Overview

Dataset statistics

Number of variables9
Number of observations1707
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory121.8 KiB
Average record size in memory73.1 B

Variable types

Numeric1
Categorical1
Text5
Unsupported2

Dataset

Description20200304전북도립미술관소장품목록전체_1,707점_230번결번
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=203181

Alerts

관리번호 has unique valuesUnique
작품번호 has unique valuesUnique
제작년도 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소장일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 00:49:48.232555
Analysis finished2024-03-14 00:49:49.366489
Duration1.13 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Real number (ℝ)

UNIQUE 

Distinct1707
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean854.86585
Minimum1
Maximum1708
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2024-03-14T09:49:49.433502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile86.3
Q1428.5
median855
Q31281.5
95-th percentile1622.7
Maximum1708
Range1707
Interquartile range (IQR)853

Descriptive statistics

Standard deviation493.1141
Coefficient of variation (CV)0.57683214
Kurtosis-1.1991743
Mean854.86585
Median Absolute Deviation (MAD)427
Skewness-0.0010363182
Sum1459256
Variance243161.51
MonotonicityStrictly increasing
2024-03-14T09:49:49.545811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1149 1
 
0.1%
1147 1
 
0.1%
1146 1
 
0.1%
1145 1
 
0.1%
1144 1
 
0.1%
1143 1
 
0.1%
1142 1
 
0.1%
1141 1
 
0.1%
1140 1
 
0.1%
Other values (1697) 1697
99.4%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1708 1
0.1%
1707 1
0.1%
1706 1
0.1%
1705 1
0.1%
1704 1
0.1%
1703 1
0.1%
1702 1
0.1%
1701 1
0.1%
1700 1
0.1%
1699 1
0.1%

부문
Categorical

Distinct21
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size13.5 KiB
회화
530 
한국화
242 
회  화
212 
사진
180 
조각
134 
Other values (16)
409 

Length

Max length5
Median length2
Mean length2.5254833
Min length2

Unique

Unique6 ?
Unique (%)0.4%

Sample

1st row한국화
2nd row한국화
3rd row한국화
4th row판화
5th row판화

Common Values

ValueCountFrequency (%)
회화 530
31.0%
한국화 242
14.2%
회  화 212
 
12.4%
사진 180
 
10.5%
조각 134
 
7.9%
서예 130
 
7.6%
판화 103
 
6.0%
판  화 78
 
4.6%
공예 48
 
2.8%
드로잉 14
 
0.8%
Other values (11) 36
 
2.1%

Length

2024-03-14T09:49:49.653734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
회화 530
26.2%
화 297
14.7%
한국화 242
12.0%
회 213
10.5%
사진 180
 
8.9%
조각 134
 
6.6%
서예 130
 
6.4%
판화 104
 
5.1%
판 84
 
4.2%
공예 48
 
2.4%
Other values (8) 59
 
2.9%

작품번호
Text

UNIQUE 

Distinct1707
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size13.5 KiB
2024-03-14T09:49:49.972533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.572935
Min length4

Characters and Unicode

Total characters9513
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1707 ?
Unique (%)100.0%

Sample

1st rowK0-1
2nd rowK0-2
3rd rowK0-3
4th rowDP-1
5th rowDP-2
ValueCountFrequency (%)
k0-1 1
 
0.1%
ko-204 1
 
0.1%
pa-423 1
 
0.1%
ko-203 1
 
0.1%
pa-422 1
 
0.1%
pa-421 1
 
0.1%
pa-420 1
 
0.1%
pa-419 1
 
0.1%
ko-202 1
 
0.1%
ko-201 1
 
0.1%
Other values (1697) 1697
99.4%
2024-03-14T09:49:50.428124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1707
17.9%
P 1125
11.8%
A 877
 
9.2%
1 836
 
8.8%
2 521
 
5.5%
3 466
 
4.9%
4 445
 
4.7%
5 423
 
4.4%
6 419
 
4.4%
7 363
 
3.8%
Other values (11) 2331
24.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4395
46.2%
Uppercase Letter 3411
35.9%
Dash Punctuation 1707
 
17.9%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
P 1125
33.0%
A 877
25.7%
C 329
 
9.6%
K 242
 
7.1%
O 239
 
7.0%
D 212
 
6.2%
H 180
 
5.3%
S 144
 
4.2%
R 53
 
1.6%
M 10
 
0.3%
Decimal Number
ValueCountFrequency (%)
1 836
19.0%
2 521
11.9%
3 466
10.6%
4 445
10.1%
5 423
9.6%
6 419
9.5%
7 363
8.3%
9 309
 
7.0%
8 309
 
7.0%
0 304
 
6.9%
Dash Punctuation
ValueCountFrequency (%)
- 1707
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6102
64.1%
Latin 3411
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1707
28.0%
1 836
13.7%
2 521
 
8.5%
3 466
 
7.6%
4 445
 
7.3%
5 423
 
6.9%
6 419
 
6.9%
7 363
 
5.9%
9 309
 
5.1%
8 309
 
5.1%
Latin
ValueCountFrequency (%)
P 1125
33.0%
A 877
25.7%
C 329
 
9.6%
K 242
 
7.1%
O 239
 
7.0%
D 212
 
6.2%
H 180
 
5.3%
S 144
 
4.2%
R 53
 
1.6%
M 10
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9513
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1707
17.9%
P 1125
11.8%
A 877
 
9.2%
1 836
 
8.8%
2 521
 
5.5%
3 466
 
4.9%
4 445
 
4.7%
5 423
 
4.4%
6 419
 
4.4%
7 363
 
3.8%
Other values (11) 2331
24.5%

작가명
Text

Distinct580
Distinct (%)34.0%
Missing0
Missing (%)0.0%
Memory size13.5 KiB
2024-03-14T09:49:50.733065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length3
Mean length3.1282953
Min length2

Characters and Unicode

Total characters5340
Distinct characters338
Distinct categories6 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique371 ?
Unique (%)21.7%

Sample

1st row김범석
2nd row조병철
3rd row박종갑
4th row홍선웅
5th row오경영
ValueCountFrequency (%)
손아유 249
 
14.2%
신철균 100
 
5.7%
윤재우 80
 
4.6%
지용출 66
 
3.8%
김광진 55
 
3.1%
조기풍 33
 
1.9%
임상진 27
 
1.5%
김용봉 21
 
1.2%
황소연 16
 
0.9%
전국광 16
 
0.9%
Other values (603) 1095
62.3%
2024-03-14T09:49:51.159684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
유 284
 
5.3%
김 279
 
5.2%
아 259
 
4.9%
손 252
 
4.7%
이 199
 
3.7%
철 148
 
2.8%
용 142
 
2.7%
신 122
 
2.3%
윤 108
 
2.0%
진 108
 
2.0%
Other values (328) 3439
64.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5201
97.4%
Lowercase Letter 63
 
1.2%
Space Separator 47
 
0.9%
Uppercase Letter 17
 
0.3%
Control 10
 
0.2%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
유 284
 
5.5%
김 279
 
5.4%
아 259
 
5.0%
손 252
 
4.8%
이 199
 
3.8%
철 148
 
2.8%
용 142
 
2.7%
신 122
 
2.3%
윤 108
 
2.1%
진 108
 
2.1%
Other values (295) 3300
63.4%
Lowercase Letter
ValueCountFrequency (%)
e 9
14.3%
n 9
14.3%
i 7
11.1%
a 7
11.1%
o 6
9.5%
c 4
 
6.3%
l 3
 
4.8%
t 3
 
4.8%
s 3
 
4.8%
u 2
 
3.2%
Other values (8) 10
15.9%
Uppercase Letter
ValueCountFrequency (%)
B 4
23.5%
D 3
17.6%
P 2
11.8%
N 1
 
5.9%
G 1
 
5.9%
Z 1
 
5.9%
T 1
 
5.9%
L 1
 
5.9%
S 1
 
5.9%
C 1
 
5.9%
Space Separator
ValueCountFrequency (%)
44
93.6%
  3
 
6.4%
Control
ValueCountFrequency (%)
10
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5148
96.4%
Latin 80
 
1.5%
Common 59
 
1.1%
Han 53
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
유 284
 
5.5%
김 279
 
5.4%
아 259
 
5.0%
손 252
 
4.9%
이 199
 
3.9%
철 148
 
2.9%
용 142
 
2.8%
신 122
 
2.4%
윤 108
 
2.1%
진 108
 
2.1%
Other values (247) 3247
63.1%
Han
ValueCountFrequency (%)
中 3
 
5.7%
村 2
 
3.8%
石 2
 
3.8%
王 2
 
3.8%
妙 1
 
1.9%
仙 1
 
1.9%
忠 1
 
1.9%
杜 1
 
1.9%
義 1
 
1.9%
卓 1
 
1.9%
Other values (38) 38
71.7%
Latin
ValueCountFrequency (%)
e 9
 
11.2%
n 9
 
11.2%
i 7
 
8.8%
a 7
 
8.8%
o 6
 
7.5%
B 4
 
5.0%
c 4
 
5.0%
l 3
 
3.8%
t 3
 
3.8%
s 3
 
3.8%
Other values (19) 25
31.2%
Common
ValueCountFrequency (%)
44
74.6%
10
 
16.9%
  3
 
5.1%
. 2
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5148
96.4%
ASCII 136
 
2.5%
CJK 52
 
1.0%
None 3
 
0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
유 284
 
5.5%
김 279
 
5.4%
아 259
 
5.0%
손 252
 
4.9%
이 199
 
3.9%
철 148
 
2.9%
용 142
 
2.8%
신 122
 
2.4%
윤 108
 
2.1%
진 108
 
2.1%
Other values (247) 3247
63.1%
ASCII
ValueCountFrequency (%)
44
32.4%
10
 
7.4%
e 9
 
6.6%
n 9
 
6.6%
i 7
 
5.1%
a 7
 
5.1%
o 6
 
4.4%
B 4
 
2.9%
c 4
 
2.9%
l 3
 
2.2%
Other values (22) 33
24.3%
CJK
ValueCountFrequency (%)
中 3
 
5.8%
村 2
 
3.8%
石 2
 
3.8%
王 2
 
3.8%
妙 1
 
1.9%
仙 1
 
1.9%
忠 1
 
1.9%
杜 1
 
1.9%
義 1
 
1.9%
卓 1
 
1.9%
Other values (37) 37
71.2%
None
ValueCountFrequency (%)
  3
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
沈 1
100.0%

명제
Text

Distinct1265
Distinct (%)74.1%
Missing0
Missing (%)0.0%
Memory size13.5 KiB
2024-03-14T09:49:51.463510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length24
Mean length6.2413591
Min length1

Characters and Unicode

Total characters10654
Distinct characters817
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1149 ?
Unique (%)67.3%

Sample

1st row모악별곡
2nd row모악-바람
3rd row행려-구이를 바라보다
4th row모악연작 화첩
5th row숨결-어린아이 1
ValueCountFrequency (%)
무제 63
 
2.2%
50
 
1.7%
형태의 47
 
1.6%
소거 47
 
1.6%
제 45
 
1.5%
무 45
 
1.5%
위치 30
 
1.0%
예향색 29
 
1.0%
자립하는 29
 
1.0%
색 29
 
1.0%
Other values (1628) 2499
85.8%
2024-03-14T09:49:51.867179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1226
 
11.5%
- 403
 
3.8%
1 284
 
2.7%
의 271
 
2.5%
0 202
 
1.9%
9 188
 
1.8%
무 149
 
1.4%
2 137
 
1.3%
도 126
 
1.2%
산 124
 
1.2%
Other values (807) 7544
70.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6764
63.5%
Space Separator 1268
 
11.9%
Decimal Number 1232
 
11.6%
Lowercase Letter 484
 
4.5%
Dash Punctuation 404
 
3.8%
Uppercase Letter 202
 
1.9%
Close Punctuation 86
 
0.8%
Open Punctuation 86
 
0.8%
Other Punctuation 72
 
0.7%
Letter Number 44
 
0.4%
Other values (4) 12
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 271
 
4.0%
무 149
 
2.2%
도 126
 
1.9%
산 124
 
1.8%
제 122
 
1.8%
는 107
 
1.6%
자 101
 
1.5%
색 100
 
1.5%
곡 97
 
1.4%
기 96
 
1.4%
Other values (722) 5471
80.9%
Lowercase Letter
ValueCountFrequency (%)
e 61
12.6%
o 52
10.7%
t 42
 
8.7%
a 37
 
7.6%
r 36
 
7.4%
n 32
 
6.6%
s 30
 
6.2%
i 25
 
5.2%
l 23
 
4.8%
c 20
 
4.1%
Other values (13) 126
26.0%
Uppercase Letter
ValueCountFrequency (%)
C 58
28.7%
A 56
27.7%
S 12
 
5.9%
W 9
 
4.5%
T 8
 
4.0%
E 6
 
3.0%
B 6
 
3.0%
F 6
 
3.0%
O 5
 
2.5%
M 5
 
2.5%
Other values (12) 31
15.3%
Decimal Number
ValueCountFrequency (%)
1 284
23.1%
0 202
16.4%
9 188
15.3%
2 137
11.1%
8 89
 
7.2%
6 83
 
6.7%
7 74
 
6.0%
5 70
 
5.7%
4 55
 
4.5%
3 50
 
4.1%
Other Punctuation
ValueCountFrequency (%)
. 31
43.1%
, 19
26.4%
# 7
 
9.7%
! 5
 
6.9%
/ 3
 
4.2%
· 2
 
2.8%
․ 2
 
2.8%
' 2
 
2.8%
… 1
 
1.4%
Letter Number
ValueCountFrequency (%)
Ⅱ 14
31.8%
Ⅰ 13
29.5%
Ⅲ 8
18.2%
Ⅳ 3
 
6.8%
Ⅹ 2
 
4.5%
Ⅵ 2
 
4.5%
Ⅻ 1
 
2.3%
Ⅷ 1
 
2.3%
Math Symbol
ValueCountFrequency (%)
+ 4
50.0%
~ 2
25.0%
> 1
 
12.5%
< 1
 
12.5%
Space Separator
ValueCountFrequency (%)
1226
96.7%
  42
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 403
99.8%
– 1
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 86
100.0%
Open Punctuation
ValueCountFrequency (%)
( 86
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 2
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6431
60.4%
Common 3160
29.7%
Latin 730
 
6.9%
Han 333
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 271
 
4.2%
무 149
 
2.3%
도 126
 
2.0%
산 124
 
1.9%
제 122
 
1.9%
는 107
 
1.7%
자 101
 
1.6%
색 100
 
1.6%
곡 97
 
1.5%
기 96
 
1.5%
Other values (530) 5138
79.9%
Han
ValueCountFrequency (%)
生 25
 
7.5%
命 21
 
6.3%
山 14
 
4.2%
無 9
 
2.7%
空 5
 
1.5%
知 5
 
1.5%
新 4
 
1.2%
下 4
 
1.2%
德 4
 
1.2%
魚 4
 
1.2%
Other values (182) 238
71.5%
Latin
ValueCountFrequency (%)
e 61
 
8.4%
C 58
 
7.9%
A 56
 
7.7%
o 52
 
7.1%
t 42
 
5.8%
a 37
 
5.1%
r 36
 
4.9%
n 32
 
4.4%
s 30
 
4.1%
i 25
 
3.4%
Other values (43) 301
41.2%
Common
ValueCountFrequency (%)
1226
38.8%
- 403
 
12.8%
1 284
 
9.0%
0 202
 
6.4%
9 188
 
5.9%
2 137
 
4.3%
8 89
 
2.8%
) 86
 
2.7%
( 86
 
2.7%
6 83
 
2.6%
Other values (22) 376
 
11.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6431
60.4%
ASCII 3795
35.6%
CJK 328
 
3.1%
None 44
 
0.4%
Number Forms 44
 
0.4%
Punctuation 7
 
0.1%
CJK Compat Ideographs 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1226
32.3%
- 403
 
10.6%
1 284
 
7.5%
0 202
 
5.3%
9 188
 
5.0%
2 137
 
3.6%
8 89
 
2.3%
) 86
 
2.3%
( 86
 
2.3%
6 83
 
2.2%
Other values (60) 1011
26.6%
Hangul
ValueCountFrequency (%)
의 271
 
4.2%
무 149
 
2.3%
도 126
 
2.0%
산 124
 
1.9%
제 122
 
1.9%
는 107
 
1.7%
자 101
 
1.6%
색 100
 
1.6%
곡 97
 
1.5%
기 96
 
1.5%
Other values (530) 5138
79.9%
None
ValueCountFrequency (%)
  42
95.5%
· 2
 
4.5%
CJK
ValueCountFrequency (%)
生 25
 
7.6%
命 21
 
6.4%
山 14
 
4.3%
無 9
 
2.7%
空 5
 
1.5%
知 5
 
1.5%
新 4
 
1.2%
下 4
 
1.2%
德 4
 
1.2%
魚 4
 
1.2%
Other values (177) 233
71.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 14
31.8%
Ⅰ 13
29.5%
Ⅲ 8
18.2%
Ⅳ 3
 
6.8%
Ⅹ 2
 
4.5%
Ⅵ 2
 
4.5%
Ⅻ 1
 
2.3%
Ⅷ 1
 
2.3%
Punctuation
ValueCountFrequency (%)
‘ 2
28.6%
․ 2
28.6%
’ 1
14.3%
– 1
14.3%
… 1
14.3%
CJK Compat Ideographs
ValueCountFrequency (%)
梨 1
20.0%
立 1
20.0%
律 1
20.0%
樂 1
20.0%
理 1
20.0%

제작년도
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size13.5 KiB

규격(㎝)
Text

Distinct1119
Distinct (%)65.6%
Missing0
Missing (%)0.0%
Memory size13.5 KiB
2024-03-14T09:49:52.114116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length26
Mean length6.7996485
Min length2

Characters and Unicode

Total characters11607
Distinct characters35
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique952 ?
Unique (%)55.8%

Sample

1st row280×700
2nd row280×635
3rd row280×700
4th row55×47(×9)
5th row180×136
ValueCountFrequency (%)
20×32 24
 
1.4%
162×130 22
 
1.3%
130×162 20
 
1.2%
227×162 17
 
1.0%
45×53 17
 
1.0%
50×60 17
 
1.0%
29.5x22 15
 
0.9%
22×32 15
 
0.9%
32×22 14
 
0.8%
53×65 14
 
0.8%
Other values (1120) 1545
89.8%
2024-03-14T09:49:52.494573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
× 1884
16.2%
1 1559
13.4%
2 1210
10.4%
5 1131
9.7%
3 1098
9.5%
0 1054
9.1%
6 658
 
5.7%
4 587
 
5.1%
7 565
 
4.9%
9 534
 
4.6%
Other values (25) 1327
11.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8890
76.6%
Math Symbol 1884
 
16.2%
Other Punctuation 417
 
3.6%
Lowercase Letter 155
 
1.3%
Open Punctuation 102
 
0.9%
Close Punctuation 102
 
0.9%
Other Letter 30
 
0.3%
Space Separator 19
 
0.2%
Control 7
 
0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
분 7
23.3%
가 4
13.3%
변 4
13.3%
초 3
10.0%
설 3
10.0%
치 3
10.0%
호 1
 
3.3%
개 1
 
3.3%
시 1
 
3.3%
간 1
 
3.3%
Other values (2) 2
 
6.7%
Decimal Number
ValueCountFrequency (%)
1 1559
17.5%
2 1210
13.6%
5 1131
12.7%
3 1098
12.4%
0 1054
11.9%
6 658
7.4%
4 587
 
6.6%
7 565
 
6.4%
9 534
 
6.0%
8 494
 
5.6%
Lowercase Letter
ValueCountFrequency (%)
x 125
80.6%
c 15
 
9.7%
m 15
 
9.7%
Space Separator
ValueCountFrequency (%)
16
84.2%
　 2
 
10.5%
  1
 
5.3%
Other Punctuation
ValueCountFrequency (%)
. 416
99.8%
, 1
 
0.2%
Math Symbol
ValueCountFrequency (%)
× 1884
100.0%
Open Punctuation
ValueCountFrequency (%)
( 102
100.0%
Close Punctuation
ValueCountFrequency (%)
) 102
100.0%
Control
ValueCountFrequency (%)
7
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11421
98.4%
Latin 156
 
1.3%
Hangul 30
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
× 1884
16.5%
1 1559
13.7%
2 1210
10.6%
5 1131
9.9%
3 1098
9.6%
0 1054
9.2%
6 658
 
5.8%
4 587
 
5.1%
7 565
 
4.9%
9 534
 
4.7%
Other values (9) 1141
10.0%
Hangul
ValueCountFrequency (%)
분 7
23.3%
가 4
13.3%
변 4
13.3%
초 3
10.0%
설 3
10.0%
치 3
10.0%
호 1
 
3.3%
개 1
 
3.3%
시 1
 
3.3%
간 1
 
3.3%
Other values (2) 2
 
6.7%
Latin
ValueCountFrequency (%)
x 125
80.1%
c 15
 
9.6%
m 15
 
9.6%
X 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9690
83.5%
None 1887
 
16.3%
Hangul 30
 
0.3%

Most frequent character per block

None
ValueCountFrequency (%)
× 1884
99.8%
　 2
 
0.1%
  1
 
0.1%
ASCII
ValueCountFrequency (%)
1 1559
16.1%
2 1210
12.5%
5 1131
11.7%
3 1098
11.3%
0 1054
10.9%
6 658
6.8%
4 587
 
6.1%
7 565
 
5.8%
9 534
 
5.5%
8 494
 
5.1%
Other values (10) 800
8.3%
Hangul
ValueCountFrequency (%)
분 7
23.3%
가 4
13.3%
변 4
13.3%
초 3
10.0%
설 3
10.0%
치 3
10.0%
호 1
 
3.3%
개 1
 
3.3%
시 1
 
3.3%
간 1
 
3.3%
Other values (2) 2
 
6.7%

소장일자
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size13.5 KiB

기법 및 재료
Text

Distinct312
Distinct (%)18.3%
Missing0
Missing (%)0.0%
Memory size13.5 KiB
2024-03-14T09:49:52.737573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length31
Mean length6.8207381
Min length1

Characters and Unicode

Total characters11643
Distinct characters298
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique200 ?
Unique (%)11.7%

Sample

1st row한지에 먹, 호분
2nd row광목천에 먹
3rd row장지에 수묵
4th row먹판화
5th row목판화
ValueCountFrequency (%)
종이에 448
 
13.9%
캔버스에 426
 
13.2%
유채 370
 
11.5%
먹 213
 
6.6%
흑백사진 118
 
3.7%
아크릴릭 107
 
3.3%
수묵담채 107
 
3.3%
수채 86
 
2.7%
혼합재료 79
 
2.4%
판화 71
 
2.2%
Other values (311) 1200
37.2%
2024-03-14T09:49:53.102825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1535
 
13.2%
에 1107
 
9.5%
채 649
 
5.6%
스 511
 
4.4%
이 483
 
4.1%
종 459
 
3.9%
버 435
 
3.7%
캔 433
 
3.7%
유 380
 
3.3%
수 306
 
2.6%
Other values (288) 5345
45.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9471
81.3%
Space Separator 1537
 
13.2%
Other Punctuation 298
 
2.6%
Lowercase Letter 282
 
2.4%
Uppercase Letter 31
 
0.3%
Open Punctuation 5
 
< 0.1%
Close Punctuation 5
 
< 0.1%
Control 5
 
< 0.1%
Decimal Number 4
 
< 0.1%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
에 1107
 
11.7%
채 649
 
6.9%
스 511
 
5.4%
이 483
 
5.1%
종 459
 
4.8%
버 435
 
4.6%
캔 433
 
4.6%
유 380
 
4.0%
수 306
 
3.2%
먹 226
 
2.4%
Other values (244) 4482
47.3%
Lowercase Letter
ValueCountFrequency (%)
r 39
13.8%
i 37
13.1%
t 33
11.7%
a 32
11.3%
n 28
9.9%
p 23
8.2%
e 19
6.7%
g 15
 
5.3%
m 12
 
4.3%
l 10
 
3.5%
Other values (9) 34
12.1%
Uppercase Letter
ValueCountFrequency (%)
P 4
12.9%
D 4
12.9%
R 3
9.7%
F 3
9.7%
C 3
9.7%
S 3
9.7%
H 3
9.7%
G 2
6.5%
L 1
 
3.2%
V 1
 
3.2%
Other values (4) 4
12.9%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
4 1
25.0%
8 1
25.0%
Space Separator
ValueCountFrequency (%)
1535
99.9%
  2
 
0.1%
Other Punctuation
ValueCountFrequency (%)
, 298
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Control
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9469
81.3%
Common 1859
 
16.0%
Latin 313
 
2.7%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
에 1107
 
11.7%
채 649
 
6.9%
스 511
 
5.4%
이 483
 
5.1%
종 459
 
4.8%
버 435
 
4.6%
캔 433
 
4.6%
유 380
 
4.0%
수 306
 
3.2%
먹 226
 
2.4%
Other values (242) 4480
47.3%
Latin
ValueCountFrequency (%)
r 39
12.5%
i 37
11.8%
t 33
10.5%
a 32
10.2%
n 28
8.9%
p 23
 
7.3%
e 19
 
6.1%
g 15
 
4.8%
m 12
 
3.8%
l 10
 
3.2%
Other values (23) 65
20.8%
Common
ValueCountFrequency (%)
1535
82.6%
, 298
 
16.0%
( 5
 
0.3%
) 5
 
0.3%
5
 
0.3%
- 3
 
0.2%
+ 2
 
0.1%
1 2
 
0.1%
  2
 
0.1%
4 1
 
0.1%
Han
ValueCountFrequency (%)
畵 1
50.0%
烙 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9469
81.3%
ASCII 2170
 
18.6%
None 2
 
< 0.1%
CJK 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1535
70.7%
, 298
 
13.7%
r 39
 
1.8%
i 37
 
1.7%
t 33
 
1.5%
a 32
 
1.5%
n 28
 
1.3%
p 23
 
1.1%
e 19
 
0.9%
g 15
 
0.7%
Other values (33) 111
 
5.1%
Hangul
ValueCountFrequency (%)
에 1107
 
11.7%
채 649
 
6.9%
스 511
 
5.4%
이 483
 
5.1%
종 459
 
4.8%
버 435
 
4.6%
캔 433
 
4.6%
유 380
 
4.0%
수 306
 
3.2%
먹 226
 
2.4%
Other values (242) 4480
47.3%
None
ValueCountFrequency (%)
  2
100.0%
CJK
ValueCountFrequency (%)
畵 1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
烙 1
100.0%

Interactions

2024-03-14T09:49:48.855752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T09:49:53.191394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호부문
관리번호1.0000.804
부문0.8041.000
2024-03-14T09:49:53.271271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호부문
관리번호1.0000.454
부문0.4541.000

Missing values

2024-03-14T09:49:48.957006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:49:49.305797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

관리번호부문작품번호작가명명제제작년도규격(㎝)소장일자기법 및 재료
01한국화K0-1김범석모악별곡2004280×7002005. 1. 5한지에 먹, 호분
12한국화K0-2조병철모악-바람2004280×6352005. 1. 5광목천에 먹
23한국화K0-3박종갑행려-구이를 바라보다2004280×7002005. 1. 5장지에 수묵
34판화DP-1홍선웅모악연작 화첩200455×47(×9)2005. 1. 5먹판화
45판화DP-2오경영숨결-어린아이 12004180×1362005. 1. 5목판화
56회화PA-1나종희들불199591×1792005. 1. 5캔버스에 유채
67조각SC-1강관욱구원 92-1199238×24×562005. 1. 5오석
78회화PA-2김용봉가을풍경199353×652005. 1. 5캔버스에 유채
89서예CA-1이용모악2004135×1022005. 1. 5종이에 먹
910서예CA-2여태명천지인 0409212004150×2102005. 1. 5장지에 수묵
관리번호부문작품번호작가명명제제작년도규격(㎝)소장일자기법 및 재료
16971699회화PA-735이복수고덕산하(高德山下)Ⅰ201738×45.32019.6.10캔버스에 유채
16981700회화PA-736이복수성하(盛夏)199538×45.32019.6.10캔버스에 유채
16991701회화PA-737이복수승암산설(僧岩山雪)198338×45.32019.6.10캔버스에 유채
17001702회화PA-738이복수담춘(曇春)1980년대38×45.32019.6.10캔버스에 유채
17011703회화PA-739이복수모악산하(母岳山下)198438×45.32019.6.10캔버스에 유채
17021704회화PA-740이복수경기전의 일우(一隅)1990년대38×45.32019.6.10캔버스에 유채
17031705회화PA-741이복수산정(山情)198538×45.32019.6.10캔버스에 유채
17041706회화PA-742이복수산촌초하(山村初夏)1980년대38×45.32019.6.10캔버스에 유채
17051707회화PA-743이복수고덕산하(高德山下)Ⅱ199438×45.32019.6.10캔버스에 유채
17061708회화PA-744이복수고덕산하(高德山下)Ⅲ199538×45.32019.6.10캔버스에 유채