Overview

Dataset statistics

Number of variables6
Number of observations249
Missing cells117
Missing cells (%)7.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.8 KiB
Average record size in memory48.5 B

Variable types

Categorical2
Text4

Alerts

한옥체험업 현황 is highly overall correlated with Unnamed: 1High correlation
Unnamed: 1 is highly overall correlated with 한옥체험업 현황High correlation
한옥체험업 현황 is highly imbalanced (95.2%)Imbalance
Unnamed: 1 is highly imbalanced (67.3%)Imbalance
Unnamed: 5 has 113 (45.4%) missing valuesMissing

Reproduction

Analysis started2024-03-14 03:18:30.700006
Analysis finished2024-03-14 03:18:31.516318
Duration0.82 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

한옥체험업 현황
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
전라북도
247 
시도
 
1
<NA>
 
1

Length

Max length4
Median length4
Mean length3.9919679
Min length2

Unique

Unique2 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
전라북도 247
99.2%
시도 1
 
0.4%
<NA> 1
 
0.4%

Length

2024-03-14T12:18:31.571926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T12:18:31.662775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라북도 247
99.2%
시도 1
 
0.4%
na 1
 
0.4%

Unnamed: 1
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct12
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
전주시
206 
남원시
 
11
완주군
 
9
정읍시
 
6
김제시
 
5
Other values (7)
 
12

Length

Max length4
Median length3
Mean length3.0040161
Min length3

Unique

Unique5 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
전주시 206
82.7%
남원시 11
 
4.4%
완주군 9
 
3.6%
정읍시 6
 
2.4%
김제시 5
 
2.0%
익산시 4
 
1.6%
부안군 3
 
1.2%
시군구 1
 
0.4%
<NA> 1
 
0.4%
진안군 1
 
0.4%
Other values (2) 2
 
0.8%

Length

2024-03-14T12:18:31.757911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주시 206
82.7%
남원시 11
 
4.4%
완주군 9
 
3.6%
정읍시 6
 
2.4%
김제시 5
 
2.0%
익산시 4
 
1.6%
부안군 3
 
1.2%
시군구 1
 
0.4%
na 1
 
0.4%
진안군 1
 
0.4%
Other values (2) 2
 
0.8%

Unnamed: 2
Text

Distinct248
Distinct (%)100.0%
Missing1
Missing (%)0.4%
Memory size2.1 KiB
2024-03-14T12:18:31.989662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length15
Mean length4.4153226
Min length1

Characters and Unicode

Total characters1095
Distinct characters258
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique248 ?
Unique (%)100.0%

Sample

1st row가옥명
2nd row문화공간 학인당
3rd row문화공간 양사재
4th row풍남헌
5th row전주한옥생활체험관
ValueCountFrequency (%)
고택 7
 
2.3%
한옥 3
 
1.0%
교동 3
 
1.0%
가인당 2
 
0.7%
동락원 2
 
0.7%
한옥마을숙박 2
 
0.7%
가은채 2
 
0.7%
숙박 2
 
0.7%
전주 2
 
0.7%
꿈 2
 
0.7%
Other values (269) 274
91.0%
2024-03-14T12:18:32.325317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
52
 
4.7%
한 38
 
3.5%
옥 36
 
3.3%
관 29
 
2.6%
당 25
 
2.3%
가 24
 
2.2%
고 21
 
1.9%
원 18
 
1.6%
이 16
 
1.5%
전 16
 
1.5%
Other values (248) 820
74.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1015
92.7%
Space Separator 52
 
4.7%
Decimal Number 8
 
0.7%
Uppercase Letter 7
 
0.6%
Open Punctuation 5
 
0.5%
Close Punctuation 5
 
0.5%
Other Punctuation 2
 
0.2%
Control 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
한 38
 
3.7%
옥 36
 
3.5%
관 29
 
2.9%
당 25
 
2.5%
가 24
 
2.4%
고 21
 
2.1%
원 18
 
1.8%
이 16
 
1.6%
전 16
 
1.6%
마 15
 
1.5%
Other values (232) 777
76.6%
Uppercase Letter
ValueCountFrequency (%)
G 2
28.6%
O 1
14.3%
E 1
14.3%
H 1
14.3%
T 1
14.3%
A 1
14.3%
Decimal Number
ValueCountFrequency (%)
2 3
37.5%
8 2
25.0%
6 1
 
12.5%
9 1
 
12.5%
1 1
 
12.5%
Space Separator
ValueCountFrequency (%)
52
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1014
92.6%
Common 73
 
6.7%
Latin 7
 
0.6%
Han 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
한 38
 
3.7%
옥 36
 
3.6%
관 29
 
2.9%
당 25
 
2.5%
가 24
 
2.4%
고 21
 
2.1%
원 18
 
1.8%
이 16
 
1.6%
전 16
 
1.6%
마 15
 
1.5%
Other values (231) 776
76.5%
Common
ValueCountFrequency (%)
52
71.2%
( 5
 
6.8%
) 5
 
6.8%
2 3
 
4.1%
8 2
 
2.7%
. 2
 
2.7%
1
 
1.4%
6 1
 
1.4%
9 1
 
1.4%
1 1
 
1.4%
Latin
ValueCountFrequency (%)
G 2
28.6%
O 1
14.3%
E 1
14.3%
H 1
14.3%
T 1
14.3%
A 1
14.3%
Han
ValueCountFrequency (%)
家 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1014
92.6%
ASCII 80
 
7.3%
CJK 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
52
65.0%
( 5
 
6.2%
) 5
 
6.2%
2 3
 
3.8%
G 2
 
2.5%
8 2
 
2.5%
. 2
 
2.5%
O 1
 
1.2%
E 1
 
1.2%
H 1
 
1.2%
Other values (6) 6
 
7.5%
Hangul
ValueCountFrequency (%)
한 38
 
3.7%
옥 36
 
3.6%
관 29
 
2.9%
당 25
 
2.5%
가 24
 
2.4%
고 21
 
2.1%
원 18
 
1.8%
이 16
 
1.6%
전 16
 
1.6%
마 15
 
1.5%
Other values (231) 776
76.5%
CJK
ValueCountFrequency (%)
家 1
100.0%

Unnamed: 3
Text

Distinct247
Distinct (%)99.6%
Missing1
Missing (%)0.4%
Memory size2.1 KiB
2024-03-14T12:18:32.698884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length24
Mean length20.181452
Min length2

Characters and Unicode

Total characters5005
Distinct characters140
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

Unique246 ?
Unique (%)99.2%

Sample

1st row주소
2nd row 완산구 향교길 45 (교동)
3rd row 완산구 오목대길 40 (교동, 양사재)
4th row 완산구 은행로 35 (풍남동3가, 풍남헌)
5th row 완산구 어진길 29 (풍남동3가)
ValueCountFrequency (%)
완산구 206
20.1%
교동 93
 
9.1%
풍남동3가 71
 
6.9%
향교길 37
 
3.6%
은행로 33
 
3.2%
최명희길 24
 
2.3%
전라북도 20
 
1.9%
한지길 18
 
1.8%
전주천동로 17
 
1.7%
오목대길 12
 
1.2%
Other values (341) 496
48.3%
2024-03-14T12:18:33.120194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
986
19.7%
동 246
 
4.9%
산 225
 
4.5%
완 217
 
4.3%
) 213
 
4.3%
( 213
 
4.3%
구 209
 
4.2%
1 186
 
3.7%
- 180
 
3.6%
길 159
 
3.2%
Other values (130) 2171
43.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2479
49.5%
Space Separator 986
 
19.7%
Decimal Number 927
 
18.5%
Close Punctuation 213
 
4.3%
Open Punctuation 213
 
4.3%
Dash Punctuation 180
 
3.6%
Other Punctuation 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 246
 
9.9%
산 225
 
9.1%
완 217
 
8.8%
구 209
 
8.4%
길 159
 
6.4%
교 134
 
5.4%
남 101
 
4.1%
가 95
 
3.8%
로 88
 
3.5%
풍 87
 
3.5%
Other values (115) 918
37.0%
Decimal Number
ValueCountFrequency (%)
1 186
20.1%
3 150
16.2%
2 113
12.2%
5 109
11.8%
4 83
9.0%
6 73
 
7.9%
8 67
 
7.2%
9 52
 
5.6%
7 51
 
5.5%
0 43
 
4.6%
Space Separator
ValueCountFrequency (%)
986
100.0%
Close Punctuation
ValueCountFrequency (%)
) 213
100.0%
Open Punctuation
ValueCountFrequency (%)
( 213
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 180
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2526
50.5%
Hangul 2479
49.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 246
 
9.9%
산 225
 
9.1%
완 217
 
8.8%
구 209
 
8.4%
길 159
 
6.4%
교 134
 
5.4%
남 101
 
4.1%
가 95
 
3.8%
로 88
 
3.5%
풍 87
 
3.5%
Other values (115) 918
37.0%
Common
ValueCountFrequency (%)
986
39.0%
) 213
 
8.4%
( 213
 
8.4%
1 186
 
7.4%
- 180
 
7.1%
3 150
 
5.9%
2 113
 
4.5%
5 109
 
4.3%
4 83
 
3.3%
6 73
 
2.9%
Other values (5) 220
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2526
50.5%
Hangul 2479
49.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
986
39.0%
) 213
 
8.4%
( 213
 
8.4%
1 186
 
7.4%
- 180
 
7.1%
3 150
 
5.9%
2 113
 
4.5%
5 109
 
4.3%
4 83
 
3.3%
6 73
 
2.9%
Other values (5) 220
 
8.7%
Hangul
ValueCountFrequency (%)
동 246
 
9.9%
산 225
 
9.1%
완 217
 
8.8%
구 209
 
8.4%
길 159
 
6.4%
교 134
 
5.4%
남 101
 
4.1%
가 95
 
3.8%
로 88
 
3.5%
풍 87
 
3.5%
Other values (115) 918
37.0%

Unnamed: 4
Text

Distinct233
Distinct (%)94.3%
Missing2
Missing (%)0.8%
Memory size2.1 KiB
2024-03-14T12:18:33.416821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length3
Mean length3.2591093
Min length2

Characters and Unicode

Total characters805
Distinct characters144
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique221 ?
Unique (%)89.5%

Sample

1st row대표자
2nd row백광제
3rd row정재민
4th row최영례
5th row김창균
ValueCountFrequency (%)
복병산 3
 
1.2%
명 3
 
1.2%
외 3
 
1.2%
이화현 3
 
1.2%
1 3
 
1.2%
박재명 2
 
0.8%
남원시장 2
 
0.8%
박미리 2
 
0.8%
김영숙 2
 
0.8%
이동근 2
 
0.8%
Other values (228) 233
90.3%
2024-03-14T12:18:33.866690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 50
 
6.2%
김 45
 
5.6%
박 28
 
3.5%
정 22
 
2.7%
영 22
 
2.7%
숙 18
 
2.2%
순 16
 
2.0%
현 16
 
2.0%
미 15
 
1.9%
유 14
 
1.7%
Other values (134) 559
69.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 783
97.3%
Space Separator 11
 
1.4%
Other Punctuation 8
 
1.0%
Decimal Number 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 50
 
6.4%
김 45
 
5.7%
박 28
 
3.6%
정 22
 
2.8%
영 22
 
2.8%
숙 18
 
2.3%
순 16
 
2.0%
현 16
 
2.0%
미 15
 
1.9%
유 14
 
1.8%
Other values (131) 537
68.6%
Space Separator
ValueCountFrequency (%)
11
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%
Decimal Number
ValueCountFrequency (%)
1 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 783
97.3%
Common 22
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 50
 
6.4%
김 45
 
5.7%
박 28
 
3.6%
정 22
 
2.8%
영 22
 
2.8%
숙 18
 
2.3%
순 16
 
2.0%
현 16
 
2.0%
미 15
 
1.9%
유 14
 
1.8%
Other values (131) 537
68.6%
Common
ValueCountFrequency (%)
11
50.0%
, 8
36.4%
1 3
 
13.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 783
97.3%
ASCII 22
 
2.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 50
 
6.4%
김 45
 
5.7%
박 28
 
3.6%
정 22
 
2.8%
영 22
 
2.8%
숙 18
 
2.3%
순 16
 
2.0%
현 16
 
2.0%
미 15
 
1.9%
유 14
 
1.8%
Other values (131) 537
68.6%
ASCII
ValueCountFrequency (%)
11
50.0%
, 8
36.4%
1 3
 
13.6%

Unnamed: 5
Text

MISSING 

Distinct120
Distinct (%)88.2%
Missing113
Missing (%)45.4%
Memory size2.1 KiB
2024-03-14T12:18:34.167628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length25
Mean length16.941176
Min length1

Characters and Unicode

Total characters2304
Distinct characters86
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique115 ?
Unique (%)84.6%

Sample

1st row웹사이트 주소 (홈페이지,블로그)
2nd rowwww.from1908.kr
3rd rowwww.yangsajae.kr
4th rowwww.poongnam.co.kr
5th rowwww.jjhanok.com
ValueCountFrequency (%)
royalroom.co.kr 11
 
8.0%
4
 
2.9%
www.gaindang.co.kr 2
 
1.4%
www.eodang.co.kr 2
 
1.4%
www.sosohanhanok.co.kr 2
 
1.4%
강령전.com 1
 
0.7%
홈페이지,블로그 1
 
0.7%
starrest.co.kr 1
 
0.7%
www.hanokmaru.com 1
 
0.7%
www.lovenamu.co.kr 1
 
0.7%
Other values (112) 112
81.2%
2024-03-14T12:18:34.550873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 267
 
11.6%
w 264
 
11.5%
o 260
 
11.3%
a 152
 
6.6%
r 129
 
5.6%
n 119
 
5.2%
k 116
 
5.0%
m 110
 
4.8%
c 102
 
4.4%
h 83
 
3.6%
Other values (76) 702
30.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1867
81.0%
Other Punctuation 335
 
14.5%
Other Letter 66
 
2.9%
Decimal Number 25
 
1.1%
Dash Punctuation 5
 
0.2%
Space Separator 3
 
0.1%
Control 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
옥 5
 
7.6%
한 5
 
7.6%
이 4
 
6.1%
전 3
 
4.5%
주 3
 
4.5%
숙 2
 
3.0%
모 2
 
3.0%
박 2
 
3.0%
사 2
 
3.0%
마 2
 
3.0%
Other values (35) 36
54.5%
Lowercase Letter
ValueCountFrequency (%)
w 264
14.1%
o 260
13.9%
a 152
 
8.1%
r 129
 
6.9%
n 119
 
6.4%
k 116
 
6.2%
m 110
 
5.9%
c 102
 
5.5%
h 83
 
4.4%
e 77
 
4.1%
Other values (14) 455
24.4%
Decimal Number
ValueCountFrequency (%)
1 6
24.0%
2 4
16.0%
0 4
16.0%
4 3
12.0%
8 3
12.0%
9 3
12.0%
7 1
 
4.0%
5 1
 
4.0%
Other Punctuation
ValueCountFrequency (%)
. 267
79.7%
/ 51
 
15.2%
: 16
 
4.8%
, 1
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Control
ValueCountFrequency (%)
1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1867
81.0%
Common 371
 
16.1%
Hangul 66
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
옥 5
 
7.6%
한 5
 
7.6%
이 4
 
6.1%
전 3
 
4.5%
주 3
 
4.5%
숙 2
 
3.0%
모 2
 
3.0%
박 2
 
3.0%
사 2
 
3.0%
마 2
 
3.0%
Other values (35) 36
54.5%
Latin
ValueCountFrequency (%)
w 264
14.1%
o 260
13.9%
a 152
 
8.1%
r 129
 
6.9%
n 119
 
6.4%
k 116
 
6.2%
m 110
 
5.9%
c 102
 
5.5%
h 83
 
4.4%
e 77
 
4.1%
Other values (14) 455
24.4%
Common
ValueCountFrequency (%)
. 267
72.0%
/ 51
 
13.7%
: 16
 
4.3%
1 6
 
1.6%
- 5
 
1.3%
2 4
 
1.1%
0 4
 
1.1%
4 3
 
0.8%
3
 
0.8%
8 3
 
0.8%
Other values (7) 9
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2238
97.1%
Hangul 66
 
2.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 267
11.9%
w 264
11.8%
o 260
11.6%
a 152
 
6.8%
r 129
 
5.8%
n 119
 
5.3%
k 116
 
5.2%
m 110
 
4.9%
c 102
 
4.6%
h 83
 
3.7%
Other values (31) 636
28.4%
Hangul
ValueCountFrequency (%)
옥 5
 
7.6%
한 5
 
7.6%
이 4
 
6.1%
전 3
 
4.5%
주 3
 
4.5%
숙 2
 
3.0%
모 2
 
3.0%
박 2
 
3.0%
사 2
 
3.0%
마 2
 
3.0%
Other values (35) 36
54.5%

Correlations

2024-03-14T12:18:34.735518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
한옥체험업 현황Unnamed: 1
한옥체험업 현황1.0001.000
Unnamed: 11.0001.000
2024-03-14T12:18:34.860417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
한옥체험업 현황Unnamed: 1
한옥체험업 현황1.0000.982
Unnamed: 10.9821.000
2024-03-14T12:18:34.933779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
한옥체험업 현황Unnamed: 1
한옥체험업 현황1.0000.982
Unnamed: 10.9821.000

Missing values

2024-03-14T12:18:31.044448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T12:18:31.368963image/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.
2024-03-14T12:18:31.458272image/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

한옥체험업 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5
0시도시군구가옥명주소대표자웹사이트 주소 (홈페이지,블로그)
1<NA><NA><NA><NA><NA><NA>
2전라북도전주시문화공간 학인당완산구 향교길 45 (교동)백광제www.from1908.kr
3전라북도전주시문화공간 양사재완산구 오목대길 40 (교동, 양사재)정재민www.yangsajae.kr
4전라북도전주시풍남헌완산구 은행로 35 (풍남동3가, 풍남헌)최영례www.poongnam.co.kr
5전라북도전주시전주한옥생활체험관완산구 어진길 29 (풍남동3가)김창균www.jjhanok.com
6전라북도전주시소담원완산구 오목대길 70 (교동, 소담원)임성숙<NA>
7전라북도전주시참다원완산구 향교길 155-9 (교동)배연식<NA>
8전라북도전주시부용헌완산구 향교길 147 (교동)이석재www.buyongheon.com
9전라북도전주시일락당완산구 최명희길 17-5 (풍남동3가)윤춘화ilrak.yghosting.kr/srb/
한옥체험업 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5
239전라북도완주군전통한지생활문화체험관 (소양대승한지마을)완주군 소양면 복은길 18-4완주군http://www.hanjivil.com
240전라북도완주군녹운재완주군 소양면 송광수만로 472-18정숙이http://nocwoonjae.alltheway.kr/
241전라북도완주군전통문화체험장완주군 고산면 대아저수로 392완주군http://wanjutc.kr/
242전라북도완주군청풍헌완주군 고산면 동봉길 20-6서금주http://sirangol.alltheway.kr/
243전라북도진안군괴정고택전라북도 진안군 주천면 감나무골길 31-3김미옥<NA>
244전라북도임실군임실필봉농악보존회전북 임실군 강진면 필봉굿길 92-3양진성http://www.pilbong.co.kr
245전라북도고창군고창읍성한옥마을전라북도 고창군 고창읍 동리로 128김영일www.고창읍성한옥마을.kr
246전라북도부안군나비의 꿈전라북도 부안군 진서면 내소사로 129박병우http://www.nabidream.net/
247전라북도부안군이갑수 고택전라북도 부안군 부안읍 선은2길 5원순연<NA>
248전라북도부안군선은동 고택전라북도 부안군 부안읍 선은2길 7-5이병훈<NA>