Overview

Dataset statistics

Number of variables11
Number of observations5967
Missing cells9954
Missing cells (%)15.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory518.7 KiB
Average record size in memory89.0 B

Variable types

Categorical1
Numeric1
Text9

Dataset

Description부문,수집연도,작품명(국문),작품명(영문),작품규격,제작년도,재료/기법,작품해설,작가명,메인이미지,썸네일이미지
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15322/S/1/datasetView.do

Alerts

작품명(영문) has 2619 (43.9%) missing valuesMissing
재료/기법 has 2088 (35.0%) missing valuesMissing
작품해설 has 5247 (87.9%) missing valuesMissing
메인이미지 has unique valuesUnique
썸네일이미지 has unique valuesUnique

Reproduction

Analysis started2024-01-27 03:46:14.811395
Analysis finished2024-01-27 03:46:18.072018
Duration3.26 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

부문
Categorical

Distinct10
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size46.7 KiB
회화
2158 
사진
1245 
드로잉&판화
708 
한국화
684 
조각
465 
Other values (5)
707 

Length

Max length6
Median length2
Mean length2.6862745
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row드로잉&판화
2nd row드로잉&판화
3rd row드로잉&판화
4th row드로잉&판화
5th row드로잉&판화

Common Values

ValueCountFrequency (%)
회화 2158
36.2%
사진 1245
20.9%
드로잉&판화 708
 
11.9%
한국화 684
 
11.5%
조각 465
 
7.8%
뉴미디어 280
 
4.7%
설치 168
 
2.8%
공예 153
 
2.6%
서예 87
 
1.5%
디자인 19
 
0.3%

Length

2024-01-27T12:46:18.171530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-27T12:46:18.357674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
회화 2158
36.2%
사진 1245
20.9%
드로잉&판화 708
 
11.9%
한국화 684
 
11.5%
조각 465
 
7.8%
뉴미디어 280
 
4.7%
설치 168
 
2.8%
공예 153
 
2.6%
서예 87
 
1.5%
디자인 19
 
0.3%

수집연도
Real number (ℝ)

Distinct39
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2009.9752
Minimum1985
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size52.6 KiB
2024-01-27T12:46:18.553789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1985
5-th percentile1996
Q12005
median2010
Q32016
95-th percentile2022
Maximum2023
Range38
Interquartile range (IQR)11

Descriptive statistics

Standard deviation8.0563546
Coefficient of variation (CV)0.0040081861
Kurtosis-0.32048839
Mean2009.9752
Median Absolute Deviation (MAD)6
Skewness-0.38464067
Sum11993522
Variance64.904849
MonotonicityDecreasing
2024-01-27T12:46:19.034531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
2005 350
 
5.9%
2001 314
 
5.3%
2009 300
 
5.0%
2003 297
 
5.0%
2016 280
 
4.7%
2010 277
 
4.6%
2008 270
 
4.5%
2017 260
 
4.4%
2019 258
 
4.3%
2011 257
 
4.3%
Other values (29) 3104
52.0%
ValueCountFrequency (%)
1985 1
 
< 0.1%
1986 1
 
< 0.1%
1987 14
 
0.2%
1988 53
0.9%
1989 29
0.5%
1990 36
0.6%
1991 33
0.6%
1992 1
 
< 0.1%
1993 2
 
< 0.1%
1994 1
 
< 0.1%
ValueCountFrequency (%)
2023 215
3.6%
2022 241
4.0%
2021 126
2.1%
2020 214
3.6%
2019 258
4.3%
2018 162
2.7%
2017 260
4.4%
2016 280
4.7%
2015 222
3.7%
2014 213
3.6%
Distinct5251
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Memory size46.7 KiB
2024-01-27T12:46:19.494098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length93
Median length68
Mean length9.6825876
Min length1

Characters and Unicode

Total characters57776
Distinct characters1506
Distinct categories16 ?
Distinct scripts4 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4977 ?
Unique (%)83.4%

Sample

1st rowCrutches III
2nd rowTrivet
3rd rowThe Crutches
4th rowThe Two Crutches
5th rowCross
ValueCountFrequency (%)
257
 
1.9%
무제 235
 
1.7%
2 113
 
0.8%
1 112
 
0.8%
시리즈 110
 
0.8%
the 91
 
0.7%
예술가 75
 
0.5%
3 73
 
0.5%
a 69
 
0.5%
of 62
 
0.5%
Other values (7168) 12534
91.3%
2024-01-27T12:46:20.151981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7805
 
13.5%
e 1408
 
2.4%
- 1243
 
2.2%
a 1031
 
1.8%
n 1016
 
1.8%
o 944
 
1.6%
1 939
 
1.6%
i 920
 
1.6%
0 893
 
1.5%
t 805
 
1.4%
Other values (1496) 40772
70.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27450
47.5%
Lowercase Letter 10940
 
18.9%
Space Separator 7805
 
13.5%
Decimal Number 4744
 
8.2%
Uppercase Letter 2812
 
4.9%
Dash Punctuation 1243
 
2.2%
Other Punctuation 1060
 
1.8%
Open Punctuation 683
 
1.2%
Close Punctuation 682
 
1.2%
Connector Punctuation 152
 
0.3%
Other values (6) 205
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
760
 
2.8%
561
 
2.0%
512
 
1.9%
488
 
1.8%
436
 
1.6%
380
 
1.4%
369
 
1.3%
358
 
1.3%
311
 
1.1%
301
 
1.1%
Other values (1383) 22974
83.7%
Uppercase Letter
ValueCountFrequency (%)
I 301
 
10.7%
S 275
 
9.8%
T 186
 
6.6%
A 171
 
6.1%
B 168
 
6.0%
P 160
 
5.7%
C 151
 
5.4%
L 143
 
5.1%
M 140
 
5.0%
N 125
 
4.4%
Other values (17) 992
35.3%
Lowercase Letter
ValueCountFrequency (%)
e 1408
12.9%
a 1031
 
9.4%
n 1016
 
9.3%
o 944
 
8.6%
i 920
 
8.4%
t 805
 
7.4%
r 737
 
6.7%
s 580
 
5.3%
l 484
 
4.4%
d 374
 
3.4%
Other values (16) 2641
24.1%
Other Punctuation
ValueCountFrequency (%)
, 474
44.7%
# 171
 
16.1%
. 160
 
15.1%
' 74
 
7.0%
? 54
 
5.1%
: 44
 
4.2%
/ 34
 
3.2%
! 14
 
1.3%
& 13
 
1.2%
10
 
0.9%
Other values (6) 12
 
1.1%
Decimal Number
ValueCountFrequency (%)
1 939
19.8%
0 893
18.8%
2 709
14.9%
9 399
8.4%
3 392
8.3%
5 311
 
6.6%
8 307
 
6.5%
4 304
 
6.4%
6 264
 
5.6%
7 226
 
4.8%
Letter Number
ValueCountFrequency (%)
45
40.5%
28
25.2%
18
 
16.2%
5
 
4.5%
4
 
3.6%
4
 
3.6%
3
 
2.7%
2
 
1.8%
2
 
1.8%
Math Symbol
ValueCountFrequency (%)
+ 17
27.0%
< 15
23.8%
> 15
23.8%
~ 13
20.6%
= 1
 
1.6%
1
 
1.6%
| 1
 
1.6%
Open Punctuation
ValueCountFrequency (%)
( 670
98.1%
10
 
1.5%
[ 2
 
0.3%
1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 669
98.1%
10
 
1.5%
] 2
 
0.3%
1
 
0.1%
Modifier Symbol
ValueCountFrequency (%)
` 4
66.7%
˚ 1
 
16.7%
^ 1
 
16.7%
Other Symbol
ValueCountFrequency (%)
° 19
95.0%
1
 
5.0%
Space Separator
ValueCountFrequency (%)
7805
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1243
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 152
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 4
100.0%
Other Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 26405
45.7%
Common 16463
28.5%
Latin 13863
24.0%
Han 1045
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
760
 
2.9%
561
 
2.1%
512
 
1.9%
488
 
1.8%
436
 
1.7%
380
 
1.4%
369
 
1.4%
358
 
1.4%
311
 
1.2%
301
 
1.1%
Other values (894) 21929
83.0%
Han
ValueCountFrequency (%)
30
 
2.9%
28
 
2.7%
17
 
1.6%
16
 
1.5%
13
 
1.2%
12
 
1.1%
12
 
1.1%
11
 
1.1%
11
 
1.1%
10
 
1.0%
Other values (479) 885
84.7%
Latin
ValueCountFrequency (%)
e 1408
 
10.2%
a 1031
 
7.4%
n 1016
 
7.3%
o 944
 
6.8%
i 920
 
6.6%
t 805
 
5.8%
r 737
 
5.3%
s 580
 
4.2%
l 484
 
3.5%
d 374
 
2.7%
Other values (52) 5564
40.1%
Common
ValueCountFrequency (%)
7805
47.4%
- 1243
 
7.6%
1 939
 
5.7%
0 893
 
5.4%
2 709
 
4.3%
( 670
 
4.1%
) 669
 
4.1%
, 474
 
2.9%
9 399
 
2.4%
3 392
 
2.4%
Other values (41) 2270
 
13.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30155
52.2%
Hangul 26401
45.7%
CJK 996
 
1.7%
Number Forms 111
 
0.2%
None 54
 
0.1%
CJK Compat Ideographs 49
 
0.1%
Compat Jamo 4
 
< 0.1%
Punctuation 3
 
< 0.1%
Modifier Letters 1
 
< 0.1%
Arrows 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7805
25.9%
e 1408
 
4.7%
- 1243
 
4.1%
a 1031
 
3.4%
n 1016
 
3.4%
o 944
 
3.1%
1 939
 
3.1%
i 920
 
3.1%
0 893
 
3.0%
t 805
 
2.7%
Other values (81) 13151
43.6%
Hangul
ValueCountFrequency (%)
760
 
2.9%
561
 
2.1%
512
 
1.9%
488
 
1.8%
436
 
1.7%
380
 
1.4%
369
 
1.4%
358
 
1.4%
311
 
1.2%
301
 
1.1%
Other values (892) 21925
83.0%
Number Forms
ValueCountFrequency (%)
45
40.5%
28
25.2%
18
 
16.2%
5
 
4.5%
4
 
3.6%
4
 
3.6%
3
 
2.7%
2
 
1.8%
2
 
1.8%
CJK
ValueCountFrequency (%)
30
 
3.0%
28
 
2.8%
17
 
1.7%
16
 
1.6%
13
 
1.3%
12
 
1.2%
12
 
1.2%
11
 
1.1%
11
 
1.1%
10
 
1.0%
Other values (450) 836
83.9%
None
ValueCountFrequency (%)
° 19
35.2%
10
18.5%
10
18.5%
10
18.5%
1
 
1.9%
1
 
1.9%
Ø 1
 
1.9%
1
 
1.9%
1
 
1.9%
CJK Compat Ideographs
ValueCountFrequency (%)
7
 
14.3%
6
 
12.2%
5
 
10.2%
3
 
6.1%
2
 
4.1%
2
 
4.1%
2
 
4.1%
1
 
2.0%
1
 
2.0%
1
 
2.0%
Other values (19) 19
38.8%
Punctuation
ValueCountFrequency (%)
3
100.0%
Compat Jamo
ValueCountFrequency (%)
3
75.0%
1
 
25.0%
Modifier Letters
ValueCountFrequency (%)
˚ 1
100.0%
Arrows
ValueCountFrequency (%)
1
100.0%
CJK Compat
ValueCountFrequency (%)
1
100.0%

작품명(영문)
Text

MISSING 

Distinct3033
Distinct (%)90.6%
Missing2619
Missing (%)43.9%
Memory size46.7 KiB
2024-01-27T12:46:20.594128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length186
Median length90
Mean length18.956691
Min length1

Characters and Unicode

Total characters63467
Distinct characters135
Distinct categories18 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2901 ?
Unique (%)86.6%

Sample

1st rowCrutches III
2nd rowTrivet
3rd rowThe Crutches
4th rowThe Two Crutches
5th rowCross
ValueCountFrequency (%)
the 405
 
3.9%
of 345
 
3.3%
a 187
 
1.8%
and 167
 
1.6%
in 152
 
1.5%
untitled 123
 
1.2%
114
 
1.1%
1 81
 
0.8%
for 78
 
0.7%
2 77
 
0.7%
Other values (3887) 8677
83.4%
2024-01-27T12:46:21.359988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7088
 
11.2%
e 5454
 
8.6%
a 3859
 
6.1%
n 3831
 
6.0%
o 3819
 
6.0%
i 3450
 
5.4%
t 3095
 
4.9%
r 2855
 
4.5%
s 2135
 
3.4%
l 1954
 
3.1%
Other values (125) 25927
40.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 42230
66.5%
Uppercase Letter 8392
 
13.2%
Space Separator 7088
 
11.2%
Decimal Number 3243
 
5.1%
Other Punctuation 1070
 
1.7%
Dash Punctuation 732
 
1.2%
Open Punctuation 215
 
0.3%
Close Punctuation 213
 
0.3%
Connector Punctuation 105
 
0.2%
Letter Number 72
 
0.1%
Other values (8) 107
 
0.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 901
 
10.7%
T 624
 
7.4%
M 602
 
7.2%
P 495
 
5.9%
A 459
 
5.5%
I 457
 
5.4%
B 441
 
5.3%
W 423
 
5.0%
C 419
 
5.0%
L 393
 
4.7%
Other values (17) 3178
37.9%
Lowercase Letter
ValueCountFrequency (%)
e 5454
12.9%
a 3859
 
9.1%
n 3831
 
9.1%
o 3819
 
9.0%
i 3450
 
8.2%
t 3095
 
7.3%
r 2855
 
6.8%
s 2135
 
5.1%
l 1954
 
4.6%
d 1503
 
3.6%
Other values (16) 10275
24.3%
Other Letter
ValueCountFrequency (%)
2
 
10.5%
2
 
10.5%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
Other values (7) 7
36.8%
Other Punctuation
ValueCountFrequency (%)
, 417
39.0%
. 184
17.2%
# 152
 
14.2%
' 116
 
10.8%
: 80
 
7.5%
? 45
 
4.2%
/ 28
 
2.6%
& 22
 
2.1%
10
 
0.9%
! 7
 
0.7%
Other values (4) 9
 
0.8%
Other Number
ValueCountFrequency (%)
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
Other values (2) 2
16.7%
Decimal Number
ValueCountFrequency (%)
1 645
19.9%
0 644
19.9%
2 469
14.5%
9 266
8.2%
3 263
8.1%
8 230
 
7.1%
4 210
 
6.5%
6 192
 
5.9%
5 166
 
5.1%
7 158
 
4.9%
Letter Number
ValueCountFrequency (%)
31
43.1%
14
19.4%
10
 
13.9%
4
 
5.6%
4
 
5.6%
3
 
4.2%
2
 
2.8%
2
 
2.8%
2
 
2.8%
Math Symbol
ValueCountFrequency (%)
< 14
29.8%
> 14
29.8%
+ 12
25.5%
~ 5
 
10.6%
| 1
 
2.1%
= 1
 
2.1%
Open Punctuation
ValueCountFrequency (%)
( 211
98.1%
[ 4
 
1.9%
Close Punctuation
ValueCountFrequency (%)
) 209
98.1%
] 4
 
1.9%
Final Punctuation
ValueCountFrequency (%)
18
94.7%
1
 
5.3%
Modifier Symbol
ValueCountFrequency (%)
` 2
66.7%
^ 1
33.3%
Space Separator
ValueCountFrequency (%)
7088
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 732
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 105
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 4
100.0%
Other Symbol
ValueCountFrequency (%)
° 2
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 50694
79.9%
Common 12754
 
20.1%
Hangul 16
 
< 0.1%
Han 3
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 5454
 
10.8%
a 3859
 
7.6%
n 3831
 
7.6%
o 3819
 
7.5%
i 3450
 
6.8%
t 3095
 
6.1%
r 2855
 
5.6%
s 2135
 
4.2%
l 1954
 
3.9%
d 1503
 
3.0%
Other values (52) 18739
37.0%
Common
ValueCountFrequency (%)
7088
55.6%
- 732
 
5.7%
1 645
 
5.1%
0 644
 
5.0%
2 469
 
3.7%
, 417
 
3.3%
9 266
 
2.1%
3 263
 
2.1%
8 230
 
1.8%
( 211
 
1.7%
Other values (46) 1789
 
14.0%
Hangul
ValueCountFrequency (%)
2
12.5%
2
12.5%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Other values (4) 4
25.0%
Han
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63329
99.8%
Number Forms 72
 
0.1%
Punctuation 20
 
< 0.1%
None 16
 
< 0.1%
Hangul 15
 
< 0.1%
Enclosed Alphanum 11
 
< 0.1%
CJK 3
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7088
 
11.2%
e 5454
 
8.6%
a 3859
 
6.1%
n 3831
 
6.0%
o 3819
 
6.0%
i 3450
 
5.4%
t 3095
 
4.9%
r 2855
 
4.5%
s 2135
 
3.4%
l 1954
 
3.1%
Other values (80) 25789
40.7%
Number Forms
ValueCountFrequency (%)
31
43.1%
14
19.4%
10
 
13.9%
4
 
5.6%
4
 
5.6%
3
 
4.2%
2
 
2.8%
2
 
2.8%
2
 
2.8%
Punctuation
ValueCountFrequency (%)
18
90.0%
1
 
5.0%
1
 
5.0%
None
ValueCountFrequency (%)
10
62.5%
° 2
 
12.5%
2
 
12.5%
Π1
 
6.2%
1
 
6.2%
Hangul
ValueCountFrequency (%)
2
13.3%
2
13.3%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
Other values (3) 3
20.0%
Enclosed Alphanum
ValueCountFrequency (%)
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Distinct4074
Distinct (%)68.3%
Missing0
Missing (%)0.0%
Memory size46.7 KiB
2024-01-27T12:46:21.776642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length250
Median length100
Mean length10.11463
Min length2

Characters and Unicode

Total characters60354
Distinct characters113
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3458 ?
Unique (%)58.0%

Sample

1st row76×56cm
2nd row76×56cm
3rd row76×56cm
4th row56×76cm
5th row76×56cm
ValueCountFrequency (%)
x 387
 
5.4%
가변설치 48
 
0.7%
130×162cm 43
 
0.6%
76×56cm 42
 
0.6%
162×130cm 38
 
0.5%
16×25cm 34
 
0.5%
90×60cm 31
 
0.4%
25 29
 
0.4%
39.5×49.5cm 28
 
0.4%
49.5×39.5cm 27
 
0.4%
Other values (4398) 6505
90.2%
2024-01-27T12:46:22.379481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 6882
11.4%
× 6539
10.8%
c 5261
 
8.7%
m 5258
 
8.7%
5 5158
 
8.5%
0 4633
 
7.7%
2 4224
 
7.0%
3 3263
 
5.4%
. 3009
 
5.0%
6 2692
 
4.5%
Other values (103) 13435
22.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35749
59.2%
Lowercase Letter 10545
 
17.5%
Math Symbol 6540
 
10.8%
Other Punctuation 3606
 
6.0%
Other Letter 1368
 
2.3%
Space Separator 1282
 
2.1%
Uppercase Letter 394
 
0.7%
Open Punctuation 376
 
0.6%
Close Punctuation 376
 
0.6%
Letter Number 99
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
350
25.6%
335
24.5%
299
21.9%
55
 
4.0%
55
 
4.0%
51
 
3.7%
51
 
3.7%
27
 
2.0%
27
 
2.0%
10
 
0.7%
Other values (60) 108
 
7.9%
Lowercase Letter
ValueCountFrequency (%)
c 5261
49.9%
m 5258
49.9%
x 9
 
0.1%
n 3
 
< 0.1%
p 3
 
< 0.1%
s 3
 
< 0.1%
g 2
 
< 0.1%
a 2
 
< 0.1%
k 2
 
< 0.1%
o 1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 6882
19.3%
5 5158
14.4%
0 4633
13.0%
2 4224
11.8%
3 3263
9.1%
6 2692
 
7.5%
4 2567
 
7.2%
9 2213
 
6.2%
7 2124
 
5.9%
8 1993
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 3009
83.4%
, 355
 
9.8%
* 169
 
4.7%
; 44
 
1.2%
# 19
 
0.5%
: 8
 
0.2%
/ 1
 
< 0.1%
' 1
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
X 386
98.0%
H 3
 
0.8%
D 2
 
0.5%
M 1
 
0.3%
W 1
 
0.3%
V 1
 
0.3%
Math Symbol
ValueCountFrequency (%)
× 6539
> 99.9%
~ 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
94
94.9%
5
 
5.1%
Space Separator
ValueCountFrequency (%)
1282
100.0%
Open Punctuation
ValueCountFrequency (%)
( 376
100.0%
Close Punctuation
ValueCountFrequency (%)
) 376
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 47948
79.4%
Latin 11038
 
18.3%
Hangul 1368
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
350
25.6%
335
24.5%
299
21.9%
55
 
4.0%
55
 
4.0%
51
 
3.7%
51
 
3.7%
27
 
2.0%
27
 
2.0%
10
 
0.7%
Other values (60) 108
 
7.9%
Common
ValueCountFrequency (%)
1 6882
14.4%
× 6539
13.6%
5 5158
10.8%
0 4633
9.7%
2 4224
8.8%
3 3263
6.8%
. 3009
6.3%
6 2692
 
5.6%
4 2567
 
5.4%
9 2213
 
4.6%
Other values (14) 6768
14.1%
Latin
ValueCountFrequency (%)
c 5261
47.7%
m 5258
47.6%
X 386
 
3.5%
94
 
0.9%
x 9
 
0.1%
5
 
< 0.1%
H 3
 
< 0.1%
n 3
 
< 0.1%
p 3
 
< 0.1%
s 3
 
< 0.1%
Other values (9) 13
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 52348
86.7%
None 6539
 
10.8%
Hangul 1368
 
2.3%
Number Forms 99
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6882
13.1%
c 5261
10.1%
m 5258
10.0%
5 5158
9.9%
0 4633
8.9%
2 4224
8.1%
3 3263
 
6.2%
. 3009
 
5.7%
6 2692
 
5.1%
4 2567
 
4.9%
Other values (30) 9401
18.0%
None
ValueCountFrequency (%)
× 6539
100.0%
Hangul
ValueCountFrequency (%)
350
25.6%
335
24.5%
299
21.9%
55
 
4.0%
55
 
4.0%
51
 
3.7%
51
 
3.7%
27
 
2.0%
27
 
2.0%
10
 
0.7%
Other values (60) 108
 
7.9%
Number Forms
ValueCountFrequency (%)
94
94.9%
5
 
5.1%
Distinct256
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size46.7 KiB
2024-01-27T12:46:22.750100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length4
Mean length4.4012066
Min length4

Characters and Unicode

Total characters26262
Distinct characters73
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

Unique140 ?
Unique (%)2.3%

Sample

1st row1981
2nd row1981
3rd row1982
4th row1982
5th row1983
ValueCountFrequency (%)
2009 254
 
4.2%
2011 246
 
4.0%
2008 232
 
3.8%
2007 193
 
3.2%
2010 193
 
3.2%
2004 191
 
3.1%
2013 171
 
2.8%
2005 166
 
2.7%
2014 155
 
2.5%
1988 154
 
2.5%
Other values (242) 4136
67.9%
2024-01-27T12:46:23.345974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5761
21.9%
1 5092
19.4%
9 4566
17.4%
2 3986
15.2%
8 1680
 
6.4%
7 1016
 
3.9%
6 895
 
3.4%
5 748
 
2.8%
4 635
 
2.4%
3 556
 
2.1%
Other values (63) 1327
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24935
94.9%
Other Letter 766
 
2.9%
Dash Punctuation 258
 
1.0%
Space Separator 124
 
0.5%
Open Punctuation 73
 
0.3%
Close Punctuation 73
 
0.3%
Other Punctuation 27
 
0.1%
Math Symbol 4
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
93
12.1%
91
11.9%
91
11.9%
91
11.9%
72
9.4%
64
8.4%
32
 
4.2%
31
 
4.0%
31
 
4.0%
24
 
3.1%
Other values (43) 146
19.1%
Decimal Number
ValueCountFrequency (%)
0 5761
23.1%
1 5092
20.4%
9 4566
18.3%
2 3986
16.0%
8 1680
 
6.7%
7 1016
 
4.1%
6 895
 
3.6%
5 748
 
3.0%
4 635
 
2.5%
3 556
 
2.2%
Other Punctuation
ValueCountFrequency (%)
, 16
59.3%
/ 7
25.9%
; 3
 
11.1%
? 1
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 258
100.0%
Space Separator
ValueCountFrequency (%)
124
100.0%
Open Punctuation
ValueCountFrequency (%)
( 73
100.0%
Close Punctuation
ValueCountFrequency (%)
) 73
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25494
97.1%
Hangul 766
 
2.9%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
93
12.1%
91
11.9%
91
11.9%
91
11.9%
72
9.4%
64
8.4%
32
 
4.2%
31
 
4.0%
31
 
4.0%
24
 
3.1%
Other values (43) 146
19.1%
Common
ValueCountFrequency (%)
0 5761
22.6%
1 5092
20.0%
9 4566
17.9%
2 3986
15.6%
8 1680
 
6.6%
7 1016
 
4.0%
6 895
 
3.5%
5 748
 
2.9%
4 635
 
2.5%
3 556
 
2.2%
Other values (9) 559
 
2.2%
Latin
ValueCountFrequency (%)
m 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25496
97.1%
Hangul 766
 
2.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5761
22.6%
1 5092
20.0%
9 4566
17.9%
2 3986
15.6%
8 1680
 
6.6%
7 1016
 
4.0%
6 895
 
3.5%
5 748
 
2.9%
4 635
 
2.5%
3 556
 
2.2%
Other values (10) 561
 
2.2%
Hangul
ValueCountFrequency (%)
93
12.1%
91
11.9%
91
11.9%
91
11.9%
72
9.4%
64
8.4%
32
 
4.2%
31
 
4.0%
31
 
4.0%
24
 
3.1%
Other values (43) 146
19.1%

재료/기법
Text

MISSING 

Distinct794
Distinct (%)20.5%
Missing2088
Missing (%)35.0%
Memory size46.7 KiB
2024-01-27T12:46:23.658390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length107
Median length96
Mean length20.774942
Min length4

Characters and Unicode

Total characters80586
Distinct characters74
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique587 ?
Unique (%)15.1%

Sample

1st rowLithograph
2nd rowLithograph
3rd rowLithograph
4th rowLithograph
5th rowLithograph
ValueCountFrequency (%)
on 2263
17.1%
canvas 1054
 
8.0%
paper 908
 
6.9%
oil 826
 
6.2%
print 678
 
5.1%
digital 496
 
3.7%
acrylic 449
 
3.4%
color 436
 
3.3%
korean 314
 
2.4%
and 297
 
2.2%
Other values (654) 5523
41.7%
2024-01-27T12:46:24.227815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9371
11.6%
n 7888
 
9.8%
a 7146
 
8.9%
i 6759
 
8.4%
o 5774
 
7.2%
e 4942
 
6.1%
r 4930
 
6.1%
l 4312
 
5.4%
t 4120
 
5.1%
p 3563
 
4.4%
Other values (64) 21781
27.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 65001
80.7%
Space Separator 9371
 
11.6%
Uppercase Letter 4472
 
5.5%
Other Punctuation 987
 
1.2%
Dash Punctuation 411
 
0.5%
Close Punctuation 143
 
0.2%
Open Punctuation 142
 
0.2%
Decimal Number 57
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 7888
12.1%
a 7146
11.0%
i 6759
10.4%
o 5774
8.9%
e 4942
7.6%
r 4930
7.6%
l 4312
 
6.6%
t 4120
 
6.3%
p 3563
 
5.5%
c 3386
 
5.2%
Other values (16) 12181
18.7%
Uppercase Letter
ValueCountFrequency (%)
O 800
17.9%
C 514
11.5%
D 514
11.5%
A 435
9.7%
I 300
 
6.7%
M 271
 
6.1%
S 261
 
5.8%
G 234
 
5.2%
K 224
 
5.0%
W 182
 
4.1%
Other values (15) 737
16.5%
Decimal Number
ValueCountFrequency (%)
2 13
22.8%
0 12
21.1%
1 11
19.3%
3 5
 
8.8%
7 4
 
7.0%
8 4
 
7.0%
6 4
 
7.0%
4 3
 
5.3%
9 1
 
1.8%
Other Punctuation
ValueCountFrequency (%)
, 957
97.0%
& 17
 
1.7%
; 6
 
0.6%
/ 3
 
0.3%
. 2
 
0.2%
# 1
 
0.1%
? 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 142
99.3%
] 1
 
0.7%
Open Punctuation
ValueCountFrequency (%)
( 141
99.3%
[ 1
 
0.7%
Space Separator
ValueCountFrequency (%)
9371
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 411
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 69473
86.2%
Common 11113
 
13.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 7888
11.4%
a 7146
10.3%
i 6759
9.7%
o 5774
 
8.3%
e 4942
 
7.1%
r 4930
 
7.1%
l 4312
 
6.2%
t 4120
 
5.9%
p 3563
 
5.1%
c 3386
 
4.9%
Other values (41) 16653
24.0%
Common
ValueCountFrequency (%)
9371
84.3%
, 957
 
8.6%
- 411
 
3.7%
) 142
 
1.3%
( 141
 
1.3%
& 17
 
0.2%
2 13
 
0.1%
0 12
 
0.1%
1 11
 
0.1%
; 6
 
0.1%
Other values (13) 32
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80586
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9371
11.6%
n 7888
 
9.8%
a 7146
 
8.9%
i 6759
 
8.4%
o 5774
 
7.2%
e 4942
 
6.1%
r 4930
 
6.1%
l 4312
 
5.4%
t 4120
 
5.1%
p 3563
 
4.4%
Other values (64) 21781
27.0%

작품해설
Text

MISSING 

Distinct517
Distinct (%)71.8%
Missing5247
Missing (%)87.9%
Memory size46.7 KiB
2024-01-27T12:46:24.656102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1024
Median length1001
Mean length857.16944
Min length87

Characters and Unicode

Total characters617162
Distinct characters143
Distinct categories16 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique471 ?
Unique (%)65.4%

Sample

1st rowThis is a photograph of flowers that Kim Jung Man has taken for 20 years while traveling around the world, including South Korea, Africa, the Philippines, Thailand, and Guam. The photograph was presented in his solo exhibition 《Naked Soul》 and later published in his photo essay 『Naked Soul』 (2005) among his 111 representative works. The artist captured the shapes of flowers in a close-up and expressed the beauty of the colorful and fascinating flowers as well as a passion for life. In order to maximize the original and mysterious feeling of flowers, he placed the base in black, red, and white colors, and sometimes waited until the flowers dried up. For Kim Jung Man, flowers were also a way to demonstrate eroticism, which is often concealed or excessively implied by modern people. Through this work, the artist conveys his idea that human desires should be sincerely communicated, cherished, and shared with one another.
2nd rowThese photos were taken by Kim Soohyun in 2012 and 2013 after moving to Chicago, USA. At the time, he was working on a photography project to examine the traces of housing experiments, such as the infamous Cabrini Green public housing redevelopment project in Chicago. Cabrini Green was a Chicago public housing project implemented from 1942 to 1958, providing housing for 15,000 people. But a majority of the buildings were demolished from 1995 to 2011 due to a new urban redevelopment project. The biggest victims of the process were mainly low income African American residents. The artist tried to visualize what was lost from the historical event by photographing houses and buildings on the verge of demolition and to record traces of the community that disappeared with demolition. Here, he continued to work on the theme of “city” and his interest in social issues. For example, he actively participated in the Tamms Year Ten, a campaign to close solitary confinement prisons, which causes the loss of humanity and a
3rd row<Absence> (2016) depicts the scenery of a leisurely and peaceful outdoor swimming pool on two panels respectively. This work illustrates the harmony between Hwang’s signature coloring and plane composition along with his realistic description. The white and sky blue areas on the bottom of the two panels represent the shadows of the children who were killed in the Sewol Ferry disaster. Rather than pointing out the controversial aspect of the incident that has yet to be officially investigated, the artist addressed that he wanted to focus on the obvious fact, namely ‘the absence of children’. Unlike children playing in that pool, the missing ones, which are no longer visible, desperately show the collision between peaceful daily life and tragedy. At the same time, the viewer can read the artist’s intention to address our current reality by moving between landscape and abstraction.
4th row<River> (2016) is a work consisting of two differently sized panels. The smaller panel describes a river and its bank on a blue colored band, while the larger panel depicts buildings and urban landscapes with the word “bangsaengdoryang” (meaning “a Buddhist ceremony releasing living creatures”). The building is the Hangang River Water Temple belonging to the Jogye Order located in Hangang River Park. People visit the temple to make a wish and release fish into the river. Above that, one can see Lotte Tower and Jamsil Stadium. The small panel depicts the construction of a cruise ship and a bridge construction site near Seongsan Bridge. The works portray the north and south sides of the Hangang River in each panel. Hwang once pointed out that he wanted to paint the daily scenery of the Hangang River and the dynamic flow running vertically in the simplest possible form. Accordingly, the work shows a unique composition in which the river and the riverbank are depicted in color bands.
5th rowThe word “mokdan” in <Mokdan Planet> (2013) refers to a peony flower that symbolizes wealth, honor, and glory. The artist defines a peony as “the flower of capitalism.” According to Hwang, South Korea is now more than a well-off country; it is disquietingly abundant. Nevertheless, the artist tries to express the inner landscape of contemporary South Korea, which is devoted solely to satisfying monetary and material needs. He uses the symbolic meaning of the peony flower in his work. He argues that South Korea has achieved rapid growth in material terms but is still obsessed with the urge to eat better and live better in everything, and <Mokdan Planet> is an allegory of such compulsion. The four landscapes, each containing a scene from different places and times, are the images of South Korea in the early 2010s that the artist witnessed. He painted scenes where desire and reality coexist. The reality, mainly in achromatic colors, contrasts with the red peony flower to convey the metaphorical and critical messa
ValueCountFrequency (%)
the 7784
 
7.8%
of 4295
 
4.3%
and 3307
 
3.3%
a 2772
 
2.8%
in 2678
 
2.7%
to 1771
 
1.8%
is 1012
 
1.0%
as 1001
 
1.0%
with 910
 
0.9%
on 897
 
0.9%
Other values (9746) 73593
73.6%
2024-01-27T12:46:25.365585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
99424
16.1%
e 59525
 
9.6%
t 42860
 
6.9%
a 39248
 
6.4%
i 39182
 
6.3%
n 36959
 
6.0%
o 35466
 
5.7%
s 33441
 
5.4%
r 31811
 
5.2%
h 25026
 
4.1%
Other values (133) 174220
28.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 484489
78.5%
Space Separator 99424
 
16.1%
Uppercase Letter 11208
 
1.8%
Other Punctuation 9851
 
1.6%
Decimal Number 6044
 
1.0%
Final Punctuation 2049
 
0.3%
Initial Punctuation 1026
 
0.2%
Open Punctuation 991
 
0.2%
Close Punctuation 985
 
0.2%
Dash Punctuation 975
 
0.2%
Other values (6) 120
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4
 
6.7%
3
 
5.0%
3
 
5.0%
3
 
5.0%
2
 
3.3%
2
 
3.3%
2
 
3.3%
2
 
3.3%
2
 
3.3%
1
 
1.7%
Other values (36) 36
60.0%
Lowercase Letter
ValueCountFrequency (%)
e 59525
12.3%
t 42860
 
8.8%
a 39248
 
8.1%
i 39182
 
8.1%
n 36959
 
7.6%
o 35466
 
7.3%
s 33441
 
6.9%
r 31811
 
6.6%
h 25026
 
5.2%
l 18063
 
3.7%
Other values (16) 122908
25.4%
Uppercase Letter
ValueCountFrequency (%)
T 1493
13.3%
C 1115
 
9.9%
S 996
 
8.9%
K 985
 
8.8%
I 773
 
6.9%
A 668
 
6.0%
M 626
 
5.6%
H 569
 
5.1%
W 443
 
4.0%
P 436
 
3.9%
Other values (15) 3104
27.7%
Other Punctuation
ValueCountFrequency (%)
, 5461
55.4%
. 3897
39.6%
? 167
 
1.7%
; 102
 
1.0%
: 98
 
1.0%
' 78
 
0.8%
23
 
0.2%
& 9
 
0.1%
/ 8
 
0.1%
# 6
 
0.1%
Other values (2) 2
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 1365
22.6%
9 1308
21.6%
0 1124
18.6%
2 631
10.4%
8 473
 
7.8%
6 317
 
5.2%
7 267
 
4.4%
4 203
 
3.4%
5 189
 
3.1%
3 167
 
2.8%
Open Punctuation
ValueCountFrequency (%)
( 703
70.9%
149
 
15.0%
[ 88
 
8.9%
41
 
4.1%
10
 
1.0%
Close Punctuation
ValueCountFrequency (%)
) 701
71.2%
145
 
14.7%
] 88
 
8.9%
41
 
4.2%
10
 
1.0%
Math Symbol
ValueCountFrequency (%)
> 14
48.3%
< 10
34.5%
+ 4
 
13.8%
× 1
 
3.4%
Final Punctuation
ValueCountFrequency (%)
1038
50.7%
1011
49.3%
Initial Punctuation
ValueCountFrequency (%)
1017
99.1%
9
 
0.9%
Space Separator
ValueCountFrequency (%)
99424
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 975
100.0%
Control
ValueCountFrequency (%)
18
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 11
100.0%
Other Number
ValueCountFrequency (%)
1
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 495698
80.3%
Common 121404
 
19.7%
Hangul 48
 
< 0.1%
Han 12
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 59525
12.0%
t 42860
 
8.6%
a 39248
 
7.9%
i 39182
 
7.9%
n 36959
 
7.5%
o 35466
 
7.2%
s 33441
 
6.7%
r 31811
 
6.4%
h 25026
 
5.0%
l 18063
 
3.6%
Other values (42) 134117
27.1%
Common
ValueCountFrequency (%)
99424
81.9%
, 5461
 
4.5%
. 3897
 
3.2%
1 1365
 
1.1%
9 1308
 
1.1%
0 1124
 
0.9%
1038
 
0.9%
1017
 
0.8%
1011
 
0.8%
- 975
 
0.8%
Other values (35) 4784
 
3.9%
Hangul
ValueCountFrequency (%)
4
 
8.3%
3
 
6.2%
3
 
6.2%
3
 
6.2%
2
 
4.2%
2
 
4.2%
2
 
4.2%
1
 
2.1%
1
 
2.1%
1
 
2.1%
Other values (26) 26
54.2%
Han
ValueCountFrequency (%)
2
16.7%
2
16.7%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 613604
99.4%
Punctuation 3076
 
0.5%
None 421
 
0.1%
Hangul 48
 
< 0.1%
CJK 12
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
99424
16.2%
e 59525
 
9.7%
t 42860
 
7.0%
a 39248
 
6.4%
i 39182
 
6.4%
n 36959
 
6.0%
o 35466
 
5.8%
s 33441
 
5.4%
r 31811
 
5.2%
h 25026
 
4.1%
Other values (72) 170662
27.8%
Punctuation
ValueCountFrequency (%)
1038
33.7%
1017
33.1%
1011
32.9%
9
 
0.3%
1
 
< 0.1%
None
ValueCountFrequency (%)
149
35.4%
145
34.4%
41
 
9.7%
41
 
9.7%
23
 
5.5%
10
 
2.4%
10
 
2.4%
1
 
0.2%
× 1
 
0.2%
Hangul
ValueCountFrequency (%)
4
 
8.3%
3
 
6.2%
3
 
6.2%
3
 
6.2%
2
 
4.2%
2
 
4.2%
2
 
4.2%
1
 
2.1%
1
 
2.1%
1
 
2.1%
Other values (26) 26
54.2%
CJK
ValueCountFrequency (%)
2
16.7%
2
16.7%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
Number Forms
ValueCountFrequency (%)
1
100.0%
Distinct1839
Distinct (%)30.8%
Missing0
Missing (%)0.0%
Memory size46.7 KiB
2024-01-27T12:46:25.856768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length167
Median length28
Mean length12.815485
Min length3

Characters and Unicode

Total characters76470
Distinct characters96
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique928 ?
Unique (%)15.6%

Sample

1st rowHan, Un-Sung
2nd rowHan, Un-Sung
3rd rowHan, Un-Sung
4th rowHan, Un-Sung
5th rowHan, Un-Sung
ValueCountFrequency (%)
kim 901
 
6.1%
lee 625
 
4.2%
park 608
 
4.1%
han 306
 
2.1%
jin 269
 
1.8%
choi 241
 
1.6%
hong 227
 
1.5%
young 221
 
1.5%
un-sung 218
 
1.5%
kwang 209
 
1.4%
Other values (1507) 11061
74.3%
2024-01-27T12:46:26.527045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8922
 
11.7%
n 8195
 
10.7%
o 6374
 
8.3%
g 4489
 
5.9%
u 4459
 
5.8%
, 3803
 
5.0%
a 3767
 
4.9%
e 3537
 
4.6%
i 2897
 
3.8%
K 2512
 
3.3%
Other values (86) 27515
36.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 44287
57.9%
Uppercase Letter 17922
23.4%
Space Separator 8922
 
11.7%
Other Punctuation 3829
 
5.0%
Dash Punctuation 1400
 
1.8%
Other Letter 71
 
0.1%
Open Punctuation 15
 
< 0.1%
Close Punctuation 15
 
< 0.1%
Decimal Number 6
 
< 0.1%
Final Punctuation 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 8195
18.5%
o 6374
14.4%
g 4489
10.1%
u 4459
10.1%
a 3767
8.5%
e 3537
8.0%
i 2897
 
6.5%
h 1935
 
4.4%
k 1798
 
4.1%
y 1610
 
3.6%
Other values (17) 5226
11.8%
Other Letter
ValueCountFrequency (%)
5
 
7.0%
5
 
7.0%
5
 
7.0%
5
 
7.0%
5
 
7.0%
5
 
7.0%
3
 
4.2%
3
 
4.2%
3
 
4.2%
3
 
4.2%
Other values (17) 29
40.8%
Uppercase Letter
ValueCountFrequency (%)
K 2512
14.0%
S 2246
12.5%
H 1886
10.5%
J 1575
 
8.8%
Y 1085
 
6.1%
C 1068
 
6.0%
M 827
 
4.6%
L 818
 
4.6%
O 741
 
4.1%
P 683
 
3.8%
Other values (16) 4481
25.0%
Decimal Number
ValueCountFrequency (%)
4 3
50.0%
5 1
 
16.7%
9 1
 
16.7%
1 1
 
16.7%
Other Punctuation
ValueCountFrequency (%)
, 3803
99.3%
. 23
 
0.6%
& 3
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 14
93.3%
[ 1
 
6.7%
Close Punctuation
ValueCountFrequency (%)
) 14
93.3%
] 1
 
6.7%
Space Separator
ValueCountFrequency (%)
8922
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1400
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 62209
81.4%
Common 14190
 
18.6%
Hangul 71
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 8195
 
13.2%
o 6374
 
10.2%
g 4489
 
7.2%
u 4459
 
7.2%
a 3767
 
6.1%
e 3537
 
5.7%
i 2897
 
4.7%
K 2512
 
4.0%
S 2246
 
3.6%
h 1935
 
3.1%
Other values (43) 21798
35.0%
Hangul
ValueCountFrequency (%)
5
 
7.0%
5
 
7.0%
5
 
7.0%
5
 
7.0%
5
 
7.0%
5
 
7.0%
3
 
4.2%
3
 
4.2%
3
 
4.2%
3
 
4.2%
Other values (17) 29
40.8%
Common
ValueCountFrequency (%)
8922
62.9%
, 3803
26.8%
- 1400
 
9.9%
. 23
 
0.2%
( 14
 
0.1%
) 14
 
0.1%
4 3
 
< 0.1%
& 3
 
< 0.1%
1
 
< 0.1%
_ 1
 
< 0.1%
Other values (6) 6
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 76397
99.9%
Hangul 71
 
0.1%
None 1
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8922
 
11.7%
n 8195
 
10.7%
o 6374
 
8.3%
g 4489
 
5.9%
u 4459
 
5.8%
, 3803
 
5.0%
a 3767
 
4.9%
e 3537
 
4.6%
i 2897
 
3.8%
K 2512
 
3.3%
Other values (57) 27442
35.9%
Hangul
ValueCountFrequency (%)
5
 
7.0%
5
 
7.0%
5
 
7.0%
5
 
7.0%
5
 
7.0%
5
 
7.0%
3
 
4.2%
3
 
4.2%
3
 
4.2%
3
 
4.2%
Other values (17) 29
40.8%
None
ValueCountFrequency (%)
ß 1
100.0%
Punctuation
ValueCountFrequency (%)
1
100.0%

메인이미지
Text

UNIQUE 

Distinct5967
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size46.7 KiB
2024-01-27T12:46:26.884567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length78
Median length77
Mean length77.431373
Min length74

Characters and Unicode

Total characters462033
Distinct characters38
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5967 ?
Unique (%)100.0%

Sample

1st rowhttp://collections.eseoul.go.kr/common/file/getImage.do?size=700&fileSeq=53883
2nd rowhttp://collections.eseoul.go.kr/common/file/getImage.do?size=700&fileSeq=53884
3rd rowhttp://collections.eseoul.go.kr/common/file/getImage.do?size=700&fileSeq=53885
4th rowhttp://collections.eseoul.go.kr/common/file/getImage.do?size=700&fileSeq=53886
5th rowhttp://collections.eseoul.go.kr/common/file/getImage.do?size=700&fileSeq=53887
ValueCountFrequency (%)
http://collections.eseoul.go.kr/common/file/getimage.do?size=700&fileseq=53883 1
 
< 0.1%
http://collections.eseoul.go.kr/common/file/getimage.do?size=700&fileseq=3925 1
 
< 0.1%
http://collections.eseoul.go.kr/common/file/getimage.do?size=700&fileseq=3909 1
 
< 0.1%
http://collections.eseoul.go.kr/common/file/getimage.do?size=700&fileseq=3910 1
 
< 0.1%
http://collections.eseoul.go.kr/common/file/getimage.do?size=700&fileseq=21738 1
 
< 0.1%
http://collections.eseoul.go.kr/common/file/getimage.do?size=700&fileseq=3914 1
 
< 0.1%
http://collections.eseoul.go.kr/common/file/getimage.do?size=700&fileseq=3917 1
 
< 0.1%
http://collections.eseoul.go.kr/common/file/getimage.do?size=700&fileseq=3920 1
 
< 0.1%
http://collections.eseoul.go.kr/common/file/getimage.do?size=700&fileseq=3921 1
 
< 0.1%
http://collections.eseoul.go.kr/common/file/getimage.do?size=700&fileseq=32009 1
 
< 0.1%
Other values (5957) 5957
99.8%
2024-01-27T12:46:27.610351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 53703
 
11.6%
o 41769
 
9.0%
/ 29835
 
6.5%
l 29835
 
6.5%
t 23868
 
5.2%
i 23868
 
5.2%
. 23868
 
5.2%
s 17901
 
3.9%
c 17901
 
3.9%
m 17901
 
3.9%
Other values (28) 181584
39.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 322218
69.7%
Other Punctuation 71604
 
15.5%
Decimal Number 44343
 
9.6%
Math Symbol 11934
 
2.6%
Uppercase Letter 11934
 
2.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 53703
16.7%
o 41769
13.0%
l 29835
9.3%
t 23868
 
7.4%
i 23868
 
7.4%
s 17901
 
5.6%
c 17901
 
5.6%
m 17901
 
5.6%
g 17901
 
5.6%
n 11934
 
3.7%
Other values (10) 65637
20.4%
Decimal Number
ValueCountFrequency (%)
0 14087
31.8%
7 8150
18.4%
2 3686
 
8.3%
1 3547
 
8.0%
3 3004
 
6.8%
5 2571
 
5.8%
4 2545
 
5.7%
9 2469
 
5.6%
6 2174
 
4.9%
8 2110
 
4.8%
Other Punctuation
ValueCountFrequency (%)
/ 29835
41.7%
. 23868
33.3%
& 5967
 
8.3%
? 5967
 
8.3%
: 5967
 
8.3%
Uppercase Letter
ValueCountFrequency (%)
S 5967
50.0%
I 5967
50.0%
Math Symbol
ValueCountFrequency (%)
= 11934
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 334152
72.3%
Common 127881
 
27.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 53703
16.1%
o 41769
12.5%
l 29835
 
8.9%
t 23868
 
7.1%
i 23868
 
7.1%
s 17901
 
5.4%
c 17901
 
5.4%
m 17901
 
5.4%
g 17901
 
5.4%
n 11934
 
3.6%
Other values (12) 77571
23.2%
Common
ValueCountFrequency (%)
/ 29835
23.3%
. 23868
18.7%
0 14087
11.0%
= 11934
 
9.3%
7 8150
 
6.4%
& 5967
 
4.7%
? 5967
 
4.7%
: 5967
 
4.7%
2 3686
 
2.9%
1 3547
 
2.8%
Other values (6) 14873
11.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 462033
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 53703
 
11.6%
o 41769
 
9.0%
/ 29835
 
6.5%
l 29835
 
6.5%
t 23868
 
5.2%
i 23868
 
5.2%
. 23868
 
5.2%
s 17901
 
3.9%
c 17901
 
3.9%
m 17901
 
3.9%
Other values (28) 181584
39.3%

썸네일이미지
Text

UNIQUE 

Distinct5967
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size46.7 KiB
2024-01-27T12:46:28.085173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length55
Mean length55.497402
Min length55

Characters and Unicode

Total characters331153
Distinct characters35
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5967 ?
Unique (%)100.0%

Sample

1st rowhttp://collections.eseoul.go.kr/data/art/thumb/53883.jpg
2nd rowhttp://collections.eseoul.go.kr/data/art/thumb/53884.jpg
3rd rowhttp://collections.eseoul.go.kr/data/art/thumb/53885.jpg
4th rowhttp://collections.eseoul.go.kr/data/art/thumb/53886.jpg
5th rowhttp://collections.eseoul.go.kr/data/art/thumb/53887.jpg
ValueCountFrequency (%)
http://collections.eseoul.go.kr/data/art/thumb/53883.jpg 1
 
< 0.1%
http://collections.eseoul.go.kr/data/art/thumb/1834.jpg 1
 
< 0.1%
http://collections.eseoul.go.kr/data/art/thumb/1824.jpg 1
 
< 0.1%
http://collections.eseoul.go.kr/data/art/thumb/1825.jpg 1
 
< 0.1%
http://collections.eseoul.go.kr/data/art/thumb/21738.jpg 1
 
< 0.1%
http://collections.eseoul.go.kr/data/art/thumb/1827.jpg 1
 
< 0.1%
http://collections.eseoul.go.kr/data/art/thumb/1828.jpg 1
 
< 0.1%
http://collections.eseoul.go.kr/data/art/thumb/1829.jpg 1
 
< 0.1%
http://collections.eseoul.go.kr/data/art/thumb/1830.jpg 1
 
< 0.1%
http://collections.eseoul.go.kr/data/art/thumb/32009.jpg 1
 
< 0.1%
Other values (5957) 5957
99.8%
2024-01-27T12:46:28.738941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 35806
 
10.8%
/ 35802
 
10.8%
. 23868
 
7.2%
o 23868
 
7.2%
e 17908
 
5.4%
a 17901
 
5.4%
l 17901
 
5.4%
r 11935
 
3.6%
h 11935
 
3.6%
c 11934
 
3.6%
Other values (25) 122295
36.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 238692
72.1%
Other Punctuation 65637
 
19.8%
Decimal Number 26802
 
8.1%
Dash Punctuation 14
 
< 0.1%
Connector Punctuation 8
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 35806
15.0%
o 23868
 
10.0%
e 17908
 
7.5%
a 17901
 
7.5%
l 17901
 
7.5%
r 11935
 
5.0%
h 11935
 
5.0%
c 11934
 
5.0%
s 11934
 
5.0%
u 11934
 
5.0%
Other values (10) 65636
27.5%
Decimal Number
ValueCountFrequency (%)
2 4260
15.9%
1 4176
15.6%
3 3230
12.1%
0 2681
10.0%
9 2397
8.9%
4 2208
8.2%
5 2190
8.2%
7 1925
7.2%
6 1918
7.2%
8 1817
6.8%
Other Punctuation
ValueCountFrequency (%)
/ 35802
54.5%
. 23868
36.4%
: 5967
 
9.1%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 238692
72.1%
Common 92461
 
27.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 35806
15.0%
o 23868
 
10.0%
e 17908
 
7.5%
a 17901
 
7.5%
l 17901
 
7.5%
r 11935
 
5.0%
h 11935
 
5.0%
c 11934
 
5.0%
s 11934
 
5.0%
u 11934
 
5.0%
Other values (10) 65636
27.5%
Common
ValueCountFrequency (%)
/ 35802
38.7%
. 23868
25.8%
: 5967
 
6.5%
2 4260
 
4.6%
1 4176
 
4.5%
3 3230
 
3.5%
0 2681
 
2.9%
9 2397
 
2.6%
4 2208
 
2.4%
5 2190
 
2.4%
Other values (5) 5682
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 331153
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 35806
 
10.8%
/ 35802
 
10.8%
. 23868
 
7.2%
o 23868
 
7.2%
e 17908
 
5.4%
a 17901
 
5.4%
l 17901
 
5.4%
r 11935
 
3.6%
h 11935
 
3.6%
c 11934
 
3.6%
Other values (25) 122295
36.9%

Interactions

2024-01-27T12:46:17.223732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-27T12:46:28.913822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부문수집연도
부문1.0000.623
수집연도0.6231.000
2024-01-27T12:46:29.032248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수집연도부문
수집연도1.0000.235
부문0.2351.000

Missing values

2024-01-27T12:46:17.499711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-27T12:46:17.773377image/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.
2024-01-27T12:46:17.982020image/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

부문수집연도작품명(국문)작품명(영문)작품규격제작년도재료/기법작품해설작가명메인이미지썸네일이미지
0드로잉&판화2023Crutches IIICrutches III76×56cm1981Lithograph<NA>Han, Un-Sunghttp://collections.eseoul.go.kr/common/file/getImage.do?size=700&fileSeq=53883http://collections.eseoul.go.kr/data/art/thumb/53883.jpg
1드로잉&판화2023TrivetTrivet76×56cm1981Lithograph<NA>Han, Un-Sunghttp://collections.eseoul.go.kr/common/file/getImage.do?size=700&fileSeq=53884http://collections.eseoul.go.kr/data/art/thumb/53884.jpg
2드로잉&판화2023The CrutchesThe Crutches76×56cm1982Lithograph<NA>Han, Un-Sunghttp://collections.eseoul.go.kr/common/file/getImage.do?size=700&fileSeq=53885http://collections.eseoul.go.kr/data/art/thumb/53885.jpg
3드로잉&판화2023The Two CrutchesThe Two Crutches56×76cm1982Lithograph<NA>Han, Un-Sunghttp://collections.eseoul.go.kr/common/file/getImage.do?size=700&fileSeq=53886http://collections.eseoul.go.kr/data/art/thumb/53886.jpg
4드로잉&판화2023CrossCross76×56cm1983Lithograph<NA>Han, Un-Sunghttp://collections.eseoul.go.kr/common/file/getImage.do?size=700&fileSeq=53887http://collections.eseoul.go.kr/data/art/thumb/53887.jpg
5드로잉&판화2023Crutches VICrutches VI56×76cm1983Lithograph<NA>Han, Un-Sunghttp://collections.eseoul.go.kr/common/file/getImage.do?size=700&fileSeq=53888http://collections.eseoul.go.kr/data/art/thumb/53888.jpg
6드로잉&판화2023Two Crutches ITwo Crutches I56×76cm1983Lithograph<NA>Han, Un-Sunghttp://collections.eseoul.go.kr/common/file/getImage.do?size=700&fileSeq=53889http://collections.eseoul.go.kr/data/art/thumb/53889.jpg
7드로잉&판화2023A Supporting Wood IA Supporting Wood I76×56cm1984Lithograph<NA>Han, Un-Sunghttp://collections.eseoul.go.kr/common/file/getImage.do?size=700&fileSeq=53890http://collections.eseoul.go.kr/data/art/thumb/53890.jpg
8드로잉&판화2023A Supporting Wood IIA Supporting Wood II76×56cm1984Lithograph<NA>Han, Un-Sunghttp://collections.eseoul.go.kr/common/file/getImage.do?size=700&fileSeq=53891http://collections.eseoul.go.kr/data/art/thumb/53891.jpg
9드로잉&판화2023Supporting WoodsSupporting Woods38×57cm1984Lithograph<NA>Han, Un-Sunghttp://collections.eseoul.go.kr/common/file/getImage.do?size=700&fileSeq=53892http://collections.eseoul.go.kr/data/art/thumb/53892.jpg
부문수집연도작품명(국문)작품명(영문)작품규격제작년도재료/기법작품해설작가명메인이미지썸네일이미지
5957회화1987한강메세지 2<NA>80.3×116.81987Oil on canvas<NA>Koo, Cha Soonghttp://collections.eseoul.go.kr/common/file/getImage.do?size=700&fileSeq=14http://collections.eseoul.go.kr/data/art/thumb/0010.jpg
5958회화1987아름다운 한강 2<NA>89.4×130.31987Oil on canvas<NA>Kim, Myung-Sikhttp://collections.eseoul.go.kr/common/file/getImage.do?size=700&fileSeq=19576http://collections.eseoul.go.kr/data/art/thumb/19576.jpg
5959회화1987아! 나의 한강<NA>53×72.71987Oil on canvas<NA>Choi, Nak Kyunghttp://collections.eseoul.go.kr/common/file/getImage.do?size=700&fileSeq=19574http://collections.eseoul.go.kr/data/art/thumb/19574.jpg
5960회화1987아름다운 한강<NA>53×72.71987Oil on canvas<NA>Lee, Soo Auckhttp://collections.eseoul.go.kr/common/file/getImage.do?size=700&fileSeq=19572http://collections.eseoul.go.kr/data/art/thumb/19572.jpg
5961회화1987축제<NA>161×3911987Oil on canvas<NA>Ha, In-doohttp://collections.eseoul.go.kr/common/file/getImage.do?size=700&fileSeq=19509http://collections.eseoul.go.kr/data/art/thumb/19509.jpg
5962회화1987환영 1<NA>160×1031987Oil on canvas<NA>Lee, Joonhttp://collections.eseoul.go.kr/common/file/getImage.do?size=700&fileSeq=19570http://collections.eseoul.go.kr/data/art/thumb/19570.jpg
5963조각1987가족Family50×94×19.5cm1987<NA><NA>Min, Bok-Jinhttp://collections.eseoul.go.kr/common/file/getImage.do?size=700&fileSeq=19584http://collections.eseoul.go.kr/data/art/thumb/19584.jpg
5964드로잉&판화1987YO-YOYO-YO25×16cm1987Etching<NA>Chun, Kyung-Jahttp://collections.eseoul.go.kr/common/file/getImage.do?size=700&fileSeq=19583http://collections.eseoul.go.kr/data/art/thumb/19583.jpg
5965회화1986신화시대<NA>130.3×1621986Oil on canvas<NA>Kim, Young Joohttp://collections.eseoul.go.kr/common/file/getImage.do?size=700&fileSeq=19566http://collections.eseoul.go.kr/data/art/thumb/19566.jpg
5966한국화1985무속Korean Residents in Japan (4)133×134cm1985Color on paper<NA>Park, Saeng-gwanghttp://collections.eseoul.go.kr/common/file/getImage.do?size=700&fileSeq=19565http://collections.eseoul.go.kr/data/art/thumb/19565.jpg