Overview

Dataset statistics

Number of variables8
Number of observations87
Missing cells24
Missing cells (%)3.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.7 KiB
Average record size in memory67.5 B

Variable types

Numeric2
Text3
Categorical3

Dataset

Description대구광역시 달서구 내 석면조사대상 건축물 현황에 대한 내용 및 정보가 담겨있음. (좌표, 건물명, 동명, 주소, 행정동)
URLhttps://www.data.go.kr/data/3047280/fileData.do

Alerts

주관부서 has constant value ""Constant
기준일자 has constant value ""Constant
위도 is highly overall correlated with 행정동High correlation
경도 is highly overall correlated with 행정동High correlation
행정동 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
동명 has 24 (27.6%) missing valuesMissing

Reproduction

Analysis started2023-12-12 21:56:35.444105
Analysis finished2023-12-12 21:56:36.357359
Duration0.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)51.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.837842
Minimum35.805789
Maximum35.861866
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size915.0 B
2023-12-13T06:56:36.423782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.805789
5-th percentile35.810655
Q135.823484
median35.834438
Q335.850945
95-th percentile35.859459
Maximum35.861866
Range0.05607746
Interquartile range (IQR)0.02746061

Descriptive statistics

Standard deviation0.015239161
Coefficient of variation (CV)0.00042522539
Kurtosis-0.89004634
Mean35.837842
Median Absolute Deviation (MAD)0.01167548
Skewness-0.13644089
Sum3117.8923
Variance0.00023223202
MonotonicityNot monotonic
2023-12-13T06:56:36.565540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
35.83408091 11
 
12.6%
35.82348419 8
 
9.2%
35.8594593 8
 
9.2%
35.85355716 5
 
5.7%
35.84477041 4
 
4.6%
35.82276281 4
 
4.6%
35.84972658 3
 
3.4%
35.83628632 3
 
3.4%
35.83139659 3
 
3.4%
35.84495178 2
 
2.3%
Other values (35) 36
41.4%
ValueCountFrequency (%)
35.80578856 1
1.1%
35.80737518 1
1.1%
35.80748297 1
1.1%
35.80900893 1
1.1%
35.81048743 1
1.1%
35.8110469 1
1.1%
35.81426653 1
1.1%
35.81881003 1
1.1%
35.81951189 1
1.1%
35.82020623 1
1.1%
ValueCountFrequency (%)
35.86186602 1
 
1.1%
35.86138023 1
 
1.1%
35.86083568 1
 
1.1%
35.8594593 8
9.2%
35.85896631 1
 
1.1%
35.85843068 1
 
1.1%
35.85690806 1
 
1.1%
35.85368938 1
 
1.1%
35.85355716 5
5.7%
35.8516518 1
 
1.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)51.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.5196
Minimum128.47336
Maximum128.57372
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size915.0 B
2023-12-13T06:56:36.697439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.47336
5-th percentile128.4815
Q1128.49376
median128.51694
Q3128.54432
95-th percentile128.5637
Maximum128.57372
Range0.1003581
Interquartile range (IQR)0.0505657

Descriptive statistics

Standard deviation0.02870076
Coefficient of variation (CV)0.00022331815
Kurtosis-1.410345
Mean128.5196
Median Absolute Deviation (MAD)0.0273898
Skewness0.18644435
Sum11181.205
Variance0.0008237336
MonotonicityNot monotonic
2023-12-13T06:56:36.818387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
128.5443249 11
 
12.6%
128.4958665 8
 
9.2%
128.4863475 8
 
9.2%
128.4814952 5
 
5.7%
128.558103 4
 
4.6%
128.4937592 4
 
4.6%
128.5698397 3
 
3.4%
128.512251 3
 
3.4%
128.4896069 3
 
3.4%
128.4985576 2
 
2.3%
Other values (35) 36
41.4%
ValueCountFrequency (%)
128.4733631 1
 
1.1%
128.4814952 5
5.7%
128.4863475 8
9.2%
128.4871847 1
 
1.1%
128.4896069 3
 
3.4%
128.4934458 1
 
1.1%
128.4937592 4
4.6%
128.4957896 1
 
1.1%
128.4958665 8
9.2%
128.4964901 1
 
1.1%
ValueCountFrequency (%)
128.5737212 1
 
1.1%
128.5698397 3
3.4%
128.5636973 2
2.3%
128.558103 4
4.6%
128.5576698 1
 
1.1%
128.5568597 1
 
1.1%
128.5559485 1
 
1.1%
128.5502901 1
 
1.1%
128.5483162 1
 
1.1%
128.5462004 1
 
1.1%

건물명
Text

Distinct45
Distinct (%)51.7%
Missing0
Missing (%)0.0%
Memory size828.0 B
2023-12-13T06:56:37.010935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length9.0344828
Min length4

Characters and Unicode

Total characters786
Distinct characters125
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

Unique34 ?
Unique (%)39.1%

Sample

1st row상인아람어린이집
2nd row소리나는 어린이집
3rd row보광병원
4th row(의)열경의료재단 허병원
5th row대구기독병원
ValueCountFrequency (%)
대구공업대학교 11
 
10.0%
대구공공시설관리공단 8
 
7.3%
서부사업소 8
 
7.3%
계명문화대학 8
 
7.3%
계명대학교(성서캠퍼스 5
 
4.5%
문화예술회관 4
 
3.6%
성서산업단지관리공단 4
 
3.6%
환경사업소 4
 
3.6%
성서사업소 3
 
2.7%
한국지역난방공사 3
 
2.7%
Other values (45) 52
47.3%
2023-12-13T06:56:37.337695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 56
 
7.1%
공 48
 
6.1%
업 33
 
4.2%
구 33
 
4.2%
서 26
 
3.3%
학 24
 
3.1%
소 23
 
2.9%
23
 
2.9%
단 20
 
2.5%
사 20
 
2.5%
Other values (115) 480
61.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 723
92.0%
Space Separator 23
 
2.9%
Uppercase Letter 15
 
1.9%
Decimal Number 9
 
1.1%
Close Punctuation 7
 
0.9%
Open Punctuation 7
 
0.9%
Dash Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 56
 
7.7%
공 48
 
6.6%
업 33
 
4.6%
구 33
 
4.6%
서 26
 
3.6%
학 24
 
3.3%
소 23
 
3.2%
단 20
 
2.8%
사 20
 
2.8%
관 20
 
2.8%
Other values (101) 420
58.1%
Uppercase Letter
ValueCountFrequency (%)
I 3
20.0%
B 3
20.0%
O 2
13.3%
P 2
13.3%
S 2
13.3%
T 2
13.3%
K 1
 
6.7%
Decimal Number
ValueCountFrequency (%)
1 5
55.6%
2 3
33.3%
9 1
 
11.1%
Space Separator
ValueCountFrequency (%)
23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 723
92.0%
Common 48
 
6.1%
Latin 15
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 56
 
7.7%
공 48
 
6.6%
업 33
 
4.6%
구 33
 
4.6%
서 26
 
3.6%
학 24
 
3.3%
소 23
 
3.2%
단 20
 
2.8%
사 20
 
2.8%
관 20
 
2.8%
Other values (101) 420
58.1%
Common
ValueCountFrequency (%)
23
47.9%
) 7
 
14.6%
( 7
 
14.6%
1 5
 
10.4%
2 3
 
6.2%
- 2
 
4.2%
9 1
 
2.1%
Latin
ValueCountFrequency (%)
I 3
20.0%
B 3
20.0%
O 2
13.3%
P 2
13.3%
S 2
13.3%
T 2
13.3%
K 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 723
92.0%
ASCII 63
 
8.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 56
 
7.7%
공 48
 
6.6%
업 33
 
4.6%
구 33
 
4.6%
서 26
 
3.6%
학 24
 
3.3%
소 23
 
3.2%
단 20
 
2.8%
사 20
 
2.8%
관 20
 
2.8%
Other values (101) 420
58.1%
ASCII
ValueCountFrequency (%)
23
36.5%
) 7
 
11.1%
( 7
 
11.1%
1 5
 
7.9%
2 3
 
4.8%
I 3
 
4.8%
B 3
 
4.8%
O 2
 
3.2%
P 2
 
3.2%
S 2
 
3.2%
Other values (4) 6
 
9.5%

동명
Text

MISSING 

Distinct59
Distinct (%)93.7%
Missing24
Missing (%)27.6%
Memory size828.0 B
2023-12-13T06:56:37.565184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length4.5873016
Min length2

Characters and Unicode

Total characters289
Distinct characters117
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)88.9%

Sample

1st row상인아람 어린이집
2nd row소리나는어린이집
3rd row보광병원
4th row(의)열경의료재단 허병원
5th row대구기독병원
ValueCountFrequency (%)
관리동 3
 
4.4%
a동 2
 
2.9%
탈수기동 2
 
2.9%
열원설비동 1
 
1.5%
창고정비동 1
 
1.5%
상인아람 1
 
1.5%
어린이집 1
 
1.5%
공연장동(팔공홀 1
 
1.5%
공장동2 1
 
1.5%
전시관동 1
 
1.5%
Other values (54) 54
79.4%
2023-12-13T06:56:37.944576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
관 31
 
10.7%
동 31
 
10.7%
리 8
 
2.8%
) 6
 
2.1%
원 6
 
2.1%
공 6
 
2.1%
( 6
 
2.1%
2 5
 
1.7%
수 5
 
1.7%
기 5
 
1.7%
Other values (107) 180
62.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 254
87.9%
Decimal Number 13
 
4.5%
Close Punctuation 6
 
2.1%
Open Punctuation 6
 
2.1%
Space Separator 5
 
1.7%
Uppercase Letter 5
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 31
 
12.2%
동 31
 
12.2%
리 8
 
3.1%
원 6
 
2.4%
공 6
 
2.4%
수 5
 
2.0%
기 5
 
2.0%
장 5
 
2.0%
호 5
 
2.0%
사 4
 
1.6%
Other values (96) 148
58.3%
Decimal Number
ValueCountFrequency (%)
2 5
38.5%
1 5
38.5%
6 1
 
7.7%
8 1
 
7.7%
9 1
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
A 3
60.0%
B 1
 
20.0%
D 1
 
20.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 254
87.9%
Common 30
 
10.4%
Latin 5
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 31
 
12.2%
동 31
 
12.2%
리 8
 
3.1%
원 6
 
2.4%
공 6
 
2.4%
수 5
 
2.0%
기 5
 
2.0%
장 5
 
2.0%
호 5
 
2.0%
사 4
 
1.6%
Other values (96) 148
58.3%
Common
ValueCountFrequency (%)
) 6
20.0%
( 6
20.0%
2 5
16.7%
5
16.7%
1 5
16.7%
6 1
 
3.3%
8 1
 
3.3%
9 1
 
3.3%
Latin
ValueCountFrequency (%)
A 3
60.0%
B 1
 
20.0%
D 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 254
87.9%
ASCII 35
 
12.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
관 31
 
12.2%
동 31
 
12.2%
리 8
 
3.1%
원 6
 
2.4%
공 6
 
2.4%
수 5
 
2.0%
기 5
 
2.0%
장 5
 
2.0%
호 5
 
2.0%
사 4
 
1.6%
Other values (96) 148
58.3%
ASCII
ValueCountFrequency (%)
) 6
17.1%
( 6
17.1%
2 5
14.3%
5
14.3%
1 5
14.3%
A 3
8.6%
B 1
 
2.9%
D 1
 
2.9%
6 1
 
2.9%
8 1
 
2.9%

도로명주소
Text

Distinct45
Distinct (%)51.7%
Missing0
Missing (%)0.0%
Memory size828.0 B
2023-12-13T06:56:38.218746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length30
Mean length23.885057
Min length21

Characters and Unicode

Total characters2078
Distinct characters78
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

Unique34 ?
Unique (%)39.1%

Sample

1st row대구광역시 달서구 상화로 380 (상인동, 장미아파트)
2nd row대구광역시 달서구 새동네로 34, 성서보람타운 (용산동)
3rd row대구광역시 달서구 구마로 128 (본동)
4th row대구광역시 달서구 학산로 121 (본동)
5th row대구광역시 달서구 달구벌대로 1750 (두류동)
ValueCountFrequency (%)
대구광역시 87
19.9%
달서구 87
19.9%
달서대로 23
 
5.3%
신당동 17
 
3.9%
대천동 16
 
3.7%
본동 14
 
3.2%
송현로 12
 
2.7%
205 11
 
2.5%
성당동 9
 
2.1%
675 8
 
1.8%
Other values (82) 153
35.0%
2023-12-13T06:56:38.707733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
350
16.8%
구 183
 
8.8%
대 133
 
6.4%
서 123
 
5.9%
달 117
 
5.6%
동 89
 
4.3%
( 87
 
4.2%
) 87
 
4.2%
시 87
 
4.2%
역 87
 
4.2%
Other values (68) 735
35.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1298
62.5%
Space Separator 350
 
16.8%
Decimal Number 253
 
12.2%
Open Punctuation 87
 
4.2%
Close Punctuation 87
 
4.2%
Other Punctuation 2
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 183
14.1%
대 133
10.2%
서 123
9.5%
달 117
9.0%
동 89
 
6.9%
시 87
 
6.7%
역 87
 
6.7%
광 87
 
6.7%
로 86
 
6.6%
당 30
 
2.3%
Other values (53) 276
21.3%
Decimal Number
ValueCountFrequency (%)
2 49
19.4%
1 42
16.6%
5 40
15.8%
0 36
14.2%
3 22
8.7%
7 20
7.9%
6 18
 
7.1%
8 10
 
4.0%
9 8
 
3.2%
4 8
 
3.2%
Space Separator
ValueCountFrequency (%)
350
100.0%
Open Punctuation
ValueCountFrequency (%)
( 87
100.0%
Close Punctuation
ValueCountFrequency (%)
) 87
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1298
62.5%
Common 780
37.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 183
14.1%
대 133
10.2%
서 123
9.5%
달 117
9.0%
동 89
 
6.9%
시 87
 
6.7%
역 87
 
6.7%
광 87
 
6.7%
로 86
 
6.6%
당 30
 
2.3%
Other values (53) 276
21.3%
Common
ValueCountFrequency (%)
350
44.9%
( 87
 
11.2%
) 87
 
11.2%
2 49
 
6.3%
1 42
 
5.4%
5 40
 
5.1%
0 36
 
4.6%
3 22
 
2.8%
7 20
 
2.6%
6 18
 
2.3%
Other values (5) 29
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1298
62.5%
ASCII 780
37.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
350
44.9%
( 87
 
11.2%
) 87
 
11.2%
2 49
 
6.3%
1 42
 
5.4%
5 40
 
5.1%
0 36
 
4.6%
3 22
 
2.8%
7 20
 
2.6%
6 18
 
2.3%
Other values (5) 29
 
3.7%
Hangul
ValueCountFrequency (%)
구 183
14.1%
대 133
10.2%
서 123
9.5%
달 117
9.0%
동 89
 
6.9%
시 87
 
6.7%
역 87
 
6.7%
광 87
 
6.7%
로 86
 
6.6%
당 30
 
2.3%
Other values (53) 276
21.3%

행정동
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)20.7%
Missing0
Missing (%)0.0%
Memory size828.0 B
월성2동
21 
신당동
19 
본동
14 
성당동
9 
두류3동
3 
Other values (13)
21 

Length

Max length6
Median length4
Mean length3.2873563
Min length2

Unique

Unique7 ?
Unique (%)8.0%

Sample

1st row상인3동
2nd row용산2동
3rd row본동
4th row본동
5th row두류3동

Common Values

ValueCountFrequency (%)
월성2동 21
24.1%
신당동 19
21.8%
본동 14
16.1%
성당동 9
10.3%
두류3동 3
 
3.4%
도원동 3
 
3.4%
장기동 3
 
3.4%
진천동 2
 
2.3%
용산2동 2
 
2.3%
이곡1동 2
 
2.3%
Other values (8) 9
10.3%

Length

2023-12-13T06:56:38.865906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
월성2동 21
24.1%
신당동 19
21.8%
본동 14
16.1%
성당동 9
10.3%
두류3동 3
 
3.4%
도원동 3
 
3.4%
장기동 3
 
3.4%
상인1동 2
 
2.3%
이곡1동 2
 
2.3%
용산2동 2
 
2.3%
Other values (8) 9
10.3%

주관부서
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size828.0 B
대구광역시 달서구 기후환경과
87 

Length

Max length15
Median length15
Mean length15
Min length15

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대구광역시 달서구 기후환경과
2nd row대구광역시 달서구 기후환경과
3rd row대구광역시 달서구 기후환경과
4th row대구광역시 달서구 기후환경과
5th row대구광역시 달서구 기후환경과

Common Values

ValueCountFrequency (%)
대구광역시 달서구 기후환경과 87
100.0%

Length

2023-12-13T06:56:39.014093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:56:39.312768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 87
33.3%
달서구 87
33.3%
기후환경과 87
33.3%

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size828.0 B
2023-03-10
87 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-03-10
2nd row2023-03-10
3rd row2023-03-10
4th row2023-03-10
5th row2023-03-10

Common Values

ValueCountFrequency (%)
2023-03-10 87
100.0%

Length

2023-12-13T06:56:39.542926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:56:39.706655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-03-10 87
100.0%

Interactions

2023-12-13T06:56:35.965521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:56:35.812568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:56:36.061216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:56:35.880915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:56:40.151394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도건물명동명도로명주소행정동
위도1.0000.9121.0000.8721.0000.903
경도0.9121.0001.0000.9351.0000.909
건물명1.0001.0001.0000.8251.0001.000
동명0.8720.9350.8251.0000.8250.953
도로명주소1.0001.0001.0000.8251.0001.000
행정동0.9030.9091.0000.9531.0001.000
2023-12-13T06:56:40.247803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도행정동
위도1.000-0.1510.608
경도-0.1511.0000.623
행정동0.6080.6231.000

Missing values

2023-12-13T06:56:36.170143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:56:36.305926image/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

위도경도건물명동명도로명주소행정동주관부서기준일자
035.807375128.555948상인아람어린이집상인아람 어린이집대구광역시 달서구 상화로 380 (상인동, 장미아파트)상인3동대구광역시 달서구 기후환경과2023-03-10
135.851024128.51828소리나는 어린이집소리나는어린이집대구광역시 달서구 새동네로 34, 성서보람타운 (용산동)용산2동대구광역시 달서구 기후환경과2023-03-10
235.836752128.541664보광병원보광병원대구광역시 달서구 구마로 128 (본동)본동대구광역시 달서구 기후환경과2023-03-10
335.833642128.53964(의)열경의료재단 허병원(의)열경의료재단 허병원대구광역시 달서구 학산로 121 (본동)본동대구광역시 달서구 기후환경과2023-03-10
435.856908128.55686대구기독병원대구기독병원대구광역시 달서구 달구벌대로 1750 (두류동)두류3동대구광역시 달서구 기후환경과2023-03-10
535.853557128.481495계명대학교(성서캠퍼스)학군단대구광역시 달서구 달구벌대로 1095 (신당동)신당동대구광역시 달서구 기후환경과2023-03-10
635.853557128.481495계명대학교(성서캠퍼스)의양관대구광역시 달서구 달구벌대로 1095 (신당동)신당동대구광역시 달서구 기후환경과2023-03-10
735.853557128.481495계명대학교(성서캠퍼스)오산관대구광역시 달서구 달구벌대로 1095 (신당동)신당동대구광역시 달서구 기후환경과2023-03-10
835.853557128.481495계명대학교(성서캠퍼스)스미스관대구광역시 달서구 달구벌대로 1095 (신당동)신당동대구광역시 달서구 기후환경과2023-03-10
935.853557128.481495계명대학교(성서캠퍼스)구조실험동대구광역시 달서구 달구벌대로 1095 (신당동)신당동대구광역시 달서구 기후환경과2023-03-10
위도경도건물명동명도로명주소행정동주관부서기준일자
7735.831397128.489607한국지역난방공사창고정비동대구광역시 달서구 달서대로 351 (대천동)월성2동대구광역시 달서구 기후환경과2023-03-10
7835.831397128.489607한국지역난방공사열원설비동대구광역시 달서구 달서대로 351 (대천동)월성2동대구광역시 달서구 기후환경과2023-03-10
7935.844952128.498558대구POST-BI공장동대구광역시 달서구 성서공단북로 235 (신당동)신당동대구광역시 달서구 기후환경과2023-03-10
8035.844952128.498558대구POST-BI사무동대구광역시 달서구 성서공단북로 235 (신당동)신당동대구광역시 달서구 기후환경과2023-03-10
8135.845162128.473363강창변전소<NA>대구광역시 달서구 성서공단북로 7 (파호동)신당동대구광역시 달서구 기후환경과2023-03-10
8235.83111128.493446성서변전소<NA>대구광역시 달서구 성서공단남로 9 (월암동)월성2동대구광역시 달서구 기후환경과2023-03-10
8335.861866128.52681와룡변전소<NA>대구광역시 달서구 장산로32길 3 (용산동)용산1동대구광역시 달서구 기후환경과2023-03-10
8435.860836128.49579달서변전소<NA>대구광역시 달서구 선원로15길 126 (신당동)신당동대구광역시 달서구 기후환경과2023-03-10
8535.805789128.5462상인변전소<NA>대구광역시 달서구 미리샘길 54 (도원동)도원동대구광역시 달서구 기후환경과2023-03-10
8635.836195128.506096한국산업인력공단 대구지역본부<NA>대구광역시 달서구 성서공단로 213 (갈산동)이곡2동대구광역시 달서구 기후환경과2023-03-10