Overview

Dataset statistics

Number of variables3
Number of observations10000
Missing cells113
Missing cells (%)0.4%
Duplicate rows433
Duplicate rows (%)4.3%
Total size in memory312.5 KiB
Average record size in memory32.0 B

Variable types

Text3

Dataset

Description문경시 문희도서관이 소장하고 있는 도서의 서지정보에 대한 데이터로 도서의 서명, 저자, 출판사 등의 항목을 제공합니다.
Author경상북도 문경시
URLhttps://www.data.go.kr/data/15052140/fileData.do

Alerts

Dataset has 433 (4.3%) duplicate rowsDuplicates
저자 has 103 (1.0%) missing valuesMissing

Reproduction

Analysis started2024-04-29 22:32:30.678710
Analysis finished2024-04-29 22:32:32.863697
Duration2.18 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

서명
Text

Distinct9165
Distinct (%)91.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T07:32:33.129042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length123
Median length87
Mean length15.1692
Min length1

Characters and Unicode

Total characters151692
Distinct characters1801
Distinct categories15 ?
Distinct scripts5 ?
Distinct blocks12 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8637 ?
Unique (%)86.4%

Sample

1st row비밀의 숲 테라비시아
2nd row(어린이들이 꼭 실천해야 할)환경 사랑 이야기
3rd row애쓰다 지친 나를 위해
4th row꽃을 잃고 나는 쓴다
5th row늑대 학교
ValueCountFrequency (%)
이야기 346
 
1.0%
장편소설 157
 
0.4%
우리 140
 
0.4%
내 136
 
0.4%
위한 123
 
0.3%
나는 108
 
0.3%
세계 96
 
0.3%
역사 93
 
0.3%
88
 
0.2%
the 72
 
0.2%
Other values (18451) 34454
96.2%
2024-04-30T07:32:33.766222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
26893
 
17.7%
의 2984
 
2.0%
이 2954
 
1.9%
는 2158
 
1.4%
: 1930
 
1.3%
기 1853
 
1.2%
사 1611
 
1.1%
) 1571
 
1.0%
( 1570
 
1.0%
리 1508
 
1.0%
Other values (1791) 106660
70.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 103575
68.3%
Space Separator 26893
 
17.7%
Lowercase Letter 9993
 
6.6%
Other Punctuation 3599
 
2.4%
Decimal Number 2017
 
1.3%
Uppercase Letter 1783
 
1.2%
Close Punctuation 1590
 
1.0%
Open Punctuation 1589
 
1.0%
Math Symbol 579
 
0.4%
Dash Punctuation 59
 
< 0.1%
Other values (5) 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 2984
 
2.9%
이 2954
 
2.9%
는 2158
 
2.1%
기 1853
 
1.8%
사 1611
 
1.6%
리 1508
 
1.5%
가 1439
 
1.4%
아 1395
 
1.3%
한 1385
 
1.3%
지 1273
 
1.2%
Other values (1683) 85015
82.1%
Lowercase Letter
ValueCountFrequency (%)
e 1124
11.2%
i 874
 
8.7%
o 868
 
8.7%
a 850
 
8.5%
n 799
 
8.0%
r 708
 
7.1%
t 689
 
6.9%
s 620
 
6.2%
l 493
 
4.9%
c 420
 
4.2%
Other values (16) 2548
25.5%
Uppercase Letter
ValueCountFrequency (%)
S 163
 
9.1%
T 153
 
8.6%
C 133
 
7.5%
E 125
 
7.0%
A 113
 
6.3%
P 112
 
6.3%
B 90
 
5.0%
I 84
 
4.7%
R 84
 
4.7%
M 84
 
4.7%
Other values (16) 642
36.0%
Other Punctuation
ValueCountFrequency (%)
: 1930
53.6%
, 639
 
17.8%
! 330
 
9.2%
? 233
 
6.5%
. 151
 
4.2%
' 93
 
2.6%
· 92
 
2.6%
& 39
 
1.1%
/ 30
 
0.8%
% 13
 
0.4%
Other values (11) 49
 
1.4%
Decimal Number
ValueCountFrequency (%)
0 530
26.3%
1 464
23.0%
2 299
14.8%
3 172
 
8.5%
5 156
 
7.7%
9 93
 
4.6%
4 92
 
4.6%
6 87
 
4.3%
7 68
 
3.4%
8 56
 
2.8%
Math Symbol
ValueCountFrequency (%)
= 536
92.6%
+ 17
 
2.9%
~ 13
 
2.2%
< 4
 
0.7%
> 4
 
0.7%
| 3
 
0.5%
∼ 2
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 1571
98.8%
] 16
 
1.0%
』 2
 
0.1%
》 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 1570
98.8%
[ 16
 
1.0%
『 2
 
0.1%
《 1
 
0.1%
Other Symbol
ValueCountFrequency (%)
★ 2
66.7%
□ 1
33.3%
Letter Number
ValueCountFrequency (%)
Ⅰ 2
66.7%
Ⅱ 1
33.3%
Modifier Symbol
ValueCountFrequency (%)
` 2
66.7%
¨ 1
33.3%
Space Separator
ValueCountFrequency (%)
26893
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 59
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 3
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 102085
67.3%
Common 36338
 
24.0%
Latin 11779
 
7.8%
Han 1486
 
1.0%
Hiragana 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 2984
 
2.9%
이 2954
 
2.9%
는 2158
 
2.1%
기 1853
 
1.8%
사 1611
 
1.6%
리 1508
 
1.5%
가 1439
 
1.4%
아 1395
 
1.4%
한 1385
 
1.4%
지 1273
 
1.2%
Other values (1225) 83525
81.8%
Han
ValueCountFrequency (%)
國 41
 
2.8%
大 27
 
1.8%
說 26
 
1.7%
法 24
 
1.6%
學 23
 
1.5%
三 22
 
1.5%
史 22
 
1.5%
小 20
 
1.3%
志 19
 
1.3%
韓 17
 
1.1%
Other values (444) 1245
83.8%
Common
ValueCountFrequency (%)
26893
74.0%
: 1930
 
5.3%
) 1571
 
4.3%
( 1570
 
4.3%
, 639
 
1.8%
= 536
 
1.5%
0 530
 
1.5%
1 464
 
1.3%
! 330
 
0.9%
2 299
 
0.8%
Other values (44) 1576
 
4.3%
Latin
ValueCountFrequency (%)
e 1124
 
9.5%
i 874
 
7.4%
o 868
 
7.4%
a 850
 
7.2%
n 799
 
6.8%
r 708
 
6.0%
t 689
 
5.8%
s 620
 
5.3%
l 493
 
4.2%
c 420
 
3.6%
Other values (44) 4334
36.8%
Hiragana
ValueCountFrequency (%)
る 1
25.0%
す 1
25.0%
に 1
25.0%
の 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 102068
67.3%
ASCII 47982
31.6%
CJK 1445
 
1.0%
None 118
 
0.1%
CJK Compat Ideographs 41
 
< 0.1%
Compat Jamo 17
 
< 0.1%
Punctuation 9
 
< 0.1%
Hiragana 4
 
< 0.1%
Number Forms 3
 
< 0.1%
Misc Symbols 2
 
< 0.1%
Other values (2) 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
26893
56.0%
: 1930
 
4.0%
) 1571
 
3.3%
( 1570
 
3.3%
e 1124
 
2.3%
i 874
 
1.8%
o 868
 
1.8%
a 850
 
1.8%
n 799
 
1.7%
r 708
 
1.5%
Other values (79) 10795
22.5%
Hangul
ValueCountFrequency (%)
의 2984
 
2.9%
이 2954
 
2.9%
는 2158
 
2.1%
기 1853
 
1.8%
사 1611
 
1.6%
리 1508
 
1.5%
가 1439
 
1.4%
아 1395
 
1.4%
한 1385
 
1.4%
지 1273
 
1.2%
Other values (1219) 83508
81.8%
None
ValueCountFrequency (%)
· 92
78.0%
＆ 9
 
7.6%
！ 5
 
4.2%
？ 3
 
2.5%
』 2
 
1.7%
『 2
 
1.7%
％ 1
 
0.8%
¨ 1
 
0.8%
》 1
 
0.8%
《 1
 
0.8%
CJK
ValueCountFrequency (%)
國 41
 
2.8%
大 27
 
1.9%
說 26
 
1.8%
法 24
 
1.7%
學 23
 
1.6%
三 22
 
1.5%
史 22
 
1.5%
小 20
 
1.4%
志 19
 
1.3%
韓 17
 
1.2%
Other values (426) 1204
83.3%
Compat Jamo
ValueCountFrequency (%)
ㆍ 5
29.4%
ㄷ 3
17.6%
ㄴ 3
17.6%
ㄱ 3
17.6%
ㅅ 2
 
11.8%
ㅎ 1
 
5.9%
CJK Compat Ideographs
ValueCountFrequency (%)
六 5
12.2%
歷 5
12.2%
理 5
12.2%
劉 4
9.8%
列 3
 
7.3%
茶 3
 
7.3%
李 2
 
4.9%
老 2
 
4.9%
蘭 2
 
4.9%
金 2
 
4.9%
Other values (8) 8
19.5%
Punctuation
ValueCountFrequency (%)
’ 3
33.3%
‘ 3
33.3%
… 3
33.3%
Misc Symbols
ValueCountFrequency (%)
★ 2
100.0%
Math Operators
ValueCountFrequency (%)
∼ 2
100.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 2
66.7%
Ⅱ 1
33.3%
Hiragana
ValueCountFrequency (%)
る 1
25.0%
す 1
25.0%
に 1
25.0%
の 1
25.0%
Geometric Shapes
ValueCountFrequency (%)
□ 1
100.0%

저자
Text

MISSING 

Distinct8484
Distinct (%)85.7%
Missing103
Missing (%)1.0%
Memory size156.2 KiB
2024-04-30T07:32:34.143970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length113
Median length75
Mean length12.508134
Min length2

Characters and Unicode

Total characters123793
Distinct characters1349
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7651 ?
Unique (%)77.3%

Sample

1st row캐더린 패터슨 글;최순희 옮김
2nd row마리오 곰볼리 글. 그림;사과나무 옮김
3rd row서덕 지음
4th row강경애 외 지음;방민호 엮음
5th row조나단 앨런 글.그림;이희재 옮김
ValueCountFrequency (%)
지음 3176
 
10.5%
옮김 2256
 
7.5%
그림 1940
 
6.4%
저 335
 
1.1%
글 309
 
1.0%
엮음 225
 
0.7%
편 223
 
0.7%
외 157
 
0.5%
글·그림 138
 
0.5%
공]지음 109
 
0.4%
Other values (13173) 21286
70.6%
2024-04-30T07:32:34.566211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20304
 
16.4%
; 6409
 
5.2%
지 5991
 
4.8%
음 5800
 
4.7%
김 4534
 
3.7%
그 3012
 
2.4%
림 2929
 
2.4%
이 2797
 
2.3%
글 2459
 
2.0%
옮 2344
 
1.9%
Other values (1339) 67214
54.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 90673
73.2%
Space Separator 20304
 
16.4%
Other Punctuation 7899
 
6.4%
Lowercase Letter 2467
 
2.0%
Uppercase Letter 951
 
0.8%
Close Punctuation 686
 
0.6%
Open Punctuation 686
 
0.6%
Decimal Number 71
 
0.1%
Dash Punctuation 35
 
< 0.1%
Math Symbol 15
 
< 0.1%
Other values (2) 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 5991
 
6.6%
음 5800
 
6.4%
김 4534
 
5.0%
그 3012
 
3.3%
림 2929
 
3.2%
이 2797
 
3.1%
글 2459
 
2.7%
옮 2344
 
2.6%
정 1357
 
1.5%
스 1307
 
1.4%
Other values (1250) 58143
64.1%
Uppercase Letter
ValueCountFrequency (%)
M 92
 
9.7%
S 89
 
9.4%
B 75
 
7.9%
A 60
 
6.3%
K 58
 
6.1%
L 56
 
5.9%
J 56
 
5.9%
R 48
 
5.0%
C 45
 
4.7%
D 43
 
4.5%
Other values (16) 329
34.6%
Lowercase Letter
ValueCountFrequency (%)
a 276
11.2%
e 234
 
9.5%
r 209
 
8.5%
i 193
 
7.8%
o 192
 
7.8%
n 182
 
7.4%
s 137
 
5.6%
t 135
 
5.5%
l 133
 
5.4%
y 113
 
4.6%
Other values (15) 663
26.9%
Other Punctuation
ValueCountFrequency (%)
; 6409
81.1%
. 865
 
11.0%
, 258
 
3.3%
· 256
 
3.2%
: 82
 
1.0%
& 10
 
0.1%
' 4
 
0.1%
? 4
 
0.1%
/ 3
 
< 0.1%
＆ 3
 
< 0.1%
Other values (3) 5
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 14
19.7%
2 12
16.9%
4 9
12.7%
3 8
11.3%
7 7
9.9%
0 6
8.5%
6 5
 
7.0%
5 5
 
7.0%
8 3
 
4.2%
9 2
 
2.8%
Close Punctuation
ValueCountFrequency (%)
] 678
98.8%
) 6
 
0.9%
》 1
 
0.1%
」 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
[ 678
98.8%
( 6
 
0.9%
《 1
 
0.1%
「 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
< 7
46.7%
> 7
46.7%
+ 1
 
6.7%
Space Separator
ValueCountFrequency (%)
20304
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%
Control
ValueCountFrequency (%)
5
100.0%
Other Symbol
ValueCountFrequency (%)
ⓔ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 89566
72.4%
Common 29702
 
24.0%
Latin 3418
 
2.8%
Han 1107
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 5991
 
6.7%
음 5800
 
6.5%
김 4534
 
5.1%
그 3012
 
3.4%
림 2929
 
3.3%
이 2797
 
3.1%
글 2459
 
2.7%
옮 2344
 
2.6%
정 1357
 
1.5%
스 1307
 
1.5%
Other values (881) 57036
63.7%
Han
ValueCountFrequency (%)
著 129
 
11.7%
編 53
 
4.8%
李 30
 
2.7%
金 29
 
2.6%
譯 18
 
1.6%
會 15
 
1.4%
社 14
 
1.3%
朴 14
 
1.3%
學 13
 
1.2%
韓 13
 
1.2%
Other values (359) 779
70.4%
Latin
ValueCountFrequency (%)
a 276
 
8.1%
e 234
 
6.8%
r 209
 
6.1%
i 193
 
5.6%
o 192
 
5.6%
n 182
 
5.3%
s 137
 
4.0%
t 135
 
3.9%
l 133
 
3.9%
y 113
 
3.3%
Other values (41) 1614
47.2%
Common
ValueCountFrequency (%)
20304
68.4%
; 6409
 
21.6%
. 865
 
2.9%
] 678
 
2.3%
[ 678
 
2.3%
, 258
 
0.9%
· 256
 
0.9%
: 82
 
0.3%
- 35
 
0.1%
1 14
 
< 0.1%
Other values (28) 123
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 89558
72.3%
ASCII 32855
 
26.5%
CJK 1053
 
0.9%
None 264
 
0.2%
CJK Compat Ideographs 54
 
< 0.1%
Compat Jamo 8
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20304
61.8%
; 6409
 
19.5%
. 865
 
2.6%
] 678
 
2.1%
[ 678
 
2.1%
a 276
 
0.8%
, 258
 
0.8%
e 234
 
0.7%
r 209
 
0.6%
i 193
 
0.6%
Other values (71) 2751
 
8.4%
Hangul
ValueCountFrequency (%)
지 5991
 
6.7%
음 5800
 
6.5%
김 4534
 
5.1%
그 3012
 
3.4%
림 2929
 
3.3%
이 2797
 
3.1%
글 2459
 
2.7%
옮 2344
 
2.6%
정 1357
 
1.5%
스 1307
 
1.5%
Other values (879) 57028
63.7%
None
ValueCountFrequency (%)
· 256
97.0%
＆ 3
 
1.1%
／ 1
 
0.4%
》 1
 
0.4%
《 1
 
0.4%
」 1
 
0.4%
「 1
 
0.4%
CJK
ValueCountFrequency (%)
著 129
 
12.3%
編 53
 
5.0%
金 29
 
2.8%
譯 18
 
1.7%
會 15
 
1.4%
社 14
 
1.3%
朴 14
 
1.3%
學 13
 
1.2%
韓 13
 
1.2%
國 11
 
1.0%
Other values (343) 744
70.7%
CJK Compat Ideographs
ValueCountFrequency (%)
李 30
55.6%
寧 5
 
9.3%
烈 3
 
5.6%
梁 2
 
3.7%
盧 2
 
3.7%
柳 2
 
3.7%
林 1
 
1.9%
隆 1
 
1.9%
寧 1
 
1.9%
玲 1
 
1.9%
Other values (6) 6
 
11.1%
Compat Jamo
ValueCountFrequency (%)
ㆍ 7
87.5%
ㅇ 1
 
12.5%
Enclosed Alphanum
ValueCountFrequency (%)
ⓔ 1
100.0%

출판사
Text

Distinct2801
Distinct (%)28.0%
Missing10
Missing (%)0.1%
Memory size156.2 KiB
2024-04-30T07:32:34.845505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length27
Mean length4.3431431
Min length1

Characters and Unicode

Total characters43388
Distinct characters833
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1600 ?
Unique (%)16.0%

Sample

1st row대교출판
2nd row크레용하우스
3rd row넥스트북스
4th row북폴리오
5th row한국몬테소리
ValueCountFrequency (%)
문학동네 177
 
1.7%
시공사 135
 
1.3%
웅진닷컴 128
 
1.2%
김영사 122
 
1.2%
비룡소 117
 
1.1%
서울문화사 98
 
0.9%
창비 96
 
0.9%
자음과모음 80
 
0.8%
아이세움 78
 
0.7%
민음사 71
 
0.7%
Other values (2818) 9322
89.4%
2024-04-30T07:32:35.253637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 2537
 
5.8%
문 1042
 
2.4%
스 982
 
2.3%
이 876
 
2.0%
판 864
 
2.0%
출 855
 
2.0%
학 767
 
1.8%
북 739
 
1.7%
아 650
 
1.5%
어 643
 
1.5%
Other values (823) 33433
77.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 40427
93.2%
Lowercase Letter 1039
 
2.4%
Uppercase Letter 704
 
1.6%
Space Separator 518
 
1.2%
Other Punctuation 483
 
1.1%
Decimal Number 116
 
0.3%
Open Punctuation 49
 
0.1%
Close Punctuation 49
 
0.1%
Dash Punctuation 2
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 2537
 
6.3%
문 1042
 
2.6%
스 982
 
2.4%
이 876
 
2.2%
판 864
 
2.1%
출 855
 
2.1%
학 767
 
1.9%
북 739
 
1.8%
아 650
 
1.6%
어 643
 
1.6%
Other values (746) 30472
75.4%
Uppercase Letter
ValueCountFrequency (%)
B 176
25.0%
M 133
18.9%
H 43
 
6.1%
O 42
 
6.0%
K 37
 
5.3%
L 36
 
5.1%
I 32
 
4.5%
C 29
 
4.1%
P 29
 
4.1%
R 25
 
3.6%
Other values (14) 122
17.3%
Lowercase Letter
ValueCountFrequency (%)
o 159
15.3%
a 91
 
8.8%
r 86
 
8.3%
n 83
 
8.0%
e 79
 
7.6%
i 73
 
7.0%
s 68
 
6.5%
k 47
 
4.5%
t 46
 
4.4%
l 42
 
4.0%
Other values (14) 265
25.5%
Other Punctuation
ValueCountFrequency (%)
: 296
61.3%
& 91
 
18.8%
* 27
 
5.6%
＆ 23
 
4.8%
. 20
 
4.1%
, 7
 
1.4%
@ 5
 
1.0%
· 4
 
0.8%
# 3
 
0.6%
; 2
 
0.4%
Other values (3) 5
 
1.0%
Decimal Number
ValueCountFrequency (%)
2 50
43.1%
1 46
39.7%
0 8
 
6.9%
9 5
 
4.3%
4 2
 
1.7%
8 2
 
1.7%
3 1
 
0.9%
5 1
 
0.9%
6 1
 
0.9%
Open Punctuation
ValueCountFrequency (%)
( 47
95.9%
[ 2
 
4.1%
Close Punctuation
ValueCountFrequency (%)
) 47
95.9%
] 2
 
4.1%
Space Separator
ValueCountFrequency (%)
518
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39799
91.7%
Latin 1743
 
4.0%
Common 1218
 
2.8%
Han 628
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 2537
 
6.4%
문 1042
 
2.6%
스 982
 
2.5%
이 876
 
2.2%
판 864
 
2.2%
출 855
 
2.1%
학 767
 
1.9%
북 739
 
1.9%
아 650
 
1.6%
어 643
 
1.6%
Other values (610) 29844
75.0%
Han
ValueCountFrequency (%)
社 87
 
13.9%
文 49
 
7.8%
出 23
 
3.7%
版 23
 
3.7%
博 21
 
3.3%
英 18
 
2.9%
東 16
 
2.5%
學 15
 
2.4%
閣 14
 
2.2%
大 12
 
1.9%
Other values (126) 350
55.7%
Latin
ValueCountFrequency (%)
B 176
 
10.1%
o 159
 
9.1%
M 133
 
7.6%
a 91
 
5.2%
r 86
 
4.9%
n 83
 
4.8%
e 79
 
4.5%
i 73
 
4.2%
s 68
 
3.9%
k 47
 
2.7%
Other values (38) 748
42.9%
Common
ValueCountFrequency (%)
518
42.5%
: 296
24.3%
& 91
 
7.5%
2 50
 
4.1%
( 47
 
3.9%
) 47
 
3.9%
1 46
 
3.8%
* 27
 
2.2%
＆ 23
 
1.9%
. 20
 
1.6%
Other values (19) 53
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39798
91.7%
ASCII 2934
 
6.8%
CJK 626
 
1.4%
None 27
 
0.1%
CJK Compat Ideographs 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 2537
 
6.4%
문 1042
 
2.6%
스 982
 
2.5%
이 876
 
2.2%
판 864
 
2.2%
출 855
 
2.1%
학 767
 
1.9%
북 739
 
1.9%
아 650
 
1.6%
어 643
 
1.6%
Other values (609) 29843
75.0%
ASCII
ValueCountFrequency (%)
518
17.7%
: 296
 
10.1%
B 176
 
6.0%
o 159
 
5.4%
M 133
 
4.5%
& 91
 
3.1%
a 91
 
3.1%
r 86
 
2.9%
n 83
 
2.8%
e 79
 
2.7%
Other values (65) 1222
41.6%
CJK
ValueCountFrequency (%)
社 87
 
13.9%
文 49
 
7.8%
出 23
 
3.7%
版 23
 
3.7%
博 21
 
3.4%
英 18
 
2.9%
東 16
 
2.6%
學 15
 
2.4%
閣 14
 
2.2%
大 12
 
1.9%
Other values (125) 348
55.6%
None
ValueCountFrequency (%)
＆ 23
85.2%
· 4
 
14.8%
CJK Compat Ideographs
ValueCountFrequency (%)
良 2
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

Missing values

2024-04-30T07:32:32.639260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T07:32:32.726187image/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.
2024-04-30T07:32:32.812423image/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

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70198애쓰다 지친 나를 위해서덕 지음넥스트북스
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53343모르코스와의 약속맥밀란교육연구소;필립 심슨 [공]글;지우 그림을파소
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23188정보통신개론정진욱;최영수 공저영진
49132호야 토야 옛날이야기 두번째차보금 글;이광익 그림교원
30104(고원정 장편소설)불타는 빙벽고원정 지음해냄출판사
7646불교 이야기김용덕 지음창작과비평사
27146태교 명화김종근 지음안그라픽스
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18946찻사발:茶碗박정상 지음태학원
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Duplicate rows

Most frequently occurring

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358잘먹고 잘사는 법 시리즈<NA>김영사12
12(戰略)三國志요코야마 미쓰테루 지음;박영 옮김대현출판사11
398탄탄 우리 옛 이야기여원미디어 편여원미디어11
273세계명작학습만화<NA>교육출판공사10
62(세계 창작동화) 앙뜨북<NA>웅진닷컴9
111Sing Sing 영어 2<NA>한국헤르만헤세8
231미래를 꿈꾼 사람들한국몬테소리한국몬테소리8
425호롱불 옛이야기웅진닷컴 편집부웅진닷컴7