Overview

Dataset statistics

Number of variables7
Number of observations59
Missing cells59
Missing cells (%)14.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory58.2 B

Variable types

Text6
DateTime1

Dataset

Description대구 정비사업 전문관리업 등록현황(2015.10월)
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=3075092&dataSetDetailId=30750921ebbc15ec9244&provdMethod=FILE

Alerts

연락처 has 40 (67.8%) missing valuesMissing
비 고 has 19 (32.2%) missing valuesMissing
등록 번호 has unique valuesUnique
대표자 has unique valuesUnique
소재지 has unique valuesUnique

Reproduction

Analysis started2023-12-10 19:04:39.695517
Analysis finished2023-12-10 19:04:40.755269
Duration1.06 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

등록 번호
Text

UNIQUE 

Distinct59
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size604.0 B
2023-12-11T04:04:41.000827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.8474576
Min length3

Characters and Unicode

Total characters227
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59 ?
Unique (%)100.0%

Sample

1st row제1호
2nd row제2호
3rd row제3호
4th row제4호
5th row제5호
ValueCountFrequency (%)
제1호 1
 
1.7%
제31호 1
 
1.7%
제33호 1
 
1.7%
제34호 1
 
1.7%
제35호 1
 
1.7%
제36호 1
 
1.7%
제37호 1
 
1.7%
제38호 1
 
1.7%
제39호 1
 
1.7%
제40호 1
 
1.7%
Other values (49) 49
83.1%
2023-12-11T04:04:41.573634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
제 59
26.0%
호 59
26.0%
1 16
 
7.0%
3 16
 
7.0%
4 16
 
7.0%
5 16
 
7.0%
2 16
 
7.0%
6 6
 
2.6%
7 6
 
2.6%
8 6
 
2.6%
Other values (2) 11
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 118
52.0%
Decimal Number 109
48.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
14.7%
3 16
14.7%
4 16
14.7%
5 16
14.7%
2 16
14.7%
6 6
 
5.5%
7 6
 
5.5%
8 6
 
5.5%
9 6
 
5.5%
0 5
 
4.6%
Other Letter
ValueCountFrequency (%)
제 59
50.0%
호 59
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 118
52.0%
Common 109
48.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
14.7%
3 16
14.7%
4 16
14.7%
5 16
14.7%
2 16
14.7%
6 6
 
5.5%
7 6
 
5.5%
8 6
 
5.5%
9 6
 
5.5%
0 5
 
4.6%
Hangul
ValueCountFrequency (%)
제 59
50.0%
호 59
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 118
52.0%
ASCII 109
48.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
제 59
50.0%
호 59
50.0%
ASCII
ValueCountFrequency (%)
1 16
14.7%
3 16
14.7%
4 16
14.7%
5 16
14.7%
2 16
14.7%
6 6
 
5.5%
7 6
 
5.5%
8 6
 
5.5%
9 6
 
5.5%
0 5
 
4.6%

등록일자
Date

Distinct56
Distinct (%)94.9%
Missing0
Missing (%)0.0%
Memory size604.0 B
Minimum2003-09-09 00:00:00
Maximum2015-07-13 00:00:00
2023-12-11T04:04:41.784288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:04:42.047085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

대표자
Text

UNIQUE 

Distinct59
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size604.0 B
2023-12-11T04:04:42.386722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.4745763
Min length3

Characters and Unicode

Total characters205
Distinct characters82
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59 ?
Unique (%)100.0%

Sample

1st row권태형
2nd row김태조
3rd row강봉기
4th row김재권
5th row문종혁
ValueCountFrequency (%)
김동만 2
 
3.0%
권태형 1
 
1.5%
양복례 1
 
1.5%
곽상의 1
 
1.5%
김형주 1
 
1.5%
박해상 1
 
1.5%
전이수 1
 
1.5%
손상호 1
 
1.5%
이동재 1
 
1.5%
안태한 1
 
1.5%
Other values (55) 55
83.3%
2023-12-11T04:04:43.351804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 19
 
9.3%
이 11
 
5.4%
태 9
 
4.4%
7
 
3.4%
희 6
 
2.9%
동 6
 
2.9%
진 6
 
2.9%
영 5
 
2.4%
박 5
 
2.4%
재 4
 
2.0%
Other values (72) 127
62.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 198
96.6%
Space Separator 7
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 19
 
9.6%
이 11
 
5.6%
태 9
 
4.5%
희 6
 
3.0%
동 6
 
3.0%
진 6
 
3.0%
영 5
 
2.5%
박 5
 
2.5%
재 4
 
2.0%
남 4
 
2.0%
Other values (71) 123
62.1%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 198
96.6%
Common 7
 
3.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 19
 
9.6%
이 11
 
5.6%
태 9
 
4.5%
희 6
 
3.0%
동 6
 
3.0%
진 6
 
3.0%
영 5
 
2.5%
박 5
 
2.5%
재 4
 
2.0%
남 4
 
2.0%
Other values (71) 123
62.1%
Common
ValueCountFrequency (%)
7
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 198
96.6%
ASCII 7
 
3.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 19
 
9.6%
이 11
 
5.6%
태 9
 
4.5%
희 6
 
3.0%
동 6
 
3.0%
진 6
 
3.0%
영 5
 
2.5%
박 5
 
2.5%
재 4
 
2.0%
남 4
 
2.0%
Other values (71) 123
62.1%
ASCII
ValueCountFrequency (%)
7
100.0%

상호명
Text

Distinct58
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size604.0 B
2023-12-11T04:04:43.743740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length8.0677966
Min length3

Characters and Unicode

Total characters476
Distinct characters103
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)96.6%

Sample

1st row(주)태진
2nd row(주)창홍시앤시
3rd row유림건설(주)
4th row(주)디알씨
5th row(주) 다원도시개발
ValueCountFrequency (%)
주 5
 
6.8%
신토도시정비 2
 
2.7%
건축사사무소 2
 
2.7%
주)태영디엔시 1
 
1.4%
주)거상이앤씨 1
 
1.4%
㈜도시재생기획원 1
 
1.4%
티알이엔씨(주 1
 
1.4%
주)그룹환경씨엠씨 1
 
1.4%
주)건축사 1
 
1.4%
사무소 1
 
1.4%
Other values (57) 57
78.1%
2023-12-11T04:04:44.297833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 62
 
13.0%
( 56
 
11.8%
) 56
 
11.8%
씨 25
 
5.3%
시 15
 
3.2%
14
 
2.9%
앤 10
 
2.1%
도 9
 
1.9%
비 9
 
1.9%
디 9
 
1.9%
Other values (93) 211
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 347
72.9%
Open Punctuation 56
 
11.8%
Close Punctuation 56
 
11.8%
Space Separator 14
 
2.9%
Other Symbol 3
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 62
 
17.9%
씨 25
 
7.2%
시 15
 
4.3%
앤 10
 
2.9%
도 9
 
2.6%
비 9
 
2.6%
디 9
 
2.6%
정 8
 
2.3%
엠 8
 
2.3%
원 7
 
2.0%
Other values (89) 185
53.3%
Open Punctuation
ValueCountFrequency (%)
( 56
100.0%
Close Punctuation
ValueCountFrequency (%)
) 56
100.0%
Space Separator
ValueCountFrequency (%)
14
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 350
73.5%
Common 126
 
26.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 62
 
17.7%
씨 25
 
7.1%
시 15
 
4.3%
앤 10
 
2.9%
도 9
 
2.6%
비 9
 
2.6%
디 9
 
2.6%
정 8
 
2.3%
엠 8
 
2.3%
원 7
 
2.0%
Other values (90) 188
53.7%
Common
ValueCountFrequency (%)
( 56
44.4%
) 56
44.4%
14
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 347
72.9%
ASCII 126
 
26.5%
None 3
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 62
 
17.9%
씨 25
 
7.2%
시 15
 
4.3%
앤 10
 
2.9%
도 9
 
2.6%
비 9
 
2.6%
디 9
 
2.6%
정 8
 
2.3%
엠 8
 
2.3%
원 7
 
2.0%
Other values (89) 185
53.3%
ASCII
ValueCountFrequency (%)
( 56
44.4%
) 56
44.4%
14
 
11.1%
None
ValueCountFrequency (%)
㈜ 3
100.0%

소재지
Text

UNIQUE 

Distinct59
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size604.0 B
2023-12-11T04:04:44.860900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length31
Mean length24.372881
Min length16

Characters and Unicode

Total characters1438
Distinct characters115
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

Unique59 ?
Unique (%)100.0%

Sample

1st row대구광역시 수성구 범어로 178(범어동)
2nd row대구광역시 수성구 범어3동 1-2
3rd row대구광역시 수성구 범어동 1-7
4th row대구광역시 수성구 범어3동 2-8
5th row대구광역시 중구 동인4가 380-2 1층
ValueCountFrequency (%)
대구광역시 59
 
20.5%
수성구 19
 
6.6%
중구 13
 
4.5%
동구 7
 
2.4%
남구 6
 
2.1%
달서구 6
 
2.1%
3층 5
 
1.7%
신천동 5
 
1.7%
범어동 4
 
1.4%
북구 4
 
1.4%
Other values (137) 160
55.6%
2023-12-11T04:04:45.535030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
229
 
15.9%
구 122
 
8.5%
동 75
 
5.2%
대 69
 
4.8%
광 60
 
4.2%
시 59
 
4.1%
역 59
 
4.1%
1 48
 
3.3%
2 44
 
3.1%
3 43
 
3.0%
Other values (105) 630
43.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 822
57.2%
Decimal Number 282
 
19.6%
Space Separator 229
 
15.9%
Dash Punctuation 33
 
2.3%
Open Punctuation 26
 
1.8%
Close Punctuation 26
 
1.8%
Other Punctuation 20
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 122
14.8%
동 75
 
9.1%
대 69
 
8.4%
광 60
 
7.3%
시 59
 
7.2%
역 59
 
7.2%
수 25
 
3.0%
로 25
 
3.0%
성 23
 
2.8%
층 21
 
2.6%
Other values (90) 284
34.5%
Decimal Number
ValueCountFrequency (%)
1 48
17.0%
2 44
15.6%
3 43
15.2%
0 28
9.9%
6 25
8.9%
4 24
8.5%
5 22
7.8%
7 19
 
6.7%
9 18
 
6.4%
8 11
 
3.9%
Space Separator
ValueCountFrequency (%)
229
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%
Other Punctuation
ValueCountFrequency (%)
, 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 822
57.2%
Common 616
42.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 122
14.8%
동 75
 
9.1%
대 69
 
8.4%
광 60
 
7.3%
시 59
 
7.2%
역 59
 
7.2%
수 25
 
3.0%
로 25
 
3.0%
성 23
 
2.8%
층 21
 
2.6%
Other values (90) 284
34.5%
Common
ValueCountFrequency (%)
229
37.2%
1 48
 
7.8%
2 44
 
7.1%
3 43
 
7.0%
- 33
 
5.4%
0 28
 
4.5%
( 26
 
4.2%
) 26
 
4.2%
6 25
 
4.1%
4 24
 
3.9%
Other values (5) 90
 
14.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 822
57.2%
ASCII 616
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
229
37.2%
1 48
 
7.8%
2 44
 
7.1%
3 43
 
7.0%
- 33
 
5.4%
0 28
 
4.5%
( 26
 
4.2%
) 26
 
4.2%
6 25
 
4.1%
4 24
 
3.9%
Other values (5) 90
 
14.6%
Hangul
ValueCountFrequency (%)
구 122
14.8%
동 75
 
9.1%
대 69
 
8.4%
광 60
 
7.3%
시 59
 
7.2%
역 59
 
7.2%
수 25
 
3.0%
로 25
 
3.0%
성 23
 
2.8%
층 21
 
2.6%
Other values (90) 284
34.5%

연락처
Text

MISSING 

Distinct19
Distinct (%)100.0%
Missing40
Missing (%)67.8%
Memory size604.0 B
2023-12-11T04:04:45.822943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters228
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

Unique19 ?
Unique (%)100.0%

Sample

1st row053-744-6339
2nd row053-355-1630
3rd row053-655-7078
4th row053-555-6951
5th row053-472-3031
ValueCountFrequency (%)
053-744-6339 1
 
5.3%
053-768-6606 1
 
5.3%
053-243-3699 1
 
5.3%
053-253-8834 1
 
5.3%
053-763-7672 1
 
5.3%
053-253-8787 1
 
5.3%
053-323-5101 1
 
5.3%
053-254-0510 1
 
5.3%
053-746-6027 1
 
5.3%
053-719-2899 1
 
5.3%
Other values (9) 9
47.4%
2023-12-11T04:04:46.346730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 39
17.1%
- 38
16.7%
3 36
15.8%
0 33
14.5%
7 15
 
6.6%
6 15
 
6.6%
2 13
 
5.7%
9 11
 
4.8%
4 10
 
4.4%
1 10
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 190
83.3%
Dash Punctuation 38
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 39
20.5%
3 36
18.9%
0 33
17.4%
7 15
 
7.9%
6 15
 
7.9%
2 13
 
6.8%
9 11
 
5.8%
4 10
 
5.3%
1 10
 
5.3%
8 8
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 228
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 39
17.1%
- 38
16.7%
3 36
15.8%
0 33
14.5%
7 15
 
6.6%
6 15
 
6.6%
2 13
 
5.7%
9 11
 
4.8%
4 10
 
4.4%
1 10
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 228
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 39
17.1%
- 38
16.7%
3 36
15.8%
0 33
14.5%
7 15
 
6.6%
6 15
 
6.6%
2 13
 
5.7%
9 11
 
4.8%
4 10
 
4.4%
1 10
 
4.4%

비 고
Text

MISSING 

Distinct35
Distinct (%)87.5%
Missing19
Missing (%)32.2%
Memory size604.0 B
2023-12-11T04:04:46.676729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length14
Mean length15.125
Min length13

Characters and Unicode

Total characters605
Distinct characters30
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

Unique33 ?
Unique (%)82.5%

Sample

1st row2014.7.11 등록취소
2nd row2006.7.25 등록취소
3rd row2006.7.25 등록취소
4th row2004.10.2 등록취소
5th row2011.4.25 등록취소
ValueCountFrequency (%)
등록취소 35
38.0%
2006.7.25 5
 
5.4%
소재지 5
 
5.4%
이관 5
 
5.4%
울산광역시로 2
 
2.2%
2004.10.2 2
 
2.2%
서울특별시로 2
 
2.2%
3.18 1
 
1.1%
2014.8.4 1
 
1.1%
부산광역시로 1
 
1.1%
Other values (33) 33
35.9%
2023-12-11T04:04:47.170887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 80
13.2%
0 77
12.7%
2 69
11.4%
52
8.6%
1 43
 
7.1%
소 40
 
6.6%
등 35
 
5.8%
록 35
 
5.8%
취 35
 
5.8%
4 20
 
3.3%
Other values (20) 119
19.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 278
46.0%
Other Letter 195
32.2%
Other Punctuation 80
 
13.2%
Space Separator 52
 
8.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 40
20.5%
등 35
17.9%
록 35
17.9%
취 35
17.9%
시 5
 
2.6%
로 5
 
2.6%
재 5
 
2.6%
지 5
 
2.6%
이 5
 
2.6%
관 5
 
2.6%
Other values (8) 20
10.3%
Decimal Number
ValueCountFrequency (%)
0 77
27.7%
2 69
24.8%
1 43
15.5%
4 20
 
7.2%
7 16
 
5.8%
6 14
 
5.0%
5 13
 
4.7%
8 11
 
4.0%
9 8
 
2.9%
3 7
 
2.5%
Other Punctuation
ValueCountFrequency (%)
. 80
100.0%
Space Separator
ValueCountFrequency (%)
52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 410
67.8%
Hangul 195
32.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 40
20.5%
등 35
17.9%
록 35
17.9%
취 35
17.9%
시 5
 
2.6%
로 5
 
2.6%
재 5
 
2.6%
지 5
 
2.6%
이 5
 
2.6%
관 5
 
2.6%
Other values (8) 20
10.3%
Common
ValueCountFrequency (%)
. 80
19.5%
0 77
18.8%
2 69
16.8%
52
12.7%
1 43
10.5%
4 20
 
4.9%
7 16
 
3.9%
6 14
 
3.4%
5 13
 
3.2%
8 11
 
2.7%
Other values (2) 15
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 410
67.8%
Hangul 195
32.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 80
19.5%
0 77
18.8%
2 69
16.8%
52
12.7%
1 43
10.5%
4 20
 
4.9%
7 16
 
3.9%
6 14
 
3.4%
5 13
 
3.2%
8 11
 
2.7%
Other values (2) 15
 
3.7%
Hangul
ValueCountFrequency (%)
소 40
20.5%
등 35
17.9%
록 35
17.9%
취 35
17.9%
시 5
 
2.6%
로 5
 
2.6%
재 5
 
2.6%
지 5
 
2.6%
이 5
 
2.6%
관 5
 
2.6%
Other values (8) 20
10.3%

Correlations

2023-12-11T04:04:47.342044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록 번호등록일자대표자상호명소재지연락처비 고
등록 번호1.0001.0001.0001.0001.0001.0001.000
등록일자1.0001.0001.0000.9911.0001.0000.934
대표자1.0001.0001.0001.0001.0001.0001.000
상호명1.0000.9911.0001.0001.0001.0000.977
소재지1.0001.0001.0001.0001.0001.0001.000
연락처1.0001.0001.0001.0001.0001.000NaN
비 고1.0000.9341.0000.9771.000NaN1.000

Missing values

2023-12-11T04:04:40.351377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T04:04:40.545094image/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.
2023-12-11T04:04:40.683947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

등록 번호등록일자대표자상호명소재지연락처비 고
0제1호2003-09-09권태형(주)태진대구광역시 수성구 범어로 178(범어동)<NA>2014.7.11 등록취소
1제2호2003-09-22김태조(주)창홍시앤시대구광역시 수성구 범어3동 1-2<NA>2006.7.25 등록취소
2제3호2003-10-07강봉기유림건설(주)대구광역시 수성구 범어동 1-7<NA>2006.7.25 등록취소
3제4호2003-10-11김재권(주)디알씨대구광역시 수성구 범어3동 2-8<NA>2004.10.2 등록취소
4제5호2003-10-13문종혁(주) 다원도시개발대구광역시 중구 동인4가 380-2 1층<NA>2011.4.25 등록취소
5제6호2003-10-22김점균(주)주성시엠시대구광역시 수성구 만촌동 1356-22<NA>2009.4.22 서울특별시로 소재지 이관
6제7호2003-10-23고중백(주)코스마씨앤엠대구광역시 동구 동부로30길 101, 다원빌딩6층 (신천동)053-744-6339<NA>
7제8호2003-10-30신용우(주)글로벌주거정비대구광역시 동구 신천동 317-2번지 3층<NA>2009.5.27 등록취소
8제9호2003-10-30김병식(주)가람에스엠대구광역시 서구 평리동 719-8<NA>2008.5.30 등록취소
9제10호2003-10-31김벽윤태영도시정비 (주)대구광역시 북구 원대로 97(노원동1가)053-355-1630<NA>
등록 번호등록일자대표자상호명소재지연락처비 고
49제50호2014-03-06장동진(주)주원도시정비대구광역시 수성구 상화로 27-1, 2층(상동)053-768-6606<NA>
50제51호2014-03-25이공조 김영주(주) 리뉴얼대구광역시 중구 경상감영길 101, 3층 307호 (포정동, 중앙상가)<NA>2014.12.03 등록취소
51제52호2014-04-10엄춘흠가람컬리션(주)대구광역시 수성구 청솔로 136, 202호(범어동, 진홍빌딩)053-746-6027<NA>
52제53호2014-06-20서성경 한태균㈜글로벌 주거정비대구광역시 중구 동덕로 36길 4, 2층 (동인동2가)053-254-0510<NA>
53제54호2014-07-01윤강모(주)남명대구광역시 북구 칠곡중앙대로 500, 2층(읍내동, 에이원빌딩)053-323-5101<NA>
54제55호2014-10-08남기복(주)유강에스앤디대구광역시 중구 국채보상로 532, 4층(수동)053-253-8787<NA>
55제56호2014-12-22이희자(주)태영디엔시대구광역시 수성구 청솔로 66, 2층(범어동)053-763-7672<NA>
56제57호2015-02-10김재학 박영식(주)태산씨엠씨대구광역시 중구 명륜로 58, 3층(남산동)053-253-8834<NA>
57제58호2015-03-09이남구㈜도시재생기획원대구광역시 남구 봉덕로10길 6(봉덕동, 1층)053-243-3699<NA>
58제59호2015-07-13이승희㈜건엽대구광역시 남구 앞산순환로63길 50(대명동)053-255-4559<NA>