Overview

Dataset statistics

Number of variables12
Number of observations115
Missing cells13
Missing cells (%)0.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.9 KiB
Average record size in memory97.1 B

Variable types

Categorical3
Text3
Unsupported6

Dataset

Description16092212-16년미술작품설치내역
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202717

Alerts

미술작품설치 내역(2012~2016년) is highly overall correlated with Unnamed: 3High correlation
Unnamed: 3 is highly overall correlated with 미술작품설치 내역(2012~2016년)High correlation
미술작품설치 내역(2012~2016년) is highly imbalanced (62.4%)Imbalance
Unnamed: 4 has 5 (4.3%) missing valuesMissing
Unnamed: 5 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
Unnamed: 7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 11 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 01:23:53.534444
Analysis finished2024-03-14 01:23:54.581644
Duration1.05 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

미술작품설치 내역(2012~2016년)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct8
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
조각
94 
회화
 
8
기타
 
4
공예
 
3
상징탑
 
3
Other values (3)
 
3

Length

Max length4
Median length2
Mean length2.0434783
Min length2

Unique

Unique3 ?
Unique (%)2.6%

Sample

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

Common Values

ValueCountFrequency (%)
조각 94
81.7%
회화 8
 
7.0%
기타 4
 
3.5%
공예 3
 
2.6%
상징탑 3
 
2.6%
<NA> 1
 
0.9%
분류 1
 
0.9%
사진 1
 
0.9%

Length

2024-03-14T10:23:54.652345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:23:54.766274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
조각 94
81.7%
회화 8
 
7.0%
기타 4
 
3.5%
공예 3
 
2.6%
상징탑 3
 
2.6%
na 1
 
0.9%
분류 1
 
0.9%
사진 1
 
0.9%

Unnamed: 1
Categorical

Distinct13
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
전북/전주시
62 
전북/익산시
14 
전북/군산시
13 
전북/완주군
11 
전북/김제시
 
4
Other values (8)
11 

Length

Max length6
Median length6
Mean length5.9478261
Min length2

Unique

Unique5 ?
Unique (%)4.3%

Sample

1st row<NA>
2nd row지역
3rd row전북/김제시
4th row전북/완주군
5th row전북/남원시

Common Values

ValueCountFrequency (%)
전북/전주시 62
53.9%
전북/익산시 14
 
12.2%
전북/군산시 13
 
11.3%
전북/완주군 11
 
9.6%
전북/김제시 4
 
3.5%
전북/남원시 2
 
1.7%
전북/정읍시 2
 
1.7%
전북/고창군 2
 
1.7%
<NA> 1
 
0.9%
지역 1
 
0.9%
Other values (3) 3
 
2.6%

Length

2024-03-14T10:23:54.916138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전북/전주시 62
53.9%
전북/익산시 14
 
12.2%
전북/군산시 13
 
11.3%
전북/완주군 11
 
9.6%
전북/김제시 4
 
3.5%
전북/남원시 2
 
1.7%
전북/정읍시 2
 
1.7%
전북/고창군 2
 
1.7%
na 1
 
0.9%
지역 1
 
0.9%
Other values (3) 3
 
2.6%

Unnamed: 2
Text

Distinct108
Distinct (%)94.7%
Missing1
Missing (%)0.9%
Memory size1.0 KiB
2024-03-14T10:23:55.155926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length15
Mean length6.377193
Min length1

Characters and Unicode

Total characters727
Distinct characters219
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

Unique104 ?
Unique (%)91.2%

Sample

1st row작품명
2nd row사랑-2014
3rd row이야기-2015
4th row가족-愛
5th row풍경이 있는 집
ValueCountFrequency (%)
6
 
3.2%
비상 5
 
2.7%
하모니 3
 
1.6%
풍경 3
 
1.6%
소리 3
 
1.6%
사람 2
 
1.1%
dream 2
 
1.1%
happy 2
 
1.1%
별을 2
 
1.1%
풍요 2
 
1.1%
Other values (151) 158
84.0%
2024-03-14T10:23:55.518079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
74
 
10.2%
의 27
 
3.7%
- 21
 
2.9%
1 13
 
1.8%
e 13
 
1.8%
이 12
 
1.7%
풍 11
 
1.5%
하 11
 
1.5%
기 11
 
1.5%
a 11
 
1.5%
Other values (209) 523
71.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 465
64.0%
Lowercase Letter 95
 
13.1%
Space Separator 74
 
10.2%
Decimal Number 39
 
5.4%
Uppercase Letter 24
 
3.3%
Dash Punctuation 21
 
2.9%
Other Punctuation 7
 
1.0%
Math Symbol 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 27
 
5.8%
이 12
 
2.6%
풍 11
 
2.4%
하 11
 
2.4%
기 11
 
2.4%
리 9
 
1.9%
는 9
 
1.9%
지 9
 
1.9%
사 8
 
1.7%
상 8
 
1.7%
Other values (166) 350
75.3%
Lowercase Letter
ValueCountFrequency (%)
e 13
13.7%
a 11
11.6%
r 10
10.5%
n 8
 
8.4%
o 5
 
5.3%
u 5
 
5.3%
m 5
 
5.3%
i 5
 
5.3%
s 5
 
5.3%
p 5
 
5.3%
Other values (9) 23
24.2%
Uppercase Letter
ValueCountFrequency (%)
S 4
16.7%
H 4
16.7%
E 3
12.5%
R 2
8.3%
F 2
8.3%
N 2
8.3%
W 1
 
4.2%
A 1
 
4.2%
C 1
 
4.2%
O 1
 
4.2%
Other values (3) 3
12.5%
Decimal Number
ValueCountFrequency (%)
1 13
33.3%
0 10
25.6%
2 10
25.6%
4 4
 
10.3%
5 1
 
2.6%
7 1
 
2.6%
Other Punctuation
ValueCountFrequency (%)
, 6
85.7%
& 1
 
14.3%
Space Separator
ValueCountFrequency (%)
74
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 463
63.7%
Common 143
 
19.7%
Latin 119
 
16.4%
Han 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 27
 
5.8%
이 12
 
2.6%
풍 11
 
2.4%
하 11
 
2.4%
기 11
 
2.4%
리 9
 
1.9%
는 9
 
1.9%
지 9
 
1.9%
사 8
 
1.7%
상 8
 
1.7%
Other values (164) 348
75.2%
Latin
ValueCountFrequency (%)
e 13
 
10.9%
a 11
 
9.2%
r 10
 
8.4%
n 8
 
6.7%
o 5
 
4.2%
u 5
 
4.2%
m 5
 
4.2%
i 5
 
4.2%
s 5
 
4.2%
p 5
 
4.2%
Other values (22) 47
39.5%
Common
ValueCountFrequency (%)
74
51.7%
- 21
 
14.7%
1 13
 
9.1%
0 10
 
7.0%
2 10
 
7.0%
, 6
 
4.2%
4 4
 
2.8%
+ 2
 
1.4%
& 1
 
0.7%
5 1
 
0.7%
Han
ValueCountFrequency (%)
線 1
50.0%
愛 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 463
63.7%
ASCII 262
36.0%
CJK 2
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
74
28.2%
- 21
 
8.0%
1 13
 
5.0%
e 13
 
5.0%
a 11
 
4.2%
r 10
 
3.8%
0 10
 
3.8%
2 10
 
3.8%
n 8
 
3.1%
, 6
 
2.3%
Other values (33) 86
32.8%
Hangul
ValueCountFrequency (%)
의 27
 
5.8%
이 12
 
2.6%
풍 11
 
2.4%
하 11
 
2.4%
기 11
 
2.4%
리 9
 
1.9%
는 9
 
1.9%
지 9
 
1.9%
사 8
 
1.7%
상 8
 
1.7%
Other values (164) 348
75.2%
CJK
ValueCountFrequency (%)
線 1
50.0%
愛 1
50.0%

Unnamed: 3
Categorical

HIGH CORRELATION 

Distinct32
Distinct (%)27.8%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
김**
23 
이**
18 
강**
10 
박**
7 
엄**
6 
Other values (27)
51 

Length

Max length4
Median length3
Mean length3.0086957
Min length3

Unique

Unique16 ?
Unique (%)13.9%

Sample

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

Common Values

ValueCountFrequency (%)
김** 23
20.0%
이** 18
15.7%
강** 10
 
8.7%
박** 7
 
6.1%
엄** 6
 
5.2%
유** 6
 
5.2%
국** 5
 
4.3%
소** 4
 
3.5%
조** 3
 
2.6%
임** 3
 
2.6%
Other values (22) 30
26.1%

Length

2024-03-14T10:23:55.632145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
김 23
20.0%
이 18
15.7%
강 10
 
8.7%
박 7
 
6.1%
엄 6
 
5.2%
유 6
 
5.2%
국 5
 
4.3%
소 4
 
3.5%
신 3
 
2.6%
권 3
 
2.6%
Other values (22) 30
26.1%

Unnamed: 4
Text

MISSING 

Distinct84
Distinct (%)76.4%
Missing5
Missing (%)4.3%
Memory size1.0 KiB
2024-03-14T10:23:55.837939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length20
Mean length11.509091
Min length2

Characters and Unicode

Total characters1266
Distinct characters110
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)67.3%

Sample

1st row재질
2nd row황등석, 대리석, 장흥석
3rd row황등석, 스텔레스스틸, 대리석 외
4th row청동, 화강석, 유화가리
5th row황등석, 고흥석, 스테인레스스틸
ValueCountFrequency (%)
화강석 49
20.9%
스테인레스스틸 32
 
13.6%
황등석 13
 
5.5%
브론즈 13
 
5.5%
스테인레스 11
 
4.7%
스틸 6
 
2.6%
고흥석 6
 
2.6%
청동 6
 
2.6%
상주석 5
 
2.1%
대리석 5
 
2.1%
Other values (65) 89
37.9%
2024-03-14T10:23:56.156413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 171
13.5%
, 129
 
10.2%
125
 
9.9%
석 115
 
9.1%
레 66
 
5.2%
강 59
 
4.7%
화 58
 
4.6%
인 52
 
4.1%
틸 51
 
4.0%
테 51
 
4.0%
Other values (100) 389
30.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 984
77.7%
Other Punctuation 129
 
10.2%
Space Separator 125
 
9.9%
Uppercase Letter 11
 
0.9%
Lowercase Letter 8
 
0.6%
Close Punctuation 4
 
0.3%
Open Punctuation 4
 
0.3%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 171
17.4%
석 115
 
11.7%
레 66
 
6.7%
강 59
 
6.0%
화 58
 
5.9%
인 52
 
5.3%
틸 51
 
5.2%
테 51
 
5.2%
황 21
 
2.1%
등 18
 
1.8%
Other values (86) 322
32.7%
Lowercase Letter
ValueCountFrequency (%)
i 2
25.0%
e 2
25.0%
d 2
25.0%
a 1
12.5%
x 1
12.5%
Uppercase Letter
ValueCountFrequency (%)
D 3
27.3%
L 3
27.3%
E 3
27.3%
M 2
18.2%
Other Punctuation
ValueCountFrequency (%)
, 129
100.0%
Space Separator
ValueCountFrequency (%)
125
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 984
77.7%
Common 263
 
20.8%
Latin 19
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 171
17.4%
석 115
 
11.7%
레 66
 
6.7%
강 59
 
6.0%
화 58
 
5.9%
인 52
 
5.3%
틸 51
 
5.2%
테 51
 
5.2%
황 21
 
2.1%
등 18
 
1.8%
Other values (86) 322
32.7%
Latin
ValueCountFrequency (%)
D 3
15.8%
L 3
15.8%
E 3
15.8%
M 2
10.5%
i 2
10.5%
e 2
10.5%
d 2
10.5%
a 1
 
5.3%
x 1
 
5.3%
Common
ValueCountFrequency (%)
, 129
49.0%
125
47.5%
) 4
 
1.5%
( 4
 
1.5%
1 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 983
77.6%
ASCII 282
 
22.3%
Compat Jamo 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 171
17.4%
석 115
 
11.7%
레 66
 
6.7%
강 59
 
6.0%
화 58
 
5.9%
인 52
 
5.3%
틸 51
 
5.2%
테 51
 
5.2%
황 21
 
2.1%
등 18
 
1.8%
Other values (85) 321
32.7%
ASCII
ValueCountFrequency (%)
, 129
45.7%
125
44.3%
) 4
 
1.4%
( 4
 
1.4%
D 3
 
1.1%
L 3
 
1.1%
E 3
 
1.1%
M 2
 
0.7%
i 2
 
0.7%
e 2
 
0.7%
Other values (4) 5
 
1.8%
Compat Jamo
ValueCountFrequency (%)
ㅅ 1
100.0%

Unnamed: 5
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)0.9%
Memory size1.0 KiB

Unnamed: 6
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)0.9%
Memory size1.0 KiB

Unnamed: 7
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)0.9%
Memory size1.0 KiB

Unnamed: 8
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)0.9%
Memory size1.0 KiB

Unnamed: 9
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)0.9%
Memory size1.0 KiB

Unnamed: 10
Text

Distinct85
Distinct (%)74.6%
Missing1
Missing (%)0.9%
Memory size1.0 KiB
2024-03-14T10:23:56.624206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length29
Mean length20.517544
Min length5

Characters and Unicode

Total characters2339
Distinct characters152
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

Unique69 ?
Unique (%)60.5%

Sample

1st row건축물주소
2nd row전북 김제시 검산동 1080-1
3rd row전북 완주군 이서면 갈산리 663-1
4th row전북 남원시 낙현길 5 (월락동, 양우내안애아파트)
5th row전북 전주시 덕진구 장동 1064
ValueCountFrequency (%)
전북 113
20.2%
전주시 62
 
11.1%
덕진구 38
 
6.8%
완산구 24
 
4.3%
익산시 14
 
2.5%
634-8 13
 
2.3%
금암동 13
 
2.3%
군산시 13
 
2.3%
완주군 11
 
2.0%
이서면 8
 
1.4%
Other values (167) 250
44.7%
2024-03-14T10:23:57.044482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
461
19.7%
전 180
 
7.7%
북 118
 
5.0%
시 103
 
4.4%
동 102
 
4.4%
1 91
 
3.9%
주 77
 
3.3%
- 73
 
3.1%
구 68
 
2.9%
산 68
 
2.9%
Other values (142) 998
42.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1387
59.3%
Space Separator 461
 
19.7%
Decimal Number 409
 
17.5%
Dash Punctuation 73
 
3.1%
Lowercase Letter 3
 
0.1%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%
Uppercase Letter 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 180
 
13.0%
북 118
 
8.5%
시 103
 
7.4%
동 102
 
7.4%
주 77
 
5.6%
구 68
 
4.9%
산 68
 
4.9%
진 44
 
3.2%
덕 44
 
3.2%
완 36
 
2.6%
Other values (124) 547
39.4%
Decimal Number
ValueCountFrequency (%)
1 91
22.2%
3 49
12.0%
6 45
11.0%
4 44
10.8%
5 44
10.8%
8 39
9.5%
2 39
9.5%
7 24
 
5.9%
0 18
 
4.4%
9 16
 
3.9%
Lowercase Letter
ValueCountFrequency (%)
c 2
66.7%
b 1
33.3%
Space Separator
ValueCountFrequency (%)
461
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 73
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1387
59.3%
Common 948
40.5%
Latin 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 180
 
13.0%
북 118
 
8.5%
시 103
 
7.4%
동 102
 
7.4%
주 77
 
5.6%
구 68
 
4.9%
산 68
 
4.9%
진 44
 
3.2%
덕 44
 
3.2%
완 36
 
2.6%
Other values (124) 547
39.4%
Common
ValueCountFrequency (%)
461
48.6%
1 91
 
9.6%
- 73
 
7.7%
3 49
 
5.2%
6 45
 
4.7%
4 44
 
4.6%
5 44
 
4.6%
8 39
 
4.1%
2 39
 
4.1%
7 24
 
2.5%
Other values (5) 39
 
4.1%
Latin
ValueCountFrequency (%)
c 2
50.0%
B 1
25.0%
b 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1387
59.3%
ASCII 952
40.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
461
48.4%
1 91
 
9.6%
- 73
 
7.7%
3 49
 
5.1%
6 45
 
4.7%
4 44
 
4.6%
5 44
 
4.6%
8 39
 
4.1%
2 39
 
4.1%
7 24
 
2.5%
Other values (8) 43
 
4.5%
Hangul
ValueCountFrequency (%)
전 180
 
13.0%
북 118
 
8.5%
시 103
 
7.4%
동 102
 
7.4%
주 77
 
5.6%
구 68
 
4.9%
산 68
 
4.9%
진 44
 
3.2%
덕 44
 
3.2%
완 36
 
2.6%
Other values (124) 547
39.4%

Unnamed: 11
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)0.9%
Memory size1.0 KiB

Correlations

2024-03-14T10:23:57.166906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
미술작품설치 내역(2012~2016년)Unnamed: 1Unnamed: 3Unnamed: 4Unnamed: 10
미술작품설치 내역(2012~2016년)1.0000.5870.8640.9260.000
Unnamed: 10.5871.0000.8260.0001.000
Unnamed: 30.8640.8261.0000.9330.000
Unnamed: 40.9260.0000.9331.0000.826
Unnamed: 100.0001.0000.0000.8261.000
2024-03-14T10:23:57.257076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 3Unnamed: 1미술작품설치 내역(2012~2016년)
Unnamed: 31.0000.3960.515
Unnamed: 10.3961.0000.326
미술작품설치 내역(2012~2016년)0.5150.3261.000
2024-03-14T10:23:57.333814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
미술작품설치 내역(2012~2016년)Unnamed: 1Unnamed: 3
미술작품설치 내역(2012~2016년)1.0000.3260.515
Unnamed: 10.3261.0000.396
Unnamed: 30.5150.3961.000

Missing values

2024-03-14T10:23:54.095131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T10:23:54.293932image/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.
2024-03-14T10:23:54.456044image/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

미술작품설치 내역(2012~2016년)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11
0<NA><NA><NA><NA><NA>NaNNaNNaNNaNNaN<NA>NaN
1분류지역작품명작가명재질규격(가로)규격(세로)규격(높이)설치일자가격(원)건축물주소연면적(㎡)
2조각전북/김제시사랑-2014김**황등석, 대리석, 장흥석2801301902016-08-22 00:00:0061000000전북 김제시 검산동 1080-151892.6992
3조각전북/완주군이야기-2015김**황등석, 스텔레스스틸, 대리석 외4501802962016-08-24 00:00:00122954000전북 완주군 이서면 갈산리 663-120219.804
4조각전북/남원시가족-愛김**청동, 화강석, 유화가리822052502016-08-02 00:00:0063000000전북 남원시 낙현길 5 (월락동, 양우내안애아파트)40247.6511
5조각전북/전주시풍경이 있는 집이**황등석, 고흥석, 스테인레스스틸8006004702016-06-02 00:00:00115361000전북 전주시 덕진구 장동 106491545.1756
6조각전북/전주시해피데이소**화강석, 고흥석, 청동2202202102016-07-15 00:00:0061000000전북 전주시 덕진구 백제대로 72146770.1
7조각전북/전주시마법박**화강석, 고흥석, 청동200901802016-06-20 00:00:0037500000전북 전주시 덕진구 고랑동 71529746.274
8기타전북/전주시책과 사람엄**황등석, 상주석, 브론즈 등2401203002016-01-14 00:00:00167100000전북 전주시 완산구 효자동 2가 1157-476541.92
9조각전북/군산시동행황**하강석130902502016-03-18 00:00:0040000000전북 군산시 대명동 385-1145259.2933
미술작품설치 내역(2012~2016년)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11
105조각전북/전주시Nature 2011조**화강석, 스텐레스스틸600cm600cm270cm2012-10-1272,000,000전북 전주시 완산구 평화동3가 94-1외58929.3
106조각전북/익산시합창 sing in chorus최**화강석, 스텐레스 스틸 황동160cm80cm280cm2012-09-1874,937,000전북 익산시 부송동 67559653.8375
107조각전북/익산시하모니2011조**화강석(백색)220cm100cm211cm2012-07-1337,000,000전북 익산시 송학동 138-24번지외 2필지21540.98
108공예전북/익산시Human & Space김**<NA>cmcmcm2012-05-31120,000,000전북 익산시 모현동1가 60
109조각전북/완주군삶의 작은 찬가오**화강석,스텐리스스틸2.3cm2.4cm6.3cm2012-05-17175,000,000전북 완주군 봉동읍 둔산리 873-261766.6444
110조각전북/전주시전통, 현재, 미래엄**화강석, 스테인레스스틸180cm160cm350cm2012-05-16152,000,000전북 전주시 덕진구 덕진동2가 68361176.394
111조각전북/완주군행복하여라,생의 공간,내안의 대화한**<NA>2.6cm2.65cm1.12cm2012-04-26212,410,000전북 완주군 용진면 운곡리 975-7814847.367
112조각전북/고창군갈망강**<NA>140cm100cm280cm2012-02-2499,000,000전북 고창군 고창읍 석정리 7950
113조각전북/고창군사랑강**화강석,고흥석,마강석150cm100cm250cm2012-02-24108,000,000전북 고창군 고창읍 석정리 7950
114조각전북/전주시관조-비상소**화강석,고흥석270cm170cm415cm2012-02-08135,000,000전북 전주시 완산구 효자동2가 1154-116118.6