Overview

Dataset statistics

Number of variables6
Number of observations224
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.6 KiB
Average record size in memory48.6 B

Variable types

Text5
Categorical1

Dataset

Description국사편찬위원회 소장 귀중자료(106종 224점)에 대한 목록 정보로 원본은 열람할 수 없으며(국사편찬위원회 소장자료의 관리에 관한 규정 제28조), 국사편찬위원회 전자도서관에서 스캔이미지 또는 마이크로필름으로 열람이 가능함
Author교육부 국사편찬위원회
URLhttps://www.data.go.kr/data/3059203/fileData.do

Alerts

등록번호 has unique valuesUnique
청구기호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 04:02:51.928037
Analysis finished2023-12-12 04:02:52.856833
Duration0.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

등록번호
Text

UNIQUE 

Distinct224
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T13:02:52.988609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters2688
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique224 ?
Unique (%)100.0%

Sample

1st rowRB0000000001
2nd rowRB0000000002
3rd rowRB0000000003
4th rowRB0000000004
5th rowRB0000000005
ValueCountFrequency (%)
rb0000000001 1
 
0.4%
rb0000000002 1
 
0.4%
rb0000000154 1
 
0.4%
rb0000000143 1
 
0.4%
rb0000000144 1
 
0.4%
rb0000000145 1
 
0.4%
rb0000000146 1
 
0.4%
rb0000000147 1
 
0.4%
rb0000000148 1
 
0.4%
rb0000000149 1
 
0.4%
Other values (214) 214
95.5%
2023-12-12T13:02:53.333127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1718
63.9%
R 224
 
8.3%
B 224
 
8.3%
1 153
 
5.7%
2 73
 
2.7%
4 43
 
1.6%
3 43
 
1.6%
5 42
 
1.6%
6 42
 
1.6%
7 42
 
1.6%
Other values (2) 84
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2240
83.3%
Uppercase Letter 448
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1718
76.7%
1 153
 
6.8%
2 73
 
3.3%
4 43
 
1.9%
3 43
 
1.9%
5 42
 
1.9%
6 42
 
1.9%
7 42
 
1.9%
8 42
 
1.9%
9 42
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
R 224
50.0%
B 224
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2240
83.3%
Latin 448
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1718
76.7%
1 153
 
6.8%
2 73
 
3.3%
4 43
 
1.9%
3 43
 
1.9%
5 42
 
1.9%
6 42
 
1.9%
7 42
 
1.9%
8 42
 
1.9%
9 42
 
1.9%
Latin
ValueCountFrequency (%)
R 224
50.0%
B 224
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2688
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1718
63.9%
R 224
 
8.3%
B 224
 
8.3%
1 153
 
5.7%
2 73
 
2.7%
4 43
 
1.6%
3 43
 
1.6%
5 42
 
1.6%
6 42
 
1.6%
7 42
 
1.6%
Other values (2) 84
 
3.1%

청구기호
Text

UNIQUE 

Distinct224
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T13:02:53.740477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.5178571
Min length5

Characters and Unicode

Total characters1460
Distinct characters14
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique224 ?
Unique (%)100.0%

Sample

1st row귀 v.1
2nd row귀 v.2
3rd row귀 v.3
4th row귀 v.4
5th row귀 v.5
ValueCountFrequency (%)
귀 224
50.0%
v.113 1
 
0.2%
v.154 1
 
0.2%
v.143 1
 
0.2%
v.144 1
 
0.2%
v.145 1
 
0.2%
v.146 1
 
0.2%
v.147 1
 
0.2%
v.148 1
 
0.2%
v.149 1
 
0.2%
Other values (215) 215
48.0%
2023-12-12T13:02:54.668277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
귀 224
15.3%
224
15.3%
v 224
15.3%
. 224
15.3%
1 153
10.5%
2 73
 
5.0%
4 43
 
2.9%
3 43
 
2.9%
5 42
 
2.9%
6 42
 
2.9%
Other values (4) 168
11.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 564
38.6%
Other Letter 224
 
15.3%
Space Separator 224
 
15.3%
Lowercase Letter 224
 
15.3%
Other Punctuation 224
 
15.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 153
27.1%
2 73
12.9%
4 43
 
7.6%
3 43
 
7.6%
5 42
 
7.4%
6 42
 
7.4%
7 42
 
7.4%
8 42
 
7.4%
9 42
 
7.4%
0 42
 
7.4%
Other Letter
ValueCountFrequency (%)
귀 224
100.0%
Space Separator
ValueCountFrequency (%)
224
100.0%
Lowercase Letter
ValueCountFrequency (%)
v 224
100.0%
Other Punctuation
ValueCountFrequency (%)
. 224
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1012
69.3%
Hangul 224
 
15.3%
Latin 224
 
15.3%

Most frequent character per script

Common
ValueCountFrequency (%)
224
22.1%
. 224
22.1%
1 153
15.1%
2 73
 
7.2%
4 43
 
4.2%
3 43
 
4.2%
5 42
 
4.2%
6 42
 
4.2%
7 42
 
4.2%
8 42
 
4.2%
Other values (2) 84
 
8.3%
Hangul
ValueCountFrequency (%)
귀 224
100.0%
Latin
ValueCountFrequency (%)
v 224
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1236
84.7%
Hangul 224
 
15.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
귀 224
100.0%
ASCII
ValueCountFrequency (%)
224
18.1%
v 224
18.1%
. 224
18.1%
1 153
12.4%
2 73
 
5.9%
4 43
 
3.5%
3 43
 
3.5%
5 42
 
3.4%
6 42
 
3.4%
7 42
 
3.4%
Other values (3) 126
10.2%

서명/저자사항
Text

Distinct110
Distinct (%)49.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T13:02:54.949000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length76
Median length44
Mean length17.589286
Min length1

Characters and Unicode

Total characters3940
Distinct characters555
Distinct categories10 ?
Distinct scripts6 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique93 ?
Unique (%)41.5%

Sample

1st row香爐之氣卷物
2nd row和歌 :漢詩
3rd row柔氣目錄 一卷
4th row和歌
5th row明美堂草彙 /李建昌 著
ValueCountFrequency (%)
1-22 44
 
6.2%
著 27
 
3.8%
新增東國輿地勝覽 24
 
3.4%
李荇 24
 
3.4%
等受命編 24
 
3.4%
1-24 24
 
3.4%
大東輿地圖 22
 
3.1%
金正浩校刊 22
 
3.1%
對馬州奉行章 22
 
3.1%
拓本 16
 
2.3%
Other values (240) 458
64.8%
2023-12-12T13:02:55.462455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
489
 
12.4%
1 178
 
4.5%
. 150
 
3.8%
2 137
 
3.5%
/ 127
 
3.2%
- 123
 
3.1%
東 63
 
1.6%
輿 58
 
1.5%
圖 55
 
1.4%
李 53
 
1.3%
Other values (545) 2507
63.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2514
63.8%
Space Separator 489
 
12.4%
Decimal Number 438
 
11.1%
Other Punctuation 288
 
7.3%
Dash Punctuation 123
 
3.1%
Other Symbol 29
 
0.7%
Open Punctuation 25
 
0.6%
Close Punctuation 25
 
0.6%
Lowercase Letter 7
 
0.2%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
東 63
 
2.5%
輿 58
 
2.3%
圖 55
 
2.2%
李 53
 
2.1%
地 50
 
2.0%
正 40
 
1.6%
國 38
 
1.5%
金 38
 
1.5%
浩 34
 
1.4%
年 33
 
1.3%
Other values (517) 2052
81.6%
Decimal Number
ValueCountFrequency (%)
1 178
40.6%
2 137
31.3%
6 31
 
7.1%
4 28
 
6.4%
0 15
 
3.4%
5 14
 
3.2%
9 14
 
3.2%
3 14
 
3.2%
7 4
 
0.9%
8 3
 
0.7%
Lowercase Letter
ValueCountFrequency (%)
n 2
28.6%
e 2
28.6%
o 1
14.3%
l 1
14.3%
f 1
14.3%
Other Punctuation
ValueCountFrequency (%)
. 150
52.1%
/ 127
44.1%
, 10
 
3.5%
: 1
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 21
84.0%
[ 4
 
16.0%
Close Punctuation
ValueCountFrequency (%)
) 21
84.0%
] 4
 
16.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
W 1
50.0%
Space Separator
ValueCountFrequency (%)
489
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 123
100.0%
Other Symbol
ValueCountFrequency (%)
■ 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 2368
60.1%
Common 1417
36.0%
Hangul 126
 
3.2%
Hiragana 14
 
0.4%
Latin 9
 
0.2%
Katakana 6
 
0.2%

Most frequent character per script

Han
ValueCountFrequency (%)
東 63
 
2.7%
輿 58
 
2.4%
圖 55
 
2.3%
李 53
 
2.2%
地 50
 
2.1%
正 40
 
1.7%
國 38
 
1.6%
金 38
 
1.6%
浩 34
 
1.4%
年 33
 
1.4%
Other values (442) 1906
80.5%
Hangul
ValueCountFrequency (%)
의 7
 
5.6%
사 7
 
5.6%
시 6
 
4.8%
통 6
 
4.8%
이 5
 
4.0%
신 5
 
4.0%
년 5
 
4.0%
축 4
 
3.2%
김 3
 
2.4%
츙 3
 
2.4%
Other values (58) 75
59.5%
Common
ValueCountFrequency (%)
489
34.5%
1 178
 
12.6%
. 150
 
10.6%
2 137
 
9.7%
/ 127
 
9.0%
- 123
 
8.7%
6 31
 
2.2%
■ 29
 
2.0%
4 28
 
2.0%
( 21
 
1.5%
Other values (11) 104
 
7.3%
Latin
ValueCountFrequency (%)
n 2
22.2%
e 2
22.2%
A 1
11.1%
W 1
11.1%
o 1
11.1%
l 1
11.1%
f 1
11.1%
Katakana
ValueCountFrequency (%)
ヘ 3
50.0%
ト 1
 
16.7%
ニ 1
 
16.7%
リ 1
 
16.7%
Hiragana
ValueCountFrequency (%)
よ 7
50.0%
り 6
42.9%
へ 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
CJK 2268
57.6%
ASCII 1397
35.5%
Hangul 126
 
3.2%
CJK Compat Ideographs 100
 
2.5%
Geometric Shapes 29
 
0.7%
Hiragana 14
 
0.4%
Katakana 6
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
489
35.0%
1 178
 
12.7%
. 150
 
10.7%
2 137
 
9.8%
/ 127
 
9.1%
- 123
 
8.8%
6 31
 
2.2%
4 28
 
2.0%
( 21
 
1.5%
) 21
 
1.5%
Other values (17) 92
 
6.6%
CJK
ValueCountFrequency (%)
東 63
 
2.8%
輿 58
 
2.6%
圖 55
 
2.4%
地 50
 
2.2%
正 40
 
1.8%
國 38
 
1.7%
金 38
 
1.7%
浩 34
 
1.5%
年 33
 
1.5%
行 32
 
1.4%
Other values (427) 1827
80.6%
CJK Compat Ideographs
ValueCountFrequency (%)
李 53
53.0%
拓 18
 
18.0%
類 10
 
10.0%
狀 5
 
5.0%
錄 2
 
2.0%
麟 2
 
2.0%
利 2
 
2.0%
留 1
 
1.0%
參 1
 
1.0%
寧 1
 
1.0%
Other values (5) 5
 
5.0%
Geometric Shapes
ValueCountFrequency (%)
■ 29
100.0%
Hangul
ValueCountFrequency (%)
의 7
 
5.6%
사 7
 
5.6%
시 6
 
4.8%
통 6
 
4.8%
이 5
 
4.0%
신 5
 
4.0%
년 5
 
4.0%
축 4
 
3.2%
김 3
 
2.4%
츙 3
 
2.4%
Other values (58) 75
59.5%
Hiragana
ValueCountFrequency (%)
よ 7
50.0%
り 6
42.9%
へ 1
 
7.1%
Katakana
ValueCountFrequency (%)
ヘ 3
50.0%
ト 1
 
16.7%
ニ 1
 
16.7%
リ 1
 
16.7%

출판사항
Text

Distinct74
Distinct (%)33.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T13:02:55.656701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length36
Mean length21.901786
Min length4

Characters and Unicode

Total characters4906
Distinct characters120
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)21.0%

Sample

1st row寬永12[1635]
2nd row寬永3[1626]
3rd row寬永8[1631]
4th row[간사년미상]
5th row[간행지불명]: 徐勳, 丁酉(1897).
ValueCountFrequency (%)
간사지미상 75
 
13.3%
간사자미상 74
 
13.1%
간사지불명 25
 
4.4%
24
 
4.2%
간사자불명 24
 
4.2%
中宗25(1530 24
 
4.2%
제작지미상 22
 
3.9%
제작자미상 22
 
3.9%
제작년미상 22
 
3.9%
哲宗 22
 
3.9%
Other values (89) 231
40.9%
2023-12-12T13:02:55.997758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
[ 520
 
10.6%
] 520
 
10.6%
341
 
7.0%
상 308
 
6.3%
미 308
 
6.3%
간 280
 
5.7%
1 264
 
5.4%
사 261
 
5.3%
, 166
 
3.4%
: 164
 
3.3%
Other values (110) 1774
36.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2321
47.3%
Decimal Number 801
 
16.3%
Open Punctuation 546
 
11.1%
Close Punctuation 546
 
11.1%
Space Separator 341
 
7.0%
Other Punctuation 340
 
6.9%
Dash Punctuation 11
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 308
13.3%
미 308
13.3%
간 280
12.1%
사 261
11.2%
지 158
 
6.8%
자 156
 
6.7%
宗 74
 
3.2%
제 69
 
3.0%
작 69
 
3.0%
명 69
 
3.0%
Other values (91) 569
24.5%
Decimal Number
ValueCountFrequency (%)
1 264
33.0%
6 99
 
12.4%
5 89
 
11.1%
2 86
 
10.7%
8 69
 
8.6%
3 54
 
6.7%
0 45
 
5.6%
4 38
 
4.7%
7 30
 
3.7%
9 27
 
3.4%
Other Punctuation
ValueCountFrequency (%)
, 166
48.8%
: 164
48.2%
. 10
 
2.9%
Open Punctuation
ValueCountFrequency (%)
[ 520
95.2%
( 26
 
4.8%
Close Punctuation
ValueCountFrequency (%)
] 520
95.2%
) 26
 
4.8%
Space Separator
ValueCountFrequency (%)
341
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2585
52.7%
Hangul 1886
38.4%
Han 435
 
8.9%

Most frequent character per script

Han
ValueCountFrequency (%)
宗 74
17.0%
年 49
 
11.3%
哲 35
 
8.0%
中 26
 
6.0%
祖 15
 
3.4%
天 14
 
3.2%
永 14
 
3.2%
君 14
 
3.2%
海 12
 
2.8%
光 12
 
2.8%
Other values (67) 170
39.1%
Hangul
ValueCountFrequency (%)
상 308
16.3%
미 308
16.3%
간 280
14.8%
사 261
13.8%
지 158
8.4%
자 156
8.3%
제 69
 
3.7%
작 69
 
3.7%
명 69
 
3.7%
불 69
 
3.7%
Other values (14) 139
7.4%
Common
ValueCountFrequency (%)
[ 520
20.1%
] 520
20.1%
341
13.2%
1 264
10.2%
, 166
 
6.4%
: 164
 
6.3%
6 99
 
3.8%
5 89
 
3.4%
2 86
 
3.3%
8 69
 
2.7%
Other values (9) 267
10.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2585
52.7%
Hangul 1886
38.4%
CJK 433
 
8.8%
CJK Compat Ideographs 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
[ 520
20.1%
] 520
20.1%
341
13.2%
1 264
10.2%
, 166
 
6.4%
: 164
 
6.3%
6 99
 
3.8%
5 89
 
3.4%
2 86
 
3.3%
8 69
 
2.7%
Other values (9) 267
10.3%
Hangul
ValueCountFrequency (%)
상 308
16.3%
미 308
16.3%
간 280
14.8%
사 261
13.8%
지 158
8.4%
자 156
8.3%
제 69
 
3.7%
작 69
 
3.7%
명 69
 
3.7%
불 69
 
3.7%
Other values (14) 139
7.4%
CJK
ValueCountFrequency (%)
宗 74
17.1%
年 49
 
11.3%
哲 35
 
8.1%
中 26
 
6.0%
祖 15
 
3.5%
天 14
 
3.2%
永 14
 
3.2%
君 14
 
3.2%
海 12
 
2.8%
光 12
 
2.8%
Other values (65) 168
38.8%
CJK Compat Ideographs
ValueCountFrequency (%)
留 1
50.0%
曆 1
50.0%

형태사항
Text

Distinct94
Distinct (%)42.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T13:02:56.264176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length126
Median length75
Mean length36.325893
Min length2

Characters and Unicode

Total characters8137
Distinct characters119
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique75 ?
Unique (%)33.5%

Sample

1st row1張 ; 18.5x222 cm.
2nd row1張 ; 18.5x495 cm.
3rd row1張 ;25×275 cm.
4th row1張 ;26.5×175 cm.
5th row1冊: 10行23字; 30×19.4cm.
ValueCountFrequency (%)
cm 164
 
12.6%
55
 
4.2%
半郭 46
 
3.5%
1張 45
 
3.5%
有界 44
 
3.4%
上下內向花紋魚尾 41
 
3.2%
四周雙邊 40
 
3.1%
地圖 37
 
2.8%
註雙行 31
 
2.4%
55卷 24
 
1.8%
Other values (227) 773
59.5%
2023-12-12T13:02:56.845590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1099
 
13.5%
. 664
 
8.2%
2 525
 
6.5%
1 506
 
6.2%
, 399
 
4.9%
m 380
 
4.7%
c 373
 
4.6%
5 367
 
4.5%
8 273
 
3.4%
x 254
 
3.1%
Other values (109) 3297
40.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2685
33.0%
Other Letter 1739
21.4%
Other Punctuation 1304
16.0%
Space Separator 1099
13.5%
Lowercase Letter 1007
 
12.4%
Math Symbol 97
 
1.2%
Close Punctuation 83
 
1.0%
Open Punctuation 83
 
1.0%
Uppercase Letter 28
 
0.3%
Dash Punctuation 9
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
行 99
 
5.7%
冊 92
 
5.3%
雙 72
 
4.1%
張 70
 
4.0%
字 68
 
3.9%
郭 47
 
2.7%
半 47
 
2.7%
圖 46
 
2.6%
界 46
 
2.6%
邊 46
 
2.6%
Other values (85) 1106
63.6%
Decimal Number
ValueCountFrequency (%)
2 525
19.6%
1 506
18.8%
5 367
13.7%
8 273
10.2%
3 236
8.8%
6 208
 
7.7%
7 151
 
5.6%
0 149
 
5.5%
4 138
 
5.1%
9 132
 
4.9%
Other Punctuation
ValueCountFrequency (%)
. 664
50.9%
, 399
30.6%
; 157
 
12.0%
: 84
 
6.4%
Lowercase Letter
ValueCountFrequency (%)
m 380
37.7%
c 373
37.0%
x 254
25.2%
Space Separator
ValueCountFrequency (%)
1099
100.0%
Math Symbol
ValueCountFrequency (%)
× 97
100.0%
Close Punctuation
ValueCountFrequency (%)
) 83
100.0%
Open Punctuation
ValueCountFrequency (%)
( 83
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 28
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Other Symbol
ValueCountFrequency (%)
㎝ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5363
65.9%
Han 1548
 
19.0%
Latin 1035
 
12.7%
Hangul 191
 
2.3%

Most frequent character per script

Han
ValueCountFrequency (%)
行 99
 
6.4%
冊 92
 
5.9%
雙 72
 
4.7%
張 70
 
4.5%
字 68
 
4.4%
郭 47
 
3.0%
半 47
 
3.0%
圖 46
 
3.0%
界 46
 
3.0%
邊 46
 
3.0%
Other values (42) 915
59.1%
Hangul
ValueCountFrequency (%)
탁 27
14.1%
족 27
14.1%
본 27
14.1%
자 24
12.6%
도 13
 
6.8%
면 8
 
4.2%
록 6
 
3.1%
지 6
 
3.1%
부 6
 
3.1%
이 4
 
2.1%
Other values (33) 43
22.5%
Common
ValueCountFrequency (%)
1099
20.5%
. 664
12.4%
2 525
9.8%
1 506
9.4%
, 399
 
7.4%
5 367
 
6.8%
8 273
 
5.1%
3 236
 
4.4%
6 208
 
3.9%
; 157
 
2.9%
Other values (10) 929
17.3%
Latin
ValueCountFrequency (%)
m 380
36.7%
c 373
36.0%
x 254
24.5%
X 28
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6298
77.4%
CJK 1500
 
18.4%
Hangul 191
 
2.3%
None 97
 
1.2%
CJK Compat Ideographs 48
 
0.6%
CJK Compat 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1099
17.4%
. 664
10.5%
2 525
 
8.3%
1 506
 
8.0%
, 399
 
6.3%
m 380
 
6.0%
c 373
 
5.9%
5 367
 
5.8%
8 273
 
4.3%
x 254
 
4.0%
Other values (12) 1458
23.2%
CJK
ValueCountFrequency (%)
行 99
 
6.6%
冊 92
 
6.1%
雙 72
 
4.8%
張 70
 
4.7%
字 68
 
4.5%
郭 47
 
3.1%
半 47
 
3.1%
圖 46
 
3.1%
界 46
 
3.1%
邊 46
 
3.1%
Other values (40) 867
57.8%
None
ValueCountFrequency (%)
× 97
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
零 45
93.8%
不 3
 
6.2%
Hangul
ValueCountFrequency (%)
탁 27
14.1%
족 27
14.1%
본 27
14.1%
자 24
12.6%
도 13
 
6.8%
면 8
 
4.2%
록 6
 
3.1%
지 6
 
3.1%
부 6
 
3.1%
이 4
 
2.1%
Other values (33) 43
22.5%
CJK Compat
ValueCountFrequency (%)
㎝ 3
100.0%

판사항
Categorical

Distinct18
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
105 
木版本
64 
筆寫本
14 
筆寫本(旋風裝)
12 
寫本.
 
9
Other values (13)
20 

Length

Max length14
Median length11
Mean length3.8392857
Min length2

Unique

Unique9 ?
Unique (%)4.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 105
46.9%
木版本 64
28.6%
筆寫本 14
 
6.2%
筆寫本(旋風裝) 12
 
5.4%
寫本. 9
 
4.0%
寫本 5
 
2.2%
한글筆寫本 2
 
0.9%
影印版 2
 
0.9%
拓本 2
 
0.9%
功臣都監字版(訓鍊都監字本) 1
 
0.4%
Other values (8) 8
 
3.6%

Length

2023-12-12T13:02:57.012362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 105
46.9%
木版本 64
28.6%
筆寫本 15
 
6.7%
寫本 14
 
6.2%
筆寫本(旋風裝 12
 
5.4%
한글筆寫本 2
 
0.9%
影印版 2
 
0.9%
拓本 2
 
0.9%
功臣都監字版(訓鍊都監字本 1
 
0.4%
戊申字版 1
 
0.4%
Other values (6) 6
 
2.7%

Correlations

2023-12-12T13:02:57.105594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
출판사항형태사항판사항
출판사항1.0000.9991.000
형태사항0.9991.0001.000
판사항1.0001.0001.000

Missing values

2023-12-12T13:02:52.705805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:02:52.812917image/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

등록번호청구기호서명/저자사항출판사항형태사항판사항
0RB0000000001귀 v.1香爐之氣卷物寬永12[1635]1張 ; 18.5x222 cm.<NA>
1RB0000000002귀 v.2和歌 :漢詩寬永3[1626]1張 ; 18.5x495 cm.<NA>
2RB0000000003귀 v.3柔氣目錄 一卷寬永8[1631]1張 ;25×275 cm.<NA>
3RB0000000004귀 v.4和歌[간사년미상]1張 ;26.5×175 cm.<NA>
4RB0000000005귀 v.5明美堂草彙 /李建昌 著[간행지불명]: 徐勳, 丁酉(1897).1冊: 10行23字; 30×19.4cm.筆寫本
5RB0000000006귀 v.6子年信使來朝之書付[간사년미상]1張 ;31.5×652 cm.<NA>
6RB0000000007귀 v.71811년 통신부사(通信副使) 이면구(李勉求)의 한시 족자[간사지미상]: [李勉求], [1811년]1張 ;37×121cm.<NA>
7RB0000000008귀 v.81637년 통신부사(通信副使) 김세렴(金世濂)의 시축(詩軸)寬永13[1636]1張 ;45×998.3cm.<NA>
8RB0000000009귀 v.9從五位下 平朝臣義質 右可從四位下/ 對馬藩主 義質文化9[1812]1張;筆寫163×26.6cm<NA>
9RB0000000010귀 v.10宗義成樣御詠奇短尺 御掛物[간사년미상]1張<NA>
등록번호청구기호서명/저자사항출판사항형태사항판사항
214RB0000000215귀 v.215學務衙門 之印[제작지미상]:[제작자미상],[제작년미상]1점 ;인장 7.3x6.8 cm.(함 11x11 cm.)<NA>
215RB0000000216귀 v.216李承晩 彫刻頭像 /Anne Wolfe 제작19441점(석고): 두상 23x33x25 cm, 나무받침대 17.5x10x17 cm, 전체 23x43x25 cm.<NA>
216RB0000000217귀 v.217올리버 박사에게 준 이승만 대통령 친필 휘호/이승만[연대미상]27x30.8 cm.<NA>
217RB0000000218귀 v.218明美堂初稿. 1-9 /李建昌 著[간행지불명]: [간행자불명], [高宗年間].9冊(零本): 行字數不定; 21.3x15.4cm, 29.8x18.5cm, 25x16.3cm, 28.5x17cm, 26.5x17.3cm, 26.7x16.2cm, 28.7x18.8cm, 27.8x18cm,28.3x18.8cm.寫本.
218RB0000000219귀 v.219明美堂初稿. 1-9 /李建昌 著[간행지불명]: [간행자불명], [高宗年間].9冊(零本): 行字數不定; 21.3x15.4cm, 29.8x18.5cm, 25x16.3cm, 28.5x17cm, 26.5x17.3cm, 26.7x16.2cm, 28.7x18.8cm, 27.8x18cm,28.3x18.8cm.寫本.
219RB0000000220귀 v.220明美堂初稿. 1-9 /李建昌 著[간행지불명]: [간행자불명], [高宗年間].9冊(零本): 行字數不定; 21.3x15.4cm, 29.8x18.5cm, 25x16.3cm, 28.5x17cm, 26.5x17.3cm, 26.7x16.2cm, 28.7x18.8cm, 27.8x18cm,28.3x18.8cm.寫本.
220RB0000000221귀 v.221明美堂初稿. 1-9 /李建昌 著[간행지불명]: [간행자불명], [高宗年間].9冊(零本): 行字數不定; 21.3x15.4cm, 29.8x18.5cm, 25x16.3cm, 28.5x17cm, 26.5x17.3cm, 26.7x16.2cm, 28.7x18.8cm, 27.8x18cm,28.3x18.8cm.寫本.
221RB0000000222귀 v.222明美堂初稿. 1-9 /李建昌 著[간행지불명]: [간행자불명], [高宗年間].9冊(零本): 行字數不定; 21.3x15.4cm, 29.8x18.5cm, 25x16.3cm, 28.5x17cm, 26.5x17.3cm, 26.7x16.2cm, 28.7x18.8cm, 27.8x18cm,28.3x18.8cm.寫本.
222RB0000000223귀 v.223明美堂初稿. 1-9 /李建昌 著[간행지불명]: [간행자불명], [高宗年間].9冊(零本): 行字數不定; 21.3x15.4cm, 29.8x18.5cm, 25x16.3cm, 28.5x17cm, 26.5x17.3cm, 26.7x16.2cm, 28.7x18.8cm, 27.8x18cm,28.3x18.8cm.寫本.
223RB0000000224귀 v.224明美堂初稿. 1-9 /李建昌 著[간행지불명]: [간행자불명], [高宗年間].9冊(零本): 行字數不定; 21.3x15.4cm, 29.8x18.5cm, 25x16.3cm, 28.5x17cm, 26.5x17.3cm, 26.7x16.2cm, 28.7x18.8cm, 27.8x18cm,28.3x18.8cm.寫本.