Overview

Dataset statistics

Number of variables16
Number of observations1800
Missing cells3205
Missing cells (%)11.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory232.2 KiB
Average record size in memory132.1 B

Variable types

Numeric4
Categorical4
Text8

Dataset

Description충청북도 청주시에서 2년마다 개최되는 청주공예비엔날레의 1~12회 공모전 입상작별 작품명/작가명/작품크기/재료/기법 등의 데이터를 제공합니다.
Author충청북도 청주시
URLhttps://www.data.go.kr/data/15110028/fileData.do

Alerts

회차 is highly overall correlated with 년도 and 1 other fieldsHigh correlation
작품크기(가로) is highly overall correlated with 작품크기(세로)High correlation
작품크기(세로) is highly overall correlated with 작품크기(가로) and 1 other fieldsHigh correlation
부문 is highly overall correlated with 작품크기(세로)High correlation
심사결과 is highly overall correlated with 기법(영문)High correlation
년도 is highly overall correlated with 회차 and 1 other fieldsHigh correlation
기법(영문) is highly overall correlated with 회차 and 2 other fieldsHigh correlation
심사결과 is highly imbalanced (72.6%)Imbalance
기법(영문) is highly imbalanced (85.8%)Imbalance
작가명(국문) has 145 (8.1%) missing valuesMissing
작품명(국문) has 264 (14.7%) missing valuesMissing
재료(국문) has 503 (27.9%) missing valuesMissing
재료(영문) has 505 (28.1%) missing valuesMissing
기법(국문) has 1773 (98.5%) missing valuesMissing
작품 사진 파일명 has unique valuesUnique
작품크기(가로) has 49 (2.7%) zerosZeros
작품크기(세로) has 62 (3.4%) zerosZeros
작품크기(높이) has 215 (11.9%) zerosZeros

Reproduction

Analysis started2023-12-11 22:51:16.863606
Analysis finished2023-12-11 22:51:21.158456
Duration4.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

회차
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.8994444
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.9 KiB
2023-12-12T07:51:21.225558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q38
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.2046034
Coefficient of variation (CV)0.54320426
Kurtosis-0.90039641
Mean5.8994444
Median Absolute Deviation (MAD)2
Skewness0.25861376
Sum10619
Variance10.269483
MonotonicityIncreasing
2023-12-12T07:51:21.331971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
8 269
14.9%
4 235
13.1%
3 188
10.4%
7 179
9.9%
1 159
8.8%
11 147
8.2%
5 144
8.0%
6 143
7.9%
2 140
7.8%
12 104
 
5.8%
ValueCountFrequency (%)
1 159
8.8%
2 140
7.8%
3 188
10.4%
4 235
13.1%
5 144
8.0%
6 143
7.9%
7 179
9.9%
8 269
14.9%
9 92
 
5.1%
11 147
8.2%
ValueCountFrequency (%)
12 104
 
5.8%
11 147
8.2%
9 92
 
5.1%
8 269
14.9%
7 179
9.9%
6 143
7.9%
5 144
8.0%
4 235
13.1%
3 188
10.4%
2 140
7.8%

부문
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
<NA>
1078 
도자
192 
섬유
155 
금속
138 
기타
125 
Other values (2)
112 

Length

Max length4
Median length4
Mean length3.1977778
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row도자
2nd row목칠
3rd row직물
4th row기타
5th row금속

Common Values

ValueCountFrequency (%)
<NA> 1078
59.9%
도자 192
 
10.7%
섬유 155
 
8.6%
금속 138
 
7.7%
기타 125
 
6.9%
목칠 109
 
6.1%
직물 3
 
0.2%

Length

2023-12-12T07:51:21.454943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:51:21.571243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1078
59.9%
도자 192
 
10.7%
섬유 155
 
8.6%
금속 138
 
7.7%
기타 125
 
6.9%
목칠 109
 
6.1%
직물 3
 
0.2%

심사결과
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct7
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
입선
1599 
동상
 
60
은상
 
44
특선
 
41
금상
 
34
Other values (2)
 
22

Length

Max length4
Median length2
Mean length2.0122222
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row금상
2nd row금상
3rd row금상
4th row금상
5th row대상

Common Values

ValueCountFrequency (%)
입선 1599
88.8%
동상 60
 
3.3%
은상 44
 
2.4%
특선 41
 
2.3%
금상 34
 
1.9%
대상 11
 
0.6%
공동대상 11
 
0.6%

Length

2023-12-12T07:51:21.692791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:51:21.820744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
입선 1599
88.8%
동상 60
 
3.3%
은상 44
 
2.4%
특선 41
 
2.3%
금상 34
 
1.9%
대상 11
 
0.6%
공동대상 11
 
0.6%

작가명(국문)
Text

MISSING 

Distinct1108
Distinct (%)66.9%
Missing145
Missing (%)8.1%
Memory size14.2 KiB
2023-12-12T07:51:22.128736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length3
Mean length3.8610272
Min length2

Characters and Unicode

Total characters6390
Distinct characters433
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique837 ?
Unique (%)50.6%

Sample

1st row박O백
2nd row이O주
3rd row윤O남
4th row장O남
5th row히로시O즈끼
ValueCountFrequency (%)
김o수 15
 
0.9%
김o영 15
 
0.9%
김o현 12
 
0.7%
김o정 12
 
0.7%
김o주 11
 
0.7%
이o영 10
 
0.6%
이o희 9
 
0.5%
김o희 9
 
0.5%
이o원 8
 
0.5%
김o연 8
 
0.5%
Other values (1101) 1549
93.4%
2023-12-12T07:51:22.536309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
O 1747
27.3%
이 287
 
4.5%
김 224
 
3.5%
스 139
 
2.2%
리 115
 
1.8%
정 107
 
1.7%
박 94
 
1.5%
라 64
 
1.0%
아 63
 
1.0%
나 59
 
0.9%
Other values (423) 3491
54.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4632
72.5%
Uppercase Letter 1749
 
27.4%
Space Separator 3
 
< 0.1%
Dash Punctuation 2
 
< 0.1%
Other Punctuation 2
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 287
 
6.2%
김 224
 
4.8%
스 139
 
3.0%
리 115
 
2.5%
정 107
 
2.3%
박 94
 
2.0%
라 64
 
1.4%
아 63
 
1.4%
나 59
 
1.3%
우 58
 
1.3%
Other values (414) 3422
73.9%
Uppercase Letter
ValueCountFrequency (%)
O 1747
99.9%
N 1
 
0.1%
R 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
. 1
50.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4632
72.5%
Latin 1749
 
27.4%
Common 9
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 287
 
6.2%
김 224
 
4.8%
스 139
 
3.0%
리 115
 
2.5%
정 107
 
2.3%
박 94
 
2.0%
라 64
 
1.4%
아 63
 
1.4%
나 59
 
1.3%
우 58
 
1.3%
Other values (414) 3422
73.9%
Common
ValueCountFrequency (%)
3
33.3%
- 2
22.2%
) 1
 
11.1%
( 1
 
11.1%
, 1
 
11.1%
. 1
 
11.1%
Latin
ValueCountFrequency (%)
O 1747
99.9%
N 1
 
0.1%
R 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4632
72.5%
ASCII 1758
 
27.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
O 1747
99.4%
3
 
0.2%
- 2
 
0.1%
) 1
 
0.1%
( 1
 
0.1%
N 1
 
0.1%
, 1
 
0.1%
R 1
 
0.1%
. 1
 
0.1%
Hangul
ValueCountFrequency (%)
이 287
 
6.2%
김 224
 
4.8%
스 139
 
3.0%
리 115
 
2.5%
정 107
 
2.3%
박 94
 
2.0%
라 64
 
1.4%
아 63
 
1.4%
나 59
 
1.3%
우 58
 
1.3%
Other values (414) 3422
73.9%

작가명(영문)
Text

Distinct1246
Distinct (%)69.2%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
2023-12-12T07:51:22.851751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length20
Mean length9.675
Min length5

Characters and Unicode

Total characters17415
Distinct characters74
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

Unique950 ?
Unique (%)52.8%

Sample

1st rowPark O Back
2nd rowLee O Joo
3rd rowYune O Nam
4th rowJang O Nam
5th rowHiroshi O
ValueCountFrequency (%)
o 1854
37.8%
kim 225
 
4.6%
lee 179
 
3.6%
park 94
 
1.9%
jung 54
 
1.1%
hee 51
 
1.0%
choi 50
 
1.0%
young 47
 
1.0%
won 46
 
0.9%
jin 41
 
0.8%
Other values (801) 2267
46.2%
2023-12-12T07:51:23.264823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3706
21.3%
O 1854
 
10.6%
n 1316
 
7.6%
o 1129
 
6.5%
e 1061
 
6.1%
i 885
 
5.1%
a 876
 
5.0%
u 616
 
3.5%
g 479
 
2.8%
K 409
 
2.3%
Other values (64) 5084
29.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8765
50.3%
Uppercase Letter 4885
28.1%
Space Separator 3706
21.3%
Other Letter 16
 
0.1%
Dash Punctuation 13
 
0.1%
Other Punctuation 12
 
0.1%
Close Punctuation 9
 
0.1%
Open Punctuation 9
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
O 1854
38.0%
K 409
 
8.4%
J 308
 
6.3%
H 304
 
6.2%
S 295
 
6.0%
L 271
 
5.5%
Y 252
 
5.2%
C 221
 
4.5%
M 147
 
3.0%
P 113
 
2.3%
Other values (16) 711
 
14.6%
Lowercase Letter
ValueCountFrequency (%)
n 1316
15.0%
o 1129
12.9%
e 1061
12.1%
i 885
10.1%
a 876
10.0%
u 616
7.0%
g 479
 
5.5%
h 394
 
4.5%
m 358
 
4.1%
k 302
 
3.4%
Other values (16) 1349
15.4%
Other Letter
ValueCountFrequency (%)
保 1
 
6.2%
知 1
 
6.2%
李 1
 
6.2%
會 1
 
6.2%
敏 1
 
6.2%
度 1
 
6.2%
皺 1
 
6.2%
覺 1
 
6.2%
山 1
 
6.2%
玉 1
 
6.2%
Other values (6) 6
37.5%
Other Punctuation
ValueCountFrequency (%)
, 8
66.7%
. 4
33.3%
Space Separator
ValueCountFrequency (%)
3706
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13650
78.4%
Common 3749
 
21.5%
Han 16
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
O 1854
13.6%
n 1316
 
9.6%
o 1129
 
8.3%
e 1061
 
7.8%
i 885
 
6.5%
a 876
 
6.4%
u 616
 
4.5%
g 479
 
3.5%
K 409
 
3.0%
h 394
 
2.9%
Other values (42) 4631
33.9%
Han
ValueCountFrequency (%)
保 1
 
6.2%
知 1
 
6.2%
李 1
 
6.2%
會 1
 
6.2%
敏 1
 
6.2%
度 1
 
6.2%
皺 1
 
6.2%
覺 1
 
6.2%
山 1
 
6.2%
玉 1
 
6.2%
Other values (6) 6
37.5%
Common
ValueCountFrequency (%)
3706
98.9%
- 13
 
0.3%
) 9
 
0.2%
( 9
 
0.2%
, 8
 
0.2%
. 4
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17399
99.9%
CJK 16
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3706
21.3%
O 1854
 
10.7%
n 1316
 
7.6%
o 1129
 
6.5%
e 1061
 
6.1%
i 885
 
5.1%
a 876
 
5.0%
u 616
 
3.5%
g 479
 
2.8%
K 409
 
2.4%
Other values (48) 5068
29.1%
CJK
ValueCountFrequency (%)
保 1
 
6.2%
知 1
 
6.2%
李 1
 
6.2%
會 1
 
6.2%
敏 1
 
6.2%
度 1
 
6.2%
皺 1
 
6.2%
覺 1
 
6.2%
山 1
 
6.2%
玉 1
 
6.2%
Other values (6) 6
37.5%

작품명(국문)
Text

MISSING 

Distinct1461
Distinct (%)95.1%
Missing264
Missing (%)14.7%
Memory size14.2 KiB
2023-12-12T07:51:23.590093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length35
Mean length6.8157552
Min length1

Characters and Unicode

Total characters10469
Distinct characters915
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks10 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1412 ?
Unique (%)91.9%

Sample

1st row재 창조자(새인류의 창조)
2nd row일식(日蝕)
3rd row평화
4th row미래를 위한 침묵
5th rowRivulet Ⅱ
ValueCountFrequency (%)
31
 
1.0%
위한 19
 
0.6%
2 15
 
0.5%
시리즈 15
 
0.5%
그릇 14
 
0.5%
자연의 13
 
0.4%
ⅱ 13
 
0.4%
그리고 12
 
0.4%
주전자 12
 
0.4%
1 11
 
0.4%
Other values (2184) 2809
94.8%
2023-12-12T07:51:24.084262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1444
 
13.8%
의 276
 
2.6%
이 160
 
1.5%
다 137
 
1.3%
리 136
 
1.3%
기 124
 
1.2%
- 119
 
1.1%
자 114
 
1.1%
( 102
 
1.0%
) 102
 
1.0%
Other values (905) 7755
74.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7268
69.4%
Space Separator 1444
 
13.8%
Lowercase Letter 564
 
5.4%
Decimal Number 397
 
3.8%
Uppercase Letter 202
 
1.9%
Other Punctuation 200
 
1.9%
Dash Punctuation 119
 
1.1%
Open Punctuation 105
 
1.0%
Close Punctuation 105
 
1.0%
Letter Number 37
 
0.4%
Other values (3) 28
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 276
 
3.8%
이 160
 
2.2%
다 137
 
1.9%
리 136
 
1.9%
기 124
 
1.7%
자 114
 
1.6%
나 92
 
1.3%
는 83
 
1.1%
한 76
 
1.0%
시 75
 
1.0%
Other values (813) 5995
82.5%
Uppercase Letter
ValueCountFrequency (%)
I 47
23.3%
C 14
 
6.9%
T 13
 
6.4%
N 12
 
5.9%
M 12
 
5.9%
S 11
 
5.4%
V 9
 
4.5%
P 9
 
4.5%
W 8
 
4.0%
R 8
 
4.0%
Other values (14) 59
29.2%
Lowercase Letter
ValueCountFrequency (%)
e 71
12.6%
o 59
10.5%
n 48
 
8.5%
t 46
 
8.2%
i 42
 
7.4%
a 42
 
7.4%
r 41
 
7.3%
s 33
 
5.9%
l 29
 
5.1%
c 20
 
3.5%
Other values (13) 133
23.6%
Other Punctuation
ValueCountFrequency (%)
, 59
29.5%
. 57
28.5%
# 24
12.0%
: 13
 
6.5%
· 10
 
5.0%
" 9
 
4.5%
' 8
 
4.0%
! 7
 
3.5%
& 4
 
2.0%
? 4
 
2.0%
Other values (3) 5
 
2.5%
Decimal Number
ValueCountFrequency (%)
1 93
23.4%
0 83
20.9%
2 74
18.6%
9 55
13.9%
3 32
 
8.1%
6 15
 
3.8%
7 14
 
3.5%
5 13
 
3.3%
4 11
 
2.8%
8 7
 
1.8%
Letter Number
ValueCountFrequency (%)
Ⅱ 19
51.4%
Ⅰ 9
24.3%
Ⅲ 4
 
10.8%
Ⅳ 3
 
8.1%
Ⅹ 1
 
2.7%
ⅳ 1
 
2.7%
Math Symbol
ValueCountFrequency (%)
+ 10
66.7%
~ 2
 
13.3%
→ 1
 
6.7%
= 1
 
6.7%
∝ 1
 
6.7%
Open Punctuation
ValueCountFrequency (%)
( 102
97.1%
[ 2
 
1.9%
《 1
 
1.0%
Close Punctuation
ValueCountFrequency (%)
) 102
97.1%
] 2
 
1.9%
》 1
 
1.0%
Other Symbol
ValueCountFrequency (%)
★ 1
50.0%
↗ 1
50.0%
Space Separator
ValueCountFrequency (%)
1444
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 119
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7089
67.7%
Common 2398
 
22.9%
Latin 803
 
7.7%
Han 179
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 276
 
3.9%
이 160
 
2.3%
다 137
 
1.9%
리 136
 
1.9%
기 124
 
1.7%
자 114
 
1.6%
나 92
 
1.3%
는 83
 
1.2%
한 76
 
1.1%
시 75
 
1.1%
Other values (670) 5816
82.0%
Han
ValueCountFrequency (%)
器 7
 
3.9%
願 3
 
1.7%
中 3
 
1.7%
心 3
 
1.7%
日 3
 
1.7%
白 3
 
1.7%
自 2
 
1.1%
光 2
 
1.1%
歸 2
 
1.1%
然 2
 
1.1%
Other values (133) 149
83.2%
Latin
ValueCountFrequency (%)
e 71
 
8.8%
o 59
 
7.3%
n 48
 
6.0%
I 47
 
5.9%
t 46
 
5.7%
i 42
 
5.2%
a 42
 
5.2%
r 41
 
5.1%
s 33
 
4.1%
l 29
 
3.6%
Other values (43) 345
43.0%
Common
ValueCountFrequency (%)
1444
60.2%
- 119
 
5.0%
( 102
 
4.3%
) 102
 
4.3%
1 93
 
3.9%
0 83
 
3.5%
2 74
 
3.1%
, 59
 
2.5%
. 57
 
2.4%
9 55
 
2.3%
Other values (29) 210
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7088
67.7%
ASCII 3148
30.1%
CJK 174
 
1.7%
Number Forms 37
 
0.4%
None 12
 
0.1%
CJK Compat Ideographs 5
 
< 0.1%
Arrows 2
 
< 0.1%
Misc Symbols 1
 
< 0.1%
Math Operators 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1444
45.9%
- 119
 
3.8%
( 102
 
3.2%
) 102
 
3.2%
1 93
 
3.0%
0 83
 
2.6%
2 74
 
2.4%
e 71
 
2.3%
, 59
 
1.9%
o 59
 
1.9%
Other values (69) 942
29.9%
Hangul
ValueCountFrequency (%)
의 276
 
3.9%
이 160
 
2.3%
다 137
 
1.9%
리 136
 
1.9%
기 124
 
1.7%
자 114
 
1.6%
나 92
 
1.3%
는 83
 
1.2%
한 76
 
1.1%
시 75
 
1.1%
Other values (669) 5815
82.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 19
51.4%
Ⅰ 9
24.3%
Ⅲ 4
 
10.8%
Ⅳ 3
 
8.1%
Ⅹ 1
 
2.7%
ⅳ 1
 
2.7%
None
ValueCountFrequency (%)
· 10
83.3%
《 1
 
8.3%
》 1
 
8.3%
CJK
ValueCountFrequency (%)
器 7
 
4.0%
願 3
 
1.7%
中 3
 
1.7%
心 3
 
1.7%
日 3
 
1.7%
白 3
 
1.7%
自 2
 
1.1%
光 2
 
1.1%
歸 2
 
1.1%
然 2
 
1.1%
Other values (128) 144
82.8%
Misc Symbols
ValueCountFrequency (%)
★ 1
100.0%
Arrows
ValueCountFrequency (%)
↗ 1
50.0%
→ 1
50.0%
Math Operators
ValueCountFrequency (%)
∝ 1
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
輪 1
20.0%
律 1
20.0%
理 1
20.0%
蓮 1
20.0%
不 1
20.0%

작품명(영문)
Text

Distinct1729
Distinct (%)96.9%
Missing15
Missing (%)0.8%
Memory size14.2 KiB
2023-12-12T07:51:24.492405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length119
Median length56
Mean length15.648739
Min length2

Characters and Unicode

Total characters27933
Distinct characters122
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1691 ?
Unique (%)94.7%

Sample

1st rowIl Ricreatore(The Creation of New Generation)
2nd rowEclipse
3rd rowPeace
4th rowSilence for the Future
5th rowRivulet Ⅱ
ValueCountFrequency (%)
the 217
 
4.7%
of 196
 
4.3%
and 82
 
1.8%
a 81
 
1.8%
in 50
 
1.1%
49
 
1.1%
for 38
 
0.8%
life 31
 
0.7%
with 30
 
0.7%
series 29
 
0.6%
Other values (2163) 3798
82.5%
2023-12-12T07:51:24.996416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 2900
 
10.4%
2829
 
10.1%
o 1755
 
6.3%
i 1708
 
6.1%
a 1674
 
6.0%
n 1664
 
6.0%
t 1523
 
5.5%
r 1492
 
5.3%
s 1114
 
4.0%
l 1053
 
3.8%
Other values (112) 10221
36.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 20691
74.1%
Uppercase Letter 3203
 
11.5%
Space Separator 2829
 
10.1%
Decimal Number 480
 
1.7%
Other Punctuation 301
 
1.1%
Dash Punctuation 187
 
0.7%
Open Punctuation 64
 
0.2%
Close Punctuation 64
 
0.2%
Letter Number 44
 
0.2%
Other Letter 26
 
0.1%
Other values (4) 44
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2900
14.0%
o 1755
 
8.5%
i 1708
 
8.3%
a 1674
 
8.1%
n 1664
 
8.0%
t 1523
 
7.4%
r 1492
 
7.2%
s 1114
 
5.4%
l 1053
 
5.1%
h 716
 
3.5%
Other values (16) 5092
24.6%
Uppercase Letter
ValueCountFrequency (%)
T 326
 
10.2%
S 322
 
10.1%
B 216
 
6.7%
C 203
 
6.3%
M 201
 
6.3%
F 162
 
5.1%
A 159
 
5.0%
P 153
 
4.8%
D 152
 
4.7%
W 152
 
4.7%
Other values (16) 1157
36.1%
Other Letter
ValueCountFrequency (%)
滿 1
 
3.8%
移 1
 
3.8%
伴 1
 
3.8%
侶 1
 
3.8%
犬 1
 
3.8%
覺 1
 
3.8%
圓 1
 
3.8%
位 1
 
3.8%
景 1
 
3.8%
依 1
 
3.8%
Other values (16) 16
61.5%
Other Punctuation
ValueCountFrequency (%)
, 83
27.6%
. 58
19.3%
# 32
 
10.6%
' 30
 
10.0%
" 23
 
7.6%
: 21
 
7.0%
& 16
 
5.3%
! 15
 
5.0%
/ 7
 
2.3%
; 7
 
2.3%
Other values (3) 9
 
3.0%
Decimal Number
ValueCountFrequency (%)
1 115
24.0%
0 101
21.0%
2 95
19.8%
9 56
11.7%
3 35
 
7.3%
5 21
 
4.4%
6 16
 
3.3%
7 15
 
3.1%
4 14
 
2.9%
8 12
 
2.5%
Letter Number
ValueCountFrequency (%)
Ⅱ 21
47.7%
Ⅰ 12
27.3%
Ⅲ 6
 
13.6%
Ⅳ 3
 
6.8%
ⅳ 1
 
2.3%
Ⅹ 1
 
2.3%
Math Symbol
ValueCountFrequency (%)
+ 12
70.6%
~ 2
 
11.8%
∝ 1
 
5.9%
= 1
 
5.9%
→ 1
 
5.9%
Open Punctuation
ValueCountFrequency (%)
( 62
96.9%
[ 2
 
3.1%
Close Punctuation
ValueCountFrequency (%)
) 62
96.9%
] 2
 
3.1%
Other Symbol
ValueCountFrequency (%)
★ 1
50.0%
↗ 1
50.0%
Space Separator
ValueCountFrequency (%)
2829
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 187
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 24
100.0%
Other Number
ValueCountFrequency (%)
² 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 23938
85.7%
Common 3969
 
14.2%
Han 25
 
0.1%
Hangul 1
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2900
 
12.1%
o 1755
 
7.3%
i 1708
 
7.1%
a 1674
 
7.0%
n 1664
 
7.0%
t 1523
 
6.4%
r 1492
 
6.2%
s 1114
 
4.7%
l 1053
 
4.4%
h 716
 
3.0%
Other values (48) 8339
34.8%
Common
ValueCountFrequency (%)
2829
71.3%
- 187
 
4.7%
1 115
 
2.9%
0 101
 
2.5%
2 95
 
2.4%
, 83
 
2.1%
( 62
 
1.6%
) 62
 
1.6%
. 58
 
1.5%
9 56
 
1.4%
Other values (28) 321
 
8.1%
Han
ValueCountFrequency (%)
滿 1
 
4.0%
移 1
 
4.0%
伴 1
 
4.0%
侶 1
 
4.0%
犬 1
 
4.0%
覺 1
 
4.0%
圓 1
 
4.0%
位 1
 
4.0%
景 1
 
4.0%
依 1
 
4.0%
Other values (15) 15
60.0%
Hangul
ValueCountFrequency (%)
ㆍ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27854
99.7%
Number Forms 44
 
0.2%
CJK 25
 
0.1%
None 5
 
< 0.1%
Arrows 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%
Misc Symbols 1
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 2900
 
10.4%
2829
 
10.2%
o 1755
 
6.3%
i 1708
 
6.1%
a 1674
 
6.0%
n 1664
 
6.0%
t 1523
 
5.5%
r 1492
 
5.4%
s 1114
 
4.0%
l 1053
 
3.8%
Other values (74) 10142
36.4%
Number Forms
ValueCountFrequency (%)
Ⅱ 21
47.7%
Ⅰ 12
27.3%
Ⅲ 6
 
13.6%
Ⅳ 3
 
6.8%
ⅳ 1
 
2.3%
Ⅹ 1
 
2.3%
None
ValueCountFrequency (%)
· 4
80.0%
² 1
 
20.0%
CJK
ValueCountFrequency (%)
滿 1
 
4.0%
移 1
 
4.0%
伴 1
 
4.0%
侶 1
 
4.0%
犬 1
 
4.0%
覺 1
 
4.0%
圓 1
 
4.0%
位 1
 
4.0%
景 1
 
4.0%
依 1
 
4.0%
Other values (15) 15
60.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%
Misc Symbols
ValueCountFrequency (%)
★ 1
100.0%
Arrows
ValueCountFrequency (%)
↗ 1
50.0%
→ 1
50.0%
Math Operators
ValueCountFrequency (%)
∝ 1
100.0%

년도
Categorical

HIGH CORRELATION 

Distinct28
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
2013
269 
<NA>
254 
2005
201 
2011
179 
2003
147 
Other values (23)
750 

Length

Max length9
Median length4
Mean length4.0161111
Min length4

Unique

Unique6 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
2013 269
14.9%
<NA> 254
14.1%
2005 201
11.2%
2011 179
9.9%
2003 147
8.2%
2007 115
6.4%
2001 111
6.2%
2009 98
 
5.4%
2019 96
 
5.3%
2021 67
 
3.7%
Other values (18) 263
14.6%

Length

2023-12-12T07:51:25.147066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2013 269
14.9%
na 254
14.1%
2005 201
11.2%
2011 179
9.9%
2003 147
8.2%
2007 115
6.4%
2001 111
6.2%
2009 98
 
5.4%
2019 96
 
5.3%
2021 67
 
3.7%
Other values (18) 263
14.6%

작품크기(가로)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct278
Distinct (%)15.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean640.75278
Minimum0
Maximum10000
Zeros49
Zeros (%)2.7%
Negative0
Negative (%)0.0%
Memory size15.9 KiB
2023-12-12T07:51:25.259184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile50
Q1220
median447.5
Q3920
95-th percentile1800
Maximum10000
Range10000
Interquartile range (IQR)700

Descriptive statistics

Standard deviation634.97569
Coefficient of variation (CV)0.9909839
Kurtosis52.689519
Mean640.75278
Median Absolute Deviation (MAD)277.5
Skewness4.4391668
Sum1153355
Variance403194.13
MonotonicityNot monotonic
2023-12-12T07:51:25.386462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
400 66
 
3.7%
300 57
 
3.2%
1000 51
 
2.8%
0 49
 
2.7%
600 49
 
2.7%
2000 48
 
2.7%
500 47
 
2.6%
200 40
 
2.2%
1200 39
 
2.2%
1500 36
 
2.0%
Other values (268) 1318
73.2%
ValueCountFrequency (%)
0 49
2.7%
15 1
 
0.1%
20 2
 
0.1%
21 1
 
0.1%
22 2
 
0.1%
23 1
 
0.1%
25 4
 
0.2%
26 2
 
0.1%
27 1
 
0.1%
29 1
 
0.1%
ValueCountFrequency (%)
10000 2
0.1%
4500 1
 
0.1%
4000 1
 
0.1%
2820 1
 
0.1%
2800 1
 
0.1%
2700 1
 
0.1%
2500 1
 
0.1%
2400 3
0.2%
2200 1
 
0.1%
2140 1
 
0.1%

작품크기(세로)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct285
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean549.86833
Minimum0
Maximum12000
Zeros62
Zeros (%)3.4%
Negative0
Negative (%)0.0%
Memory size15.9 KiB
2023-12-12T07:51:25.509876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile24.9
Q1170
median357.5
Q3672.5
95-th percentile1800
Maximum12000
Range12000
Interquartile range (IQR)502.5

Descriptive statistics

Standard deviation666.21084
Coefficient of variation (CV)1.2115825
Kurtosis79.536635
Mean549.86833
Median Absolute Deviation (MAD)222.5
Skewness6.1304546
Sum989763
Variance443836.89
MonotonicityNot monotonic
2023-12-12T07:51:25.661636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
300 76
 
4.2%
500 68
 
3.8%
0 62
 
3.4%
400 53
 
2.9%
2000 50
 
2.8%
600 46
 
2.6%
250 46
 
2.6%
100 38
 
2.1%
200 36
 
2.0%
120 32
 
1.8%
Other values (275) 1293
71.8%
ValueCountFrequency (%)
0 62
3.4%
4 1
 
0.1%
5 5
 
0.3%
6 2
 
0.1%
10 3
 
0.2%
12 1
 
0.1%
14 1
 
0.1%
15 3
 
0.2%
20 8
 
0.4%
21 1
 
0.1%
ValueCountFrequency (%)
12000 1
0.1%
10000 1
0.1%
7600 1
0.1%
5600 1
0.1%
4000 1
0.1%
3900 1
0.1%
3420 1
0.1%
2650 1
0.1%
2400 2
0.1%
2300 1
0.1%

작품크기(높이)
Real number (ℝ)

ZEROS 

Distinct274
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean424.34556
Minimum0
Maximum9140
Zeros215
Zeros (%)11.9%
Negative0
Negative (%)0.0%
Memory size15.9 KiB
2023-12-12T07:51:25.797801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q164
median229
Q3550
95-th percentile1500
Maximum9140
Range9140
Interquartile range (IQR)486

Descriptive statistics

Standard deviation576.89738
Coefficient of variation (CV)1.3594991
Kurtosis45.349457
Mean424.34556
Median Absolute Deviation (MAD)198
Skewness4.4444322
Sum763822
Variance332810.59
MonotonicityNot monotonic
2023-12-12T07:51:25.915171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 215
 
11.9%
300 53
 
2.9%
150 48
 
2.7%
200 41
 
2.3%
250 41
 
2.3%
50 37
 
2.1%
100 33
 
1.8%
500 33
 
1.8%
1500 31
 
1.7%
400 30
 
1.7%
Other values (264) 1238
68.8%
ValueCountFrequency (%)
0 215
11.9%
1 6
 
0.3%
2 1
 
0.1%
3 3
 
0.2%
4 2
 
0.1%
5 5
 
0.3%
6 1
 
0.1%
7 2
 
0.1%
8 3
 
0.2%
9 1
 
0.1%
ValueCountFrequency (%)
9140 1
0.1%
7600 1
0.1%
4400 1
0.1%
4200 1
0.1%
4000 1
0.1%
3150 1
0.1%
3000 1
0.1%
2700 1
0.1%
2500 1
0.1%
2300 2
0.1%

재료(국문)
Text

MISSING 

Distinct733
Distinct (%)56.5%
Missing503
Missing (%)27.9%
Memory size14.2 KiB
2023-12-12T07:51:26.137016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length32
Mean length6.4795682
Min length1

Characters and Unicode

Total characters8404
Distinct characters471
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique634 ?
Unique (%)48.9%

Sample

1st row듀랄루민,스테인레스 스틸,아크릴,황동
2nd row정은,황동
3rd row,못,유약,점토
4th row가링,홍송,흑단
5th row나뭇가지,미싱사,실크사
ValueCountFrequency (%)
도자기 96
 
6.0%
유리 73
 
4.6%
금속 37
 
2.3%
나무 34
 
2.1%
섬유 31
 
1.9%
은 29
 
1.8%
자기토 25
 
1.6%
백자토 21
 
1.3%
도자 19
 
1.2%
직물 16
 
1.0%
Other values (899) 1223
76.2%
2023-12-12T07:51:26.483837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 1092
 
13.0%
308
 
3.7%
자 306
 
3.6%
리 250
 
3.0%
스 221
 
2.6%
유 212
 
2.5%
기 209
 
2.5%
나 205
 
2.4%
무 184
 
2.2%
은 172
 
2.0%
Other values (461) 5245
62.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6710
79.8%
Other Punctuation 1109
 
13.2%
Space Separator 308
 
3.7%
Decimal Number 96
 
1.1%
Uppercase Letter 96
 
1.1%
Lowercase Letter 41
 
0.5%
Open Punctuation 20
 
0.2%
Close Punctuation 20
 
0.2%
Dash Punctuation 3
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 306
 
4.6%
리 250
 
3.7%
스 221
 
3.3%
유 212
 
3.2%
기 209
 
3.1%
나 205
 
3.1%
무 184
 
2.7%
은 172
 
2.6%
동 168
 
2.5%
도 166
 
2.5%
Other values (409) 4617
68.8%
Lowercase Letter
ValueCountFrequency (%)
k 6
14.6%
a 5
12.2%
s 4
9.8%
i 4
9.8%
m 3
7.3%
l 3
7.3%
e 3
7.3%
x 3
7.3%
g 2
 
4.9%
r 2
 
4.9%
Other values (6) 6
14.6%
Uppercase Letter
ValueCountFrequency (%)
D 15
15.6%
P 12
12.5%
K 12
12.5%
L 10
10.4%
E 9
9.4%
C 9
9.4%
V 6
 
6.2%
B 5
 
5.2%
A 3
 
3.1%
R 3
 
3.1%
Other values (5) 12
12.5%
Decimal Number
ValueCountFrequency (%)
2 23
24.0%
5 17
17.7%
9 15
15.6%
1 14
14.6%
4 11
11.5%
0 6
 
6.2%
8 6
 
6.2%
3 3
 
3.1%
6 1
 
1.0%
Other Punctuation
ValueCountFrequency (%)
, 1092
98.5%
. 6
 
0.5%
% 3
 
0.3%
/ 3
 
0.3%
: 3
 
0.3%
& 1
 
0.1%
· 1
 
0.1%
Space Separator
ValueCountFrequency (%)
308
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6709
79.8%
Common 1557
 
18.5%
Latin 137
 
1.6%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 306
 
4.6%
리 250
 
3.7%
스 221
 
3.3%
유 212
 
3.2%
기 209
 
3.1%
나 205
 
3.1%
무 184
 
2.7%
은 172
 
2.6%
동 168
 
2.5%
도 166
 
2.5%
Other values (408) 4616
68.8%
Latin
ValueCountFrequency (%)
D 15
 
10.9%
P 12
 
8.8%
K 12
 
8.8%
L 10
 
7.3%
E 9
 
6.6%
C 9
 
6.6%
V 6
 
4.4%
k 6
 
4.4%
B 5
 
3.6%
a 5
 
3.6%
Other values (21) 48
35.0%
Common
ValueCountFrequency (%)
, 1092
70.1%
308
 
19.8%
2 23
 
1.5%
( 20
 
1.3%
) 20
 
1.3%
5 17
 
1.1%
9 15
 
1.0%
1 14
 
0.9%
4 11
 
0.7%
. 6
 
0.4%
Other values (11) 31
 
2.0%
Han
ValueCountFrequency (%)
古 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6709
79.8%
ASCII 1693
 
20.1%
None 1
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 1092
64.5%
308
 
18.2%
2 23
 
1.4%
( 20
 
1.2%
) 20
 
1.2%
5 17
 
1.0%
9 15
 
0.9%
D 15
 
0.9%
1 14
 
0.8%
P 12
 
0.7%
Other values (41) 157
 
9.3%
Hangul
ValueCountFrequency (%)
자 306
 
4.6%
리 250
 
3.7%
스 221
 
3.3%
유 212
 
3.2%
기 209
 
3.1%
나 205
 
3.1%
무 184
 
2.7%
은 172
 
2.6%
동 168
 
2.5%
도 166
 
2.5%
Other values (408) 4616
68.8%
None
ValueCountFrequency (%)
· 1
100.0%
CJK
ValueCountFrequency (%)
古 1
100.0%

재료(영문)
Text

MISSING 

Distinct708
Distinct (%)54.7%
Missing505
Missing (%)28.1%
Memory size14.2 KiB
2023-12-12T07:51:26.750003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length148
Median length60
Mean length16.76139
Min length3

Characters and Unicode

Total characters21706
Distinct characters69
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique601 ?
Unique (%)46.4%

Sample

1st rowaclylic,brass,duralumin,stainless-steel
2nd rowbrass,Pure Silver
3rd rowClay,Copper,Glaze,nails
4th row,ebony,Red pine
5th rowbranch,sewing thread,silk
ValueCountFrequency (%)
porcelain 123
 
5.2%
ceramic 101
 
4.3%
glass 81
 
3.4%
silver 79
 
3.3%
clay 67
 
2.8%
white 57
 
2.4%
soil 54
 
2.3%
copper 43
 
1.8%
wood 41
 
1.7%
steel 40
 
1.7%
Other values (965) 1689
71.1%
2023-12-12T07:51:27.192720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 2376
 
10.9%
a 1726
 
8.0%
l 1635
 
7.5%
r 1578
 
7.3%
i 1388
 
6.4%
o 1281
 
5.9%
1081
 
5.0%
, 1075
 
5.0%
s 1040
 
4.8%
t 1013
 
4.7%
Other values (59) 7513
34.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 18181
83.8%
Uppercase Letter 1188
 
5.5%
Other Punctuation 1090
 
5.0%
Space Separator 1081
 
5.0%
Decimal Number 93
 
0.4%
Dash Punctuation 55
 
0.3%
Close Punctuation 9
 
< 0.1%
Open Punctuation 9
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2376
13.1%
a 1726
9.5%
l 1635
 
9.0%
r 1578
 
8.7%
i 1388
 
7.6%
o 1281
 
7.0%
s 1040
 
5.7%
t 1013
 
5.6%
c 940
 
5.2%
n 892
 
4.9%
Other values (16) 4312
23.7%
Uppercase Letter
ValueCountFrequency (%)
S 265
22.3%
C 223
18.8%
P 161
13.6%
W 87
 
7.3%
M 72
 
6.1%
B 57
 
4.8%
D 36
 
3.0%
R 36
 
3.0%
L 27
 
2.3%
T 27
 
2.3%
Other values (14) 197
16.6%
Decimal Number
ValueCountFrequency (%)
2 23
24.7%
9 14
15.1%
5 14
15.1%
1 13
14.0%
4 11
11.8%
0 8
 
8.6%
8 6
 
6.5%
3 3
 
3.2%
6 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
, 1075
98.6%
. 7
 
0.6%
% 3
 
0.3%
; 2
 
0.2%
: 2
 
0.2%
& 1
 
0.1%
Space Separator
ValueCountFrequency (%)
1081
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 55
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 19369
89.2%
Common 2337
 
10.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2376
12.3%
a 1726
 
8.9%
l 1635
 
8.4%
r 1578
 
8.1%
i 1388
 
7.2%
o 1281
 
6.6%
s 1040
 
5.4%
t 1013
 
5.2%
c 940
 
4.9%
n 892
 
4.6%
Other values (40) 5500
28.4%
Common
ValueCountFrequency (%)
1081
46.3%
, 1075
46.0%
- 55
 
2.4%
2 23
 
1.0%
9 14
 
0.6%
5 14
 
0.6%
1 13
 
0.6%
4 11
 
0.5%
) 9
 
0.4%
( 9
 
0.4%
Other values (9) 33
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21706
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 2376
 
10.9%
a 1726
 
8.0%
l 1635
 
7.5%
r 1578
 
7.3%
i 1388
 
6.4%
o 1281
 
5.9%
1081
 
5.0%
, 1075
 
5.0%
s 1040
 
4.8%
t 1013
 
4.7%
Other values (59) 7513
34.6%

기법(국문)
Text

MISSING 

Distinct25
Distinct (%)92.6%
Missing1773
Missing (%)98.5%
Memory size14.2 KiB
2023-12-12T07:51:27.389246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length10
Mean length6.4074074
Min length1

Characters and Unicode

Total characters173
Distinct characters93
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)85.2%

Sample

1st row건칠제작기법,끊음질
2nd row가공기법
3rd row슬러시 기법
4th row옻칠
5th row상감기법
ValueCountFrequency (%)
업다지 2
 
4.7%
상감기법 2
 
4.7%
기법 2
 
4.7%
옻칠 2
 
4.7%
페인트 1
 
2.3%
건칠제작기법,끊음질 1
 
2.3%
음각 1
 
2.3%
내부 1
 
2.3%
옻 1
 
2.3%
석간주칠,아교,황옻칠 1
 
2.3%
Other values (29) 29
67.4%
2023-12-12T07:51:27.737138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16
 
9.2%
기 9
 
5.2%
, 7
 
4.0%
법 7
 
4.0%
칠 6
 
3.5%
아 4
 
2.3%
연 4
 
2.3%
옻 4
 
2.3%
유 3
 
1.7%
에 3
 
1.7%
Other values (83) 110
63.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 145
83.8%
Space Separator 16
 
9.2%
Other Punctuation 7
 
4.0%
Decimal Number 4
 
2.3%
Other Symbol 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 9
 
6.2%
법 7
 
4.8%
칠 6
 
4.1%
아 4
 
2.8%
연 4
 
2.8%
옻 4
 
2.8%
유 3
 
2.1%
에 3
 
2.1%
자 3
 
2.1%
다 3
 
2.1%
Other values (76) 99
68.3%
Decimal Number
ValueCountFrequency (%)
1 1
25.0%
2 1
25.0%
8 1
25.0%
0 1
25.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%
Other Symbol
ValueCountFrequency (%)
℃ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 145
83.8%
Common 28
 
16.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 9
 
6.2%
법 7
 
4.8%
칠 6
 
4.1%
아 4
 
2.8%
연 4
 
2.8%
옻 4
 
2.8%
유 3
 
2.1%
에 3
 
2.1%
자 3
 
2.1%
다 3
 
2.1%
Other values (76) 99
68.3%
Common
ValueCountFrequency (%)
16
57.1%
, 7
25.0%
℃ 1
 
3.6%
1 1
 
3.6%
2 1
 
3.6%
8 1
 
3.6%
0 1
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 145
83.8%
ASCII 27
 
15.6%
Letterlike Symbols 1
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16
59.3%
, 7
25.9%
1 1
 
3.7%
2 1
 
3.7%
8 1
 
3.7%
0 1
 
3.7%
Hangul
ValueCountFrequency (%)
기 9
 
6.2%
법 7
 
4.8%
칠 6
 
4.1%
아 4
 
2.8%
연 4
 
2.8%
옻 4
 
2.8%
유 3
 
2.1%
에 3
 
2.1%
자 3
 
2.1%
다 3
 
2.1%
Other values (76) 99
68.3%
Letterlike Symbols
ValueCountFrequency (%)
℃ 1
100.0%

기법(영문)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct21
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
<NA>
1589 
metal fabricating
190 
Inlaying Technique
 
2
Eopdaji
 
2
Kilnworking
 
1
Other values (16)
 
16

Length

Max length67
Median length4
Mean length5.5261111
Min length4

Unique

Unique17 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1589
88.3%
metal fabricating 190
 
10.6%
Inlaying Technique 2
 
0.1%
Eopdaji 2
 
0.1%
Kilnworking 1
 
0.1%
03_02_01_091_001 1
 
0.1%
Processing Technique 1
 
0.1%
Slush Technique 1
 
0.1%
Lacquer 1
 
0.1%
Gobelin Techique 1
 
0.1%
Other values (11) 11
 
0.6%

Length

2023-12-12T07:51:27.903881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1589
78.9%
fabricating 190
 
9.4%
metal 190
 
9.4%
technique 4
 
0.2%
glaze 3
 
0.1%
inlaying 2
 
0.1%
eopdaji 2
 
0.1%
lacquer 2
 
0.1%
of 2
 
0.1%
waste 1
 
< 0.1%
Other values (29) 29
 
1.4%

작품 사진 파일명
Text

UNIQUE 

Distinct1800
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
2023-12-12T07:51:28.147204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length968
Median length230
Mean length81.342778
Min length28

Characters and Unicode

Total characters146417
Distinct characters1054
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks10 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1800 ?
Unique (%)100.0%

Sample

1st row박O백(Park O Back)_재 창조자(새인류의 창조)(Il Ricreatore(The Creation of New Generation))_001.jpg
2nd row이O주(Lee O Joo)_일식(日蝕)(Eclipse)_001.jpg
3rd row윤O남(Yune O Nam)_평화(Peace)_001.jpg
4th row장O남(Jang O Nam)_미래를 위한 침묵(Silence for the Future)_001.jpg
5th row히로시O즈끼(Hiroshi O )_Rivulet Ⅱ(Rivulet Ⅱ)_001.jpg
ValueCountFrequency (%)
o 3195
 
20.8%
of 319
 
2.1%
the 181
 
1.2%
and 134
 
0.9%
113
 
0.7%
in 73
 
0.5%
a 70
 
0.5%
for 50
 
0.3%
with 46
 
0.3%
h 39
 
0.3%
Other values (7127) 11129
72.5%
2023-12-12T07:51:28.658866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13595
 
9.3%
e 6893
 
4.7%
0 6466
 
4.4%
( 6430
 
4.4%
) 6430
 
4.4%
O 6306
 
4.3%
_ 6225
 
4.3%
n 5153
 
3.5%
o 5047
 
3.4%
g 4824
 
3.3%
Other values (1044) 79048
54.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 60554
41.4%
Other Letter 19316
 
13.2%
Uppercase Letter 17283
 
11.8%
Space Separator 13595
 
9.3%
Decimal Number 10724
 
7.3%
Open Punctuation 6438
 
4.4%
Close Punctuation 6438
 
4.4%
Connector Punctuation 6225
 
4.3%
Other Punctuation 5135
 
3.5%
Dash Punctuation 526
 
0.4%
Other values (4) 183
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 739
 
3.8%
의 449
 
2.3%
김 401
 
2.1%
리 379
 
2.0%
스 291
 
1.5%
다 266
 
1.4%
기 241
 
1.2%
나 238
 
1.2%
정 232
 
1.2%
자 215
 
1.1%
Other values (948) 15865
82.1%
Lowercase Letter
ValueCountFrequency (%)
e 6893
11.4%
n 5153
 
8.5%
o 5047
 
8.3%
g 4824
 
8.0%
i 4460
 
7.4%
a 4392
 
7.3%
p 3828
 
6.3%
r 3167
 
5.2%
j 3160
 
5.2%
t 2869
 
4.7%
Other values (16) 16761
27.7%
Uppercase Letter
ValueCountFrequency (%)
O 6306
36.5%
S 1061
 
6.1%
H 796
 
4.6%
K 758
 
4.4%
L 756
 
4.4%
C 743
 
4.3%
T 630
 
3.6%
J 596
 
3.4%
M 586
 
3.4%
P 528
 
3.1%
Other values (16) 4523
26.2%
Decimal Number
ValueCountFrequency (%)
0 6466
60.3%
1 2190
 
20.4%
2 1341
 
12.5%
3 238
 
2.2%
9 155
 
1.4%
4 91
 
0.8%
5 77
 
0.7%
6 72
 
0.7%
7 51
 
0.5%
8 43
 
0.4%
Other Punctuation
ValueCountFrequency (%)
. 3269
63.7%
, 1582
30.8%
# 116
 
2.3%
' 52
 
1.0%
; 37
 
0.7%
! 30
 
0.6%
& 26
 
0.5%
· 19
 
0.4%
@ 4
 
0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 53
48.2%
Ⅰ 36
32.7%
Ⅲ 11
 
10.0%
Ⅳ 6
 
5.5%
Ⅹ 2
 
1.8%
ⅳ 2
 
1.8%
Math Symbol
ValueCountFrequency (%)
+ 34
59.6%
~ 12
 
21.1%
→ 6
 
10.5%
= 2
 
3.5%
∝ 2
 
3.5%
＋ 1
 
1.8%
Open Punctuation
ValueCountFrequency (%)
( 6430
99.9%
[ 6
 
0.1%
《 2
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 6430
99.9%
] 6
 
0.1%
》 2
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 525
99.8%
－ 1
 
0.2%
Other Symbol
ValueCountFrequency (%)
★ 8
57.1%
↗ 6
42.9%
Space Separator
ValueCountFrequency (%)
13595
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6225
100.0%
Other Number
ValueCountFrequency (%)
² 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 77947
53.2%
Common 49154
33.6%
Hangul 18933
 
12.9%
Han 383
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 739
 
3.9%
의 449
 
2.4%
김 401
 
2.1%
리 379
 
2.0%
스 291
 
1.5%
다 266
 
1.4%
기 241
 
1.3%
나 238
 
1.3%
정 232
 
1.2%
자 215
 
1.1%
Other values (771) 15482
81.8%
Han
ValueCountFrequency (%)
器 19
 
5.0%
白 9
 
2.3%
聯 7
 
1.8%
茶 5
 
1.3%
碗 5
 
1.3%
戶 5
 
1.3%
井 5
 
1.3%
梅 5
 
1.3%
皮 5
 
1.3%
作 5
 
1.3%
Other values (167) 313
81.7%
Latin
ValueCountFrequency (%)
e 6893
 
8.8%
O 6306
 
8.1%
n 5153
 
6.6%
o 5047
 
6.5%
g 4824
 
6.2%
i 4460
 
5.7%
a 4392
 
5.6%
p 3828
 
4.9%
r 3167
 
4.1%
j 3160
 
4.1%
Other values (48) 30717
39.4%
Common
ValueCountFrequency (%)
13595
27.7%
0 6466
13.2%
( 6430
13.1%
) 6430
13.1%
_ 6225
12.7%
. 3269
 
6.7%
1 2190
 
4.5%
, 1582
 
3.2%
2 1341
 
2.7%
- 525
 
1.1%
Other values (28) 1101
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 126942
86.7%
Hangul 18931
 
12.9%
CJK 376
 
0.3%
Number Forms 110
 
0.1%
None 27
 
< 0.1%
Arrows 12
 
< 0.1%
Misc Symbols 8
 
< 0.1%
CJK Compat Ideographs 7
 
< 0.1%
Math Operators 2
 
< 0.1%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13595
 
10.7%
e 6893
 
5.4%
0 6466
 
5.1%
( 6430
 
5.1%
) 6430
 
5.1%
O 6306
 
5.0%
_ 6225
 
4.9%
n 5153
 
4.1%
o 5047
 
4.0%
g 4824
 
3.8%
Other values (70) 59573
46.9%
Hangul
ValueCountFrequency (%)
이 739
 
3.9%
의 449
 
2.4%
김 401
 
2.1%
리 379
 
2.0%
스 291
 
1.5%
다 266
 
1.4%
기 241
 
1.3%
나 238
 
1.3%
정 232
 
1.2%
자 215
 
1.1%
Other values (770) 15480
81.8%
Number Forms
ValueCountFrequency (%)
Ⅱ 53
48.2%
Ⅰ 36
32.7%
Ⅲ 11
 
10.0%
Ⅳ 6
 
5.5%
Ⅹ 2
 
1.8%
ⅳ 2
 
1.8%
None
ValueCountFrequency (%)
· 19
70.4%
》 2
 
7.4%
《 2
 
7.4%
² 2
 
7.4%
＋ 1
 
3.7%
－ 1
 
3.7%
CJK
ValueCountFrequency (%)
器 19
 
5.1%
白 9
 
2.4%
聯 7
 
1.9%
茶 5
 
1.3%
碗 5
 
1.3%
戶 5
 
1.3%
井 5
 
1.3%
梅 5
 
1.3%
皮 5
 
1.3%
作 5
 
1.3%
Other values (162) 306
81.4%
Misc Symbols
ValueCountFrequency (%)
★ 8
100.0%
Arrows
ValueCountFrequency (%)
→ 6
50.0%
↗ 6
50.0%
Math Operators
ValueCountFrequency (%)
∝ 2
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
不 2
28.6%
蓮 2
28.6%
理 1
14.3%
律 1
14.3%
輪 1
14.3%
Compat Jamo
ValueCountFrequency (%)
ㆍ 2
100.0%

Interactions

2023-12-12T07:51:19.996136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:18.952940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:19.302238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:19.636993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:20.080796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:19.035359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:19.389718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:19.744295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:20.158702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:19.122476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:19.470404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:19.827700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:20.272215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:19.219742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:19.560163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:19.912037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T07:51:28.785333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회차부문심사결과년도작품크기(가로)작품크기(세로)작품크기(높이)기법(국문)기법(영문)
회차1.0000.0000.2620.9940.1460.1180.1351.0000.977
부문0.0001.0000.2190.0910.6770.7510.323NaN0.075
심사결과0.2620.2191.0000.3900.0000.0000.0000.7790.825
년도0.9940.0910.3901.0000.0760.1020.0981.0000.920
작품크기(가로)0.1460.6770.0000.0761.0000.8430.6501.0000.331
작품크기(세로)0.1180.7510.0000.1020.8431.0000.7511.0000.441
작품크기(높이)0.1350.3230.0000.0980.6500.7511.0001.0000.304
기법(국문)1.000NaN0.7791.0001.0001.0001.0001.0001.000
기법(영문)0.9770.0750.8250.9200.3310.4410.3041.0001.000
2023-12-12T07:51:28.951908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
심사결과년도기법(영문)부문
심사결과1.0000.1720.5480.081
년도0.1721.0000.6230.049
기법(영문)0.5480.6231.0000.090
부문0.0810.0490.0901.000
2023-12-12T07:51:29.071310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회차작품크기(가로)작품크기(세로)작품크기(높이)부문심사결과년도기법(영문)
회차1.000-0.113-0.096-0.0440.0000.1410.9600.772
작품크기(가로)-0.1131.0000.6850.1860.3620.0000.0330.249
작품크기(세로)-0.0960.6851.0000.0540.5570.0000.0420.333
작품크기(높이)-0.0440.1860.0541.0000.2130.0000.0430.228
부문0.0000.3620.5570.2131.0000.0810.0490.090
심사결과0.1410.0000.0000.0000.0811.0000.1720.548
년도0.9600.0330.0420.0430.0490.1721.0000.623
기법(영문)0.7720.2490.3330.2280.0900.5480.6231.000

Missing values

2023-12-12T07:51:20.439814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T07:51:20.622972image/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.
2023-12-12T07:51:21.020592image/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

회차부문심사결과작가명(국문)작가명(영문)작품명(국문)작품명(영문)년도작품크기(가로)작품크기(세로)작품크기(높이)재료(국문)재료(영문)기법(국문)기법(영문)작품 사진 파일명
01도자금상박O백Park O Back재 창조자(새인류의 창조)Il Ricreatore(The Creation of New Generation)<NA>805840195<NA><NA><NA><NA>박O백(Park O Back)_재 창조자(새인류의 창조)(Il Ricreatore(The Creation of New Generation))_001.jpg
11목칠금상이O주Lee O Joo일식(日蝕)Eclipse<NA>3742001360<NA><NA><NA><NA>이O주(Lee O Joo)_일식(日蝕)(Eclipse)_001.jpg
21직물금상윤O남Yune O Nam평화Peace<NA>200017000<NA><NA><NA><NA>윤O남(Yune O Nam)_평화(Peace)_001.jpg
31기타금상장O남Jang O Nam미래를 위한 침묵Silence for the Future<NA>400400200<NA><NA><NA><NA>장O남(Jang O Nam)_미래를 위한 침묵(Silence for the Future)_001.jpg
41금속대상히로시O즈끼Hiroshi ORivulet ⅡRivulet Ⅱ<NA>220220140<NA><NA><NA><NA>히로시O즈끼(Hiroshi O )_Rivulet Ⅱ(Rivulet Ⅱ)_001.jpg
51금속동상류O희Ryu O Hee항해 2000Voyage 2000<NA>1440420790<NA><NA><NA><NA>류O희(Ryu O Hee)_항해 2000(Voyage 2000)_001.jpg
61도자동상하O숙Ha O Sook사계Four Season<NA>1800900150<NA><NA><NA><NA>하O숙(Ha O Sook)_사계(Four Season)_001.jpg
71목칠동상박O정Park O Jung밀레니엄을 맞이하여Hello! New Millennium<NA>4202101400<NA><NA><NA><NA>박O정(Park O Jung)_밀레니엄을 맞이하여(Hello! New Millennium)_001.jpg
81직물동상히로미O로타니Hiromi OVigor 99-7Vigor 99-7<NA>20003501250<NA><NA><NA><NA>히로미O로타니(Hiromi O )_Vigor 99-7(Vigor 99-7)_001.jpg
91기타동상권O춘Kwon O Chun99 - 흔적 Ⅱ99 - Trace Ⅱ<NA>610135890<NA><NA><NA><NA>권O춘(Kwon O Chun)_99 - 흔적 Ⅱ(99 - Trace Ⅱ)_001.jpg
회차부문심사결과작가명(국문)작가명(영문)작품명(국문)작품명(영문)년도작품크기(가로)작품크기(세로)작품크기(높이)재료(국문)재료(영문)기법(국문)기법(영문)작품 사진 파일명
179012<NA>입선송O원Song O Won30개의 반지30 rings Series20192020293128레몬수정,백수정,정은Lemon Quartz,Pure Silver,Rock Crystal<NA><NA>송O원(Song O Won)_30개의 반지(30 rings Series)_001.jpg,송O원(Song O Won)_30개의 반지(30 rings Series)_002.jpg
179112<NA>입선이퀴야오OYiqiao O<NA>Red Bean2019555575달걀,마키에,콩,패브릭,황동Beans,brass,Eggshell,Fabric,Makie<NA><NA>이퀴야오O(Yiqiao O )_(Red Bean)_001.jpg,이퀴야오O(Yiqiao O )_(Red Bean)_002.jpg
179212<NA>입선이O호Lee O Ho흐르는 선Flowing Line2020500500250백자White porcelain<NA><NA>이O호(Lee O Ho)_흐르는 선(Flowing Line)_001.jpg,이O호(Lee O Ho)_흐르는 선(Flowing Line)_002.jpg,이O호(Lee O Ho)_흐르는 선(Flowing Line)_003.jpg,이O호(Lee O Ho)_흐르는 선(Flowing Line)_004.jpg
179312<NA>입선김O주Kim O Ju<NA>Another Pearl_20212021305305355동,자개copper,mother-of-pearl<NA><NA>김O주(Kim O Ju)_(Another Pearl_2021)_001.jpg,김O주(Kim O Ju)_(Another Pearl_2021)_002.jpg
179412<NA>입선강O철Kang O Chul먹(玄) 달항아리Moon Jar2021490490500백자토White porcelain soil매트유약Matt Glaze강O철(Kang O Chul)_먹(玄) 달항아리(Moon Jar)_001.jpg,강O철(Kang O Chul)_먹(玄) 달항아리(Moon Jar)_002.jpg
179512<NA>입선김O영Kim O Young<NA>Anyone20216002501100조형토Stoneware<NA><NA>김O영(Kim O Young)_(Anyone)_001.jpg,김O영(Kim O Young)_(Anyone)_002.jpg
179612<NA>입선권O현Kwon O Hyeon<NA>Map Projection20203707405백자White porcelain<NA><NA>권O현(Kwon O Hyeon)_(Map Projection)_001.jpg,권O현(Kwon O Hyeon)_(Map Projection)_002.jpg,권O현(Kwon O Hyeon)_(Map Projection)_003.jpg,권O현(Kwon O Hyeon)_(Map Projection)_004.jpg
179712<NA>입선박O일Park O Il<NA>New Old 86-180202045042020백토,청자토,흑토Black Clay,celadon porcelain clay,White soil<NA>metal fabricating박O일(Park O Il)_(New Old 86-180)_001.jpg,박O일(Park O Il)_(New Old 86-180)_002.jpg,박O일(Park O Il)_(New Old 86-180)_003.jpg,박O일(Park O Il)_(New Old 86-180)_004.jpg
179812<NA>입선윤O경Yun O Gyeong위장된 공감Disguised Empathy202120041080금박,정은,코팅된 동선coated copper wire,gilt,Pure Silver<NA><NA>윤O경(Yun O Gyeong)_위장된 공감(Disguised Empathy)_001.jpg,윤O경(Yun O Gyeong)_위장된 공감(Disguised Empathy)_002.jpg
179912<NA>입선김O은Kim O Eun담다To contain20213101320880붕규산유리,소다유리Borosilicate Glass,soda glass<NA><NA>김O은(Kim O Eun)_담다(To contain)_001.jpg,김O은(Kim O Eun)_담다(To contain)_002.jpg