Overview

Dataset statistics

Number of variables8
Number of observations127
Missing cells1
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.2 KiB
Average record size in memory66.0 B

Variable types

Numeric1
Text3
Categorical4

Dataset

Description전라남도 산하 도립미술관에 있는 소장품 중 기증목록 정보로 작품명, 작가명, 제작연도, 유형, 제작기법, 작품크기를 포함하고 있다
Author전라남도
URLhttps://www.data.go.kr/data/15105763/fileData.do

Alerts

연번 is highly overall correlated with 제작년도High correlation
작가명(국문) is highly overall correlated with 재료(국문) and 1 other fieldsHigh correlation
제작년도 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
재료(국문) is highly overall correlated with 작가명(국문) and 2 other fieldsHigh correlation
장르 is highly overall correlated with 작가명(국문) and 2 other fieldsHigh correlation
재료(국문) is highly imbalanced (54.9%)Imbalance
장르 is highly imbalanced (59.6%)Imbalance
연번 has unique valuesUnique
관리번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:56:50.953964
Analysis finished2023-12-12 12:56:51.791357
Duration0.84 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct127
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64
Minimum1
Maximum127
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T21:56:51.871620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.3
Q132.5
median64
Q395.5
95-th percentile120.7
Maximum127
Range126
Interquartile range (IQR)63

Descriptive statistics

Standard deviation36.805797
Coefficient of variation (CV)0.57509057
Kurtosis-1.2
Mean64
Median Absolute Deviation (MAD)32
Skewness0
Sum8128
Variance1354.6667
MonotonicityStrictly increasing
2023-12-12T21:56:52.033357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
2 1
 
0.8%
95 1
 
0.8%
94 1
 
0.8%
93 1
 
0.8%
92 1
 
0.8%
91 1
 
0.8%
90 1
 
0.8%
89 1
 
0.8%
88 1
 
0.8%
Other values (117) 117
92.1%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
127 1
0.8%
126 1
0.8%
125 1
0.8%
124 1
0.8%
123 1
0.8%
122 1
0.8%
121 1
0.8%
120 1
0.8%
119 1
0.8%
118 1
0.8%

관리번호
Text

UNIQUE 

Distinct127
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T21:56:52.406675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters1016
Distinct characters19
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique127 ?
Unique (%)100.0%

Sample

1st rowPA-00090
2nd rowPA-00091
3rd rowPA-00092
4th rowPA-00093
5th rowPA-00094
ValueCountFrequency (%)
pa-00090 1
 
0.8%
pa-00221 1
 
0.8%
pa-00218 1
 
0.8%
pa-00217 1
 
0.8%
pa-00216 1
 
0.8%
pa-00215 1
 
0.8%
pa-00214 1
 
0.8%
pa-00213 1
 
0.8%
pa-00212 1
 
0.8%
pa-00211 1
 
0.8%
Other values (117) 117
92.1%
2023-12-12T21:56:52.910968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 329
32.4%
- 127
 
12.5%
P 101
 
9.9%
A 100
 
9.8%
2 74
 
7.3%
1 62
 
6.1%
9 32
 
3.1%
4 30
 
3.0%
K 24
 
2.4%
O 24
 
2.4%
Other values (9) 113
 
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 635
62.5%
Uppercase Letter 252
 
24.8%
Dash Punctuation 127
 
12.5%
Other Letter 2
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 329
51.8%
2 74
 
11.7%
1 62
 
9.8%
9 32
 
5.0%
4 30
 
4.7%
6 24
 
3.8%
5 24
 
3.8%
3 22
 
3.5%
7 22
 
3.5%
8 16
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
P 101
40.1%
A 100
39.7%
K 24
 
9.5%
O 24
 
9.5%
D 2
 
0.8%
C 1
 
0.4%
Other Letter
ValueCountFrequency (%)
조 1
50.0%
각 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 127
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 762
75.0%
Latin 252
 
24.8%
Hangul 2
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 329
43.2%
- 127
 
16.7%
2 74
 
9.7%
1 62
 
8.1%
9 32
 
4.2%
4 30
 
3.9%
6 24
 
3.1%
5 24
 
3.1%
3 22
 
2.9%
7 22
 
2.9%
Latin
ValueCountFrequency (%)
P 101
40.1%
A 100
39.7%
K 24
 
9.5%
O 24
 
9.5%
D 2
 
0.8%
C 1
 
0.4%
Hangul
ValueCountFrequency (%)
조 1
50.0%
각 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1014
99.8%
Hangul 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 329
32.4%
- 127
 
12.5%
P 101
 
10.0%
A 100
 
9.9%
2 74
 
7.3%
1 62
 
6.1%
9 32
 
3.2%
4 30
 
3.0%
K 24
 
2.4%
O 24
 
2.4%
Other values (7) 111
 
10.9%
Hangul
ValueCountFrequency (%)
조 1
50.0%
각 1
50.0%

작가명(국문)
Categorical

HIGH CORRELATION 

Distinct33
Distinct (%)26.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
윤재우
65 
고화흠
12 
오지호
 
5
김은호
 
4
송창
 
4
Other values (28)
37 

Length

Max length3
Median length3
Mean length2.9527559
Min length2

Unique

Unique21 ?
Unique (%)16.5%

Sample

1st row송창
2nd row송창
3rd row송창
4th row송창
5th row이희중

Common Values

ValueCountFrequency (%)
윤재우 65
51.2%
고화흠 12
 
9.4%
오지호 5
 
3.9%
김은호 4
 
3.1%
송창 4
 
3.1%
허백련 3
 
2.4%
박대성 3
 
2.4%
김지하 2
 
1.6%
유영국 2
 
1.6%
이희중 2
 
1.6%
Other values (23) 25
 
19.7%

Length

2023-12-12T21:56:53.096415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
윤재우 65
51.2%
고화흠 12
 
9.4%
오지호 5
 
3.9%
김은호 4
 
3.1%
송창 4
 
3.1%
허백련 3
 
2.4%
박대성 3
 
2.4%
이희중 2
 
1.6%
천경자 2
 
1.6%
오경환 2
 
1.6%
Other values (23) 25
 
19.7%

작품명(국문)
Text

Distinct106
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T21:56:53.489536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length18
Mean length4.7086614
Min length1

Characters and Unicode

Total characters598
Distinct characters205
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique99 ?
Unique (%)78.0%

Sample

1st row식을수 없는 강
2nd row금강산 가던 철길
3rd row누가 해송에 흠집을 냈는가
4th row임진교각
5th row계룡산 인상
ValueCountFrequency (%)
무제 10
 
5.7%
누드와상 5
 
2.9%
백안(白岸 4
 
2.3%
장미 3
 
1.7%
여인 3
 
1.7%
항구풍경 3
 
1.7%
하일 2
 
1.1%
작품 2
 
1.1%
공간과 2
 
1.1%
물정 2
 
1.1%
Other values (134) 138
79.3%
2023-12-12T21:56:54.017792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
47
 
7.9%
경 15
 
2.5%
상 15
 
2.5%
무 11
 
1.8%
풍 11
 
1.8%
제 11
 
1.8%
산 11
 
1.8%
( 10
 
1.7%
) 10
 
1.7%
과 9
 
1.5%
Other values (195) 448
74.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 493
82.4%
Space Separator 47
 
7.9%
Decimal Number 20
 
3.3%
Open Punctuation 10
 
1.7%
Close Punctuation 10
 
1.7%
Dash Punctuation 8
 
1.3%
Other Punctuation 6
 
1.0%
Letter Number 2
 
0.3%
Uppercase Letter 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 15
 
3.0%
상 15
 
3.0%
무 11
 
2.2%
풍 11
 
2.2%
제 11
 
2.2%
산 11
 
2.2%
과 9
 
1.8%
누 9
 
1.8%
수 8
 
1.6%
도 8
 
1.6%
Other values (177) 385
78.1%
Decimal Number
ValueCountFrequency (%)
0 4
20.0%
1 3
15.0%
9 3
15.0%
8 3
15.0%
2 3
15.0%
7 2
10.0%
3 1
 
5.0%
5 1
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 5
83.3%
. 1
 
16.7%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅰ 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
L 1
50.0%
M 1
50.0%
Space Separator
ValueCountFrequency (%)
47
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 478
79.9%
Common 101
 
16.9%
Han 15
 
2.5%
Latin 4
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 15
 
3.1%
상 15
 
3.1%
무 11
 
2.3%
풍 11
 
2.3%
제 11
 
2.3%
산 11
 
2.3%
과 9
 
1.9%
누 9
 
1.9%
수 8
 
1.7%
도 8
 
1.7%
Other values (172) 370
77.4%
Common
ValueCountFrequency (%)
47
46.5%
( 10
 
9.9%
) 10
 
9.9%
- 8
 
7.9%
, 5
 
5.0%
0 4
 
4.0%
1 3
 
3.0%
9 3
 
3.0%
8 3
 
3.0%
2 3
 
3.0%
Other values (4) 5
 
5.0%
Han
ValueCountFrequency (%)
岸 6
40.0%
白 6
40.0%
像 1
 
6.7%
畵 1
 
6.7%
自 1
 
6.7%
Latin
ValueCountFrequency (%)
Ⅱ 1
25.0%
L 1
25.0%
Ⅰ 1
25.0%
M 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 478
79.9%
ASCII 103
 
17.2%
CJK 15
 
2.5%
Number Forms 2
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
47
45.6%
( 10
 
9.7%
) 10
 
9.7%
- 8
 
7.8%
, 5
 
4.9%
0 4
 
3.9%
1 3
 
2.9%
9 3
 
2.9%
8 3
 
2.9%
2 3
 
2.9%
Other values (6) 7
 
6.8%
Hangul
ValueCountFrequency (%)
경 15
 
3.1%
상 15
 
3.1%
무 11
 
2.3%
풍 11
 
2.3%
제 11
 
2.3%
산 11
 
2.3%
과 9
 
1.9%
누 9
 
1.9%
수 8
 
1.7%
도 8
 
1.7%
Other values (172) 370
77.4%
CJK
ValueCountFrequency (%)
岸 6
40.0%
白 6
40.0%
像 1
 
6.7%
畵 1
 
6.7%
自 1
 
6.7%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅰ 1
50.0%

사이즈(센티미터)
Text

Distinct93
Distinct (%)73.8%
Missing1
Missing (%)0.8%
Memory size1.1 KiB
2023-12-12T21:56:54.351535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length19
Mean length10.142857
Min length5

Characters and Unicode

Total characters1278
Distinct characters22
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique79 ?
Unique (%)62.7%

Sample

1st row3piece 91x183 (1piece 91x61)
2nd row91x150cm
3rd row2piece 150x182 (1piece 150x91)cm
4th row227x181.5cm
5th row180x150cm
ValueCountFrequency (%)
45.5x60.612호 10
 
7.5%
27.3x40.96호 6
 
4.5%
33.4x45.58호 5
 
3.8%
90.9x72.730호 4
 
3.0%
53x72.720호 3
 
2.3%
53x40.910호 3
 
2.3%
40.9x27.36호 2
 
1.5%
1piece 2
 
1.5%
65.1x5015호 2
 
1.5%
72.7x5320호 2
 
1.5%
Other values (89) 94
70.7%
2023-12-12T21:56:54.832375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 160
12.5%
1 131
10.3%
x 128
10.0%
5 122
9.5%
0 121
9.5%
3 99
7.7%
2 86
 
6.7%
4 73
 
5.7%
6 69
 
5.4%
7 63
 
4.9%
Other values (12) 226
17.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 859
67.2%
Lowercase Letter 182
 
14.2%
Other Punctuation 160
 
12.5%
Other Letter 60
 
4.7%
Space Separator 9
 
0.7%
Open Punctuation 3
 
0.2%
Close Punctuation 3
 
0.2%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 131
15.3%
5 122
14.2%
0 121
14.1%
3 99
11.5%
2 86
10.0%
4 73
8.5%
6 69
8.0%
7 63
7.3%
9 56
6.5%
8 39
 
4.5%
Lowercase Letter
ValueCountFrequency (%)
x 128
70.3%
c 21
 
11.5%
m 17
 
9.3%
e 8
 
4.4%
p 4
 
2.2%
i 4
 
2.2%
Other Punctuation
ValueCountFrequency (%)
. 160
100.0%
Other Letter
ValueCountFrequency (%)
호 60
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1034
80.9%
Latin 184
 
14.4%
Hangul 60
 
4.7%

Most frequent character per script

Common
ValueCountFrequency (%)
. 160
15.5%
1 131
12.7%
5 122
11.8%
0 121
11.7%
3 99
9.6%
2 86
8.3%
4 73
7.1%
6 69
6.7%
7 63
 
6.1%
9 56
 
5.4%
Other values (4) 54
 
5.2%
Latin
ValueCountFrequency (%)
x 128
69.6%
c 21
 
11.4%
m 17
 
9.2%
e 8
 
4.3%
p 4
 
2.2%
i 4
 
2.2%
X 2
 
1.1%
Hangul
ValueCountFrequency (%)
호 60
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1218
95.3%
Hangul 60
 
4.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 160
13.1%
1 131
10.8%
x 128
10.5%
5 122
10.0%
0 121
9.9%
3 99
8.1%
2 86
7.1%
4 73
6.0%
6 69
5.7%
7 63
 
5.2%
Other values (11) 166
13.6%
Hangul
ValueCountFrequency (%)
호 60
100.0%

제작년도
Categorical

HIGH CORRELATION 

Distinct43
Distinct (%)33.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
연도미상
22 
<NA>
10 
2000
 
7
1990
 
7
2003
 
5
Other values (38)
76 

Length

Max length9
Median length4
Mean length4.0866142
Min length4

Unique

Unique17 ?
Unique (%)13.4%

Sample

1st row1990
2nd row1990
3rd row1990
4th row1990
5th row1987

Common Values

ValueCountFrequency (%)
연도미상 22
 
17.3%
<NA> 10
 
7.9%
2000 7
 
5.5%
1990 7
 
5.5%
2003 5
 
3.9%
1987 5
 
3.9%
1989 4
 
3.1%
1991 4
 
3.1%
1970 4
 
3.1%
1999 4
 
3.1%
Other values (33) 55
43.3%

Length

2023-12-12T21:56:55.020860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연도미상 22
 
17.3%
na 10
 
7.9%
2000 7
 
5.5%
1990 7
 
5.5%
2003 5
 
3.9%
1987 5
 
3.9%
1989 4
 
3.1%
1991 4
 
3.1%
1970 4
 
3.1%
1999 4
 
3.1%
Other values (33) 55
43.3%

재료(국문)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct18
Distinct (%)14.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
캔버스에 유채
90 
종이에 수묵담채
11 
종이에 수묵
 
6
캔버스에 오일
 
3
<NA>
 
2
Other values (13)
15 

Length

Max length32
Median length7
Mean length7.5275591
Min length2

Unique

Unique11 ?
Unique (%)8.7%

Sample

1st row캔버스에 혼합재료
2nd row합판에 혼합재료
3rd row캔버스에 유채
4th row캔버스에 유채
5th row캔버스에 유채

Common Values

ValueCountFrequency (%)
캔버스에 유채 90
70.9%
종이에 수묵담채 11
 
8.7%
종이에 수묵 6
 
4.7%
캔버스에 오일 3
 
2.4%
<NA> 2
 
1.6%
한지에 수묵담채 2
 
1.6%
종이에 채색(석채, 분채, 아교) 2
 
1.6%
캔버스에 아크릴릭 1
 
0.8%
한지에 채색 1
 
0.8%
한지에 먹, 복합재료 1
 
0.8%
Other values (8) 8
 
6.3%

Length

2023-12-12T21:56:55.151963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
캔버스에 97
37.2%
유채 90
34.5%
종이에 19
 
7.3%
수묵담채 13
 
5.0%
수묵 6
 
2.3%
한지에 4
 
1.5%
오일 3
 
1.1%
채색 2
 
0.8%
혼합재료 2
 
0.8%
아교 2
 
0.8%
Other values (20) 23
 
8.8%

장르
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
회화
99 
한국화
24 
판화
 
2
서예
 
1
조각
 
1

Length

Max length3
Median length2
Mean length2.1889764
Min length2

Unique

Unique2 ?
Unique (%)1.6%

Sample

1st row회화
2nd row회화
3rd row회화
4th row회화
5th row회화

Common Values

ValueCountFrequency (%)
회화 99
78.0%
한국화 24
 
18.9%
판화 2
 
1.6%
서예 1
 
0.8%
조각 1
 
0.8%

Length

2023-12-12T21:56:55.314051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:56:55.465760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
회화 99
78.0%
한국화 24
 
18.9%
판화 2
 
1.6%
서예 1
 
0.8%
조각 1
 
0.8%

Interactions

2023-12-12T21:56:51.496178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:56:55.579675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번작가명(국문)사이즈(센티미터)제작년도재료(국문)장르
연번1.0000.8780.9040.9080.7040.662
작가명(국문)0.8781.0001.0000.9410.9841.000
사이즈(센티미터)0.9041.0001.0000.9851.0001.000
제작년도0.9080.9410.9851.0000.9530.958
재료(국문)0.7040.9841.0000.9531.0000.953
장르0.6621.0001.0000.9580.9531.000
2023-12-12T21:56:56.036514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
제작년도장르작가명(국문)재료(국문)
제작년도1.0000.6710.4680.558
장르0.6711.0000.8780.822
작가명(국문)0.4680.8781.0000.782
재료(국문)0.5580.8220.7821.000
2023-12-12T21:56:56.143651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번작가명(국문)제작년도재료(국문)장르
연번1.0000.4950.5060.3530.327
작가명(국문)0.4951.0000.4680.7820.878
제작년도0.5060.4681.0000.5580.671
재료(국문)0.3530.7820.5581.0000.822
장르0.3270.8780.6710.8221.000

Missing values

2023-12-12T21:56:51.618597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:56:51.744950image/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

연번관리번호작가명(국문)작품명(국문)사이즈(센티미터)제작년도재료(국문)장르
01PA-00090송창식을수 없는 강3piece 91x183 (1piece 91x61)1990캔버스에 혼합재료회화
12PA-00091송창금강산 가던 철길91x150cm1990합판에 혼합재료회화
23PA-00092송창누가 해송에 흠집을 냈는가2piece 150x182 (1piece 150x91)cm1990캔버스에 유채회화
34PA-00093송창임진교각227x181.5cm1990캔버스에 유채회화
45PA-00094이희중계룡산 인상180x150cm1987캔버스에 유채회화
56PA-00095이희중용150x190cm1989캔버스에 유채회화
67PA-00096오경환공간과 물정 87-Ⅱ180x100cm1987캔버스에 유채회화
78PA-00097오경환공간과 물정 87-Ⅰ 이것과 이것에 시간은 없고, 공간은 있다.180x100cm1987캔버스에 유채회화
89PA-00098진유영무제174x174cm1991캔버스에 유채회화
910PA-00099박재곤무제144x97cm1990캔버스에 유채회화
연번관리번호작가명(국문)작품명(국문)사이즈(센티미터)제작년도재료(국문)장르
117118PA-00242윤재우전원65.1x5015호연도미상캔버스에 유채회화
118119PA-00243윤재우추경65.1x5015호연도미상캔버스에 유채회화
119120PA-00244윤재우항구풍경45.5x60.612호연도미상캔버스에 유채회화
120121PA-00245윤재우양평풍경45.5x60.612호연도미상캔버스에 유채회화
121122PA-00246윤재우무제45.5x60.612호연도미상캔버스에 유채회화
122123PA-00247윤재우무제45.5x60.612호연도미상캔버스에 유채회화
123124PA-00248윤재우감45.5x60.612호연도미상캔버스에 유채회화
124125PA-00249윤재우무제33.4x45.58호연도미상캔버스에 유채회화
125126PA-00250윤재우항구풍경33.4x45.58호연도미상캔버스에 유채회화
126127PA-00251윤재우동강풍경90.9x65.130호연도미상캔버스에 유채회화