
16.4%
0 4091
13.2%
3 3923
12.7%
1 3812
12.3%
8 2802
9.1%
2 2604
8.4%
4 2500
8.1%
6 1844
 
6.0%
7 1666
 
5.4%
9 1322
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30888
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 5066
16.4%
0 4091
13.2%
3 3923
12.7%
1 3812
12.3%
8 2802
9.1%
2 2604
8.4%
4 2500
8.1%
6 1844
 
6.0%
7 1666
 
5.4%
9 1322
 
4.3%

관리기관명
Text

Distinct237
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
2024-05-03T19:17:47.879962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length23
Mean length6.9148446
Min length3

Characters and Unicode

Total characters24036
Distinct characters222
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

Unique109 ?
Unique (%)3.1%

Sample

1st row북 면
2nd row북 면
3rd row가평읍
4th row가평읍
5th row가평읍
ValueCountFrequency (%)
경기도 1430
25.8%
관리사무소 289
 
5.2%
수원시청 280
 
5.0%
부천시 226
 
4.1%
화성시 171
 
3.1%
덕양구 163
 
2.9%
파주시청 158
 
2.8%
안산시 155
 
2.8%
분당구청 139
 
2.5%
일산서구 132
 
2.4%
Other values (253) 2407
43.4%
2024-05-03T19:17:49.025764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 2106
 
8.8%
2082
 
8.7%
도 1449
 
6.0%
청 1445
 
6.0%
기 1437
 
6.0%
경 1431
 
6.0%
동 980
 
4.1%
구 750
 
3.1%
천 518
 
2.2%
산 512
 
2.1%
Other values (212) 11326
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21466
89.3%
Space Separator 2082
 
8.7%
Decimal Number 361
 
1.5%
Close Punctuation 54
 
0.2%
Open Punctuation 54
 
0.2%
Uppercase Letter 13
 
0.1%
Lowercase Letter 4
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 2106
 
9.8%
도 1449
 
6.8%
청 1445
 
6.7%
기 1437
 
6.7%
경 1431
 
6.7%
동 980
 
4.6%
구 750
 
3.5%
천 518
 
2.4%
산 512
 
2.4%
주 505
 
2.4%
Other values (190) 10333
48.1%
Decimal Number
ValueCountFrequency (%)
1 152
42.1%
2 135
37.4%
3 63
17.5%
6 3
 
0.8%
5 2
 
0.6%
4 2
 
0.6%
7 1
 
0.3%
8 1
 
0.3%
9 1
 
0.3%
0 1
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
C 2
15.4%
H 2
15.4%
L 2
15.4%
P 2
15.4%
T 2
15.4%
A 2
15.4%
K 1
7.7%
Space Separator
ValueCountFrequency (%)
2082
100.0%
Close Punctuation
ValueCountFrequency (%)
) 54
100.0%
Open Punctuation
ValueCountFrequency (%)
( 54
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21466
89.3%
Common 2553
 
10.6%
Latin 17
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 2106
 
9.8%
도 1449
 
6.8%
청 1445
 
6.7%
기 1437
 
6.7%
경 1431
 
6.7%
동 980
 
4.6%
구 750
 
3.5%
천 518
 
2.4%
산 512
 
2.4%
주 505
 
2.4%
Other values (190) 10333
48.1%
Common
ValueCountFrequency (%)
2082
81.6%
1 152
 
6.0%
2 135
 
5.3%
3 63
 
2.5%
) 54
 
2.1%
( 54
 
2.1%
6 3
 
0.1%
- 2
 
0.1%
5 2
 
0.1%
4 2
 
0.1%
Other values (4) 4
 
0.2%
Latin
ValueCountFrequency (%)
e 4
23.5%
C 2
11.8%
H 2
11.8%
L 2
11.8%
P 2
11.8%
T 2
11.8%
A 2
11.8%
K 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21466
89.3%
ASCII 2570
 
10.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 2106
 
9.8%
도 1449
 
6.8%
청 1445
 
6.7%
기 1437
 
6.7%
경 1431
 
6.7%
동 980
 
4.6%
구 750
 
3.5%
천 518
 
2.4%
산 512
 
2.4%
주 505
 
2.4%
Other values (190) 10333
48.1%
ASCII
ValueCountFrequency (%)
2082
81.0%
1 152
 
5.9%
2 135
 
5.3%
3 63
 
2.5%
) 54
 
2.1%
( 54
 
2.1%
e 4
 
0.2%
6 3
 
0.1%
C 2
 
0.1%
H 2
 
0.1%
Other values (12) 19
 
0.7%

데이터기준일자
Date

Distinct24
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
Minimum2018-06-25 00:00:00
Maximum2024-04-26 00:00:00
2024-05-03T19:17:49.592803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:17:50.017052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)

Interactions

2024-05-03T19:17:28.667150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:17:25.282566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:17:26.359313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:17:27.557363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:17:28.948602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:17:25.517642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:17:26.658386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:17:27.843141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:17:29.318458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:17:25.729604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:17:26.963637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:17:28.134534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:17:29.659710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:17:26.023733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:17:27.297558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:17:28.397719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-03T19:17:50.410505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설구분명정제WGS84위도정제WGS84경도시설면적수용인원수개방여부관련정보데이터기준일자
시설구분명1.0000.2330.4900.0820.0840.6180.9800.452
정제WGS84위도0.2331.0000.8770.0000.0000.9540.7620.858
정제WGS84경도0.4900.8771.0000.0630.0570.4440.8260.913
시설면적0.0820.0000.0631.0000.9990.0530.0000.217
수용인원수0.0840.0000.0570.9991.0000.0490.0000.242
개방여부0.6180.9540.4440.0530.0491.0000.9170.899
관련정보0.9800.7620.8260.0000.0000.9171.0000.933
데이터기준일자0.4520.8580.9130.2170.2420.8990.9331.000
2024-05-03T19:17:50.865776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설구분명개방여부
시설구분명1.0000.424
개방여부0.4241.000
2024-05-03T19:17:51.203311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정제WGS84위도정제WGS84경도시설면적수용인원수시설구분명개방여부
정제WGS84위도1.000-0.410-0.012-0.0080.1780.814
정제WGS84경도-0.4101.0000.1220.1160.3770.340
시설면적-0.0120.1221.0000.9480.0820.053
수용인원수-0.0080.1160.9481.0000.0840.049
시설구분명0.1780.3770.0820.0841.0000.424
개방여부0.8140.3400.0530.0490.4241.000

Missing values

2024-05-03T19:17:30.165404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-03T19:17:31.026814image/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.
2024-05-03T19:17:31.451378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시설명시설구분명정제도로명주소정제지번주소정제WGS84위도정제WGS84경도시설면적수용인원수개방여부관련정보관리기관전화번호관리기관명데이터기준일자
0목동초등학교공공용<NA><NA><NA><NA>472.0572Y<NA><NA>북 면2024-02-26
1북면우체국공공용<NA><NA><NA><NA>163.0198Y<NA><NA>북 면2024-02-26
2태광아파트(101동)(지하1층주차장)공공용<NA><NA><NA><NA>1110.01345Y<NA><NA>가평읍2024-02-26
3태광아파트(102동)(지하1층주차장)공공용<NA><NA><NA><NA>1230.01490Y<NA><NA>가평읍2024-02-26
4대현빌라트(지하 1층 주차장)공공용<NA><NA><NA><NA>538.0652Y<NA><NA>가평읍2024-02-26
5가평군청(지하식당)공공용<NA><NA><NA><NA>169.0204Y<NA><NA>가평읍2024-02-26
6선힐아파트(지하 1층 주차장)공공용<NA><NA><NA><NA>2830.03430Y<NA><NA>가평읍2024-02-26
7에이원파란채아파트(지하 1층 주차장)공공용<NA><NA><NA><NA>2763.03349Y<NA><NA>가평읍2024-02-26
8우림필유아파트(지하1층 주차장)공공용<NA><NA><NA><NA>971.01176Y<NA><NA>가평읍2024-02-26
9휴먼시아아파트(지하1층 주차장)공공용<NA><NA><NA><NA>6250.07575Y<NA><NA>가평읍2024-02-26
시설명시설구분명정제도로명주소정제지번주소정제WGS84위도정제WGS84경도시설면적수용인원수개방여부관련정보관리기관전화번호관리기관명데이터기준일자
3466서봉마을 사랑으로 부영3단지 지하주차장 1층공공용<NA><NA><NA><NA>36337.044044Y주거시설<NA>화성시2023-08-28
3467서봉마을 모아엘가 지하주차장 1층공공용<NA><NA><NA><NA>20515.024866Y주거시설<NA>화성시2023-08-28
3468오색마을 사랑으로 부영9단지 지하주차장 1층공공용<NA><NA><NA><NA>21481.026037Y주거시설<NA>화성시2023-08-28
3469오색마을 사랑으로 부영10단지 지하주차장 1층공공용<NA><NA><NA><NA>31979.038762Y주거시설<NA>화성시2023-08-28
3470오색마을 사랑으로 부영11단지 지하주차장 1층공공용<NA><NA><NA><NA>36568.044324Y주거시설<NA>화성시2023-08-28
3471동탄센트럴자이아파트 지하주차장 1층공공용<NA><NA><NA><NA>22778.027609Y주거시설<NA>화성시2023-08-28
3472시범우남퍼스트빌 지하주차장 1층공공용<NA><NA><NA><NA>54785.066406Y주거시설<NA>화성시2023-08-28
3473동탄능동마을 주공아파트(지하주차장 1층)(7-1단지)공공용<NA><NA><NA><NA>2833.03433Y주거시설<NA>화성시2023-08-28
3474시범계룡리슈빌아파트 지하주차장 1층공공용<NA><NA><NA><NA>24688.029924Y주거시설<NA>화성시2023-08-28
3475시범예미지아파트 지하주차장 1층공공용<NA><NA><NA><NA>23718.028749Y주거시설<NA>화성시2023-08-28