Overview

Dataset statistics

Number of variables7
Number of observations141
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.5 KiB
Average record size in memory61.9 B

Variable types

Numeric5
Text2

Dataset

Description대구광역시 달성군에 위치하고 있는데 공동주택(아파트) 현황 정보를 합니다. 연번, 아파트명, 도로명주소, 동수, 층수, 세대수, 준공년도 등의 데이터를 포함하고 있습니다.
Author대구광역시 달성군
URLhttps://www.data.go.kr/data/15110580/fileData.do

Alerts

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

Reproduction

Analysis started2023-12-12 04:45:02.533646
Analysis finished2023-12-12 04:45:06.266486
Duration3.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct141
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean71
Minimum1
Maximum141
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T13:45:06.355651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q136
median71
Q3106
95-th percentile134
Maximum141
Range140
Interquartile range (IQR)70

Descriptive statistics

Standard deviation40.847277
Coefficient of variation (CV)0.57531375
Kurtosis-1.2
Mean71
Median Absolute Deviation (MAD)35
Skewness0
Sum10011
Variance1668.5
MonotonicityStrictly increasing
2023-12-12T13:45:06.493904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
98 1
 
0.7%
92 1
 
0.7%
93 1
 
0.7%
94 1
 
0.7%
95 1
 
0.7%
96 1
 
0.7%
97 1
 
0.7%
99 1
 
0.7%
90 1
 
0.7%
Other values (131) 131
92.9%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
141 1
0.7%
140 1
0.7%
139 1
0.7%
138 1
0.7%
137 1
0.7%
136 1
0.7%
135 1
0.7%
134 1
0.7%
133 1
0.7%
132 1
0.7%

아파트명
Text

Distinct140
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T13:45:06.823705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length20
Mean length10.914894
Min length4

Characters and Unicode

Total characters1539
Distinct characters201
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

Unique139 ?
Unique (%)98.6%

Sample

1st row 가창중석타운
2nd row 달성용계주공(국민임대)
3rd row 국태모닝포유
4th row달성화성파크드림
5th row과학마을청아람
ValueCountFrequency (%)
대구테크노폴리스 15
 
7.0%
국가산단 7
 
3.3%
아이비파크 4
 
1.9%
반도유보라 4
 
1.9%
에코폴리스 3
 
1.4%
동화아이위시 3
 
1.4%
대실역청아람 2
 
0.9%
옥포 2
 
0.9%
2단지 2
 
0.9%
서한이다음 2
 
0.9%
Other values (163) 170
79.4%
2023-12-12T13:45:07.307288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
145
 
9.4%
대 57
 
3.7%
아 50
 
3.2%
스 39
 
2.5%
트 34
 
2.2%
단 34
 
2.2%
리 34
 
2.2%
파 33
 
2.1%
지 32
 
2.1%
구 31
 
2.0%
Other values (191) 1050
68.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1288
83.7%
Space Separator 145
 
9.4%
Decimal Number 38
 
2.5%
Close Punctuation 23
 
1.5%
Open Punctuation 23
 
1.5%
Uppercase Letter 10
 
0.6%
Lowercase Letter 9
 
0.6%
Dash Punctuation 2
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 57
 
4.4%
아 50
 
3.9%
스 39
 
3.0%
트 34
 
2.6%
단 34
 
2.6%
리 34
 
2.6%
파 33
 
2.6%
지 32
 
2.5%
구 31
 
2.4%
크 29
 
2.3%
Other values (171) 915
71.0%
Decimal Number
ValueCountFrequency (%)
2 13
34.2%
1 11
28.9%
3 7
18.4%
4 5
 
13.2%
6 1
 
2.6%
5 1
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
L 3
30.0%
H 3
30.0%
O 2
20.0%
Z 1
 
10.0%
M 1
 
10.0%
Lowercase Letter
ValueCountFrequency (%)
h 3
33.3%
l 3
33.3%
e 2
22.2%
s 1
 
11.1%
Space Separator
ValueCountFrequency (%)
145
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1288
83.7%
Common 232
 
15.1%
Latin 19
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 57
 
4.4%
아 50
 
3.9%
스 39
 
3.0%
트 34
 
2.6%
단 34
 
2.6%
리 34
 
2.6%
파 33
 
2.6%
지 32
 
2.5%
구 31
 
2.4%
크 29
 
2.3%
Other values (171) 915
71.0%
Common
ValueCountFrequency (%)
145
62.5%
) 23
 
9.9%
( 23
 
9.9%
2 13
 
5.6%
1 11
 
4.7%
3 7
 
3.0%
4 5
 
2.2%
- 2
 
0.9%
6 1
 
0.4%
5 1
 
0.4%
Latin
ValueCountFrequency (%)
h 3
15.8%
L 3
15.8%
H 3
15.8%
l 3
15.8%
O 2
10.5%
e 2
10.5%
s 1
 
5.3%
Z 1
 
5.3%
M 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1288
83.7%
ASCII 251
 
16.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
145
57.8%
) 23
 
9.2%
( 23
 
9.2%
2 13
 
5.2%
1 11
 
4.4%
3 7
 
2.8%
4 5
 
2.0%
h 3
 
1.2%
L 3
 
1.2%
H 3
 
1.2%
Other values (10) 15
 
6.0%
Hangul
ValueCountFrequency (%)
대 57
 
4.4%
아 50
 
3.9%
스 39
 
3.0%
트 34
 
2.6%
단 34
 
2.6%
리 34
 
2.6%
파 33
 
2.6%
지 32
 
2.5%
구 31
 
2.4%
크 29
 
2.3%
Other values (171) 915
71.0%

도로명주소
Text

UNIQUE 

Distinct141
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T13:45:07.722879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length25
Mean length22.602837
Min length13

Characters and Unicode

Total characters3187
Distinct characters86
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

Unique141 ?
Unique (%)100.0%

Sample

1st row대구광역시 달성군 가창면 가창로 1008
2nd row대구광역시 달성군 가창면 가창로216길 25
3rd row대구광역시 달성군 가창면 가창로216길 55
4th row대구광역시 달성군 구지면 과학마을로2길 6
5th row대구광역시 달성군 구지면 과학마을로 70
ValueCountFrequency (%)
대구광역시 141
19.9%
달성군 141
19.9%
다사읍 47
 
6.6%
화원읍 31
 
4.4%
현풍읍 14
 
2.0%
유가읍 12
 
1.7%
논공읍 12
 
1.7%
옥포읍 11
 
1.6%
구지면 9
 
1.3%
달구벌대로 7
 
1.0%
Other values (166) 282
39.9%
2023-12-12T13:45:08.365418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
569
17.9%
대 169
 
5.3%
구 158
 
5.0%
역 152
 
4.8%
달 149
 
4.7%
성 144
 
4.5%
광 141
 
4.4%
시 141
 
4.4%
군 141
 
4.4%
로 133
 
4.2%
Other values (76) 1290
40.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2166
68.0%
Space Separator 569
 
17.9%
Decimal Number 446
 
14.0%
Dash Punctuation 6
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 169
 
7.8%
구 158
 
7.3%
역 152
 
7.0%
달 149
 
6.9%
성 144
 
6.6%
광 141
 
6.5%
시 141
 
6.5%
군 141
 
6.5%
로 133
 
6.1%
읍 127
 
5.9%
Other values (64) 711
32.8%
Decimal Number
ValueCountFrequency (%)
1 81
18.2%
2 70
15.7%
5 52
11.7%
3 45
10.1%
4 40
9.0%
0 39
8.7%
7 37
8.3%
6 35
7.8%
9 24
 
5.4%
8 23
 
5.2%
Space Separator
ValueCountFrequency (%)
569
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2166
68.0%
Common 1021
32.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 169
 
7.8%
구 158
 
7.3%
역 152
 
7.0%
달 149
 
6.9%
성 144
 
6.6%
광 141
 
6.5%
시 141
 
6.5%
군 141
 
6.5%
로 133
 
6.1%
읍 127
 
5.9%
Other values (64) 711
32.8%
Common
ValueCountFrequency (%)
569
55.7%
1 81
 
7.9%
2 70
 
6.9%
5 52
 
5.1%
3 45
 
4.4%
4 40
 
3.9%
0 39
 
3.8%
7 37
 
3.6%
6 35
 
3.4%
9 24
 
2.4%
Other values (2) 29
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2166
68.0%
ASCII 1021
32.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
569
55.7%
1 81
 
7.9%
2 70
 
6.9%
5 52
 
5.1%
3 45
 
4.4%
4 40
 
3.9%
0 39
 
3.8%
7 37
 
3.6%
6 35
 
3.4%
9 24
 
2.4%
Other values (2) 29
 
2.8%
Hangul
ValueCountFrequency (%)
대 169
 
7.8%
구 158
 
7.3%
역 152
 
7.0%
달 149
 
6.9%
성 144
 
6.6%
광 141
 
6.5%
시 141
 
6.5%
군 141
 
6.5%
로 133
 
6.1%
읍 127
 
5.9%
Other values (64) 711
32.8%

동수
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.9007092
Minimum1
Maximum19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T13:45:08.531156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q39
95-th percentile13
Maximum19
Range18
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.6494715
Coefficient of variation (CV)0.52885456
Kurtosis0.097608372
Mean6.9007092
Median Absolute Deviation (MAD)3
Skewness0.4858973
Sum973
Variance13.318642
MonotonicityNot monotonic
2023-12-12T13:45:08.643978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
6 18
12.8%
4 14
9.9%
7 14
9.9%
8 14
9.9%
3 11
7.8%
5 10
7.1%
10 10
7.1%
11 10
7.1%
9 10
7.1%
1 9
6.4%
Other values (6) 21
14.9%
ValueCountFrequency (%)
1 9
6.4%
2 7
 
5.0%
3 11
7.8%
4 14
9.9%
5 10
7.1%
6 18
12.8%
7 14
9.9%
8 14
9.9%
9 10
7.1%
10 10
7.1%
ValueCountFrequency (%)
19 1
 
0.7%
16 2
 
1.4%
15 2
 
1.4%
13 4
 
2.8%
12 5
 
3.5%
11 10
7.1%
10 10
7.1%
9 10
7.1%
8 14
9.9%
7 14
9.9%

층수
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.234043
Minimum3
Maximum38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T13:45:08.769627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile5
Q115
median20
Q325
95-th percentile32
Maximum38
Range35
Interquartile range (IQR)10

Descriptive statistics

Standard deviation7.7649747
Coefficient of variation (CV)0.40370997
Kurtosis0.0058824436
Mean19.234043
Median Absolute Deviation (MAD)5
Skewness-0.41354197
Sum2712
Variance60.294833
MonotonicityNot monotonic
2023-12-12T13:45:08.937856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
25 24
17.0%
20 19
13.5%
18 14
9.9%
5 14
9.9%
15 13
9.2%
22 11
7.8%
21 6
 
4.3%
23 6
 
4.3%
33 4
 
2.8%
24 4
 
2.8%
Other values (14) 26
18.4%
ValueCountFrequency (%)
3 2
 
1.4%
4 2
 
1.4%
5 14
9.9%
6 3
 
2.1%
10 3
 
2.1%
13 2
 
1.4%
15 13
9.2%
17 1
 
0.7%
18 14
9.9%
19 2
 
1.4%
ValueCountFrequency (%)
38 2
 
1.4%
35 1
 
0.7%
33 4
 
2.8%
32 1
 
0.7%
30 1
 
0.7%
29 2
 
1.4%
27 3
 
2.1%
26 1
 
0.7%
25 24
17.0%
24 4
 
2.8%

세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct134
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean610.0922
Minimum27
Maximum1553
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T13:45:09.090698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum27
5-th percentile99
Q1316
median601
Q3827
95-th percentile1278
Maximum1553
Range1526
Interquartile range (IQR)511

Descriptive statistics

Standard deviation352.45763
Coefficient of variation (CV)0.57771208
Kurtosis-0.35414201
Mean610.0922
Median Absolute Deviation (MAD)261
Skewness0.42396223
Sum86023
Variance124226.38
MonotonicityNot monotonic
2023-12-12T13:45:09.277277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
360 3
 
2.1%
72 2
 
1.4%
933 2
 
1.4%
220 2
 
1.4%
99 2
 
1.4%
302 2
 
1.4%
44 1
 
0.7%
730 1
 
0.7%
1020 1
 
0.7%
870 1
 
0.7%
Other values (124) 124
87.9%
ValueCountFrequency (%)
27 1
0.7%
40 1
0.7%
42 1
0.7%
44 1
0.7%
72 2
1.4%
88 1
0.7%
99 2
1.4%
107 1
0.7%
117 1
0.7%
128 1
0.7%
ValueCountFrequency (%)
1553 1
0.7%
1457 1
0.7%
1451 1
0.7%
1390 1
0.7%
1366 1
0.7%
1364 1
0.7%
1316 1
0.7%
1278 1
0.7%
1228 1
0.7%
1204 1
0.7%

준공년도
Real number (ℝ)

HIGH CORRELATION 

Distinct34
Distinct (%)24.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2006.1418
Minimum1981
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T13:45:09.459850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1981
5-th percentile1989
Q11996
median2008
Q32016
95-th percentile2020
Maximum2022
Range41
Interquartile range (IQR)20

Descriptive statistics

Standard deviation10.962652
Coefficient of variation (CV)0.0054645448
Kurtosis-1.2440502
Mean2006.1418
Median Absolute Deviation (MAD)9
Skewness-0.30776767
Sum282866
Variance120.17974
MonotonicityNot monotonic
2023-12-12T13:45:09.587023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
2016 16
 
11.3%
2017 13
 
9.2%
2000 8
 
5.7%
2015 8
 
5.7%
2008 8
 
5.7%
1996 6
 
4.3%
2018 6
 
4.3%
1991 6
 
4.3%
1997 6
 
4.3%
2007 5
 
3.5%
Other values (24) 59
41.8%
ValueCountFrequency (%)
1981 1
 
0.7%
1984 1
 
0.7%
1985 1
 
0.7%
1987 2
 
1.4%
1989 3
2.1%
1990 5
3.5%
1991 6
4.3%
1992 4
2.8%
1993 2
 
1.4%
1995 5
3.5%
ValueCountFrequency (%)
2022 3
 
2.1%
2021 3
 
2.1%
2020 5
 
3.5%
2019 2
 
1.4%
2018 6
 
4.3%
2017 13
9.2%
2016 16
11.3%
2015 8
5.7%
2014 1
 
0.7%
2012 2
 
1.4%

Interactions

2023-12-12T13:45:05.490932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:45:02.902220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:45:03.447473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:45:04.351451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:45:04.943889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:45:05.617353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:45:03.037928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:45:03.557487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:45:04.496123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:45:05.047611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:45:05.739300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:45:03.153188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:45:03.686374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:45:04.626091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:45:05.144980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:45:05.847883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:45:03.252682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:45:04.125022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:45:04.735467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:45:05.263202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:45:05.952004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:45:03.353132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:45:04.240615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:45:04.850760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:45:05.389987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:45:09.695784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번동수층수세대수준공년도
연번1.0000.5910.5580.7040.854
동수0.5911.0000.2550.8200.532
층수0.5580.2551.0000.5640.647
세대수0.7040.8200.5641.0000.602
준공년도0.8540.5320.6470.6021.000
2023-12-12T13:45:09.854871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번동수층수세대수준공년도
연번1.000-0.092-0.317-0.245-0.193
동수-0.0921.0000.2040.7600.482
층수-0.3170.2041.0000.5380.622
세대수-0.2450.7600.5381.0000.538
준공년도-0.1930.4820.6220.5381.000

Missing values

2023-12-12T13:45:06.074399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:45:06.216743image/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

연번아파트명도로명주소동수층수세대수준공년도
01가창중석타운대구광역시 달성군 가창면 가창로 10083183601997
12달성용계주공(국민임대)대구광역시 달성군 가창면 가창로216길 255153022005
23국태모닝포유대구광역시 달성군 가창면 가창로216길 553201502005
34달성화성파크드림대구광역시 달성군 구지면 과학마을로2길 6132012282011
45과학마을청아람대구광역시 달성군 구지면 과학마을로 709228952016
56대구국가산단 반도유보라 아이비파크대구광역시 달성군 구지면 과학마을로3길 149258132017
67국가산단 반도유보라 아이비파크 2대구광역시 달성군 구지면 국가산단북로60길 596255272020
78국가산단 ZOOM 파크대구광역시 달성군 구지면 국가산단대로64길 637255962020
89국가산단 반도유보라 아이비파크 3대구광역시 달성군 구지면 국가산단북로34길 108257752020
910국가산단 영무예다음대구광역시 달성군 구지면 국가산단서로84길 11812259342020
연번아파트명도로명주소동수층수세대수준공년도
131132금성아파트대구광역시 달성군 현풍읍 현풍중앙로14길 8525991990
132133제일아파트대구광역시 달성군 현풍읍 현풍로24길 6110721992
133134대호사원아파트(우리아파트)대구광역시 달성군 현풍읍 현풍동로27길 1315401991
134135현풍상리군영주택대구광역시 달성군 현풍읍 현풍동로20길 48-226441991
135136현풍주공대구광역시 달성군 현풍읍 비슬로120길 13652301985
136137천내보성타운대구광역시 달성군 화원읍 화원로 37531071991
137138천내평광현대1차대구광역시 달성군 화원읍 비슬로525길 243991990
138139가창용계아파트대구광역시 달성군 가창면 가창로216길 5144881981
139140논공서광빌라(연립)대구광역시 달성군 논공읍 논공로26길 1334271991
140141프리미어힐대구광역시 달성군 화원읍 비슬로506길 11119722018