Overview

Dataset statistics

Number of variables9
Number of observations30
Missing cells6
Missing cells (%)2.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory76.4 B

Variable types

Unsupported2
Categorical3
Text4

Dataset

Description소방시설설계,공사,감리,방염,관리업현황201711
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202866

Alerts

Unnamed: 7 is highly overall correlated with Unnamed: 1High correlation
Unnamed: 2 is highly overall correlated with Unnamed: 1High correlation
Unnamed: 1 is highly overall correlated with Unnamed: 2 and 1 other fieldsHigh correlation
Unnamed: 1 is highly imbalanced (73.5%)Imbalance
Unnamed: 7 is highly imbalanced (50.5%)Imbalance
소방시설 설계업 등록 현황 has 1 (3.3%) missing valuesMissing
Unnamed: 3 has 1 (3.3%) missing valuesMissing
Unnamed: 4 has 1 (3.3%) missing valuesMissing
Unnamed: 5 has 1 (3.3%) missing valuesMissing
Unnamed: 6 has 1 (3.3%) missing valuesMissing
Unnamed: 8 has 1 (3.3%) missing valuesMissing
소방시설 설계업 등록 현황 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 6 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 01:22:47.791914
Analysis finished2024-03-14 01:22:48.471811
Duration0.68 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

소방시설 설계업 등록 현황
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1
Missing (%)3.3%
Memory size372.0 B

Unnamed: 1
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
전북
28 
<NA>
 
1
도
 
1

Length

Max length4
Median length2
Mean length2.0333333
Min length1

Unique

Unique2 ?
Unique (%)6.7%

Sample

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

Common Values

ValueCountFrequency (%)
전북 28
93.3%
<NA> 1
 
3.3%
도 1
 
3.3%

Length

2024-03-14T10:22:48.526350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:22:48.612261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전북 28
93.3%
na 1
 
3.3%
도 1
 
3.3%

Unnamed: 2
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
전주시
19 
익산시
3 
군산시
2 
부안군
2 
<NA>
 
1
Other values (3)
3 

Length

Max length4
Median length3
Mean length3.0333333
Min length3

Unique

Unique4 ?
Unique (%)13.3%

Sample

1st row<NA>
2nd row시.군
3rd row전주시
4th row전주시
5th row전주시

Common Values

ValueCountFrequency (%)
전주시 19
63.3%
익산시 3
 
10.0%
군산시 2
 
6.7%
부안군 2
 
6.7%
<NA> 1
 
3.3%
시.군 1
 
3.3%
정읍시 1
 
3.3%
남원시 1
 
3.3%

Length

2024-03-14T10:22:48.721604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:22:48.835682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전주시 19
63.3%
익산시 3
 
10.0%
군산시 2
 
6.7%
부안군 2
 
6.7%
na 1
 
3.3%
시.군 1
 
3.3%
정읍시 1
 
3.3%
남원시 1
 
3.3%

Unnamed: 3
Text

MISSING 

Distinct29
Distinct (%)100.0%
Missing1
Missing (%)3.3%
Memory size372.0 B
2024-03-14T10:22:49.012794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length7.8965517
Min length2

Characters and Unicode

Total characters229
Distinct characters72
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

Unique29 ?
Unique (%)100.0%

Sample

1st row상호
2nd row티앤제이건설(주)
3rd row(주)주연이엔지
4th row(주)덕진소방
5th row(주)대신기술단
ValueCountFrequency (%)
주식회사 2
 
6.5%
상호 1
 
3.2%
주)호원엔지니어링 1
 
3.2%
태인엔지니어링(주 1
 
3.2%
세웅이엔씨 1
 
3.2%
유)우석엔지니어링 1
 
3.2%
주)대성건축사사무소 1
 
3.2%
유)광진이엔지 1
 
3.2%
지오방재이엔씨(주 1
 
3.2%
유스파워(주 1
 
3.2%
Other values (20) 20
64.5%
2024-03-14T10:22:49.483983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 21
 
9.2%
) 21
 
9.2%
주 16
 
7.0%
엔 14
 
6.1%
지 13
 
5.7%
유 10
 
4.4%
이 9
 
3.9%
링 8
 
3.5%
어 8
 
3.5%
니 8
 
3.5%
Other values (62) 101
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 182
79.5%
Open Punctuation 21
 
9.2%
Close Punctuation 21
 
9.2%
Uppercase Letter 3
 
1.3%
Space Separator 2
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 16
 
8.8%
엔 14
 
7.7%
지 13
 
7.1%
유 10
 
5.5%
이 9
 
4.9%
링 8
 
4.4%
어 8
 
4.4%
니 8
 
4.4%
사 7
 
3.8%
대 4
 
2.2%
Other values (56) 85
46.7%
Uppercase Letter
ValueCountFrequency (%)
E 1
33.3%
S 1
33.3%
C 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 182
79.5%
Common 44
 
19.2%
Latin 3
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 16
 
8.8%
엔 14
 
7.7%
지 13
 
7.1%
유 10
 
5.5%
이 9
 
4.9%
링 8
 
4.4%
어 8
 
4.4%
니 8
 
4.4%
사 7
 
3.8%
대 4
 
2.2%
Other values (56) 85
46.7%
Common
ValueCountFrequency (%)
( 21
47.7%
) 21
47.7%
2
 
4.5%
Latin
ValueCountFrequency (%)
E 1
33.3%
S 1
33.3%
C 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 182
79.5%
ASCII 47
 
20.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 21
44.7%
) 21
44.7%
2
 
4.3%
E 1
 
2.1%
S 1
 
2.1%
C 1
 
2.1%
Hangul
ValueCountFrequency (%)
주 16
 
8.8%
엔 14
 
7.7%
지 13
 
7.1%
유 10
 
5.5%
이 9
 
4.9%
링 8
 
4.4%
어 8
 
4.4%
니 8
 
4.4%
사 7
 
3.8%
대 4
 
2.2%
Other values (56) 85
46.7%

Unnamed: 4
Text

MISSING 

Distinct29
Distinct (%)100.0%
Missing1
Missing (%)3.3%
Memory size372.0 B
2024-03-14T10:22:49.645264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9655172
Min length2

Characters and Unicode

Total characters86
Distinct characters55
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)100.0%

Sample

1st row대표자
2nd row고태유
3rd row김종배
4th row박동규
5th row왕영식
ValueCountFrequency (%)
대표자 1
 
3.4%
신장근 1
 
3.4%
시춘근 1
 
3.4%
이영욱 1
 
3.4%
이성준 1
 
3.4%
김창호 1
 
3.4%
이춘우 1
 
3.4%
장영철 1
 
3.4%
고환구 1
 
3.4%
권성훈 1
 
3.4%
Other values (19) 19
65.5%
2024-03-14T10:22:49.899257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
영 7
 
8.1%
김 6
 
7.0%
종 3
 
3.5%
박 3
 
3.5%
이 3
 
3.5%
장 2
 
2.3%
성 2
 
2.3%
섭 2
 
2.3%
우 2
 
2.3%
송 2
 
2.3%
Other values (45) 54
62.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 86
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 7
 
8.1%
김 6
 
7.0%
종 3
 
3.5%
박 3
 
3.5%
이 3
 
3.5%
장 2
 
2.3%
성 2
 
2.3%
섭 2
 
2.3%
우 2
 
2.3%
송 2
 
2.3%
Other values (45) 54
62.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 86
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 7
 
8.1%
김 6
 
7.0%
종 3
 
3.5%
박 3
 
3.5%
이 3
 
3.5%
장 2
 
2.3%
성 2
 
2.3%
섭 2
 
2.3%
우 2
 
2.3%
송 2
 
2.3%
Other values (45) 54
62.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 86
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
영 7
 
8.1%
김 6
 
7.0%
종 3
 
3.5%
박 3
 
3.5%
이 3
 
3.5%
장 2
 
2.3%
성 2
 
2.3%
섭 2
 
2.3%
우 2
 
2.3%
송 2
 
2.3%
Other values (45) 54
62.8%

Unnamed: 5
Text

MISSING 

Distinct29
Distinct (%)100.0%
Missing1
Missing (%)3.3%
Memory size372.0 B
2024-03-14T10:22:50.148795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length33
Mean length27.413793
Min length2

Characters and Unicode

Total characters795
Distinct characters97
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

Unique29 ?
Unique (%)100.0%

Sample

1st row주소
2nd row전라북도 전주시 덕진구 팽나무4길 15-5 (인후동1가)
3rd row전라북도 전주시 완산구 호암로 82 402호(그린빌딩) (효자동2가)
4th row전라북도 전주시 덕진구 조경단로 38 (금암동)
5th row전라북도 전주시 완산구 전주천동로 210 (다가동2가)
ValueCountFrequency (%)
전라북도 28
 
16.4%
전주시 19
 
11.1%
완산구 15
 
8.8%
덕진구 4
 
2.3%
3층 3
 
1.8%
익산시 3
 
1.8%
효자동2가 3
 
1.8%
서신동 3
 
1.8%
군산시 2
 
1.2%
중화산동2가 2
 
1.2%
Other values (82) 89
52.0%
2024-03-14T10:22:50.486443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
151
19.0%
전 53
 
6.7%
라 28
 
3.5%
북 28
 
3.5%
도 28
 
3.5%
) 28
 
3.5%
( 28
 
3.5%
시 27
 
3.4%
동 27
 
3.4%
2 26
 
3.3%
Other values (87) 371
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 468
58.9%
Space Separator 151
 
19.0%
Decimal Number 112
 
14.1%
Close Punctuation 28
 
3.5%
Open Punctuation 28
 
3.5%
Dash Punctuation 5
 
0.6%
Other Punctuation 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 53
 
11.3%
라 28
 
6.0%
북 28
 
6.0%
도 28
 
6.0%
시 27
 
5.8%
동 27
 
5.8%
산 26
 
5.6%
주 21
 
4.5%
로 20
 
4.3%
구 19
 
4.1%
Other values (72) 191
40.8%
Decimal Number
ValueCountFrequency (%)
2 26
23.2%
1 22
19.6%
3 12
10.7%
4 12
10.7%
5 10
 
8.9%
0 9
 
8.0%
6 8
 
7.1%
7 6
 
5.4%
8 4
 
3.6%
9 3
 
2.7%
Space Separator
ValueCountFrequency (%)
151
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 468
58.9%
Common 327
41.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 53
 
11.3%
라 28
 
6.0%
북 28
 
6.0%
도 28
 
6.0%
시 27
 
5.8%
동 27
 
5.8%
산 26
 
5.6%
주 21
 
4.5%
로 20
 
4.3%
구 19
 
4.1%
Other values (72) 191
40.8%
Common
ValueCountFrequency (%)
151
46.2%
) 28
 
8.6%
( 28
 
8.6%
2 26
 
8.0%
1 22
 
6.7%
3 12
 
3.7%
4 12
 
3.7%
5 10
 
3.1%
0 9
 
2.8%
6 8
 
2.4%
Other values (5) 21
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 468
58.9%
ASCII 327
41.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
151
46.2%
) 28
 
8.6%
( 28
 
8.6%
2 26
 
8.0%
1 22
 
6.7%
3 12
 
3.7%
4 12
 
3.7%
5 10
 
3.1%
0 9
 
2.8%
6 8
 
2.4%
Other values (5) 21
 
6.4%
Hangul
ValueCountFrequency (%)
전 53
 
11.3%
라 28
 
6.0%
북 28
 
6.0%
도 28
 
6.0%
시 27
 
5.8%
동 27
 
5.8%
산 26
 
5.6%
주 21
 
4.5%
로 20
 
4.3%
구 19
 
4.1%
Other values (72) 191
40.8%

Unnamed: 6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1
Missing (%)3.3%
Memory size372.0 B

Unnamed: 7
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
일반(전기),일반(기계)
23 
일반(기계)
3 
<NA>
 
1
분야(설계업)
 
1
일반(전기)
 
1

Length

Max length13
Median length13
Mean length11.2
Min length2

Unique

Unique4 ?
Unique (%)13.3%

Sample

1st row<NA>
2nd row분야(설계업)
3rd row일반(전기),일반(기계)
4th row일반(전기),일반(기계)
5th row일반(전기),일반(기계)

Common Values

ValueCountFrequency (%)
일반(전기),일반(기계) 23
76.7%
일반(기계) 3
 
10.0%
<NA> 1
 
3.3%
분야(설계업) 1
 
3.3%
일반(전기) 1
 
3.3%
전문 1
 
3.3%

Length

2024-03-14T10:22:50.597544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:22:50.689028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반(전기),일반(기계 23
76.7%
일반(기계 3
 
10.0%
na 1
 
3.3%
분야(설계업 1
 
3.3%
일반(전기 1
 
3.3%
전문 1
 
3.3%

Unnamed: 8
Text

MISSING 

Distinct29
Distinct (%)100.0%
Missing1
Missing (%)3.3%
Memory size372.0 B
2024-03-14T10:22:50.866537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length12.413793
Min length7

Characters and Unicode

Total characters360
Distinct characters37
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)100.0%

Sample

1st row등록번호(설계업)
2nd row전주덕진 제2010-4호
3rd row전주완산 제2007-4호
4th row전주덕진제2012-12호
5th row전주완산 제98-71호
ValueCountFrequency (%)
전주완산 2
 
5.9%
등록번호(설계업 1
 
2.9%
전북익산제2007-03호 1
 
2.9%
전주완산제2015-12호 1
 
2.9%
2016-01-00153 1
 
2.9%
2017-01-00041 1
 
2.9%
전북군산제2011-02호 1
 
2.9%
전북군산제2013-04호 1
 
2.9%
2016-01-00057 1
 
2.9%
제97-53호 1
 
2.9%
Other values (23) 23
67.6%
2024-03-14T10:22:51.209749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 66
18.3%
1 37
10.3%
2 33
9.2%
- 32
8.9%
호 25
 
6.9%
제 23
 
6.4%
전 21
 
5.8%
주 17
 
4.7%
산 15
 
4.2%
완 12
 
3.3%
Other values (27) 79
21.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 179
49.7%
Other Letter 142
39.4%
Dash Punctuation 32
 
8.9%
Space Separator 5
 
1.4%
Close Punctuation 1
 
0.3%
Open Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
호 25
17.6%
제 23
16.2%
전 21
14.8%
주 17
12.0%
산 15
10.6%
완 12
8.5%
덕 5
 
3.5%
진 5
 
3.5%
북 4
 
2.8%
군 2
 
1.4%
Other values (13) 13
9.2%
Decimal Number
ValueCountFrequency (%)
0 66
36.9%
1 37
20.7%
2 33
18.4%
5 10
 
5.6%
6 9
 
5.0%
3 7
 
3.9%
7 7
 
3.9%
9 5
 
2.8%
4 4
 
2.2%
8 1
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 218
60.6%
Hangul 142
39.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
호 25
17.6%
제 23
16.2%
전 21
14.8%
주 17
12.0%
산 15
10.6%
완 12
8.5%
덕 5
 
3.5%
진 5
 
3.5%
북 4
 
2.8%
군 2
 
1.4%
Other values (13) 13
9.2%
Common
ValueCountFrequency (%)
0 66
30.3%
1 37
17.0%
2 33
15.1%
- 32
14.7%
5 10
 
4.6%
6 9
 
4.1%
3 7
 
3.2%
7 7
 
3.2%
9 5
 
2.3%
5
 
2.3%
Other values (4) 7
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 218
60.6%
Hangul 142
39.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 66
30.3%
1 37
17.0%
2 33
15.1%
- 32
14.7%
5 10
 
4.6%
6 9
 
4.1%
3 7
 
3.2%
7 7
 
3.2%
9 5
 
2.3%
5
 
2.3%
Other values (4) 7
 
3.2%
Hangul
ValueCountFrequency (%)
호 25
17.6%
제 23
16.2%
전 21
14.8%
주 17
12.0%
산 15
10.6%
완 12
8.5%
덕 5
 
3.5%
진 5
 
3.5%
북 4
 
2.8%
군 2
 
1.4%
Other values (13) 13
9.2%

Correlations

2024-03-14T10:22:51.290832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 7Unnamed: 8
Unnamed: 11.0001.0001.0001.0001.0001.0001.000
Unnamed: 21.0001.0001.0001.0001.0000.6061.000
Unnamed: 31.0001.0001.0001.0001.0001.0001.000
Unnamed: 41.0001.0001.0001.0001.0001.0001.000
Unnamed: 51.0001.0001.0001.0001.0001.0001.000
Unnamed: 71.0000.6061.0001.0001.0001.0001.000
Unnamed: 81.0001.0001.0001.0001.0001.0001.000
2024-03-14T10:22:51.392323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 7Unnamed: 2Unnamed: 1
Unnamed: 71.0000.4200.943
Unnamed: 20.4201.0000.903
Unnamed: 10.9430.9031.000
2024-03-14T10:22:51.461207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 2Unnamed: 7
Unnamed: 11.0000.9030.943
Unnamed: 20.9031.0000.420
Unnamed: 70.9430.4201.000

Missing values

2024-03-14T10:22:48.169204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T10:22:48.278420image/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.
2024-03-14T10:22:48.392418image/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

소방시설 설계업 등록 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8
0NaN<NA><NA><NA><NA><NA>NaN<NA><NA>
1순번도시.군상호대표자주소최초면허(설계업)분야(설계업)등록번호(설계업)
21전북전주시티앤제이건설(주)고태유전라북도 전주시 덕진구 팽나무4길 15-5 (인후동1가)2010-11-10일반(전기),일반(기계)전주덕진 제2010-4호
32전북전주시(주)주연이엔지김종배전라북도 전주시 완산구 호암로 82 402호(그린빌딩) (효자동2가)2003-01-08일반(전기),일반(기계)전주완산 제2007-4호
44전북전주시(주)덕진소방박동규전라북도 전주시 덕진구 조경단로 38 (금암동)2012-12-28일반(전기),일반(기계)전주덕진제2012-12호
56전북전주시(주)대신기술단왕영식전라북도 전주시 완산구 전주천동로 210 (다가동2가)1998-01-22일반(전기),일반(기계)전주완산 제98-71호
68전북전주시주식회사 대화박진형전라북도 전주시 완산구 우전2길 45 (효자동2가)2006-03-31일반(전기),일반(기계)전주완산제2006-10호
711전북전주시(유)다산이엔지권영관전라북도 전주시 완산구 서곡로 69 (효자동3가,2층)2002-07-29일반(전기),일반(기계)전주완산제2002-11호
812전북전주시(유)전일기술단강병삼전라북도 전주시 덕진구 아중로 140 (인후동1가)2005-10-12일반(전기),일반(기계)전주덕진제2005-10호
913전북전주시(유)중앙기술공사양인숙전라북도 전주시 완산구 홍산로 275 (효자동2가) 춘광빌딩 6층2006-07-13일반(전기),일반(기계)전주덕진제2006-06호
소방시설 설계업 등록 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8
2028전북전주시(주)세흥이엔지오민옥전라북도 전주시 완산구 전룡로 73 (서신동)2017-03-13 00:00:00일반(전기),일반(기계)2017-01-00041
219전북군산시주식회사 다올권성훈전라북도 군산시 조촌로 105 (조촌동)2011-07-07일반(전기),일반(기계)전북군산제2011-02호
2214전북군산시유스파워(주)고환구전라북도 군산시 조촌4길 24-6 (조촌동)2013-06-26일반(전기),일반(기계)전북군산제2013-04호
233전북익산시지오방재이엔씨(주)장영철전라북도 익산시 하나로1길 16 (금강동)2016-04-11전문2016-01-00057
2415전북익산시(유)광진이엔지이춘우전라북도 익산시 무왕로2길 50 (목천동)2007-05-08일반(전기),일반(기계)전북익산제2007-03호
2520전북익산시(주)대성건축사사무소김창호전라북도 익산시 선화로 259 (남중동)1997-06-24일반(전기),일반(기계)제97-53호
265전북정읍시(유)우석엔지니어링이성준전라북도 정읍시 대흥3길 16-7 (시기동) 2층2011-06-22일반(전기),일반(기계)전북정읍 제2011-01호
2710전북남원시세웅이엔씨이영욱전라북도 남원시 요천로 1871 (고죽동)2010-01-15일반(전기),일반(기계)남원제2010-01호
287전북부안군태인엔지니어링(주)시춘근전라북도 부안군 백산면 부평로 214-20 ()2006-04-10일반(전기),일반(기계)부안 제2015-02호
2926전북부안군(유)영화건축사사무소송영섭전라북도 부안군 부안읍 용암로 15 , 2층2016-11-16일반(기계)2016-01-00165