Overview

Dataset statistics

Number of variables9
Number of observations111
Missing cells18
Missing cells (%)1.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.4 KiB
Average record size in memory77.2 B

Variable types

Text2
Numeric4
Boolean1
DateTime2

Dataset

Description대전광역시 대덕구 행정기관 데이터로 대덕구의 공동주택 현황(명칭, 주소, 엘리베이터 유/무, 세대수 등)의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15013602/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
동수 is highly overall correlated with 세대수 and 1 other fieldsHigh correlation
층수 is highly overall correlated with 세대수 and 2 other fieldsHigh correlation
세대수 is highly overall correlated with 동수 and 2 other fieldsHigh correlation
대지면적 is highly overall correlated with 동수 and 2 other fieldsHigh correlation
엘리베이터 설치 is highly overall correlated with 층수High correlation
대지면적 has 18 (16.2%) missing valuesMissing

Reproduction

Analysis started2023-12-12 00:16:21.749428
Analysis finished2023-12-12 00:16:23.480141
Duration1.73 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트단지명
Text

Distinct95
Distinct (%)85.6%
Missing0
Missing (%)0.0%
Memory size1020.0 B
2023-12-12T09:16:23.701435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length4.3513514
Min length2

Characters and Unicode

Total characters483
Distinct characters149
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

Unique86 ?
Unique (%)77.5%

Sample

1st row금강
2nd row대화
3rd row신대화
4th row금성백조
5th row성은맨션
ValueCountFrequency (%)
삼호 4
 
3.5%
현대 4
 
3.5%
임광하이츠 3
 
2.7%
한라 3
 
2.7%
영진로얄 3
 
2.7%
흥진 2
 
1.8%
금성백조 2
 
1.8%
원창 2
 
1.8%
평화로운 2
 
1.8%
선비마을4단지 1
 
0.9%
Other values (87) 87
77.0%
2023-12-12T09:16:24.125286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 21
 
4.3%
임 12
 
2.5%
마 11
 
2.3%
금 10
 
2.1%
지 10
 
2.1%
이 10
 
2.1%
한 10
 
2.1%
을 10
 
2.1%
( 9
 
1.9%
스 9
 
1.9%
Other values (139) 371
76.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 432
89.4%
Decimal Number 17
 
3.5%
Open Punctuation 9
 
1.9%
Close Punctuation 9
 
1.9%
Dash Punctuation 6
 
1.2%
Math Symbol 6
 
1.2%
Space Separator 2
 
0.4%
Lowercase Letter 1
 
0.2%
Uppercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 21
 
4.9%
임 12
 
2.8%
마 11
 
2.5%
금 10
 
2.3%
지 10
 
2.3%
이 10
 
2.3%
한 10
 
2.3%
을 10
 
2.3%
스 9
 
2.1%
로 9
 
2.1%
Other values (126) 320
74.1%
Decimal Number
ValueCountFrequency (%)
1 6
35.3%
2 4
23.5%
3 3
17.6%
0 2
 
11.8%
4 1
 
5.9%
5 1
 
5.9%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Math Symbol
ValueCountFrequency (%)
> 6
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
K 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 432
89.4%
Common 49
 
10.1%
Latin 2
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 21
 
4.9%
임 12
 
2.8%
마 11
 
2.5%
금 10
 
2.3%
지 10
 
2.3%
이 10
 
2.3%
한 10
 
2.3%
을 10
 
2.3%
스 9
 
2.1%
로 9
 
2.1%
Other values (126) 320
74.1%
Common
ValueCountFrequency (%)
( 9
18.4%
) 9
18.4%
- 6
12.2%
> 6
12.2%
1 6
12.2%
2 4
8.2%
3 3
 
6.1%
0 2
 
4.1%
2
 
4.1%
4 1
 
2.0%
Latin
ValueCountFrequency (%)
e 1
50.0%
K 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 432
89.4%
ASCII 51
 
10.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 21
 
4.9%
임 12
 
2.8%
마 11
 
2.5%
금 10
 
2.3%
지 10
 
2.3%
이 10
 
2.3%
한 10
 
2.3%
을 10
 
2.3%
스 9
 
2.1%
로 9
 
2.1%
Other values (126) 320
74.1%
ASCII
ValueCountFrequency (%)
( 9
17.6%
) 9
17.6%
- 6
11.8%
> 6
11.8%
1 6
11.8%
2 4
7.8%
3 3
 
5.9%
0 2
 
3.9%
2
 
3.9%
e 1
 
2.0%
Other values (3) 3
 
5.9%

동수
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)17.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3153153
Minimum1
Maximum19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T09:16:24.240055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q36
95-th percentile13.5
Maximum19
Range18
Interquartile range (IQR)5

Descriptive statistics

Standard deviation4.4781936
Coefficient of variation (CV)1.0377442
Kurtosis1.4705442
Mean4.3153153
Median Absolute Deviation (MAD)1
Skewness1.5242961
Sum479
Variance20.054218
MonotonicityNot monotonic
2023-12-12T09:16:24.341850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
1 40
36.0%
2 23
20.7%
5 8
 
7.2%
4 6
 
5.4%
7 6
 
5.4%
3 5
 
4.5%
12 5
 
4.5%
6 3
 
2.7%
11 3
 
2.7%
13 2
 
1.8%
Other values (9) 10
 
9.0%
ValueCountFrequency (%)
1 40
36.0%
2 23
20.7%
3 5
 
4.5%
4 6
 
5.4%
5 8
 
7.2%
6 3
 
2.7%
7 6
 
5.4%
8 1
 
0.9%
9 2
 
1.8%
10 1
 
0.9%
ValueCountFrequency (%)
19 1
 
0.9%
18 1
 
0.9%
17 1
 
0.9%
16 1
 
0.9%
15 1
 
0.9%
14 1
 
0.9%
13 2
 
1.8%
12 5
4.5%
11 3
2.7%
10 1
 
0.9%

소재지도로명주소
Text

Distinct109
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size1020.0 B
2023-12-12T09:16:24.607164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length37
Mean length26.963964
Min length16

Characters and Unicode

Total characters2993
Distinct characters101
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

Unique107 ?
Unique (%)96.4%

Sample

1st row대전광역시 대덕구 대전로 1247 (대화동)
2nd row대전광역시 대덕구 대화로 53 (대화동)
3rd row대전광역시 대덕구 대전로 1255 (대화동)
4th row대전광역시 대덕구 대화로 19 (대화동)
5th row대전광역시 대덕구 비래동로16번길 17 (비래동)
ValueCountFrequency (%)
대전광역시 111
20.0%
대덕구 110
19.9%
비래동 19
 
3.4%
법동 11
 
2.0%
송촌동 9
 
1.6%
대화동 9
 
1.6%
신탄진동 8
 
1.4%
덕암동 8
 
1.4%
30 7
 
1.3%
오정동 6
 
1.1%
Other values (177) 256
46.2%
2023-12-12T09:16:24.977218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
456
 
15.2%
대 274
 
9.2%
덕 141
 
4.7%
동 131
 
4.4%
전 118
 
3.9%
광 111
 
3.7%
역 111
 
3.7%
시 111
 
3.7%
구 110
 
3.7%
1 106
 
3.5%
Other values (91) 1324
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1839
61.4%
Decimal Number 474
 
15.8%
Space Separator 456
 
15.2%
Open Punctuation 105
 
3.5%
Close Punctuation 105
 
3.5%
Other Punctuation 13
 
0.4%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 274
14.9%
덕 141
 
7.7%
동 131
 
7.1%
전 118
 
6.4%
광 111
 
6.0%
역 111
 
6.0%
시 111
 
6.0%
구 110
 
6.0%
로 105
 
5.7%
길 84
 
4.6%
Other values (76) 543
29.5%
Decimal Number
ValueCountFrequency (%)
1 106
22.4%
3 62
13.1%
2 62
13.1%
5 54
11.4%
4 44
9.3%
0 42
 
8.9%
6 39
 
8.2%
7 33
 
7.0%
8 23
 
4.9%
9 9
 
1.9%
Space Separator
ValueCountFrequency (%)
456
100.0%
Open Punctuation
ValueCountFrequency (%)
( 105
100.0%
Close Punctuation
ValueCountFrequency (%)
) 105
100.0%
Other Punctuation
ValueCountFrequency (%)
, 13
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1839
61.4%
Common 1154
38.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 274
14.9%
덕 141
 
7.7%
동 131
 
7.1%
전 118
 
6.4%
광 111
 
6.0%
역 111
 
6.0%
시 111
 
6.0%
구 110
 
6.0%
로 105
 
5.7%
길 84
 
4.6%
Other values (76) 543
29.5%
Common
ValueCountFrequency (%)
456
39.5%
1 106
 
9.2%
( 105
 
9.1%
) 105
 
9.1%
3 62
 
5.4%
2 62
 
5.4%
5 54
 
4.7%
4 44
 
3.8%
0 42
 
3.6%
6 39
 
3.4%
Other values (5) 79
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1839
61.4%
ASCII 1154
38.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
456
39.5%
1 106
 
9.2%
( 105
 
9.1%
) 105
 
9.1%
3 62
 
5.4%
2 62
 
5.4%
5 54
 
4.7%
4 44
 
3.8%
0 42
 
3.6%
6 39
 
3.4%
Other values (5) 79
 
6.8%
Hangul
ValueCountFrequency (%)
대 274
14.9%
덕 141
 
7.7%
동 131
 
7.1%
전 118
 
6.4%
광 111
 
6.0%
역 111
 
6.0%
시 111
 
6.0%
구 110
 
6.0%
로 105
 
5.7%
길 84
 
4.6%
Other values (76) 543
29.5%

층수
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.189189
Minimum5
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T09:16:25.091452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile5
Q15
median11
Q315
95-th percentile25
Maximum50
Range45
Interquartile range (IQR)10

Descriptive statistics

Standard deviation7.5948709
Coefficient of variation (CV)0.62308253
Kurtosis6.7726132
Mean12.189189
Median Absolute Deviation (MAD)5
Skewness2.0042319
Sum1353
Variance57.682064
MonotonicityNot monotonic
2023-12-12T09:16:25.203504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
5 30
27.0%
15 24
21.6%
14 7
 
6.3%
10 7
 
6.3%
6 6
 
5.4%
9 6
 
5.4%
20 6
 
5.4%
11 5
 
4.5%
8 3
 
2.7%
18 3
 
2.7%
Other values (10) 14
12.6%
ValueCountFrequency (%)
5 30
27.0%
6 6
 
5.4%
7 1
 
0.9%
8 3
 
2.7%
9 6
 
5.4%
10 7
 
6.3%
11 5
 
4.5%
12 1
 
0.9%
13 1
 
0.9%
14 7
 
6.3%
ValueCountFrequency (%)
50 1
 
0.9%
43 1
 
0.9%
33 1
 
0.9%
29 1
 
0.9%
25 3
 
2.7%
20 6
 
5.4%
19 1
 
0.9%
18 3
 
2.7%
17 3
 
2.7%
15 24
21.6%

엘리베이터 설치
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size243.0 B
True
81 
False
30 
ValueCountFrequency (%)
True 81
73.0%
False 30
 
27.0%
2023-12-12T09:16:25.299042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct93
Distinct (%)83.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean378.61261
Minimum18
Maximum2312
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T09:16:25.392700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile30
Q151
median150
Q3474
95-th percentile1528.5
Maximum2312
Range2294
Interquartile range (IQR)423

Descriptive statistics

Standard deviation498.51959
Coefficient of variation (CV)1.316701
Kurtosis2.9786114
Mean378.61261
Median Absolute Deviation (MAD)110
Skewness1.888436
Sum42026
Variance248521.78
MonotonicityNot monotonic
2023-12-12T09:16:25.512809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40 6
 
5.4%
49 5
 
4.5%
50 3
 
2.7%
30 3
 
2.7%
270 2
 
1.8%
150 2
 
1.8%
60 2
 
1.8%
90 2
 
1.8%
55 2
 
1.8%
66 1
 
0.9%
Other values (83) 83
74.8%
ValueCountFrequency (%)
18 1
 
0.9%
20 1
 
0.9%
23 1
 
0.9%
24 1
 
0.9%
30 3
2.7%
32 1
 
0.9%
34 1
 
0.9%
36 1
 
0.9%
40 6
5.4%
42 1
 
0.9%
ValueCountFrequency (%)
2312 1
0.9%
1872 1
0.9%
1770 1
0.9%
1757 1
0.9%
1735 1
0.9%
1554 1
0.9%
1503 1
0.9%
1488 1
0.9%
1428 1
0.9%
1344 1
0.9%

대지면적
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct88
Distinct (%)94.6%
Missing18
Missing (%)16.2%
Infinite0
Infinite (%)0.0%
Mean15626.717
Minimum805
Maximum83353
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T09:16:25.690141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum805
5-th percentile1354
Q12364
median5289
Q325520
95-th percentile59352.2
Maximum83353
Range82548
Interquartile range (IQR)23156

Descriptive statistics

Standard deviation19431.873
Coefficient of variation (CV)1.2435032
Kurtosis2.2758755
Mean15626.717
Median Absolute Deviation (MAD)3679
Skewness1.6719481
Sum1453284.7
Variance3.7759769 × 108
MonotonicityNot monotonic
2023-12-12T09:16:25.842938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2716.0 4
 
3.6%
2095.0 2
 
1.8%
12419.0 2
 
1.8%
31488.0 1
 
0.9%
20158.0 1
 
0.9%
15173.0 1
 
0.9%
21692.0 1
 
0.9%
1945.0 1
 
0.9%
40834.0 1
 
0.9%
4767.0 1
 
0.9%
Other values (78) 78
70.3%
(Missing) 18
 
16.2%
ValueCountFrequency (%)
805.0 1
0.9%
1085.0 1
0.9%
1190.0 1
0.9%
1261.0 1
0.9%
1270.0 1
0.9%
1410.0 1
0.9%
1486.0 1
0.9%
1610.0 1
0.9%
1649.0 1
0.9%
1655.0 1
0.9%
ValueCountFrequency (%)
83353.0 1
0.9%
76839.0 1
0.9%
73763.7 1
0.9%
62916.0 1
0.9%
62888.0 1
0.9%
56995.0 1
0.9%
49955.0 1
0.9%
46011.0 1
0.9%
44729.0 1
0.9%
42700.0 1
0.9%

사용검사일자
Date

Distinct110
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size1020.0 B
Minimum1978-08-04 00:00:00
Maximum2021-11-29 00:00:00
2023-12-12T09:16:26.016064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:16:26.149929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1020.0 B
Minimum2023-08-30 00:00:00
Maximum2023-08-30 00:00:00
2023-12-12T09:16:26.252971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:16:26.347526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T09:16:22.964577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:16:22.051727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:16:22.370374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:16:22.667194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:16:23.052125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:16:22.140578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:16:22.451047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:16:22.743927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:16:23.127608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:16:22.205948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:16:22.513865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:16:22.812174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:16:23.208559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:16:22.288349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:16:22.582826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:16:22.881088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:16:26.413876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
아파트단지명동수층수엘리베이터 설치세대수대지면적
아파트단지명1.0000.9040.9920.5510.9290.939
동수0.9041.0000.6220.0000.9010.920
층수0.9920.6221.0000.6870.8020.792
엘리베이터 설치0.5510.0000.6871.0000.2390.212
세대수0.9290.9010.8020.2391.0000.869
대지면적0.9390.9200.7920.2120.8691.000
2023-12-12T09:16:26.513943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동수층수세대수대지면적엘리베이터 설치
동수1.0000.4560.8210.8310.000
층수0.4561.0000.7440.6140.674
세대수0.8210.7441.0000.9250.175
대지면적0.8310.6140.9251.0000.171
엘리베이터 설치0.0000.6740.1750.1711.000

Missing values

2023-12-12T09:16:23.311378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:16:23.432198image/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

아파트단지명동수소재지도로명주소층수엘리베이터 설치세대수대지면적사용검사일자데이터기준일자
0금강2대전광역시 대덕구 대전로 1247 (대화동)5N904012.01978-08-042023-08-30
1대화1대전광역시 대덕구 대화로 53 (대화동)5N502976.01979-03-302023-08-30
2신대화2대전광역시 대덕구 대전로 1255 (대화동)5N552006.01983-03-112023-08-30
3금성백조3대전광역시 대덕구 대화로 19 (대화동)5N1608017.01985-03-142023-08-30
4성은맨션1대전광역시 대덕구 비래동로16번길 17 (비래동)10Y501831.01985-11-062023-08-30
5삼창2대전광역시 대덕구 대덕대로1524번길 37 (목상동)5N402267.01985-12-092023-08-30
6금호1대전광역시 대덕구 덕암북로 86 (덕암동)5N201947.01985-12-272023-08-30
7안전로얄2대전광역시 대덕구 홍도로135번길 121 (중리동)5N653438.01986-04-012023-08-30
8금성백조1차1대전광역시 대덕구 우암로412번길 45 (비래동)10Y1003312.01986-05-242023-08-30
9장미4대전광역시 대덕구 동심5길 16 (대화동)5N1597369.01986-09-052023-08-30
아파트단지명동수소재지도로명주소층수엘리베이터 설치세대수대지면적사용검사일자데이터기준일자
101두레마을1011대전광역시 대덕구 대덕대로1520번길 55(목상동)9Y49<NA>2014-06-052023-08-30
102두레마을2011대전광역시 대덕구 대덕대로1486번길 65(목상동)9Y49<NA>2014-04-222023-08-30
103평원아파트1대전광역시 대덕구 동춘당로15번길 54(송촌동)9Y52<NA>2014-10-142023-08-30
104금강로하스엘크루10대전광역시 대덕구 대덕대로 158725Y765<NA>2017-10-262023-08-30
105나이스팰리스1대전광역시 대덕구 대전로1032번길 13-1315Y98<NA>2017-12-222023-08-30
106그레이스K2대전광역시 대덕구 한밭대로1140(중리동)11Y661261.02020-08-142023-08-30
107금강센트럴파크서희스타힐스12대전광역시 대덕구 대덕대로1585번길 4433Y83533935.02020-08-312023-08-30
108대전법동e편한세상12대전광역시 대덕구 중리북로 4629Y150362888.02020-09-172023-08-30
109상서동행복주택(임대)2대전광역시 대덕구 새말3길 4118Y296<NA>2020-11-272023-08-30
110동일스위트 리버스카이 1차12대전광역시 대덕구 대청로 4343Y175773763.72021-11-292023-08-30