Overview

Dataset statistics

Number of variables6
Number of observations366
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.6 KiB
Average record size in memory49.4 B

Variable types

Numeric1
Text4
DateTime1

Dataset

Description대전광역시 중구 소재 전문건설업등록현황에 대한 데이터로, 전문건설업 등록업체별 보유 업종, 도로명주소, 전화번호 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15119837/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:49:19.446409
Analysis finished2023-12-12 05:49:20.199765
Duration0.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct366
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean183.5
Minimum1
Maximum366
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2023-12-12T14:49:20.304349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile19.25
Q192.25
median183.5
Q3274.75
95-th percentile347.75
Maximum366
Range365
Interquartile range (IQR)182.5

Descriptive statistics

Standard deviation105.79934
Coefficient of variation (CV)0.57656315
Kurtosis-1.2
Mean183.5
Median Absolute Deviation (MAD)91.5
Skewness0
Sum67161
Variance11193.5
MonotonicityStrictly increasing
2023-12-12T14:49:20.505034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
253 1
 
0.3%
251 1
 
0.3%
250 1
 
0.3%
249 1
 
0.3%
248 1
 
0.3%
247 1
 
0.3%
246 1
 
0.3%
245 1
 
0.3%
244 1
 
0.3%
Other values (356) 356
97.3%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
366 1
0.3%
365 1
0.3%
364 1
0.3%
363 1
0.3%
362 1
0.3%
361 1
0.3%
360 1
0.3%
359 1
0.3%
358 1
0.3%
357 1
0.3%

상호명
Text

Distinct365
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-12T14:49:20.881296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length7.2978142
Min length3

Characters and Unicode

Total characters2671
Distinct characters261
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique364 ?
Unique (%)99.5%

Sample

1st row(JS)에너지
2nd row(유)미목조경개발
3rd row(주)가람
4th row(주)가온종합건설
5th row(주)강산기업
ValueCountFrequency (%)
귀뚜라미보일러설비 2
 
0.5%
신한건설산업㈜ 1
 
0.3%
에스포건설주식회사 1
 
0.3%
오양건설산업(주 1
 
0.3%
오성보일러 1
 
0.3%
오륙철물설비공사 1
 
0.3%
오뚜기설비 1
 
0.3%
예송원주식회사 1
 
0.3%
영홍설비 1
 
0.3%
엠케이이엔지(주 1
 
0.3%
Other values (355) 355
97.0%
2023-12-12T14:49:21.354666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 221
 
8.3%
( 168
 
6.3%
) 168
 
6.3%
설 131
 
4.9%
건 117
 
4.4%
사 91
 
3.4%
회 62
 
2.3%
식 62
 
2.3%
이 60
 
2.2%
비 50
 
1.9%
Other values (251) 1541
57.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2293
85.8%
Open Punctuation 168
 
6.3%
Close Punctuation 168
 
6.3%
Uppercase Letter 29
 
1.1%
Other Symbol 9
 
0.3%
Other Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 221
 
9.6%
설 131
 
5.7%
건 117
 
5.1%
사 91
 
4.0%
회 62
 
2.7%
식 62
 
2.7%
이 60
 
2.6%
비 50
 
2.2%
업 49
 
2.1%
산 46
 
2.0%
Other values (234) 1404
61.2%
Uppercase Letter
ValueCountFrequency (%)
E 6
20.7%
N 5
17.2%
G 4
13.8%
S 4
13.8%
A 2
 
6.9%
J 2
 
6.9%
O 2
 
6.9%
T 1
 
3.4%
C 1
 
3.4%
H 1
 
3.4%
Other Punctuation
ValueCountFrequency (%)
/ 2
50.0%
· 1
25.0%
. 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 168
100.0%
Close Punctuation
ValueCountFrequency (%)
) 168
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2302
86.2%
Common 340
 
12.7%
Latin 29
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 221
 
9.6%
설 131
 
5.7%
건 117
 
5.1%
사 91
 
4.0%
회 62
 
2.7%
식 62
 
2.7%
이 60
 
2.6%
비 50
 
2.2%
업 49
 
2.1%
산 46
 
2.0%
Other values (235) 1413
61.4%
Latin
ValueCountFrequency (%)
E 6
20.7%
N 5
17.2%
G 4
13.8%
S 4
13.8%
A 2
 
6.9%
J 2
 
6.9%
O 2
 
6.9%
T 1
 
3.4%
C 1
 
3.4%
H 1
 
3.4%
Common
ValueCountFrequency (%)
( 168
49.4%
) 168
49.4%
/ 2
 
0.6%
· 1
 
0.3%
. 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2293
85.8%
ASCII 368
 
13.8%
None 10
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 221
 
9.6%
설 131
 
5.7%
건 117
 
5.1%
사 91
 
4.0%
회 62
 
2.7%
식 62
 
2.7%
이 60
 
2.6%
비 50
 
2.2%
업 49
 
2.1%
산 46
 
2.0%
Other values (234) 1404
61.2%
ASCII
ValueCountFrequency (%)
( 168
45.7%
) 168
45.7%
E 6
 
1.6%
N 5
 
1.4%
G 4
 
1.1%
S 4
 
1.1%
A 2
 
0.5%
/ 2
 
0.5%
J 2
 
0.5%
O 2
 
0.5%
Other values (5) 5
 
1.4%
None
ValueCountFrequency (%)
㈜ 9
90.0%
· 1
 
10.0%

업종
Text

Distinct125
Distinct (%)34.2%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-12T14:49:21.618729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length182
Median length108
Mean length36.860656
Min length7

Characters and Unicode

Total characters13491
Distinct characters82
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)25.7%

Sample

1st row가스ㆍ난방공사업가스시설시공업 제3종(대업종전환), 난방시공업 제2종(대업종전환)
2nd row조경식재ㆍ시설물공사업 조경시설물설치공사업(대업종전환)
3rd row금속ㆍ창호ㆍ지붕ㆍ건축물조립공사업 금속구조물ㆍ창호ㆍ온실공사업(대업종전환)
4th row도장ㆍ습식ㆍ방수ㆍ석공사업 금속ㆍ창호ㆍ지붕ㆍ건축물조립공사업 지붕판금ㆍ건축물조립공사업(대업종전환) 습식ㆍ방수공사업(대업종전환)
5th row도장ㆍ습식ㆍ방수ㆍ석공사업 도장공사업(대업종전환)
ValueCountFrequency (%)
가스ㆍ난방공사업 132
 
11.1%
제2종(대업종전환 131
 
11.0%
난방시공업 98
 
8.2%
가스시설시공업 93
 
7.8%
시설물유지관리업 40
 
3.4%
실내건축공사업 39
 
3.3%
도장ㆍ습식ㆍ방수ㆍ석공사업 38
 
3.2%
기계설비ㆍ가스공사업 37
 
3.1%
금속ㆍ창호ㆍ지붕ㆍ건축물조립공사업 37
 
3.1%
제3종(대업종전환 36
 
3.0%
Other values (58) 509
42.8%
2023-12-12T14:49:22.131131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
업 1512
 
11.2%
공 959
 
7.1%
824
 
6.1%
사 767
 
5.7%
ㆍ 716
 
5.3%
종 653
 
4.8%
) 532
 
3.9%
( 532
 
3.9%
전 461
 
3.4%
대 461
 
3.4%
Other values (72) 6074
45.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11410
84.6%
Space Separator 824
 
6.1%
Close Punctuation 532
 
3.9%
Open Punctuation 532
 
3.9%
Decimal Number 192
 
1.4%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 1512
 
13.3%
공 959
 
8.4%
사 767
 
6.7%
ㆍ 716
 
6.3%
종 653
 
5.7%
전 461
 
4.0%
대 461
 
4.0%
환 461
 
4.0%
시 370
 
3.2%
설 326
 
2.9%
Other values (65) 4724
41.4%
Decimal Number
ValueCountFrequency (%)
2 133
69.3%
3 39
 
20.3%
1 20
 
10.4%
Space Separator
ValueCountFrequency (%)
824
100.0%
Close Punctuation
ValueCountFrequency (%)
) 532
100.0%
Open Punctuation
ValueCountFrequency (%)
( 532
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11410
84.6%
Common 2081
 
15.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 1512
 
13.3%
공 959
 
8.4%
사 767
 
6.7%
ㆍ 716
 
6.3%
종 653
 
5.7%
전 461
 
4.0%
대 461
 
4.0%
환 461
 
4.0%
시 370
 
3.2%
설 326
 
2.9%
Other values (65) 4724
41.4%
Common
ValueCountFrequency (%)
824
39.6%
) 532
25.6%
( 532
25.6%
2 133
 
6.4%
3 39
 
1.9%
1 20
 
1.0%
, 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10694
79.3%
ASCII 2081
 
15.4%
Compat Jamo 716
 
5.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
업 1512
 
14.1%
공 959
 
9.0%
사 767
 
7.2%
종 653
 
6.1%
전 461
 
4.3%
대 461
 
4.3%
환 461
 
4.3%
시 370
 
3.5%
설 326
 
3.0%
방 297
 
2.8%
Other values (64) 4427
41.4%
ASCII
ValueCountFrequency (%)
824
39.6%
) 532
25.6%
( 532
25.6%
2 133
 
6.4%
3 39
 
1.9%
1 20
 
1.0%
, 1
 
< 0.1%
Compat Jamo
ValueCountFrequency (%)
ㆍ 716
100.0%

도로명주소
Text

Distinct360
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-12T14:49:22.488580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length40
Mean length27.983607
Min length20

Characters and Unicode

Total characters10242
Distinct characters149
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique354 ?
Unique (%)96.7%

Sample

1st row대전광역시 중구 문화로94번길 27 (문화동)
2nd row대전광역시 중구 계룡로 803 (용두동)
3rd row대전광역시 중구 보문산로 363, 3층 (문화동)
4th row대전광역시 중구 뿌리공원로23번길 6, 1층 (안영동)
5th row대전광역시 중구 유천로142번길 17-6， 지하 1층 (태평동)
ValueCountFrequency (%)
중구 366
 
17.4%
대전광역시 365
 
17.3%
유천동 62
 
2.9%
45
 
2.1%
산성동 43
 
2.0%
1층 42
 
2.0%
태평동 33
 
1.6%
대종로 31
 
1.5%
중촌동 28
 
1.3%
2층 23
 
1.1%
Other values (481) 1071
50.8%
2023-12-12T14:49:22.981398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1743
 
17.0%
1 505
 
4.9%
대 496
 
4.8%
중 411
 
4.0%
동 404
 
3.9%
전 370
 
3.6%
) 368
 
3.6%
구 367
 
3.6%
( 367
 
3.6%
광 366
 
3.6%
Other values (139) 4845
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5686
55.5%
Decimal Number 1861
 
18.2%
Space Separator 1743
 
17.0%
Close Punctuation 368
 
3.6%
Open Punctuation 367
 
3.6%
Other Punctuation 133
 
1.3%
Dash Punctuation 77
 
0.8%
Uppercase Letter 4
 
< 0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 496
 
8.7%
중 411
 
7.2%
동 404
 
7.1%
전 370
 
6.5%
구 367
 
6.5%
광 366
 
6.4%
역 365
 
6.4%
시 365
 
6.4%
로 363
 
6.4%
길 188
 
3.3%
Other values (117) 1991
35.0%
Decimal Number
ValueCountFrequency (%)
1 505
27.1%
2 219
11.8%
3 184
 
9.9%
4 173
 
9.3%
0 162
 
8.7%
5 149
 
8.0%
6 141
 
7.6%
7 127
 
6.8%
9 110
 
5.9%
8 91
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
B 2
50.0%
D 1
25.0%
A 1
25.0%
Lowercase Letter
ValueCountFrequency (%)
o 1
33.3%
n 1
33.3%
e 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 115
86.5%
， 18
 
13.5%
Space Separator
ValueCountFrequency (%)
1743
100.0%
Close Punctuation
ValueCountFrequency (%)
) 368
100.0%
Open Punctuation
ValueCountFrequency (%)
( 367
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 77
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5686
55.5%
Common 4549
44.4%
Latin 7
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 496
 
8.7%
중 411
 
7.2%
동 404
 
7.1%
전 370
 
6.5%
구 367
 
6.5%
광 366
 
6.4%
역 365
 
6.4%
시 365
 
6.4%
로 363
 
6.4%
길 188
 
3.3%
Other values (117) 1991
35.0%
Common
ValueCountFrequency (%)
1743
38.3%
1 505
 
11.1%
) 368
 
8.1%
( 367
 
8.1%
2 219
 
4.8%
3 184
 
4.0%
4 173
 
3.8%
0 162
 
3.6%
5 149
 
3.3%
6 141
 
3.1%
Other values (6) 538
 
11.8%
Latin
ValueCountFrequency (%)
B 2
28.6%
D 1
14.3%
o 1
14.3%
n 1
14.3%
e 1
14.3%
A 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5686
55.5%
ASCII 4538
44.3%
None 18
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1743
38.4%
1 505
 
11.1%
) 368
 
8.1%
( 367
 
8.1%
2 219
 
4.8%
3 184
 
4.1%
4 173
 
3.8%
0 162
 
3.6%
5 149
 
3.3%
6 141
 
3.1%
Other values (11) 527
 
11.6%
Hangul
ValueCountFrequency (%)
대 496
 
8.7%
중 411
 
7.2%
동 404
 
7.1%
전 370
 
6.5%
구 367
 
6.5%
광 366
 
6.4%
역 365
 
6.4%
시 365
 
6.4%
로 363
 
6.4%
길 188
 
3.3%
Other values (117) 1991
35.0%
None
ValueCountFrequency (%)
， 18
100.0%

전화번호
Text

Distinct339
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-12T14:49:23.223877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.114754
Min length11

Characters and Unicode

Total characters4434
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

Unique329 ?
Unique (%)89.9%

Sample

1st row042-000-0000
2nd row042-222-1155
3rd row042-581-1404
4th row043-295-1214
5th row042-582-9602
ValueCountFrequency (%)
042-0000-0000 8
 
2.2%
00-000-0000 8
 
2.2%
0000-0000-0000 6
 
1.6%
042-000-0000 3
 
0.8%
000-0000-0000 2
 
0.5%
042-632-7988 2
 
0.5%
042-534-8012 2
 
0.5%
042-586-3756 2
 
0.5%
042-632-3456 2
 
0.5%
042-622-7723 2
 
0.5%
Other values (329) 329
89.9%
2023-12-12T14:49:23.587410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 873
19.7%
- 732
16.5%
2 697
15.7%
4 500
11.3%
5 385
8.7%
8 260
 
5.9%
3 239
 
5.4%
1 233
 
5.3%
7 198
 
4.5%
6 195
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3702
83.5%
Dash Punctuation 732
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 873
23.6%
2 697
18.8%
4 500
13.5%
5 385
10.4%
8 260
 
7.0%
3 239
 
6.5%
1 233
 
6.3%
7 198
 
5.3%
6 195
 
5.3%
9 122
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 732
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4434
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 873
19.7%
- 732
16.5%
2 697
15.7%
4 500
11.3%
5 385
8.7%
8 260
 
5.9%
3 239
 
5.4%
1 233
 
5.3%
7 198
 
4.5%
6 195
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4434
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 873
19.7%
- 732
16.5%
2 697
15.7%
4 500
11.3%
5 385
8.7%
8 260
 
5.9%
3 239
 
5.4%
1 233
 
5.3%
7 198
 
4.5%
6 195
 
4.4%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
Minimum2023-08-22 00:00:00
Maximum2023-08-22 00:00:00
2023-12-12T14:49:23.720042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:49:23.831176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T14:49:19.814306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T14:49:19.993415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:49:20.133478image/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

연번상호명업종도로명주소전화번호데이터기준일자
01(JS)에너지가스ㆍ난방공사업가스시설시공업 제3종(대업종전환), 난방시공업 제2종(대업종전환)대전광역시 중구 문화로94번길 27 (문화동)042-000-00002023-08-22
12(유)미목조경개발조경식재ㆍ시설물공사업 조경시설물설치공사업(대업종전환)대전광역시 중구 계룡로 803 (용두동)042-222-11552023-08-22
23(주)가람금속ㆍ창호ㆍ지붕ㆍ건축물조립공사업 금속구조물ㆍ창호ㆍ온실공사업(대업종전환)대전광역시 중구 보문산로 363, 3층 (문화동)042-581-14042023-08-22
34(주)가온종합건설도장ㆍ습식ㆍ방수ㆍ석공사업 금속ㆍ창호ㆍ지붕ㆍ건축물조립공사업 지붕판금ㆍ건축물조립공사업(대업종전환) 습식ㆍ방수공사업(대업종전환)대전광역시 중구 뿌리공원로23번길 6, 1층 (안영동)043-295-12142023-08-22
45(주)강산기업도장ㆍ습식ㆍ방수ㆍ석공사업 도장공사업(대업종전환)대전광역시 중구 유천로142번길 17-6， 지하 1층 (태평동)042-582-96022023-08-22
56(주)거성이앤씨구조물해체ㆍ비계공사업 비계ㆍ구조물해체공사업(대업종전환)대전광역시 중구 목중로10번길 8 1층 (중촌동)042-522-88312023-08-22
67(주)거웅특수건설도장ㆍ습식ㆍ방수ㆍ석공사업 습식ㆍ방수공사업(대업종전환)대전광역시 중구 대종로 553 , 107호 (선화동,청구빌딩)042-632-19662023-08-22
78(주)건국도장ㆍ습식ㆍ방수ㆍ석공사업 석공사업(대업종전환)대전광역시 중구 대둔산로184번길 48 2층 (안영동)042-583-64072023-08-22
89(주)경국기계설비ㆍ가스공사업 기계설비공사업(대업종전환)대전광역시 중구 동서대로 1270 2층 (태평동)042-256-54002023-08-22
910(주)경원건설산업실내건축공사업 실내건축공사업(대업종전환)대전광역시 중구 대둔산로 419-4, 308호 (산성동, 한밭프라자)042-362-58762023-08-22
연번상호명업종도로명주소전화번호데이터기준일자
356357행복테크가스ㆍ난방공사업대전광역시 중구 대종로 698 (중촌동)042-252-52662023-08-22
357358현대공영(주)조경식재ㆍ시설물공사업 시설물유지관리업 조경식재공사업(대업종전환)대전광역시 중구 태평로44번길 27 132호 (유천동, 현암에버드림아파트)042-256-22002023-08-22
358359현대포장건설(주)지반조성ㆍ포장공사업 포장공사업(대업종전환)대전광역시 중구 태평로113번길 53 1층 (태평동)042-537-01562023-08-22
359360현주설비가스ㆍ난방공사업 가스시설시공업 제2종(대업종전환) 난방시공업 제2종(대업종전환)대전광역시 중구 산성로15번길 18(산성동，1층)042-000-00002023-08-22
360361현진건설창호지닷컴가스ㆍ난방공사업 가스시설시공업 제2종(대업종전환)대전광역시 중구 동서대로1250번길 8-2 , 401호 (태평동)042-528-90912023-08-22
361362현진설비가스ㆍ난방공사업 가스시설시공업 제3종(폐업) 난방시공업 제2종(대업종전환)대전광역시 중구 유천로33번길 41 (유천동)042-584-97042023-08-22
362363혜성산업가스ㆍ난방공사업 난방시공업 제2종(대업종전환) 가스시설시공업 제3종(대업종전환)대전광역시 중구 문화로163번길 27 (문화동)042-585-75232023-08-22
363364호ENG가스ㆍ난방공사업 난방시공업 제2종(대업종전환) 가스시설시공업 제3종(대업종전환)대전광역시 중구 보문로 134-1 (대사동)042-5218-30352023-08-22
364365호광건설(주)시설물유지관리업대전광역시 중구 대둔산로446번길 36 1층 상가 (산성동)042-824-25452023-08-22
365366효성조경개발(주)기계설비ㆍ가스공사업 철근ㆍ콘크리트공사업 조경식재ㆍ시설물공사업 상ㆍ하수도설비공사업 시설물유지관리업 조경시설물설치공사업(폐업) 조경식재공사업(대업종전환) 철근ㆍ콘크리트공사업(대업종전환) 기계설비공사업(대업종전환) 상ㆍ하수도설비공사업(대업종전환)대전광역시 중구 대둔산로 419-4， 901-1호(산성동，한밭프라자)042-584-21462023-08-22