Overview

Dataset statistics

Number of variables8
Number of observations126
Missing cells20
Missing cells (%)2.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.0 KiB
Average record size in memory65.0 B

Variable types

Categorical4
Text3
DateTime1

Dataset

Description전라남도 소방시설 설계업체 현황 (상호명, 주소, 소방시설업 등록번호, 등록일자, 폐업여부)에 관한 데이터를 조회하실 수 있게 제공하고 있습니다.
Author전라남도
URLhttps://www.data.go.kr/data/3036060/fileData.do

Alerts

업종 has constant value ""Constant
지역 is highly overall correlated with 폐업여부High correlation
분야 is highly overall correlated with 폐업여부High correlation
폐업여부 is highly overall correlated with 지역 and 1 other fieldsHigh correlation
등록일자 has 20 (15.9%) missing valuesMissing

Reproduction

Analysis started2023-12-12 13:11:07.921003
Analysis finished2023-12-12 13:11:08.770584
Duration0.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지역
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
여수시
31 
목포시
24 
순천시
20 
나주시
16 
해남군
6 
Other values (8)
29 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st row여수시
2nd row여수시
3rd row여수시
4th row여수시
5th row여수시

Common Values

ValueCountFrequency (%)
여수시 31
24.6%
목포시 24
19.0%
순천시 20
15.9%
나주시 16
12.7%
해남군 6
 
4.8%
광양시 6
 
4.8%
담양군 5
 
4.0%
장성군 5
 
4.0%
영광군 4
 
3.2%
화순군 3
 
2.4%
Other values (3) 6
 
4.8%

Length

2023-12-12T22:11:08.834917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
여수시 31
24.6%
목포시 24
19.0%
순천시 20
15.9%
나주시 16
12.7%
해남군 6
 
4.8%
광양시 6
 
4.8%
담양군 5
 
4.0%
장성군 5
 
4.0%
영광군 4
 
3.2%
화순군 3
 
2.4%
Other values (3) 6
 
4.8%

상호
Text

Distinct74
Distinct (%)58.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T22:11:09.123878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12.5
Mean length9.1190476
Min length5

Characters and Unicode

Total characters1149
Distinct characters119
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)17.5%

Sample

1st row(주)영동이앤씨
2nd row(유)성전이엔씨
3rd row(유)성전이엔씨
4th row(유)대성소방공사
5th row(유)대성소방공사
ValueCountFrequency (%)
주식회사 46
 
24.6%
유한회사 9
 
4.8%
유)우영소방 2
 
1.1%
성전소방이엔지 2
 
1.1%
대담 2
 
1.1%
유)성전이엔씨 2
 
1.1%
한동건설엔지니어링 2
 
1.1%
건축사사무소 2
 
1.1%
가인 2
 
1.1%
우리소방eng 2
 
1.1%
Other values (69) 116
62.0%
2023-12-12T22:11:09.531295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 86
 
7.5%
사 66
 
5.7%
61
 
5.3%
엔 56
 
4.9%
회 55
 
4.8%
( 55
 
4.8%
) 55
 
4.8%
지 54
 
4.7%
식 46
 
4.0%
이 43
 
3.7%
Other values (109) 572
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 941
81.9%
Space Separator 61
 
5.3%
Open Punctuation 55
 
4.8%
Close Punctuation 55
 
4.8%
Uppercase Letter 37
 
3.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 86
 
9.1%
사 66
 
7.0%
엔 56
 
6.0%
회 55
 
5.8%
지 54
 
5.7%
식 46
 
4.9%
이 43
 
4.6%
니 29
 
3.1%
유 29
 
3.1%
링 29
 
3.1%
Other values (98) 448
47.6%
Uppercase Letter
ValueCountFrequency (%)
E 9
24.3%
N 9
24.3%
G 7
18.9%
S 4
10.8%
C 2
 
5.4%
K 2
 
5.4%
T 2
 
5.4%
F 2
 
5.4%
Space Separator
ValueCountFrequency (%)
61
100.0%
Open Punctuation
ValueCountFrequency (%)
( 55
100.0%
Close Punctuation
ValueCountFrequency (%)
) 55
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 941
81.9%
Common 171
 
14.9%
Latin 37
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 86
 
9.1%
사 66
 
7.0%
엔 56
 
6.0%
회 55
 
5.8%
지 54
 
5.7%
식 46
 
4.9%
이 43
 
4.6%
니 29
 
3.1%
유 29
 
3.1%
링 29
 
3.1%
Other values (98) 448
47.6%
Latin
ValueCountFrequency (%)
E 9
24.3%
N 9
24.3%
G 7
18.9%
S 4
10.8%
C 2
 
5.4%
K 2
 
5.4%
T 2
 
5.4%
F 2
 
5.4%
Common
ValueCountFrequency (%)
61
35.7%
( 55
32.2%
) 55
32.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 941
81.9%
ASCII 208
 
18.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 86
 
9.1%
사 66
 
7.0%
엔 56
 
6.0%
회 55
 
5.8%
지 54
 
5.7%
식 46
 
4.9%
이 43
 
4.6%
니 29
 
3.1%
유 29
 
3.1%
링 29
 
3.1%
Other values (98) 448
47.6%
ASCII
ValueCountFrequency (%)
61
29.3%
( 55
26.4%
) 55
26.4%
E 9
 
4.3%
N 9
 
4.3%
G 7
 
3.4%
S 4
 
1.9%
C 2
 
1.0%
K 2
 
1.0%
T 2
 
1.0%

주소
Text

Distinct73
Distinct (%)57.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T22:11:09.913670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length43
Mean length34.031746
Min length29

Characters and Unicode

Total characters4288
Distinct characters160
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

Unique20 ?
Unique (%)15.9%

Sample

1st row(59632) 전라남도 여수시 봉계6길 12-1 (봉계동)
2nd row(59635) 전라남도 여수시 좌수영로 889 , 2층(여천동)
3rd row(59635) 전라남도 여수시 좌수영로 889 , 2층(여천동)
4th row(59680) 전라남도 여수시 신기북2길 15 (신기동)
5th row(59680) 전라남도 여수시 신기북2길 15 (신기동)
ValueCountFrequency (%)
전라남도 126
 
15.3%
35
 
4.2%
여수시 31
 
3.8%
목포시 24
 
2.9%
순천시 20
 
2.4%
나주시 16
 
1.9%
조례동 7
 
0.8%
57970 7
 
0.8%
58325 7
 
0.8%
59674 6
 
0.7%
Other values (258) 545
66.1%
2023-12-12T22:11:10.470832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
706
 
16.5%
( 242
 
5.6%
) 242
 
5.6%
5 195
 
4.5%
남 154
 
3.6%
전 129
 
3.0%
라 128
 
3.0%
도 126
 
2.9%
2 125
 
2.9%
7 120
 
2.8%
Other values (150) 2121
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1904
44.4%
Decimal Number 1103
25.7%
Space Separator 706
 
16.5%
Open Punctuation 242
 
5.6%
Close Punctuation 242
 
5.6%
Other Punctuation 56
 
1.3%
Dash Punctuation 35
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 154
 
8.1%
전 129
 
6.8%
라 128
 
6.7%
도 126
 
6.6%
동 119
 
6.2%
시 105
 
5.5%
로 71
 
3.7%
길 69
 
3.6%
여 42
 
2.2%
수 39
 
2.0%
Other values (135) 922
48.4%
Decimal Number
ValueCountFrequency (%)
5 195
17.7%
2 125
11.3%
7 120
10.9%
1 120
10.9%
3 111
10.1%
6 96
8.7%
8 94
8.5%
9 85
7.7%
0 81
7.3%
4 76
 
6.9%
Space Separator
ValueCountFrequency (%)
706
100.0%
Open Punctuation
ValueCountFrequency (%)
( 242
100.0%
Close Punctuation
ValueCountFrequency (%)
) 242
100.0%
Other Punctuation
ValueCountFrequency (%)
, 56
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2384
55.6%
Hangul 1904
44.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 154
 
8.1%
전 129
 
6.8%
라 128
 
6.7%
도 126
 
6.6%
동 119
 
6.2%
시 105
 
5.5%
로 71
 
3.7%
길 69
 
3.6%
여 42
 
2.2%
수 39
 
2.0%
Other values (135) 922
48.4%
Common
ValueCountFrequency (%)
706
29.6%
( 242
 
10.2%
) 242
 
10.2%
5 195
 
8.2%
2 125
 
5.2%
7 120
 
5.0%
1 120
 
5.0%
3 111
 
4.7%
6 96
 
4.0%
8 94
 
3.9%
Other values (5) 333
14.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2384
55.6%
Hangul 1904
44.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
706
29.6%
( 242
 
10.2%
) 242
 
10.2%
5 195
 
8.2%
2 125
 
5.2%
7 120
 
5.0%
1 120
 
5.0%
3 111
 
4.7%
6 96
 
4.0%
8 94
 
3.9%
Other values (5) 333
14.0%
Hangul
ValueCountFrequency (%)
남 154
 
8.1%
전 129
 
6.8%
라 128
 
6.7%
도 126
 
6.6%
동 119
 
6.2%
시 105
 
5.5%
로 71
 
3.7%
길 69
 
3.6%
여 42
 
2.2%
수 39
 
2.0%
Other values (135) 922
48.4%

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
설계업
126 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row설계업
2nd row설계업
3rd row설계업
4th row설계업
5th row설계업

Common Values

ValueCountFrequency (%)
설계업 126
100.0%

Length

2023-12-12T22:11:10.629385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:11:10.726259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
설계업 126
100.0%

분야
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
일반(전기)
50 
일반(기계)
48 
전문
10 
일반(전기),일반(기계)
6 
일반(전기),일반(전기),일반(기계),일반(기계)
 
4
Other values (5)
8 

Length

Max length34
Median length6
Mean length7.7539683
Min length2

Unique

Unique2 ?
Unique (%)1.6%

Sample

1st row전문
2nd row일반(기계)
3rd row일반(전기)
4th row일반(기계)
5th row일반(전기)

Common Values

ValueCountFrequency (%)
일반(전기) 50
39.7%
일반(기계) 48
38.1%
전문 10
 
7.9%
일반(전기),일반(기계) 6
 
4.8%
일반(전기),일반(전기),일반(기계),일반(기계) 4
 
3.2%
전문,일반(전기),일반(전기),일반(기계),일반(기계) 2
 
1.6%
전문,일반(전기),일반(기계) 2
 
1.6%
전문,전문,일반(전기),일반(기계),일반(기계) 2
 
1.6%
전문,전문 1
 
0.8%
일반(전기),일반(전기),일반(기계),일반(기계),일반(기계) 1
 
0.8%

Length

2023-12-12T22:11:10.851552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:11:10.986912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반(전기 50
39.7%
일반(기계 48
38.1%
전문 10
 
7.9%
일반(전기),일반(기계 6
 
4.8%
일반(전기),일반(전기),일반(기계),일반(기계 4
 
3.2%
전문,일반(전기),일반(전기),일반(기계),일반(기계 2
 
1.6%
전문,일반(전기),일반(기계 2
 
1.6%
전문,전문,일반(전기),일반(기계),일반(기계 2
 
1.6%
전문,전문 1
 
0.8%
일반(전기),일반(전기),일반(기계),일반(기계),일반(기계 1
 
0.8%

소방시설업 등록번호
Text

Distinct78
Distinct (%)61.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T22:11:11.225385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length13
Mean length11.84127
Min length8

Characters and Unicode

Total characters1492
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)24.6%

Sample

1st row2021-01-00107
2nd row제2011-나-8호
3rd row제2011-나-8호
4th row2019-01-00132
5th row2019-01-00132
ValueCountFrequency (%)
제2005-2호 3
 
2.4%
제2013-카-02호 2
 
1.6%
제2011-나-8호 2
 
1.6%
2019-01-00038 2
 
1.6%
2020-01-00024 2
 
1.6%
2018-01-00028 2
 
1.6%
제2006-가-1호 2
 
1.6%
제2008-가-1호 2
 
1.6%
제2003-3호 2
 
1.6%
제2014-나-3호 2
 
1.6%
Other values (68) 105
83.3%
2023-12-12T22:11:11.619730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 476
31.9%
- 243
16.3%
2 216
14.5%
1 208
13.9%
제 47
 
3.2%
호 47
 
3.2%
3 41
 
2.7%
8 38
 
2.5%
4 32
 
2.1%
6 29
 
1.9%
Other values (16) 115
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1113
74.6%
Dash Punctuation 243
 
16.3%
Other Letter 136
 
9.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 47
34.6%
호 47
34.6%
가 11
 
8.1%
나 11
 
8.1%
라 5
 
3.7%
카 3
 
2.2%
아 2
 
1.5%
차 2
 
1.5%
자 2
 
1.5%
마 1
 
0.7%
Other values (5) 5
 
3.7%
Decimal Number
ValueCountFrequency (%)
0 476
42.8%
2 216
19.4%
1 208
18.7%
3 41
 
3.7%
8 38
 
3.4%
4 32
 
2.9%
6 29
 
2.6%
9 29
 
2.6%
5 26
 
2.3%
7 18
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 243
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1356
90.9%
Hangul 136
 
9.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 47
34.6%
호 47
34.6%
가 11
 
8.1%
나 11
 
8.1%
라 5
 
3.7%
카 3
 
2.2%
아 2
 
1.5%
차 2
 
1.5%
자 2
 
1.5%
마 1
 
0.7%
Other values (5) 5
 
3.7%
Common
ValueCountFrequency (%)
0 476
35.1%
- 243
17.9%
2 216
15.9%
1 208
15.3%
3 41
 
3.0%
8 38
 
2.8%
4 32
 
2.4%
6 29
 
2.1%
9 29
 
2.1%
5 26
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1356
90.9%
Hangul 136
 
9.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 476
35.1%
- 243
17.9%
2 216
15.9%
1 208
15.3%
3 41
 
3.0%
8 38
 
2.8%
4 32
 
2.4%
6 29
 
2.1%
9 29
 
2.1%
5 26
 
1.9%
Hangul
ValueCountFrequency (%)
제 47
34.6%
호 47
34.6%
가 11
 
8.1%
나 11
 
8.1%
라 5
 
3.7%
카 3
 
2.2%
아 2
 
1.5%
차 2
 
1.5%
자 2
 
1.5%
마 1
 
0.7%
Other values (5) 5
 
3.7%

등록일자
Date

MISSING 

Distinct65
Distinct (%)61.3%
Missing20
Missing (%)15.9%
Memory size1.1 KiB
Minimum1995-01-06 00:00:00
Maximum2023-07-24 00:00:00
2023-12-12T22:11:11.814552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:11:12.010351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

폐업여부
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
101 
폐업
20 
휴업
 
5

Length

Max length4
Median length4
Mean length3.6031746
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 101
80.2%
폐업 20
 
15.9%
휴업 5
 
4.0%

Length

2023-12-12T22:11:12.158722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:11:12.284951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 101
80.2%
폐업 20
 
15.9%
휴업 5
 
4.0%

Correlations

2023-12-12T22:11:12.367230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역상호주소분야소방시설업 등록번호등록일자폐업여부
지역1.0001.0001.0000.0001.0001.0000.769
상호1.0001.0001.0000.9851.0001.0000.916
주소1.0001.0001.0000.9821.0001.0000.916
분야0.0000.9850.9821.0000.9720.0000.974
소방시설업 등록번호1.0001.0001.0000.9721.0001.0000.585
등록일자1.0001.0001.0000.0001.0001.000NaN
폐업여부0.7690.9160.9160.9740.585NaN1.000
2023-12-12T22:11:12.483513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
폐업여부지역분야
폐업여부1.0000.5020.692
지역0.5021.0000.000
분야0.6920.0001.000
2023-12-12T22:11:12.600105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역분야폐업여부
지역1.0000.0000.502
분야0.0001.0000.692
폐업여부0.5020.6921.000

Missing values

2023-12-12T22:11:08.568566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:11:08.712339image/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

지역상호주소업종분야소방시설업 등록번호등록일자폐업여부
0여수시(주)영동이앤씨(59632) 전라남도 여수시 봉계6길 12-1 (봉계동)설계업전문2021-01-001072021-08-25<NA>
1여수시(유)성전이엔씨(59635) 전라남도 여수시 좌수영로 889 , 2층(여천동)설계업일반(기계)제2011-나-8호2011-05-31<NA>
2여수시(유)성전이엔씨(59635) 전라남도 여수시 좌수영로 889 , 2층(여천동)설계업일반(전기)제2011-나-8호2011-05-31<NA>
3여수시(유)대성소방공사(59680) 전라남도 여수시 신기북2길 15 (신기동)설계업일반(기계)2019-01-001322019-08-22<NA>
4여수시(유)대성소방공사(59680) 전라남도 여수시 신기북2길 15 (신기동)설계업일반(전기)2019-01-001322019-08-22<NA>
5순천시(주)두일이앤씨(58024) 전라남도 순천시 해룡면 여순로 1211 ()설계업일반(전기),일반(전기),일반(기계),일반(기계)2015-01-00076<NA>폐업
6순천시(주)두일이앤씨(58024) 전라남도 순천시 해룡면 여순로 1211 ()설계업일반(전기),일반(전기),일반(기계),일반(기계)2021-01-00024<NA>폐업
7목포시(주)백두기연(58600) 전라남도 목포시 대양산단로97번길 33 (대양동)설계업일반(기계)2020-01-001032020-07-15<NA>
8목포시(주)백두기연(58600) 전라남도 목포시 대양산단로97번길 33 (대양동)설계업일반(전기)2020-01-001032020-07-15<NA>
9화순군주식회사 유탑엔지니어링(58118) 전라남도 화순군 화순읍 자치샘로 48 ,310호(미래타워)설계업전문제2012-카-26호<NA>폐업
지역상호주소업종분야소방시설업 등록번호등록일자폐업여부
116순천시금아이엔지 주식회사(57978) 전라남도 순천시 연향2로 19 (연향동)설계업일반(전기)2022-01-001042022-10-12<NA>
117여수시주식회사 대신소방기술(59678) 전라남도 여수시 쌍봉로 135 , 2층(학동)설계업일반(기계)2022-01-001162022-11-30<NA>
118여수시주식회사 대신소방기술(59678) 전라남도 여수시 쌍봉로 135 , 2층(학동)설계업일반(전기)2022-01-001162022-11-30<NA>
119해남군강부건설이엔지 주식회사(59031) 전라남도 해남군 해남읍 중앙1로 477 ()설계업일반(기계)2023-01-000082023-01-17<NA>
120해남군강부건설이엔지 주식회사(59031) 전라남도 해남군 해남읍 중앙1로 477 ()설계업일반(전기)2023-01-000082023-01-17<NA>
121광양시주식회사 이레기술사사무소(57784) 전라남도 광양시 중동1길 21 ,2층(중동)설계업일반(기계)2023-01-000182023-01-31<NA>
122광양시주식회사 이레기술사사무소(57784) 전라남도 광양시 중동1길 21 ,2층(중동)설계업일반(전기)2023-01-000182023-01-31<NA>
123고흥군유한회사 장강(59540) 전라남도 고흥군 고흥읍 여산당촌길 23 ,301호(고흥군산림조합청사)설계업전문2023-01-000792023-07-24<NA>
124순천시유한회사 로운이엔지(57924) 전라남도 순천시 고지5길 11 (가곡동)설계업일반(기계)2023-01-000482023-04-28<NA>
125순천시유한회사 로운이엔지(57924) 전라남도 순천시 고지5길 11 (가곡동)설계업일반(전기)2023-01-000482023-04-28<NA>