Overview

Dataset statistics

Number of variables8
Number of observations23
Missing cells21
Missing cells (%)11.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 KiB
Average record size in memory69.7 B

Variable types

Unsupported2
Categorical1
Text5

Dataset

Description전문예술법인단체지정현황201412
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202029

Alerts

Unnamed: 7 has 21 (91.3%) missing valuesMissing
Unnamed: 4 has unique valuesUnique
Unnamed: 5 has unique valuesUnique
Unnamed: 6 has unique valuesUnique
전라북도 전문예술법인 및 단체 지정현황(22개소 작성일:2014.12.02) is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 1 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 02:23:31.345912
Analysis finished2024-03-14 02:23:31.777476
Duration0.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

전라북도 전문예술법인 및 단체 지정현황(22개소 작성일:2014.12.02)
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size316.0 B

Unnamed: 1
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size316.0 B

Unnamed: 2
Categorical

Distinct3
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
전문예술법인
14 
전문예술단체
8 
지정형태
 
1

Length

Max length6
Median length6
Mean length5.9130435
Min length4

Unique

Unique1 ?
Unique (%)4.3%

Sample

1st row지정형태
2nd row전문예술법인
3rd row전문예술법인
4th row전문예술법인
5th row전문예술법인

Common Values

ValueCountFrequency (%)
전문예술법인 14
60.9%
전문예술단체 8
34.8%
지정형태 1
 
4.3%

Length

2024-03-14T11:23:31.843142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:23:31.950688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전문예술법인 14
60.9%
전문예술단체 8
34.8%
지정형태 1
 
4.3%

Unnamed: 3
Text

Distinct12
Distinct (%)52.2%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-03-14T11:23:32.078723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.6521739
Min length2

Characters and Unicode

Total characters84
Distinct characters28
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

Unique8 ?
Unique (%)34.8%

Sample

1st row유형
2nd row오페라단
3rd row종합예술단
4th row전통예술단
5th row전통예술단
ValueCountFrequency (%)
전통예술단 5
21.7%
연극단 4
17.4%
음악 4
17.4%
문화단체 2
 
8.7%
유형 1
 
4.3%
오페라단 1
 
4.3%
종합예술단 1
 
4.3%
국악공연단 1
 
4.3%
서예전시 1
 
4.3%
필봉농악단 1
 
4.3%
Other values (2) 2
 
8.7%
2024-03-14T11:23:32.399928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
단 15
17.9%
예 8
 
9.5%
전 7
 
8.3%
술 7
 
8.3%
악 6
 
7.1%
통 6
 
7.1%
연 5
 
6.0%
극 4
 
4.8%
음 4
 
4.8%
체 2
 
2.4%
Other values (18) 20
23.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 84
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
단 15
17.9%
예 8
 
9.5%
전 7
 
8.3%
술 7
 
8.3%
악 6
 
7.1%
통 6
 
7.1%
연 5
 
6.0%
극 4
 
4.8%
음 4
 
4.8%
체 2
 
2.4%
Other values (18) 20
23.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 84
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
단 15
17.9%
예 8
 
9.5%
전 7
 
8.3%
술 7
 
8.3%
악 6
 
7.1%
통 6
 
7.1%
연 5
 
6.0%
극 4
 
4.8%
음 4
 
4.8%
체 2
 
2.4%
Other values (18) 20
23.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 84
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
단 15
17.9%
예 8
 
9.5%
전 7
 
8.3%
술 7
 
8.3%
악 6
 
7.1%
통 6
 
7.1%
연 5
 
6.0%
극 4
 
4.8%
음 4
 
4.8%
체 2
 
2.4%
Other values (18) 20
23.8%

Unnamed: 4
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-03-14T11:23:32.585646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length9.5217391
Min length4

Characters and Unicode

Total characters219
Distinct characters108
Distinct categories7 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st row법인명(단체)
2nd row사)호남 오페라단
3rd row사)예술기획 예루
4th row사)전통예술원 모악
5th row사)전통문화 마을
ValueCountFrequency (%)
법인명(단체 1
 
2.3%
미디어 1
 
2.3%
임실필봉 1
 
2.3%
농악보존회 1
 
2.3%
극단 1
 
2.3%
까치동 1
 
2.3%
사)전주세계소리축제조직위원회 1
 
2.3%
재)전주문화재단 1
 
2.3%
재)익산문화재단 1
 
2.3%
사)현대사진 1
 
2.3%
Other values (33) 33
76.7%
2024-03-14T11:23:32.870856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20
 
9.1%
) 14
 
6.4%
사 13
 
5.9%
단 7
 
3.2%
전 6
 
2.7%
예 5
 
2.3%
화 5
 
2.3%
문 5
 
2.3%
회 5
 
2.3%
소 4
 
1.8%
Other values (98) 135
61.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 174
79.5%
Space Separator 20
 
9.1%
Close Punctuation 14
 
6.4%
Lowercase Letter 5
 
2.3%
Open Punctuation 3
 
1.4%
Uppercase Letter 2
 
0.9%
Other Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 13
 
7.5%
단 7
 
4.0%
전 6
 
3.4%
예 5
 
2.9%
화 5
 
2.9%
문 5
 
2.9%
회 5
 
2.9%
소 4
 
2.3%
재 4
 
2.3%
악 4
 
2.3%
Other values (87) 116
66.7%
Lowercase Letter
ValueCountFrequency (%)
k 1
20.0%
c 1
20.0%
i 1
20.0%
t 1
20.0%
s 1
20.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
T 1
50.0%
Space Separator
ValueCountFrequency (%)
20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 173
79.0%
Common 38
 
17.4%
Latin 7
 
3.2%
Han 1
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 13
 
7.5%
단 7
 
4.0%
전 6
 
3.5%
예 5
 
2.9%
화 5
 
2.9%
문 5
 
2.9%
회 5
 
2.9%
소 4
 
2.3%
재 4
 
2.3%
악 4
 
2.3%
Other values (86) 115
66.5%
Latin
ValueCountFrequency (%)
B 1
14.3%
T 1
14.3%
k 1
14.3%
c 1
14.3%
i 1
14.3%
t 1
14.3%
s 1
14.3%
Common
ValueCountFrequency (%)
20
52.6%
) 14
36.8%
( 3
 
7.9%
& 1
 
2.6%
Han
ValueCountFrequency (%)
打 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 173
79.0%
ASCII 45
 
20.5%
CJK 1
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20
44.4%
) 14
31.1%
( 3
 
6.7%
B 1
 
2.2%
& 1
 
2.2%
T 1
 
2.2%
k 1
 
2.2%
c 1
 
2.2%
i 1
 
2.2%
t 1
 
2.2%
Hangul
ValueCountFrequency (%)
사 13
 
7.5%
단 7
 
4.0%
전 6
 
3.5%
예 5
 
2.9%
화 5
 
2.9%
문 5
 
2.9%
회 5
 
2.9%
소 4
 
2.3%
재 4
 
2.3%
악 4
 
2.3%
Other values (86) 115
66.5%
CJK
ValueCountFrequency (%)
打 1
100.0%

Unnamed: 5
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-03-14T11:23:33.244316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.1304348
Min length2

Characters and Unicode

Total characters72
Distinct characters45
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

Unique23 ?
Unique (%)100.0%

Sample

1st row성명(대표자)
2nd row김영구
3rd row이종례
4th row최기춘
5th row김진형
ValueCountFrequency (%)
성명(대표자 1
 
4.3%
심재균 1
 
4.3%
정기주 1
 
4.3%
이은희 1
 
4.3%
김선식 1
 
4.3%
박승환 1
 
4.3%
이한수 1
 
4.3%
유광찬 1
 
4.3%
김한 1
 
4.3%
전춘근 1
 
4.3%
Other values (13) 13
56.5%
2024-03-14T11:23:33.523820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 7
 
9.7%
성 4
 
5.6%
진 4
 
5.6%
이 3
 
4.2%
최 2
 
2.8%
한 2
 
2.8%
찬 2
 
2.8%
박 2
 
2.8%
환 2
 
2.8%
양 2
 
2.8%
Other values (35) 42
58.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 70
97.2%
Close Punctuation 1
 
1.4%
Open Punctuation 1
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 7
 
10.0%
성 4
 
5.7%
진 4
 
5.7%
이 3
 
4.3%
최 2
 
2.9%
한 2
 
2.9%
찬 2
 
2.9%
박 2
 
2.9%
환 2
 
2.9%
양 2
 
2.9%
Other values (33) 40
57.1%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 70
97.2%
Common 2
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 7
 
10.0%
성 4
 
5.7%
진 4
 
5.7%
이 3
 
4.3%
최 2
 
2.9%
한 2
 
2.9%
찬 2
 
2.9%
박 2
 
2.9%
환 2
 
2.9%
양 2
 
2.9%
Other values (33) 40
57.1%
Common
ValueCountFrequency (%)
) 1
50.0%
( 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 70
97.2%
ASCII 2
 
2.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 7
 
10.0%
성 4
 
5.7%
진 4
 
5.7%
이 3
 
4.3%
최 2
 
2.9%
한 2
 
2.9%
찬 2
 
2.9%
박 2
 
2.9%
환 2
 
2.9%
양 2
 
2.9%
Other values (33) 40
57.1%
ASCII
ValueCountFrequency (%)
) 1
50.0%
( 1
50.0%

Unnamed: 6
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-03-14T11:23:33.741076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length29
Mean length22.652174
Min length3

Characters and Unicode

Total characters521
Distinct characters95
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

Unique23 ?
Unique (%)100.0%

Sample

1st row소재지
2nd row전주시 완산구 서노송동 568-134 성지빌딩 5층
3rd row전주시 완산구 중앙동 1가 55-3번지
4th row전주시 완산구 현무3길 77-15, 4층 (경원동 3가)
5th row전주시 완산구 경원동 1가 111-9
ValueCountFrequency (%)
전주시 19
 
17.1%
완산구 17
 
15.3%
경원동 4
 
3.6%
1가 4
 
3.6%
용머리로 2
 
1.8%
2가 2
 
1.8%
1길 2
 
1.8%
덕진구 2
 
1.8%
소재지 1
 
0.9%
28-4(평화동 1
 
0.9%
Other values (57) 57
51.4%
2024-03-14T11:23:34.068605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
88
 
16.9%
1 23
 
4.4%
주 22
 
4.2%
전 21
 
4.0%
산 21
 
4.0%
시 20
 
3.8%
구 20
 
3.8%
동 20
 
3.8%
2 19
 
3.6%
완 19
 
3.6%
Other values (85) 248
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 294
56.4%
Decimal Number 99
 
19.0%
Space Separator 88
 
16.9%
Close Punctuation 13
 
2.5%
Open Punctuation 13
 
2.5%
Dash Punctuation 11
 
2.1%
Other Punctuation 3
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 22
 
7.5%
전 21
 
7.1%
산 21
 
7.1%
시 20
 
6.8%
구 20
 
6.8%
동 20
 
6.8%
완 19
 
6.5%
가 14
 
4.8%
로 10
 
3.4%
길 6
 
2.0%
Other values (70) 121
41.2%
Decimal Number
ValueCountFrequency (%)
1 23
23.2%
2 19
19.2%
3 17
17.2%
4 12
12.1%
5 6
 
6.1%
7 6
 
6.1%
0 5
 
5.1%
8 4
 
4.0%
6 4
 
4.0%
9 3
 
3.0%
Space Separator
ValueCountFrequency (%)
88
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 294
56.4%
Common 227
43.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 22
 
7.5%
전 21
 
7.1%
산 21
 
7.1%
시 20
 
6.8%
구 20
 
6.8%
동 20
 
6.8%
완 19
 
6.5%
가 14
 
4.8%
로 10
 
3.4%
길 6
 
2.0%
Other values (70) 121
41.2%
Common
ValueCountFrequency (%)
88
38.8%
1 23
 
10.1%
2 19
 
8.4%
3 17
 
7.5%
) 13
 
5.7%
( 13
 
5.7%
4 12
 
5.3%
- 11
 
4.8%
5 6
 
2.6%
7 6
 
2.6%
Other values (5) 19
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 294
56.4%
ASCII 227
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
88
38.8%
1 23
 
10.1%
2 19
 
8.4%
3 17
 
7.5%
) 13
 
5.7%
( 13
 
5.7%
4 12
 
5.3%
- 11
 
4.8%
5 6
 
2.6%
7 6
 
2.6%
Other values (5) 19
 
8.4%
Hangul
ValueCountFrequency (%)
주 22
 
7.5%
전 21
 
7.1%
산 21
 
7.1%
시 20
 
6.8%
구 20
 
6.8%
동 20
 
6.8%
완 19
 
6.5%
가 14
 
4.8%
로 10
 
3.4%
길 6
 
2.0%
Other values (70) 121
41.2%

Unnamed: 7
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing21
Missing (%)91.3%
Memory size316.0 B
2024-03-14T11:23:34.212082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters18
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row변경내용및변경일자
2nd row‘12년 법인전환
ValueCountFrequency (%)
변경내용및변경일자 1
33.3%
‘12년 1
33.3%
법인전환 1
33.3%
2024-03-14T11:23:34.479275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
변 2
 
11.1%
경 2
 
11.1%
내 1
 
5.6%
용 1
 
5.6%
및 1
 
5.6%
일 1
 
5.6%
자 1
 
5.6%
‘ 1
 
5.6%
1 1
 
5.6%
2 1
 
5.6%
Other values (6) 6
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14
77.8%
Decimal Number 2
 
11.1%
Initial Punctuation 1
 
5.6%
Space Separator 1
 
5.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
변 2
14.3%
경 2
14.3%
내 1
7.1%
용 1
7.1%
및 1
7.1%
일 1
7.1%
자 1
7.1%
년 1
7.1%
법 1
7.1%
인 1
7.1%
Other values (2) 2
14.3%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14
77.8%
Common 4
 
22.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
변 2
14.3%
경 2
14.3%
내 1
7.1%
용 1
7.1%
및 1
7.1%
일 1
7.1%
자 1
7.1%
년 1
7.1%
법 1
7.1%
인 1
7.1%
Other values (2) 2
14.3%
Common
ValueCountFrequency (%)
‘ 1
25.0%
1 1
25.0%
2 1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14
77.8%
ASCII 3
 
16.7%
Punctuation 1
 
5.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
변 2
14.3%
경 2
14.3%
내 1
7.1%
용 1
7.1%
및 1
7.1%
일 1
7.1%
자 1
7.1%
년 1
7.1%
법 1
7.1%
인 1
7.1%
Other values (2) 2
14.3%
Punctuation
ValueCountFrequency (%)
‘ 1
100.0%
ASCII
ValueCountFrequency (%)
1 1
33.3%
2 1
33.3%
1
33.3%

Correlations

2024-03-14T11:23:34.596024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7
Unnamed: 21.0000.9091.0001.0001.0000.000
Unnamed: 30.9091.0001.0001.0001.0000.000
Unnamed: 41.0001.0001.0001.0001.0000.000
Unnamed: 51.0001.0001.0001.0001.0000.000
Unnamed: 61.0001.0001.0001.0001.0000.000
Unnamed: 70.0000.0000.0000.0000.0001.000

Missing values

2024-03-14T11:23:31.634646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:23:31.732808image/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

전라북도 전문예술법인 및 단체 지정현황(22개소 작성일:2014.12.02)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7
0연번호지정번호지정형태유형법인명(단체)성명(대표자)소재지변경내용및변경일자
111전문예술법인오페라단사)호남 오페라단김영구전주시 완산구 서노송동 568-134 성지빌딩 5층<NA>
222전문예술법인종합예술단사)예술기획 예루이종례전주시 완산구 중앙동 1가 55-3번지<NA>
335전문예술법인전통예술단사)전통예술원 모악최기춘전주시 완산구 현무3길 77-15, 4층 (경원동 3가)‘12년 법인전환
446전문예술법인전통예술단사)전통문화 마을김진형전주시 완산구 경원동 1가 111-9<NA>
5511전문예술단체전통예술단예술단 판 打 stick양진환전주시 완산구 은행로 34(풍남동3가)<NA>
6612전문예술법인연극단사)공연문화발전소 명태최경성전주시 완산구 전주객사4길 74-11(고사동)<NA>
7714전문예술법인국악공연단사)타악연희원 아퀴박종대전주시 완산구 중화산동 1가 219-14<NA>
8816전문예술단체연극단창작극회홍석찬전주시 완산구 경원동 1가 10-2<NA>
9917전문예술법인전통예술단사)온고을 소리청김영자전주시 완산구 한지길 92(풍남동3가)<NA>
전라북도 전문예술법인 및 단체 지정현황(22개소 작성일:2014.12.02)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7
131325전문예술단체필봉농악단임실필봉 농악보존회양진성임실군 강진면 필봉리 234<NA>
141426전문예술단체연극단극단 까치동전춘근전주시 완산구 경원동 2가 24-6<NA>
151527전문예술법인전통예술사)전주세계소리축제조직위원회김한전주시 덕진구 소리로 31(덕진동1가)<NA>
161628전문예술법인문화단체(재)전주문화재단유광찬전주시 완산구 권삼득로 76(서노송동)<NA>
171729전문예술법인문화단체(재)익산문화재단이한수익산시 평동로 1길 28-4(평화동)<NA>
181830전문예술법인사진사)현대사진 미디어 연구소박승환전주시 완산구 천잠로 303 전주대학교 예술관 별관 306호<NA>
191931전문예술단체음악팝페라 T&B김선식전주시 완산구 따박골 1길 3, 2층 (중화산동2가)<NA>
202032전문예술단체음악뮤직씨어터 슈바빙이은희완주군 용진면 구억명덕로 343-28<NA>
212133전문예술단체음악프로인데 성악 연구회정기주전주시 완산구 용머리로 73(효자동1가)<NA>
222234전문예술법인음악사단법인 드림필김재원전주시 완산구 용머리로 203, 2층(서완산동 2가)<NA>