Overview

Dataset statistics

Number of variables7
Number of observations93
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.4 KiB
Average record size in memory59.4 B

Variable types

Numeric2
Categorical1
Text4

Dataset

Description전북특별자치도 가구제조업체 현황 데이터입니다. 지역, 사업체명, 업종코드, 주생산품 등의 데이터를 제공합니다.참고사항 : 2021 전북특별자치도 제조업체 총람(2020.12.31.기준)으로 작성하였으며 본 총람의 현황은 전라북도 내에 소재한 중소제조업체의 생산제품 홍보와 판로 촉진을 위한 자료로 활용하기 위해 제작하였으므로, 상업 및 부정한 목적으로 사용할 수 없으며, 아울러 대외적인 통계자료로 사용할 수 없음을 알려드립니다.해당 저작물은 전라북도청 홈페이지에서 무료로 다운받으실 수 있습니다.
Author전북특별자치도
URLhttps://www.data.go.kr/data/15098531/fileData.do

Alerts

연번 has unique valuesUnique
사업체명 has unique valuesUnique

Reproduction

Analysis started2024-03-14 09:22:15.500391
Analysis finished2024-03-14 09:22:18.263807
Duration2.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct93
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47
Minimum1
Maximum93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size965.0 B
2024-03-14T18:22:18.474339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.6
Q124
median47
Q370
95-th percentile88.4
Maximum93
Range92
Interquartile range (IQR)46

Descriptive statistics

Standard deviation26.990739
Coefficient of variation (CV)0.57427105
Kurtosis-1.2
Mean47
Median Absolute Deviation (MAD)23
Skewness0
Sum4371
Variance728.5
MonotonicityStrictly increasing
2024-03-14T18:22:18.900825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.1%
60 1
 
1.1%
69 1
 
1.1%
68 1
 
1.1%
67 1
 
1.1%
66 1
 
1.1%
65 1
 
1.1%
64 1
 
1.1%
63 1
 
1.1%
62 1
 
1.1%
Other values (83) 83
89.2%
ValueCountFrequency (%)
1 1
1.1%
2 1
1.1%
3 1
1.1%
4 1
1.1%
5 1
1.1%
6 1
1.1%
7 1
1.1%
8 1
1.1%
9 1
1.1%
10 1
1.1%
ValueCountFrequency (%)
93 1
1.1%
92 1
1.1%
91 1
1.1%
90 1
1.1%
89 1
1.1%
88 1
1.1%
87 1
1.1%
86 1
1.1%
85 1
1.1%
84 1
1.1%

지역
Categorical

Distinct11
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Memory size872.0 B
전주
33 
군산
15 
완주
12 
익산
11 
김제
11 
Other values (6)
11 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique3 ?
Unique (%)3.2%

Sample

1st row익산
2nd row전주
3rd row군산
4th row군산
5th row군산

Common Values

ValueCountFrequency (%)
전주 33
35.5%
군산 15
16.1%
완주 12
 
12.9%
익산 11
 
11.8%
김제 11
 
11.8%
정읍 4
 
4.3%
무주 2
 
2.2%
남원 2
 
2.2%
순창 1
 
1.1%
임실 1
 
1.1%

Length

2024-03-14T18:22:19.294310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주 33
35.5%
군산 15
16.1%
완주 12
 
12.9%
익산 11
 
11.8%
김제 11
 
11.8%
정읍 4
 
4.3%
무주 2
 
2.2%
남원 2
 
2.2%
순창 1
 
1.1%
임실 1
 
1.1%

사업체명
Text

UNIQUE 

Distinct93
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size872.0 B
2024-03-14T18:22:20.531075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length5.9462366
Min length3

Characters and Unicode

Total characters553
Distinct characters169
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

Unique93 ?
Unique (%)100.0%

Sample

1st row진성시스템 주방가구
2nd row디어마이우드
3rd row보석주방가구
4th row송선목공방
5th row럭키방음부스
ValueCountFrequency (%)
진성시스템 1
 
1.0%
주방가구 1
 
1.0%
호성주방가구 1
 
1.0%
주)고진케이우드 1
 
1.0%
우드카운티 1
 
1.0%
전북사무가구협동조합 1
 
1.0%
예담부엌가구 1
 
1.0%
나무뜨락 1
 
1.0%
황제쇼파 1
 
1.0%
드림디자인 1
 
1.0%
Other values (86) 86
89.6%
2024-03-14T18:22:22.010090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 25
 
4.5%
( 25
 
4.5%
가 22
 
4.0%
구 21
 
3.8%
업 17
 
3.1%
주 16
 
2.9%
유 15
 
2.7%
산 12
 
2.2%
리 10
 
1.8%
부 9
 
1.6%
Other values (159) 381
68.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 495
89.5%
Close Punctuation 25
 
4.5%
Open Punctuation 25
 
4.5%
Uppercase Letter 4
 
0.7%
Space Separator 3
 
0.5%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
가 22
 
4.4%
구 21
 
4.2%
업 17
 
3.4%
주 16
 
3.2%
유 15
 
3.0%
산 12
 
2.4%
리 10
 
2.0%
부 9
 
1.8%
사 8
 
1.6%
인 8
 
1.6%
Other values (152) 357
72.1%
Uppercase Letter
ValueCountFrequency (%)
S 2
50.0%
J 1
25.0%
K 1
25.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 495
89.5%
Common 54
 
9.8%
Latin 4
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
가 22
 
4.4%
구 21
 
4.2%
업 17
 
3.4%
주 16
 
3.2%
유 15
 
3.0%
산 12
 
2.4%
리 10
 
2.0%
부 9
 
1.8%
사 8
 
1.6%
인 8
 
1.6%
Other values (152) 357
72.1%
Common
ValueCountFrequency (%)
) 25
46.3%
( 25
46.3%
3
 
5.6%
. 1
 
1.9%
Latin
ValueCountFrequency (%)
S 2
50.0%
J 1
25.0%
K 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 495
89.5%
ASCII 58
 
10.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 25
43.1%
( 25
43.1%
3
 
5.2%
S 2
 
3.4%
J 1
 
1.7%
. 1
 
1.7%
K 1
 
1.7%
Hangul
ValueCountFrequency (%)
가 22
 
4.4%
구 21
 
4.2%
업 17
 
3.4%
주 16
 
3.2%
유 15
 
3.0%
산 12
 
2.4%
리 10
 
2.0%
부 9
 
1.8%
사 8
 
1.6%
인 8
 
1.6%
Other values (152) 357
72.1%

대표자
Text

Distinct87
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size872.0 B
2024-03-14T18:22:23.110953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9784946
Min length2

Characters and Unicode

Total characters277
Distinct characters84
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

Unique82 ?
Unique (%)88.2%

Sample

1st row박*인
2nd row백*관
3rd row윤*원
4th row이*선
5th row김*수
ValueCountFrequency (%)
강*원 3
 
3.2%
이*섭 2
 
2.2%
장*호 2
 
2.2%
이*현 2
 
2.2%
김*수 2
 
2.2%
장*성 1
 
1.1%
김*선 1
 
1.1%
정*형 1
 
1.1%
김*태 1
 
1.1%
문*국 1
 
1.1%
Other values (77) 77
82.8%
2024-03-14T18:22:24.592613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 93
33.6%
김 21
 
7.6%
이 15
 
5.4%
강 7
 
2.5%
정 7
 
2.5%
수 6
 
2.2%
원 5
 
1.8%
장 5
 
1.8%
영 4
 
1.4%
전 4
 
1.4%
Other values (74) 110
39.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 184
66.4%
Other Punctuation 93
33.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 21
 
11.4%
이 15
 
8.2%
강 7
 
3.8%
정 7
 
3.8%
수 6
 
3.3%
원 5
 
2.7%
장 5
 
2.7%
영 4
 
2.2%
전 4
 
2.2%
박 4
 
2.2%
Other values (73) 106
57.6%
Other Punctuation
ValueCountFrequency (%)
* 93
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 184
66.4%
Common 93
33.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 21
 
11.4%
이 15
 
8.2%
강 7
 
3.8%
정 7
 
3.8%
수 6
 
3.3%
원 5
 
2.7%
장 5
 
2.7%
영 4
 
2.2%
전 4
 
2.2%
박 4
 
2.2%
Other values (73) 106
57.6%
Common
ValueCountFrequency (%)
* 93
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 184
66.4%
ASCII 93
33.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 93
100.0%
Hangul
ValueCountFrequency (%)
김 21
 
11.4%
이 15
 
8.2%
강 7
 
3.8%
정 7
 
3.8%
수 6
 
3.3%
원 5
 
2.7%
장 5
 
2.7%
영 4
 
2.2%
전 4
 
2.2%
박 4
 
2.2%
Other values (73) 106
57.6%

업종코드2자리
Real number (ℝ)

Distinct8
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.096774
Minimum10
Maximum33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size965.0 B
2024-03-14T18:22:24.951216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile16
Q132
median32
Q332
95-th percentile32
Maximum33
Range23
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6.0416391
Coefficient of variation (CV)0.20763948
Kurtosis1.4168634
Mean29.096774
Median Absolute Deviation (MAD)0
Skewness-1.7526455
Sum2706
Variance36.501403
MonotonicityNot monotonic
2024-03-14T18:22:25.301758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
32 73
78.5%
16 12
 
12.9%
25 2
 
2.2%
23 2
 
2.2%
33 1
 
1.1%
10 1
 
1.1%
22 1
 
1.1%
17 1
 
1.1%
ValueCountFrequency (%)
10 1
 
1.1%
16 12
 
12.9%
17 1
 
1.1%
22 1
 
1.1%
23 2
 
2.2%
25 2
 
2.2%
32 73
78.5%
33 1
 
1.1%
ValueCountFrequency (%)
33 1
 
1.1%
32 73
78.5%
25 2
 
2.2%
23 2
 
2.2%
22 1
 
1.1%
17 1
 
1.1%
16 12
 
12.9%
10 1
 
1.1%

주생산품
Text

Distinct51
Distinct (%)54.8%
Missing0
Missing (%)0.0%
Memory size872.0 B
2024-03-14T18:22:26.186404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length13
Mean length6.0860215
Min length2

Characters and Unicode

Total characters566
Distinct characters83
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)45.2%

Sample

1st row주방용및음식점용 목재가구제조
2nd row목재가구(목공방)
3rd row주방가구,붙박이장
4th row목재가구
5th row가구
ValueCountFrequency (%)
가구 17
 
15.9%
목재가구 15
 
14.0%
주방가구 8
 
7.5%
사무용가구 6
 
5.6%
주방용및음식점용 3
 
2.8%
목재가구제조 2
 
1.9%
주방용목재가구 2
 
1.9%
주방가구제조 2
 
1.9%
가구제작 2
 
1.9%
주방용가구 2
 
1.9%
Other values (47) 48
44.9%
2024-03-14T18:22:27.532775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
가 100
17.7%
구 100
17.7%
목 32
 
5.7%
, 30
 
5.3%
용 26
 
4.6%
재 26
 
4.6%
주 25
 
4.4%
방 24
 
4.2%
제 15
 
2.7%
14
 
2.5%
Other values (73) 174
30.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 516
91.2%
Other Punctuation 30
 
5.3%
Space Separator 14
 
2.5%
Open Punctuation 3
 
0.5%
Close Punctuation 3
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
가 100
19.4%
구 100
19.4%
목 32
 
6.2%
용 26
 
5.0%
재 26
 
5.0%
주 25
 
4.8%
방 24
 
4.7%
제 15
 
2.9%
무 13
 
2.5%
사 13
 
2.5%
Other values (69) 142
27.5%
Other Punctuation
ValueCountFrequency (%)
, 30
100.0%
Space Separator
ValueCountFrequency (%)
14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 516
91.2%
Common 50
 
8.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
가 100
19.4%
구 100
19.4%
목 32
 
6.2%
용 26
 
5.0%
재 26
 
5.0%
주 25
 
4.8%
방 24
 
4.7%
제 15
 
2.9%
무 13
 
2.5%
사 13
 
2.5%
Other values (69) 142
27.5%
Common
ValueCountFrequency (%)
, 30
60.0%
14
28.0%
( 3
 
6.0%
) 3
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 516
91.2%
ASCII 50
 
8.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
가 100
19.4%
구 100
19.4%
목 32
 
6.2%
용 26
 
5.0%
재 26
 
5.0%
주 25
 
4.8%
방 24
 
4.7%
제 15
 
2.9%
무 13
 
2.5%
사 13
 
2.5%
Other values (69) 142
27.5%
ASCII
ValueCountFrequency (%)
, 30
60.0%
14
28.0%
( 3
 
6.0%
) 3
 
6.0%

주소
Text

Distinct91
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size872.0 B
2024-03-14T18:22:28.608021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length19
Mean length15.193548
Min length8

Characters and Unicode

Total characters1413
Distinct characters146
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique89 ?
Unique (%)95.7%

Sample

1st row익산시 망산길 61
2nd row전주시 덕진구 오송로 7
3rd row군산시 문화안길 18
4th row군산시 동령길 22-17
5th row군산시 회현면 남내로 320
ValueCountFrequency (%)
전주시 32
 
9.2%
덕진구 19
 
5.5%
군산시 15
 
4.3%
완산구 13
 
3.8%
완주군 12
 
3.5%
김제시 11
 
3.2%
익산시 11
 
3.2%
20 7
 
2.0%
금구면 6
 
1.7%
상관면 5
 
1.4%
Other values (188) 215
62.1%
2024-03-14T18:22:30.124239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
265
 
18.8%
시 76
 
5.4%
1 59
 
4.2%
2 55
 
3.9%
산 53
 
3.8%
길 49
 
3.5%
주 48
 
3.4%
로 47
 
3.3%
구 44
 
3.1%
4 43
 
3.0%
Other values (136) 674
47.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 814
57.6%
Decimal Number 299
 
21.2%
Space Separator 265
 
18.8%
Dash Punctuation 32
 
2.3%
Other Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 76
 
9.3%
산 53
 
6.5%
길 49
 
6.0%
주 48
 
5.9%
로 47
 
5.8%
구 44
 
5.4%
전 39
 
4.8%
군 32
 
3.9%
면 30
 
3.7%
완 26
 
3.2%
Other values (122) 370
45.5%
Decimal Number
ValueCountFrequency (%)
1 59
19.7%
2 55
18.4%
4 43
14.4%
3 35
11.7%
0 24
8.0%
7 22
 
7.4%
5 20
 
6.7%
6 16
 
5.4%
9 14
 
4.7%
8 11
 
3.7%
Other Punctuation
ValueCountFrequency (%)
, 2
66.7%
. 1
33.3%
Space Separator
ValueCountFrequency (%)
265
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 814
57.6%
Common 599
42.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 76
 
9.3%
산 53
 
6.5%
길 49
 
6.0%
주 48
 
5.9%
로 47
 
5.8%
구 44
 
5.4%
전 39
 
4.8%
군 32
 
3.9%
면 30
 
3.7%
완 26
 
3.2%
Other values (122) 370
45.5%
Common
ValueCountFrequency (%)
265
44.2%
1 59
 
9.8%
2 55
 
9.2%
4 43
 
7.2%
3 35
 
5.8%
- 32
 
5.3%
0 24
 
4.0%
7 22
 
3.7%
5 20
 
3.3%
6 16
 
2.7%
Other values (4) 28
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 814
57.6%
ASCII 599
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
265
44.2%
1 59
 
9.8%
2 55
 
9.2%
4 43
 
7.2%
3 35
 
5.8%
- 32
 
5.3%
0 24
 
4.0%
7 22
 
3.7%
5 20
 
3.3%
6 16
 
2.7%
Other values (4) 28
 
4.7%
Hangul
ValueCountFrequency (%)
시 76
 
9.3%
산 53
 
6.5%
길 49
 
6.0%
주 48
 
5.9%
로 47
 
5.8%
구 44
 
5.4%
전 39
 
4.8%
군 32
 
3.9%
면 30
 
3.7%
완 26
 
3.2%
Other values (122) 370
45.5%

Interactions

2024-03-14T18:22:17.175483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:22:16.717885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:22:17.408866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:22:16.944396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T18:22:30.393239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번지역사업체명대표자업종코드2자리주생산품주소
연번1.0000.6251.0000.6010.3100.0000.974
지역0.6251.0001.0000.8460.0000.9221.000
사업체명1.0001.0001.0001.0001.0001.0001.000
대표자0.6010.8461.0001.0000.7070.9570.999
업종코드2자리0.3100.0001.0000.7071.0000.9731.000
주생산품0.0000.9221.0000.9570.9731.0000.961
주소0.9741.0001.0000.9991.0000.9611.000
2024-03-14T18:22:30.673982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종코드2자리지역
연번1.000-0.0330.321
업종코드2자리-0.0331.0000.000
지역0.3210.0001.000

Missing values

2024-03-14T18:22:17.734670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T18:22:18.114003image/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

연번지역사업체명대표자업종코드2자리주생산품주소
01익산진성시스템 주방가구박*인32주방용및음식점용 목재가구제조익산시 망산길 61
12전주디어마이우드백*관32목재가구(목공방)전주시 덕진구 오송로 7
23군산보석주방가구윤*원32주방가구,붙박이장군산시 문화안길 18
34군산송선목공방이*선32목재가구군산시 동령길 22-17
45군산럭키방음부스김*수25가구군산시 회현면 남내로 320
56군산미래종합씽크이*훈16씽크대주방가구군산시 칠성안4길 43-4
67익산한그루김*중32목재가구제조익산시 중앙로 12-129
78전주현성부엌가구장*규32가구전주시 덕진구 산재마을길 57
89완주새샘목공소박*현32목재가구 현장에서 작업완주군 상관면 춘향로 4233
910전주(유)현대종합주방설비전*표25상업용스텐레스주방가구전주시 덕진구 대정안길 27
연번지역사업체명대표자업종코드2자리주생산품주소
8384전주(유)전주송원가구백화점이*섭32사무용가구전주시 완산구 쑥고개로 242
8485전주(주)태광기업이*32의자,사무가구전주시 덕진구 기린대로 256
8586전주나무갤러리손*균32가구제작전주시 덕진구 온고을로 286
8687김제(유)리조김*민32가구김제시 백구면 유강로 602-33
8788김제메인가구산업이*열32사무용가구(목재)김제시 금구면 용마로 411
8889전주(주)에프샵김*섭32금속가구전주시 덕진구 팔과정로 20
8990익산장산공예사김*진32일반가구및 나전칠기가구익산시 평동로14길 76-18
9091정읍(주)보림가구정*순32주방가구제조정읍시 북면 북면공단2길 57
9192완주(주)이태리도어산업이*규32창호,가구완주군 상관면 상관소양로 21-36
9293완주진성오피스방*선16목재도구및 가구제품완주군 이서면 이서남로 213