Overview

Dataset statistics

Number of variables7
Number of observations259
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.6 KiB
Average record size in memory61.5 B

Variable types

Numeric5
Text2

Dataset

Description대구광역시 동구 아파트 현황 데이터로 아파트명, 아파트의 주소, 동수, 층수, 세대수, 입주년도 등의 정보를 제공합니다.
Author대구광역시 동구
URLhttps://www.data.go.kr/data/15109952/fileData.do

Alerts

연번 is highly overall correlated with 층수 and 2 other fieldsHigh correlation
동수 is highly overall correlated with 세대수High correlation
층수 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
세대수 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
입주년도 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
연번 has unique valuesUnique
주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 02:05:16.789507
Analysis finished2023-12-12 02:05:20.256496
Duration3.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct259
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean130
Minimum1
Maximum259
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T11:05:20.335285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13.9
Q165.5
median130
Q3194.5
95-th percentile246.1
Maximum259
Range258
Interquartile range (IQR)129

Descriptive statistics

Standard deviation74.911058
Coefficient of variation (CV)0.57623891
Kurtosis-1.2
Mean130
Median Absolute Deviation (MAD)65
Skewness0
Sum33670
Variance5611.6667
MonotonicityStrictly increasing
2023-12-12T11:05:20.482558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
164 1
 
0.4%
166 1
 
0.4%
167 1
 
0.4%
168 1
 
0.4%
169 1
 
0.4%
170 1
 
0.4%
171 1
 
0.4%
172 1
 
0.4%
173 1
 
0.4%
Other values (249) 249
96.1%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
259 1
0.4%
258 1
0.4%
257 1
0.4%
256 1
0.4%
255 1
0.4%
254 1
0.4%
253 1
0.4%
252 1
0.4%
251 1
0.4%
250 1
0.4%

아파트명
Text

Distinct256
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-12T11:05:20.713428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length7.4440154
Min length2

Characters and Unicode

Total characters1928
Distinct characters265
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique253 ?
Unique (%)97.7%

Sample

1st row영도행복한마을
2nd row불로우방아파트
3rd row강변아파트
4th row금오
5th row동림
ValueCountFrequency (%)
이시아폴리스 5
 
1.5%
대구혁신도시 5
 
1.5%
율하 4
 
1.2%
서한이다음 3
 
0.9%
동대구 3
 
0.9%
럭키 3
 
0.9%
2차 3
 
0.9%
각산역 3
 
0.9%
아파트 3
 
0.9%
신암 2
 
0.6%
Other values (284) 306
90.0%
2023-12-12T11:05:21.455910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 88
 
4.6%
83
 
4.3%
파 70
 
3.6%
트 69
 
3.6%
신 63
 
3.3%
동 46
 
2.4%
대 44
 
2.3%
스 43
 
2.2%
구 40
 
2.1%
이 40
 
2.1%
Other values (255) 1342
69.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1741
90.3%
Space Separator 83
 
4.3%
Decimal Number 74
 
3.8%
Uppercase Letter 20
 
1.0%
Lowercase Letter 8
 
0.4%
Dash Punctuation 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 88
 
5.1%
파 70
 
4.0%
트 69
 
4.0%
신 63
 
3.6%
동 46
 
2.6%
대 44
 
2.5%
스 43
 
2.5%
구 40
 
2.3%
이 40
 
2.3%
지 37
 
2.1%
Other values (229) 1201
69.0%
Decimal Number
ValueCountFrequency (%)
2 23
31.1%
1 19
25.7%
3 12
16.2%
0 6
 
8.1%
4 5
 
6.8%
6 3
 
4.1%
7 2
 
2.7%
5 2
 
2.7%
8 1
 
1.4%
9 1
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
L 6
30.0%
H 5
25.0%
S 3
15.0%
D 1
 
5.0%
P 1
 
5.0%
M 1
 
5.0%
A 1
 
5.0%
O 1
 
5.0%
T 1
 
5.0%
Lowercase Letter
ValueCountFrequency (%)
e 4
50.0%
a 2
25.0%
n 1
 
12.5%
i 1
 
12.5%
Space Separator
ValueCountFrequency (%)
83
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1741
90.3%
Common 159
 
8.2%
Latin 28
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 88
 
5.1%
파 70
 
4.0%
트 69
 
4.0%
신 63
 
3.6%
동 46
 
2.6%
대 44
 
2.5%
스 43
 
2.5%
구 40
 
2.3%
이 40
 
2.3%
지 37
 
2.1%
Other values (229) 1201
69.0%
Common
ValueCountFrequency (%)
83
52.2%
2 23
 
14.5%
1 19
 
11.9%
3 12
 
7.5%
0 6
 
3.8%
4 5
 
3.1%
6 3
 
1.9%
7 2
 
1.3%
5 2
 
1.3%
8 1
 
0.6%
Other values (3) 3
 
1.9%
Latin
ValueCountFrequency (%)
L 6
21.4%
H 5
17.9%
e 4
14.3%
S 3
10.7%
a 2
 
7.1%
D 1
 
3.6%
n 1
 
3.6%
i 1
 
3.6%
P 1
 
3.6%
M 1
 
3.6%
Other values (3) 3
10.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1741
90.3%
ASCII 187
 
9.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 88
 
5.1%
파 70
 
4.0%
트 69
 
4.0%
신 63
 
3.6%
동 46
 
2.6%
대 44
 
2.5%
스 43
 
2.5%
구 40
 
2.3%
이 40
 
2.3%
지 37
 
2.1%
Other values (229) 1201
69.0%
ASCII
ValueCountFrequency (%)
83
44.4%
2 23
 
12.3%
1 19
 
10.2%
3 12
 
6.4%
L 6
 
3.2%
0 6
 
3.2%
4 5
 
2.7%
H 5
 
2.7%
e 4
 
2.1%
6 3
 
1.6%
Other values (16) 21
 
11.2%

주소
Text

UNIQUE 

Distinct259
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-12T11:05:21.850518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length17.281853
Min length14

Characters and Unicode

Total characters4476
Distinct characters83
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique259 ?
Unique (%)100.0%

Sample

1st row대구광역시 동구 경안로 810
2nd row대구광역시 동구 공항로 150
3rd row대구광역시 동구 국채보상로165길 30
4th row대구광역시 동구 국채보상로171길 41
5th row대구광역시 동구 동대구로83길 18
ValueCountFrequency (%)
대구광역시 259
25.0%
동구 258
24.9%
30 12
 
1.2%
20 9
 
0.9%
반야월북로 9
 
0.9%
동부로 8
 
0.8%
10 7
 
0.7%
화랑로25길 7
 
0.7%
46 6
 
0.6%
아양로 6
 
0.6%
Other values (268) 457
44.0%
2023-12-12T11:05:22.427239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
782
17.5%
구 521
11.6%
동 329
 
7.4%
대 267
 
6.0%
역 261
 
5.8%
광 259
 
5.8%
시 259
 
5.8%
로 259
 
5.8%
1 150
 
3.4%
길 140
 
3.1%
Other values (73) 1249
27.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2833
63.3%
Decimal Number 856
 
19.1%
Space Separator 782
 
17.5%
Dash Punctuation 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 521
18.4%
동 329
11.6%
대 267
9.4%
역 261
9.2%
광 259
9.1%
시 259
9.1%
로 259
9.1%
길 140
 
4.9%
화 26
 
0.9%
안 24
 
0.8%
Other values (61) 488
17.2%
Decimal Number
ValueCountFrequency (%)
1 150
17.5%
2 124
14.5%
3 110
12.9%
5 90
10.5%
0 84
9.8%
4 72
8.4%
6 70
8.2%
7 60
 
7.0%
9 50
 
5.8%
8 46
 
5.4%
Space Separator
ValueCountFrequency (%)
782
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2833
63.3%
Common 1643
36.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 521
18.4%
동 329
11.6%
대 267
9.4%
역 261
9.2%
광 259
9.1%
시 259
9.1%
로 259
9.1%
길 140
 
4.9%
화 26
 
0.9%
안 24
 
0.8%
Other values (61) 488
17.2%
Common
ValueCountFrequency (%)
782
47.6%
1 150
 
9.1%
2 124
 
7.5%
3 110
 
6.7%
5 90
 
5.5%
0 84
 
5.1%
4 72
 
4.4%
6 70
 
4.3%
7 60
 
3.7%
9 50
 
3.0%
Other values (2) 51
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2833
63.3%
ASCII 1643
36.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
782
47.6%
1 150
 
9.1%
2 124
 
7.5%
3 110
 
6.7%
5 90
 
5.5%
0 84
 
5.1%
4 72
 
4.4%
6 70
 
4.3%
7 60
 
3.7%
9 50
 
3.0%
Other values (2) 51
 
3.1%
Hangul
ValueCountFrequency (%)
구 521
18.4%
동 329
11.6%
대 267
9.4%
역 261
9.2%
광 259
9.1%
시 259
9.1%
로 259
9.1%
길 140
 
4.9%
화 26
 
0.9%
안 24
 
0.8%
Other values (61) 488
17.2%

동수
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.0694981
Minimum1
Maximum22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T11:05:22.586874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median4
Q38
95-th percentile13.1
Maximum22
Range21
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.5378465
Coefficient of variation (CV)0.89512737
Kurtosis1.2434198
Mean5.0694981
Median Absolute Deviation (MAD)3
Skewness1.2428683
Sum1313
Variance20.592051
MonotonicityNot monotonic
2023-12-12T11:05:22.720058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
1 83
32.0%
2 24
 
9.3%
4 22
 
8.5%
3 19
 
7.3%
7 15
 
5.8%
6 15
 
5.8%
9 14
 
5.4%
5 13
 
5.0%
8 11
 
4.2%
10 10
 
3.9%
Other values (10) 33
 
12.7%
ValueCountFrequency (%)
1 83
32.0%
2 24
 
9.3%
3 19
 
7.3%
4 22
 
8.5%
5 13
 
5.0%
6 15
 
5.8%
7 15
 
5.8%
8 11
 
4.2%
9 14
 
5.4%
10 10
 
3.9%
ValueCountFrequency (%)
22 1
 
0.4%
21 1
 
0.4%
20 2
 
0.8%
17 3
 
1.2%
16 3
 
1.2%
15 2
 
0.8%
14 1
 
0.4%
13 6
2.3%
12 5
1.9%
11 9
3.5%

층수
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.065637
Minimum5
Maximum37
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T11:05:22.865756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile5
Q15
median14
Q318
95-th percentile27
Maximum37
Range32
Interquartile range (IQR)13

Descriptive statistics

Standard deviation7.0978445
Coefficient of variation (CV)0.54324519
Kurtosis-0.27046574
Mean13.065637
Median Absolute Deviation (MAD)6
Skewness0.57619484
Sum3384
Variance50.379396
MonotonicityNot monotonic
2023-12-12T11:05:23.027157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
5 70
27.0%
15 48
18.5%
20 18
 
6.9%
12 14
 
5.4%
18 13
 
5.0%
6 12
 
4.6%
10 10
 
3.9%
29 7
 
2.7%
13 7
 
2.7%
14 7
 
2.7%
Other values (16) 53
20.5%
ValueCountFrequency (%)
5 70
27.0%
6 12
 
4.6%
7 5
 
1.9%
8 1
 
0.4%
9 5
 
1.9%
10 10
 
3.9%
11 4
 
1.5%
12 14
 
5.4%
13 7
 
2.7%
14 7
 
2.7%
ValueCountFrequency (%)
37 1
 
0.4%
32 1
 
0.4%
29 7
2.7%
28 2
 
0.8%
27 3
1.2%
26 1
 
0.4%
25 6
2.3%
24 3
1.2%
23 4
1.5%
22 4
1.5%

세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct191
Distinct (%)73.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean361.40541
Minimum16
Maximum1859
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T11:05:23.208022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16
5-th percentile35.9
Q166
median226
Q3568
95-th percentile985.5
Maximum1859
Range1843
Interquartile range (IQR)502

Descriptive statistics

Standard deviation352.89106
Coefficient of variation (CV)0.97644102
Kurtosis2.2710979
Mean361.40541
Median Absolute Deviation (MAD)182
Skewness1.4128375
Sum93604
Variance124532.1
MonotonicityNot monotonic
2023-12-12T11:05:23.420169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49 9
 
3.5%
36 6
 
2.3%
90 4
 
1.5%
40 4
 
1.5%
130 4
 
1.5%
38 3
 
1.2%
50 3
 
1.2%
32 3
 
1.2%
48 3
 
1.2%
184 3
 
1.2%
Other values (181) 217
83.8%
ValueCountFrequency (%)
16 1
 
0.4%
26 3
1.2%
30 1
 
0.4%
31 2
 
0.8%
32 3
1.2%
33 1
 
0.4%
35 2
 
0.8%
36 6
2.3%
38 3
1.2%
39 1
 
0.4%
ValueCountFrequency (%)
1859 1
0.4%
1812 1
0.4%
1686 1
0.4%
1504 1
0.4%
1376 1
0.4%
1265 1
0.4%
1167 1
0.4%
1122 1
0.4%
1088 1
0.4%
1079 1
0.4%

입주년도
Real number (ℝ)

HIGH CORRELATION 

Distinct47
Distinct (%)18.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2001.2625
Minimum1974
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T11:05:23.628591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1974
5-th percentile1979
Q11990
median2003
Q32014.5
95-th percentile2022
Maximum2023
Range49
Interquartile range (IQR)24.5

Descriptive statistics

Standard deviation13.892743
Coefficient of variation (CV)0.0069419894
Kurtosis-1.152788
Mean2001.2625
Median Absolute Deviation (MAD)12
Skewness-0.19353464
Sum518327
Variance193.00832
MonotonicityNot monotonic
2023-12-12T11:05:23.855036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
2003 17
 
6.6%
1980 15
 
5.8%
2015 13
 
5.0%
2016 12
 
4.6%
2023 10
 
3.9%
2009 10
 
3.9%
1981 9
 
3.5%
2017 8
 
3.1%
1997 8
 
3.1%
1995 8
 
3.1%
Other values (37) 149
57.5%
ValueCountFrequency (%)
1974 1
 
0.4%
1975 1
 
0.4%
1977 1
 
0.4%
1978 5
 
1.9%
1979 8
3.1%
1980 15
5.8%
1981 9
3.5%
1982 3
 
1.2%
1984 1
 
0.4%
1985 3
 
1.2%
ValueCountFrequency (%)
2023 10
3.9%
2022 4
 
1.5%
2021 6
2.3%
2020 5
 
1.9%
2018 7
2.7%
2017 8
3.1%
2016 12
4.6%
2015 13
5.0%
2014 3
 
1.2%
2013 5
 
1.9%

Interactions

2023-12-12T11:05:19.504396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:05:17.195545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:05:17.776059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:05:18.333369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:05:18.930165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:05:19.608235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:05:17.297822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:05:17.895575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:05:18.442801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:05:19.054601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:05:19.720552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:05:17.391304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:05:17.991648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:05:18.543948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:05:19.161692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:05:19.830210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:05:17.524376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:05:18.107508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:05:18.690292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:05:19.263523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:05:19.952933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:05:17.657275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:05:18.227195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:05:18.810024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:05:19.399410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T11:05:23.969567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번동수층수세대수입주년도
연번1.0000.4680.9480.5910.809
동수0.4681.0000.4130.7310.407
층수0.9480.4131.0000.5550.753
세대수0.5910.7310.5551.0000.541
입주년도0.8090.4070.7530.5411.000
2023-12-12T11:05:24.100880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번동수층수세대수입주년도
연번1.0000.4470.9620.6060.775
동수0.4471.0000.4280.9120.390
층수0.9620.4281.0000.5940.751
세대수0.6060.9120.5941.0000.455
입주년도0.7750.3900.7510.4551.000

Missing values

2023-12-12T11:05:20.090591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:05:20.210949image/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

연번아파트명주소동수층수세대수입주년도
01영도행복한마을대구광역시 동구 경안로 81025902003
12불로우방아파트대구광역시 동구 공항로 150551841993
23강변아파트대구광역시 동구 국채보상로165길 3015521982
34금오대구광역시 동구 국채보상로171길 4115761981
45동림대구광역시 동구 동대구로83길 1815441979
56효신대구광역시 동구 동부로32길 99351481981
67신동아맨션대구광역시 동구 동부로34길 6445601979
78무궁화아파트대구광역시 동구 동촌로 222251201988
89우방백자아파트대구광역시 동구 동촌로 346752901989
910문화아파트대구광역시 동구 동촌로14길 14652301985
연번아파트명주소동수층수세대수입주년도
249250대구파라곤프레스티지대구광역시 동구 안심뉴타운7로 1314187592023
250251동대구더센트로데시앙대구광역시 동구 신암로20길 639298602023
251252용계역 푸르지오 아츠베르 1단지대구광역시 동구 화랑로108길 4213157452023
252253용계역 푸르지오 아츠베르 2단지대구광역시 동구 화랑로108길 4610155682023
253254동대구해모로스퀘어이스트대구광역시 동구 동북로75길 1315159352023
254255동대구비스타2차대구광역시 동구 화랑로25길 6012156272023
255256해링턴플레이스동대구아파트대구광역시 동구 경대로 126171512652023
256257동대구해모로스퀘어웨스트대구광역시 동구 동북로 340201511222023
257258동대구역 화성 파크드림대구광역시 동구 동대구로 590131710792023
258259극동스타클래스대구광역시 동구 반야월로26길 11-42181422023