Overview

Dataset statistics

Number of variables9
Number of observations92
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.8 KiB
Average record size in memory75.4 B

Variable types

Text4
Numeric2
DateTime3

Dataset

Description오산시에 위치한 공동주택 현황으로 아파트명, 도로명주소, 동수, 세대수, 사업승인일, 사용검사일, 전화번호, 팩스 항목 정보를 제공하고 있습니다.
Author경기도 오산시
URLhttps://www.data.go.kr/data/3082160/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
동수 is highly overall correlated with 세대수 High correlation
세대수 is highly overall correlated with 동수High correlation
아파트명 has unique valuesUnique
도로명주소 has unique valuesUnique
전화번호 has unique valuesUnique
팩스(FAX) has unique valuesUnique

Reproduction

Analysis started2023-12-12 08:24:16.927263
Analysis finished2023-12-12 08:24:18.730920
Duration1.8 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

UNIQUE 

Distinct92
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size868.0 B
2023-12-12T17:24:18.944543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length14
Mean length8.173913
Min length2

Characters and Unicode

Total characters752
Distinct characters165
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique92 ?
Unique (%)100.0%

Sample

1st row은계주공
2nd row원동주공
3rd row수청주공
4th row가수주공
5th row한주
ValueCountFrequency (%)
원동e-편한세상 2
 
1.9%
은계주공 1
 
0.9%
금암마을데시앙6단지(c-3bl 1
 
0.9%
잔다리마을1단지(b-1bl 1
 
0.9%
힐스테이트 1
 
0.9%
원동 1
 
0.9%
오산청호1단지 1
 
0.9%
죽미마을9단지(b-3bl 1
 
0.9%
죽미마을꿈에그린11단지(c-1bl 1
 
0.9%
물향기마을꿈에그린13단지(c-4bl 1
 
0.9%
Other values (95) 95
89.6%
2023-12-12T17:24:19.370147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 33
 
4.4%
단 30
 
4.0%
오 25
 
3.3%
1 23
 
3.1%
산 22
 
2.9%
B 20
 
2.7%
( 20
 
2.7%
) 20
 
2.7%
마 18
 
2.4%
- 17
 
2.3%
Other values (155) 524
69.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 558
74.2%
Decimal Number 66
 
8.8%
Uppercase Letter 52
 
6.9%
Open Punctuation 20
 
2.7%
Close Punctuation 20
 
2.7%
Dash Punctuation 17
 
2.3%
Space Separator 14
 
1.9%
Lowercase Letter 3
 
0.4%
Other Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 33
 
5.9%
단 30
 
5.4%
오 25
 
4.5%
산 22
 
3.9%
마 18
 
3.2%
이 16
 
2.9%
을 15
 
2.7%
암 14
 
2.5%
주 14
 
2.5%
세 13
 
2.3%
Other values (129) 358
64.2%
Decimal Number
ValueCountFrequency (%)
1 23
34.8%
2 17
25.8%
3 7
 
10.6%
4 5
 
7.6%
6 4
 
6.1%
7 3
 
4.5%
5 3
 
4.5%
9 2
 
3.0%
0 1
 
1.5%
8 1
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
B 20
38.5%
L 15
28.8%
A 8
 
15.4%
C 3
 
5.8%
K 2
 
3.8%
S 1
 
1.9%
R 1
 
1.9%
P 1
 
1.9%
I 1
 
1.9%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
' 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Space Separator
ValueCountFrequency (%)
14
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 558
74.2%
Common 139
 
18.5%
Latin 55
 
7.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 33
 
5.9%
단 30
 
5.4%
오 25
 
4.5%
산 22
 
3.9%
마 18
 
3.2%
이 16
 
2.9%
을 15
 
2.7%
암 14
 
2.5%
주 14
 
2.5%
세 13
 
2.3%
Other values (129) 358
64.2%
Common
ValueCountFrequency (%)
1 23
16.5%
( 20
14.4%
) 20
14.4%
- 17
12.2%
2 17
12.2%
14
10.1%
3 7
 
5.0%
4 5
 
3.6%
6 4
 
2.9%
7 3
 
2.2%
Other values (6) 9
 
6.5%
Latin
ValueCountFrequency (%)
B 20
36.4%
L 15
27.3%
A 8
 
14.5%
e 3
 
5.5%
C 3
 
5.5%
K 2
 
3.6%
S 1
 
1.8%
R 1
 
1.8%
P 1
 
1.8%
I 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 558
74.2%
ASCII 194
 
25.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 33
 
5.9%
단 30
 
5.4%
오 25
 
4.5%
산 22
 
3.9%
마 18
 
3.2%
이 16
 
2.9%
을 15
 
2.7%
암 14
 
2.5%
주 14
 
2.5%
세 13
 
2.3%
Other values (129) 358
64.2%
ASCII
ValueCountFrequency (%)
1 23
11.9%
B 20
10.3%
( 20
10.3%
) 20
10.3%
- 17
8.8%
2 17
8.8%
L 15
7.7%
14
7.2%
A 8
 
4.1%
3 7
 
3.6%
Other values (16) 33
17.0%

도로명주소
Text

UNIQUE 

Distinct92
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size868.0 B
2023-12-12T17:24:19.703870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length26
Mean length21.978261
Min length18

Characters and Unicode

Total characters2022
Distinct characters79
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique92 ?
Unique (%)100.0%

Sample

1st row경기도 오산시 은여울로43번길 16 (은계동)
2nd row경기도 오산시 밀머리로1번길 3 (원동)
3rd row경기도 오산시 내삼미로 40 (수청동)
4th row경기도 오산시 발안로 1419-13 (가수동)
5th row경기도 오산시 동부대로 429-9 (원동)
ValueCountFrequency (%)
경기도 92
20.1%
오산시 92
20.1%
원동 20
 
4.4%
금암동 10
 
2.2%
수청로 9
 
2.0%
경기대로 8
 
1.7%
운암로 7
 
1.5%
수청동 7
 
1.5%
갈곶동 7
 
1.5%
오산동 6
 
1.3%
Other values (138) 200
43.7%
2023-12-12T17:24:20.152881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
366
18.1%
산 123
 
6.1%
오 107
 
5.3%
경 102
 
5.0%
기 102
 
5.0%
동 95
 
4.7%
시 93
 
4.6%
도 92
 
4.5%
로 91
 
4.5%
) 91
 
4.5%
Other values (69) 760
37.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1156
57.2%
Space Separator 366
 
18.1%
Decimal Number 292
 
14.4%
Close Punctuation 91
 
4.5%
Open Punctuation 91
 
4.5%
Dash Punctuation 25
 
1.2%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 123
10.6%
오 107
 
9.3%
경 102
 
8.8%
기 102
 
8.8%
동 95
 
8.2%
시 93
 
8.0%
도 92
 
8.0%
로 91
 
7.9%
원 28
 
2.4%
수 26
 
2.2%
Other values (54) 297
25.7%
Decimal Number
ValueCountFrequency (%)
1 64
21.9%
2 41
14.0%
3 31
10.6%
4 29
9.9%
0 25
 
8.6%
9 24
 
8.2%
5 23
 
7.9%
6 20
 
6.8%
7 19
 
6.5%
8 16
 
5.5%
Space Separator
ValueCountFrequency (%)
366
100.0%
Close Punctuation
ValueCountFrequency (%)
) 91
100.0%
Open Punctuation
ValueCountFrequency (%)
( 91
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1156
57.2%
Common 866
42.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 123
10.6%
오 107
 
9.3%
경 102
 
8.8%
기 102
 
8.8%
동 95
 
8.2%
시 93
 
8.0%
도 92
 
8.0%
로 91
 
7.9%
원 28
 
2.4%
수 26
 
2.2%
Other values (54) 297
25.7%
Common
ValueCountFrequency (%)
366
42.3%
) 91
 
10.5%
( 91
 
10.5%
1 64
 
7.4%
2 41
 
4.7%
3 31
 
3.6%
4 29
 
3.3%
- 25
 
2.9%
0 25
 
2.9%
9 24
 
2.8%
Other values (5) 79
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1156
57.2%
ASCII 866
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
366
42.3%
) 91
 
10.5%
( 91
 
10.5%
1 64
 
7.4%
2 41
 
4.7%
3 31
 
3.6%
4 29
 
3.3%
- 25
 
2.9%
0 25
 
2.9%
9 24
 
2.8%
Other values (5) 79
 
9.1%
Hangul
ValueCountFrequency (%)
산 123
10.6%
오 107
 
9.3%
경 102
 
8.8%
기 102
 
8.8%
동 95
 
8.2%
시 93
 
8.0%
도 92
 
8.0%
로 91
 
7.9%
원 28
 
2.4%
수 26
 
2.2%
Other values (54) 297
25.7%

동수
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)23.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.8586957
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size960.0 B
2023-12-12T17:24:20.293976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median8.5
Q312
95-th percentile18.45
Maximum30
Range29
Interquartile range (IQR)8

Descriptive statistics

Standard deviation5.5994143
Coefficient of variation (CV)0.63208112
Kurtosis1.2644403
Mean8.8586957
Median Absolute Deviation (MAD)4
Skewness0.86857645
Sum815
Variance31.35344
MonotonicityNot monotonic
2023-12-12T17:24:20.425659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
10 11
12.0%
14 7
 
7.6%
4 7
 
7.6%
1 7
 
7.6%
5 7
 
7.6%
8 7
 
7.6%
3 6
 
6.5%
12 5
 
5.4%
7 5
 
5.4%
9 5
 
5.4%
Other values (12) 25
27.2%
ValueCountFrequency (%)
1 7
7.6%
2 4
 
4.3%
3 6
6.5%
4 7
7.6%
5 7
7.6%
6 3
 
3.3%
7 5
5.4%
8 7
7.6%
9 5
5.4%
10 11
12.0%
ValueCountFrequency (%)
30 1
 
1.1%
23 1
 
1.1%
21 1
 
1.1%
20 1
 
1.1%
19 1
 
1.1%
18 2
 
2.2%
16 3
3.3%
15 1
 
1.1%
14 7
7.6%
13 4
4.3%

세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct87
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean721.97826
Minimum164
Maximum2400
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size960.0 B
2023-12-12T17:24:20.558444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum164
5-th percentile174.4
Q1383
median655
Q31011.75
95-th percentile1488.7
Maximum2400
Range2236
Interquartile range (IQR)628.75

Descriptive statistics

Standard deviation439.688
Coefficient of variation (CV)0.60900449
Kurtosis1.8581351
Mean721.97826
Median Absolute Deviation (MAD)306.5
Skewness1.1055687
Sum66422
Variance193325.54
MonotonicityNot monotonic
2023-12-12T17:24:20.675205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1060 2
 
2.2%
168 2
 
2.2%
498 2
 
2.2%
1023 2
 
2.2%
320 2
 
2.2%
1167 1
 
1.1%
1071 1
 
1.1%
297 1
 
1.1%
580 1
 
1.1%
412 1
 
1.1%
Other values (77) 77
83.7%
ValueCountFrequency (%)
164 1
1.1%
168 2
2.2%
169 1
1.1%
170 1
1.1%
178 1
1.1%
191 1
1.1%
192 1
1.1%
198 1
1.1%
208 1
1.1%
211 1
1.1%
ValueCountFrequency (%)
2400 1
1.1%
2050 1
1.1%
1755 1
1.1%
1651 1
1.1%
1646 1
1.1%
1360 1
1.1%
1275 1
1.1%
1262 1
1.1%
1186 1
1.1%
1179 1
1.1%

사업승인일
Date

Distinct81
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Memory size868.0 B
Minimum1985-09-25 00:00:00
Maximum2020-11-24 00:00:00
2023-12-12T17:24:20.794945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:24:20.912052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사용검사일
Date

Distinct87
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Memory size868.0 B
Minimum1987-03-31 00:00:00
Maximum2023-06-30 00:00:00
2023-12-12T17:24:21.024211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:24:21.135923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

전화번호
Text

UNIQUE 

Distinct92
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size868.0 B
2023-12-12T17:24:21.664142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.01087
Min length12

Characters and Unicode

Total characters1105
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

Unique92 ?
Unique (%)100.0%

Sample

1st row031-374-3592
2nd row031-373-2629
3rd row031-373-4233
4th row031-372-8581
5th row031-375-3407
ValueCountFrequency (%)
031-374-3592 1
 
1.1%
031-372-3690 1
 
1.1%
031-611-3870 1
 
1.1%
031-372-0351 1
 
1.1%
031-373-5530 1
 
1.1%
031-377-5062 1
 
1.1%
031-373-9786 1
 
1.1%
031-375-1230 1
 
1.1%
031-372-1062 1
 
1.1%
031-378-3442 1
 
1.1%
Other values (82) 82
89.1%
2023-12-12T17:24:22.102443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 236
21.4%
- 184
16.7%
0 135
12.2%
7 134
12.1%
1 133
12.0%
8 57
 
5.2%
2 52
 
4.7%
6 49
 
4.4%
5 48
 
4.3%
4 44
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 921
83.3%
Dash Punctuation 184
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 236
25.6%
0 135
14.7%
7 134
14.5%
1 133
14.4%
8 57
 
6.2%
2 52
 
5.6%
6 49
 
5.3%
5 48
 
5.2%
4 44
 
4.8%
9 33
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 184
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1105
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 236
21.4%
- 184
16.7%
0 135
12.2%
7 134
12.1%
1 133
12.0%
8 57
 
5.2%
2 52
 
4.7%
6 49
 
4.4%
5 48
 
4.3%
4 44
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1105
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 236
21.4%
- 184
16.7%
0 135
12.2%
7 134
12.1%
1 133
12.0%
8 57
 
5.2%
2 52
 
4.7%
6 49
 
4.4%
5 48
 
4.3%
4 44
 
4.0%

팩스(FAX)
Text

UNIQUE 

Distinct92
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size868.0 B
2023-12-12T17:24:22.377919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.01087
Min length12

Characters and Unicode

Total characters1105
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

Unique92 ?
Unique (%)100.0%

Sample

1st row031-375-3592
2nd row031-377-2629
3rd row031-372-2033
4th row031-377-8586
5th row031-374-3409
ValueCountFrequency (%)
031-375-3592 1
 
1.1%
031-375-3690 1
 
1.1%
031-611-3869 1
 
1.1%
031-372-0352 1
 
1.1%
031-373-5513 1
 
1.1%
031-377-5063 1
 
1.1%
031-373-9787 1
 
1.1%
031-375-1290 1
 
1.1%
031-372-1063 1
 
1.1%
031-378-3443 1
 
1.1%
Other values (82) 82
89.1%
2023-12-12T17:24:22.848719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 233
21.1%
- 184
16.7%
7 131
11.9%
0 127
11.5%
1 125
11.3%
8 60
 
5.4%
6 54
 
4.9%
5 52
 
4.7%
2 51
 
4.6%
9 47
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 921
83.3%
Dash Punctuation 184
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 233
25.3%
7 131
14.2%
0 127
13.8%
1 125
13.6%
8 60
 
6.5%
6 54
 
5.9%
5 52
 
5.6%
2 51
 
5.5%
9 47
 
5.1%
4 41
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 184
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1105
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 233
21.1%
- 184
16.7%
7 131
11.9%
0 127
11.5%
1 125
11.3%
8 60
 
5.4%
6 54
 
4.9%
5 52
 
4.7%
2 51
 
4.6%
9 47
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1105
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 233
21.1%
- 184
16.7%
7 131
11.9%
0 127
11.5%
1 125
11.3%
8 60
 
5.4%
6 54
 
4.9%
5 52
 
4.7%
2 51
 
4.6%
9 47
 
4.3%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size868.0 B
Minimum2023-11-13 00:00:00
Maximum2023-11-13 00:00:00
2023-12-12T17:24:22.973418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:24:23.067093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T17:24:18.245403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:24:18.027095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:24:18.353766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:24:18.139345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:24:23.148376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
아파트명도로명주소동수세대수사업승인일사용검사일전화번호팩스(FAX)
아파트명1.0001.0001.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.0001.0001.000
동수1.0001.0001.0000.8390.8380.8671.0001.000
세대수1.0001.0000.8391.0000.8860.0001.0001.000
사업승인일1.0001.0000.8380.8861.0000.9951.0001.000
사용검사일1.0001.0000.8670.0000.9951.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.000
팩스(FAX)1.0001.0001.0001.0001.0001.0001.0001.000
2023-12-12T17:24:23.268329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동수세대수
동수1.0000.847
세대수0.8471.000

Missing values

2023-12-12T17:24:18.522518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:24:18.675359image/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

아파트명도로명주소동수세대수사업승인일사용검사일전화번호팩스(FAX)데이터기준일자
0은계주공경기도 오산시 은여울로43번길 16 (은계동)124601985-09-251987-03-31031-374-3592031-375-35922023-11-13
1원동주공경기도 오산시 밀머리로1번길 3 (원동)83201987-11-101988-10-09031-373-2629031-377-26292023-11-13
2수청주공경기도 오산시 내삼미로 40 (수청동)83101987-12-291989-05-24031-373-4233031-372-20332023-11-13
3가수주공경기도 오산시 발안로 1419-13 (가수동)166201989-01-241990-10-05031-372-8581031-377-85862023-11-13
4한주경기도 오산시 동부대로 429-9 (원동)42991990-09-281992-04-16031-375-3407031-374-34092023-11-13
5삼익경기도 오산시 박동길 8 (수청동)22201990-08-181992-11-05031-375-5360031-375-53802023-11-13
6대우(1,2차)경기도 오산시 청학로173번길 9, 12 (수청동)1611441992-01-291993-10-14031-374-6798031-374-67952023-11-13
7신양경기도 오산시 대원로 47 (원동)11701993-08-231995-06-08031-373-8710031-375-87102023-11-13
8신동아(1차)경기도 오산시 초평로 35 (서동)34981993-02-251995-08-26031-374-5329031-372-53292023-11-13
9신현대경기도 오산시 현충로72번길 41 (은계동)11641993-11-111996-08-01031-375-3770031-375-37412023-11-13
아파트명도로명주소동수세대수사업승인일사용검사일전화번호팩스(FAX)데이터기준일자
82오산세교2 엘에이치12단지경기도 오산시 가수행복로 55-5 (가수동)711362017-01-122019-01-30031-375-6648031-375-66492023-11-13
83오산청학행복주택경기도 오산시 대호로 39 (청학동)21782016-02-012019-02-01031-378-5350031-378-53492023-11-13
84오산원동한양수자인경기도 오산시 부원로87번길 19 (원동)44952016-04-182019-06-07031-372-5781031-372-57852023-11-13
85서동탄역더샵파크시티경기도 오산시 문시로 183-19 (외삼미동)1824002016-09-092019-07-30031-375-0080031-375-00812023-11-13
86오산시티자이2차경기도 오산시 부산중앙로 42 (부산동)1010902017-01-032019-10-25031-8077-9264031-8077-92652023-11-13
87더샵오산센트럴경기도 오산시 내삼미로 65 (수청동)85962018-04-242020-07-24031-378-8935031-378-89372023-11-13
88오산세교2엘에이치21단지경기도 오산시 초평중앙로 15 (탑동)36942019-06-292022-03-22031-374-9962031-374-99632023-11-13
89오산역 영무 파라드경기도 오산시 오산로198번길 32 (원동)44042017-12-182022-05-25031-377-8864031-377-88652023-11-13
90호반써밋라테라스경기도 오산시 수청로 13(수청동)102082020-11-242023-04-06031-375-0558031-375-05592023-11-13
91호반써밋라포레경기도 오산시 죽담로 108(궐동)98672019-03-292023-06-30031-376-7258031-375-72592023-11-13