Overview

Dataset statistics

Number of variables8
Number of observations3000
Missing cells30
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory196.4 KiB
Average record size in memory67.0 B

Variable types

Numeric3
Text4
Categorical1

Dataset

Description제어번호,제목,저자,발행처,발행년도,ISBN번호,분류기호,대출횟수
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15475/S/1/datasetView.do

Alerts

제어번호 is highly overall correlated with 발행년도High correlation
발행년도 is highly overall correlated with 제어번호High correlation
제어번호 has unique valuesUnique
분류기호 has 154 (5.1%) zerosZeros

Reproduction

Analysis started2024-05-10 23:51:36.989972
Analysis finished2024-05-10 23:51:46.581486
Duration9.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

제어번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct3000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1318276.8
Minimum149
Maximum1674332
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.5 KiB
2024-05-10T23:51:46.815599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum149
5-th percentile173761.25
Q11185849
median1543214
Q31643739.5
95-th percentile1661834.4
Maximum1674332
Range1674183
Interquartile range (IQR)457890.5

Descriptive statistics

Standard deviation460767.96
Coefficient of variation (CV)0.34952292
Kurtosis1.3052695
Mean1318276.8
Median Absolute Deviation (MAD)111391.5
Skewness-1.5417191
Sum3.9548304 × 109
Variance2.1230711 × 1011
MonotonicityNot monotonic
2024-05-10T23:51:47.380913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1297078 1
 
< 0.1%
1578777 1
 
< 0.1%
1630771 1
 
< 0.1%
1508529 1
 
< 0.1%
1239650 1
 
< 0.1%
1651904 1
 
< 0.1%
723367 1
 
< 0.1%
294507 1
 
< 0.1%
1350278 1
 
< 0.1%
1220724 1
 
< 0.1%
Other values (2990) 2990
99.7%
ValueCountFrequency (%)
149 1
< 0.1%
313 1
< 0.1%
692 1
< 0.1%
869 1
< 0.1%
1105 1
< 0.1%
1113 1
< 0.1%
1555 1
< 0.1%
1757 1
< 0.1%
1787 1
< 0.1%
2196 1
< 0.1%
ValueCountFrequency (%)
1674332 1
< 0.1%
1672671 1
< 0.1%
1672668 1
< 0.1%
1672613 1
< 0.1%
1672563 1
< 0.1%
1672560 1
< 0.1%
1671951 1
< 0.1%
1671297 1
< 0.1%
1671295 1
< 0.1%
1671168 1
< 0.1%

제목
Text

Distinct2967
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
2024-05-10T23:51:48.197054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length150
Median length84
Mean length29.930333
Min length2

Characters and Unicode

Total characters89791
Distinct characters1303
Distinct categories16 ?
Distinct scripts7 ?
Distinct blocks13 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2935 ?
Unique (%)97.8%

Sample

1st row여행의 이유 :김영하 산문
2nd row소년이 온다 :한강 장편소설
3rd row홍학의 자리 :정해연 장편소설
4th row미드나잇 라이브러리
5th row지구 끝의 온실 :김초엽 장편소설
ValueCountFrequency (%)
192
 
0.9%
1 154
 
0.7%
장편소설 150
 
0.7%
위한 149
 
0.7%
the 138
 
0.7%
2 129
 
0.6%
이야기 107
 
0.5%
of 67
 
0.3%
3 60
 
0.3%
읽는 58
 
0.3%
Other values (10018) 19766
94.3%
2024-05-10T23:51:49.594446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17981
 
20.0%
: 1807
 
2.0%
의 1632
 
1.8%
e 1206
 
1.3%
이 1204
 
1.3%
는 1193
 
1.3%
( 945
 
1.1%
) 943
 
1.1%
i 909
 
1.0%
a 887
 
1.0%
Other values (1293) 61084
68.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 51470
57.3%
Space Separator 17981
 
20.0%
Lowercase Letter 10552
 
11.8%
Other Punctuation 3873
 
4.3%
Decimal Number 1929
 
2.1%
Uppercase Letter 1427
 
1.6%
Open Punctuation 1035
 
1.2%
Close Punctuation 1033
 
1.2%
Math Symbol 397
 
0.4%
Dash Punctuation 75
 
0.1%
Other values (6) 19
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 1632
 
3.2%
이 1204
 
2.3%
는 1193
 
2.3%
사 840
 
1.6%
기 820
 
1.6%
한 748
 
1.5%
가 709
 
1.4%
지 679
 
1.3%
리 655
 
1.3%
로 626
 
1.2%
Other values (1171) 42364
82.3%
Lowercase Letter
ValueCountFrequency (%)
e 1206
11.4%
i 909
 
8.6%
a 887
 
8.4%
o 880
 
8.3%
n 792
 
7.5%
t 758
 
7.2%
r 681
 
6.5%
s 661
 
6.3%
l 465
 
4.4%
h 433
 
4.1%
Other values (33) 2880
27.3%
Uppercase Letter
ValueCountFrequency (%)
T 153
 
10.7%
A 115
 
8.1%
P 102
 
7.1%
G 102
 
7.1%
S 96
 
6.7%
I 94
 
6.6%
C 80
 
5.6%
E 64
 
4.5%
D 60
 
4.2%
M 54
 
3.8%
Other values (18) 507
35.5%
Other Punctuation
ValueCountFrequency (%)
: 1807
46.7%
, 838
21.6%
. 600
 
15.5%
? 234
 
6.0%
! 195
 
5.0%
' 101
 
2.6%
& 46
 
1.2%
/ 24
 
0.6%
# 9
 
0.2%
% 8
 
0.2%
Other values (5) 11
 
0.3%
Decimal Number
ValueCountFrequency (%)
1 480
24.9%
2 386
20.0%
0 357
18.5%
3 179
 
9.3%
4 125
 
6.5%
5 106
 
5.5%
9 86
 
4.5%
6 76
 
3.9%
8 67
 
3.5%
7 67
 
3.5%
Math Symbol
ValueCountFrequency (%)
= 323
81.4%
~ 50
 
12.6%
+ 16
 
4.0%
< 4
 
1.0%
> 4
 
1.0%
Open Punctuation
ValueCountFrequency (%)
( 945
91.3%
[ 84
 
8.1%
『 5
 
0.5%
「 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 943
91.3%
] 84
 
8.1%
』 5
 
0.5%
」 1
 
0.1%
Other Number
ValueCountFrequency (%)
① 3
60.0%
② 1
 
20.0%
③ 1
 
20.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 2
33.3%
Ⅹ 2
33.3%
Ⅴ 2
33.3%
Other Symbol
ValueCountFrequency (%)
│ 3
75.0%
ⓔ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
17981
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 75
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 51195
57.0%
Common 26336
29.3%
Latin 11943
 
13.3%
Han 240
 
0.3%
Cyrillic 42
 
< 0.1%
Hiragana 25
 
< 0.1%
Katakana 10
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 1632
 
3.2%
이 1204
 
2.4%
는 1193
 
2.3%
사 840
 
1.6%
기 820
 
1.6%
한 748
 
1.5%
가 709
 
1.4%
지 679
 
1.3%
리 655
 
1.3%
로 626
 
1.2%
Other values (1014) 42089
82.2%
Han
ValueCountFrequency (%)
誌 14
 
5.8%
滸 14
 
5.8%
水 14
 
5.8%
新 11
 
4.6%
志 7
 
2.9%
國 7
 
2.9%
三 5
 
2.1%
日 5
 
2.1%
經 4
 
1.7%
生 4
 
1.7%
Other values (121) 155
64.6%
Latin
ValueCountFrequency (%)
e 1206
 
10.1%
i 909
 
7.6%
a 887
 
7.4%
o 880
 
7.4%
n 792
 
6.6%
t 758
 
6.3%
r 681
 
5.7%
s 661
 
5.5%
l 465
 
3.9%
h 433
 
3.6%
Other values (46) 4271
35.8%
Common
ValueCountFrequency (%)
17981
68.3%
: 1807
 
6.9%
( 945
 
3.6%
) 943
 
3.6%
, 838
 
3.2%
. 600
 
2.3%
1 480
 
1.8%
2 386
 
1.5%
0 357
 
1.4%
= 323
 
1.2%
Other values (38) 1676
 
6.4%
Cyrillic
ValueCountFrequency (%)
с 5
11.9%
о 5
11.9%
к 4
9.5%
й 4
9.5%
и 4
9.5%
е 4
9.5%
р 3
 
7.1%
ц 2
 
4.8%
а 2
 
4.8%
я 1
 
2.4%
Other values (8) 8
19.0%
Hiragana
ValueCountFrequency (%)
い 3
12.0%
る 3
12.0%
す 3
12.0%
せ 2
 
8.0%
く 2
 
8.0%
の 2
 
8.0%
し 1
 
4.0%
ら 1
 
4.0%
に 1
 
4.0%
か 1
 
4.0%
Other values (6) 6
24.0%
Katakana
ValueCountFrequency (%)
ン 1
10.0%
バ 1
10.0%
マ 1
10.0%
ト 1
10.0%
ス 1
10.0%
ニ 1
10.0%
ア 1
10.0%
ピ 1
10.0%
グ 1
10.0%
ロ 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 51194
57.0%
ASCII 38243
42.6%
CJK 231
 
0.3%
Cyrillic 42
 
< 0.1%
Hiragana 25
 
< 0.1%
None 16
 
< 0.1%
Katakana 10
 
< 0.1%
CJK Compat Ideographs 9
 
< 0.1%
Enclosed Alphanum 6
 
< 0.1%
Number Forms 6
 
< 0.1%
Other values (3) 9
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17981
47.0%
: 1807
 
4.7%
e 1206
 
3.2%
( 945
 
2.5%
) 943
 
2.5%
i 909
 
2.4%
a 887
 
2.3%
o 880
 
2.3%
, 838
 
2.2%
n 792
 
2.1%
Other values (75) 11055
28.9%
Hangul
ValueCountFrequency (%)
의 1632
 
3.2%
이 1204
 
2.4%
는 1193
 
2.3%
사 840
 
1.6%
기 820
 
1.6%
한 748
 
1.5%
가 709
 
1.4%
지 679
 
1.3%
리 655
 
1.3%
로 626
 
1.2%
Other values (1013) 42088
82.2%
CJK
ValueCountFrequency (%)
誌 14
 
6.1%
滸 14
 
6.1%
水 14
 
6.1%
新 11
 
4.8%
志 7
 
3.0%
國 7
 
3.0%
三 5
 
2.2%
日 5
 
2.2%
經 4
 
1.7%
生 4
 
1.7%
Other values (113) 146
63.2%
Cyrillic
ValueCountFrequency (%)
с 5
11.9%
о 5
11.9%
к 4
9.5%
й 4
9.5%
и 4
9.5%
е 4
9.5%
р 3
 
7.1%
ц 2
 
4.8%
а 2
 
4.8%
я 1
 
2.4%
Other values (8) 8
19.0%
None
ValueCountFrequency (%)
』 5
31.2%
『 5
31.2%
！ 1
 
6.2%
、 1
 
6.2%
＆ 1
 
6.2%
「 1
 
6.2%
」 1
 
6.2%
ß 1
 
6.2%
Enclosed Alphanum
ValueCountFrequency (%)
① 3
50.0%
ⓔ 1
 
16.7%
② 1
 
16.7%
③ 1
 
16.7%
Box Drawing
ValueCountFrequency (%)
│ 3
100.0%
Punctuation
ValueCountFrequency (%)
… 3
60.0%
‘ 1
 
20.0%
’ 1
 
20.0%
Hiragana
ValueCountFrequency (%)
い 3
12.0%
る 3
12.0%
す 3
12.0%
せ 2
 
8.0%
く 2
 
8.0%
の 2
 
8.0%
し 1
 
4.0%
ら 1
 
4.0%
に 1
 
4.0%
か 1
 
4.0%
Other values (6) 6
24.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 2
33.3%
Ⅹ 2
33.3%
Ⅴ 2
33.3%
CJK Compat Ideographs
ValueCountFrequency (%)
烈 2
22.2%
論 1
11.1%
易 1
11.1%
歷 1
11.1%
林 1
11.1%
理 1
11.1%
流 1
11.1%
不 1
11.1%
Katakana
ValueCountFrequency (%)
ン 1
10.0%
バ 1
10.0%
マ 1
10.0%
ト 1
10.0%
ス 1
10.0%
ニ 1
10.0%
ア 1
10.0%
ピ 1
10.0%
グ 1
10.0%
ロ 1
10.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

저자
Text

Distinct2376
Distinct (%)79.2%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
2024-05-10T23:51:50.196550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length154
Median length52
Mean length8.0266667
Min length2

Characters and Unicode

Total characters24080
Distinct characters777
Distinct categories11 ?
Distinct scripts5 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2086 ?
Unique (%)69.5%

Sample

1st row김영하 지음
2nd row한강 지음
3rd row정해연 지음
4th row매트 헤이그 지음
5th row김초엽 지음
ValueCountFrequency (%)
지음 1758
 
25.2%
글 287
 
4.1%
저 109
 
1.6%
by 75
 
1.1%
원작 66
 
0.9%
글?그림 55
 
0.8%
설민석 39
 
0.6%
히가시노 27
 
0.4%
게이고 26
 
0.4%
박시백 23
 
0.3%
Other values (3123) 4519
64.7%
2024-05-10T23:51:51.705997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3985
 
16.5%
지 1866
 
7.7%
음 1779
 
7.4%
이 477
 
2.0%
글 400
 
1.7%
스 337
 
1.4%
김 325
 
1.3%
리 264
 
1.1%
[ 215
 
0.9%
] 215
 
0.9%
Other values (767) 14217
59.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16951
70.4%
Space Separator 3985
 
16.5%
Lowercase Letter 1860
 
7.7%
Uppercase Letter 480
 
2.0%
Other Punctuation 297
 
1.2%
Open Punctuation 242
 
1.0%
Close Punctuation 242
 
1.0%
Dash Punctuation 10
 
< 0.1%
Math Symbol 7
 
< 0.1%
Decimal Number 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 1866
 
11.0%
음 1779
 
10.5%
이 477
 
2.8%
글 400
 
2.4%
스 337
 
2.0%
김 325
 
1.9%
리 264
 
1.6%
정 188
 
1.1%
마 175
 
1.0%
미 175
 
1.0%
Other values (695) 10965
64.7%
Lowercase Letter
ValueCountFrequency (%)
a 201
 
10.8%
e 197
 
10.6%
r 160
 
8.6%
n 146
 
7.8%
i 139
 
7.5%
o 135
 
7.3%
y 106
 
5.7%
b 90
 
4.8%
l 86
 
4.6%
t 82
 
4.4%
Other values (16) 518
27.8%
Uppercase Letter
ValueCountFrequency (%)
S 43
 
9.0%
M 42
 
8.8%
J 38
 
7.9%
A 38
 
7.9%
B 36
 
7.5%
R 31
 
6.5%
H 31
 
6.5%
C 30
 
6.2%
D 25
 
5.2%
L 22
 
4.6%
Other values (16) 144
30.0%
Other Punctuation
ValueCountFrequency (%)
. 111
37.4%
? 96
32.3%
, 55
18.5%
: 17
 
5.7%
/ 11
 
3.7%
; 7
 
2.4%
Decimal Number
ValueCountFrequency (%)
8 2
40.0%
2 1
20.0%
3 1
20.0%
1 1
20.0%
Math Symbol
ValueCountFrequency (%)
< 3
42.9%
> 3
42.9%
｜ 1
 
14.3%
Open Punctuation
ValueCountFrequency (%)
[ 215
88.8%
( 27
 
11.2%
Close Punctuation
ValueCountFrequency (%)
] 215
88.8%
) 27
 
11.2%
Space Separator
ValueCountFrequency (%)
3985
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Other Symbol
ValueCountFrequency (%)
ⓔ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16867
70.0%
Common 4789
 
19.9%
Latin 2340
 
9.7%
Han 77
 
0.3%
Katakana 7
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 1866
 
11.1%
음 1779
 
10.5%
이 477
 
2.8%
글 400
 
2.4%
스 337
 
2.0%
김 325
 
1.9%
리 264
 
1.6%
정 188
 
1.1%
마 175
 
1.0%
미 175
 
1.0%
Other values (626) 10881
64.5%
Han
ValueCountFrequency (%)
著 7
 
9.1%
加 3
 
3.9%
硏 2
 
2.6%
典 2
 
2.6%
室 2
 
2.6%
究 2
 
2.6%
古 2
 
2.6%
朴 2
 
2.6%
路 2
 
2.6%
王 1
 
1.3%
Other values (52) 52
67.5%
Latin
ValueCountFrequency (%)
a 201
 
8.6%
e 197
 
8.4%
r 160
 
6.8%
n 146
 
6.2%
i 139
 
5.9%
o 135
 
5.8%
y 106
 
4.5%
b 90
 
3.8%
l 86
 
3.7%
t 82
 
3.5%
Other values (42) 998
42.6%
Common
ValueCountFrequency (%)
3985
83.2%
[ 215
 
4.5%
] 215
 
4.5%
. 111
 
2.3%
? 96
 
2.0%
, 55
 
1.1%
( 27
 
0.6%
) 27
 
0.6%
: 17
 
0.4%
/ 11
 
0.2%
Other values (10) 30
 
0.6%
Katakana
ValueCountFrequency (%)
チ 1
14.3%
フ 1
14.3%
レ 1
14.3%
ジ 1
14.3%
デ 1
14.3%
ン 1
14.3%
ト 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16867
70.0%
ASCII 7127
29.6%
CJK 76
 
0.3%
Katakana 7
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%
None 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3985
55.9%
[ 215
 
3.0%
] 215
 
3.0%
a 201
 
2.8%
e 197
 
2.8%
r 160
 
2.2%
n 146
 
2.0%
i 139
 
2.0%
o 135
 
1.9%
. 111
 
1.6%
Other values (60) 1623
22.8%
Hangul
ValueCountFrequency (%)
지 1866
 
11.1%
음 1779
 
10.5%
이 477
 
2.8%
글 400
 
2.4%
스 337
 
2.0%
김 325
 
1.9%
리 264
 
1.6%
정 188
 
1.1%
마 175
 
1.0%
미 175
 
1.0%
Other values (626) 10881
64.5%
CJK
ValueCountFrequency (%)
著 7
 
9.2%
加 3
 
3.9%
硏 2
 
2.6%
典 2
 
2.6%
室 2
 
2.6%
究 2
 
2.6%
古 2
 
2.6%
朴 2
 
2.6%
路 2
 
2.6%
王 1
 
1.3%
Other values (51) 51
67.1%
Enclosed Alphanum
ValueCountFrequency (%)
ⓔ 1
100.0%
None
ValueCountFrequency (%)
｜ 1
100.0%
Katakana
ValueCountFrequency (%)
チ 1
14.3%
フ 1
14.3%
レ 1
14.3%
ジ 1
14.3%
デ 1
14.3%
ン 1
14.3%
ト 1
14.3%
CJK Compat Ideographs
ValueCountFrequency (%)
沈 1
100.0%

발행처
Text

Distinct1443
Distinct (%)48.1%
Missing2
Missing (%)0.1%
Memory size23.6 KiB
2024-05-10T23:51:52.367945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length33
Mean length7.4312875
Min length1

Characters and Unicode

Total characters22279
Distinct characters639
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique984 ?
Unique (%)32.8%

Sample

1st row문학동네
2nd row창비
3rd row엘릭시르 : 문학동네
4th row인플루엔셜
5th rowGiant Books(자이언트북스)
ValueCountFrequency (%)
279
 
6.3%
아이세움 68
 
1.5%
미래엔 67
 
1.5%
북이십일 65
 
1.5%
김영사 63
 
1.4%
민음사 60
 
1.4%
문학동네 56
 
1.3%
books 47
 
1.1%
mirae 44
 
1.0%
n 44
 
1.0%
Other values (1535) 3602
82.0%
2024-05-10T23:51:53.972915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1398
 
6.3%
스 723
 
3.2%
이 617
 
2.8%
사 588
 
2.6%
: 588
 
2.6%
북 524
 
2.4%
o 409
 
1.8%
아 348
 
1.6%
a 344
 
1.5%
e 312
 
1.4%
Other values (629) 16428
73.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15125
67.9%
Lowercase Letter 3256
 
14.6%
Space Separator 1398
 
6.3%
Uppercase Letter 1155
 
5.2%
Other Punctuation 667
 
3.0%
Open Punctuation 283
 
1.3%
Close Punctuation 283
 
1.3%
Decimal Number 100
 
0.4%
Math Symbol 11
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 723
 
4.8%
이 617
 
4.1%
사 588
 
3.9%
북 524
 
3.5%
아 348
 
2.3%
어 264
 
1.7%
문 263
 
1.7%
미 256
 
1.7%
판 240
 
1.6%
출 232
 
1.5%
Other values (554) 11070
73.2%
Lowercase Letter
ValueCountFrequency (%)
o 409
12.6%
a 344
10.6%
e 312
9.6%
i 299
9.2%
s 293
9.0%
r 250
 
7.7%
n 227
 
7.0%
k 196
 
6.0%
t 101
 
3.1%
l 99
 
3.0%
Other values (15) 726
22.3%
Uppercase Letter
ValueCountFrequency (%)
B 151
13.1%
M 121
 
10.5%
N 98
 
8.5%
K 95
 
8.2%
P 73
 
6.3%
H 66
 
5.7%
S 62
 
5.4%
A 57
 
4.9%
D 50
 
4.3%
R 50
 
4.3%
Other values (15) 332
28.7%
Other Punctuation
ValueCountFrequency (%)
: 588
88.2%
. 20
 
3.0%
& 18
 
2.7%
; 13
 
1.9%
? 12
 
1.8%
/ 8
 
1.2%
' 5
 
0.7%
, 2
 
0.3%
# 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
2 41
41.0%
1 33
33.0%
4 6
 
6.0%
6 6
 
6.0%
8 4
 
4.0%
3 3
 
3.0%
5 3
 
3.0%
0 2
 
2.0%
9 2
 
2.0%
Open Punctuation
ValueCountFrequency (%)
( 264
93.3%
[ 19
 
6.7%
Close Punctuation
ValueCountFrequency (%)
) 264
93.3%
] 19
 
6.7%
Space Separator
ValueCountFrequency (%)
1398
100.0%
Math Symbol
ValueCountFrequency (%)
× 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15075
67.7%
Latin 4411
 
19.8%
Common 2743
 
12.3%
Han 50
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 723
 
4.8%
이 617
 
4.1%
사 588
 
3.9%
북 524
 
3.5%
아 348
 
2.3%
어 264
 
1.8%
문 263
 
1.7%
미 256
 
1.7%
판 240
 
1.6%
출 232
 
1.5%
Other values (524) 11020
73.1%
Latin
ValueCountFrequency (%)
o 409
 
9.3%
a 344
 
7.8%
e 312
 
7.1%
i 299
 
6.8%
s 293
 
6.6%
r 250
 
5.7%
n 227
 
5.1%
k 196
 
4.4%
B 151
 
3.4%
M 121
 
2.7%
Other values (40) 1809
41.0%
Han
ValueCountFrequency (%)
社 5
 
10.0%
出 5
 
10.0%
版 4
 
8.0%
法 3
 
6.0%
文 3
 
6.0%
公 2
 
4.0%
司 2
 
4.0%
大 2
 
4.0%
夏 2
 
4.0%
雨 2
 
4.0%
Other values (20) 20
40.0%
Common
ValueCountFrequency (%)
1398
51.0%
: 588
21.4%
( 264
 
9.6%
) 264
 
9.6%
2 41
 
1.5%
1 33
 
1.2%
. 20
 
0.7%
[ 19
 
0.7%
] 19
 
0.7%
& 18
 
0.7%
Other values (15) 79
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15071
67.6%
ASCII 7143
32.1%
CJK 50
 
0.2%
None 11
 
< 0.1%
Compat Jamo 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1398
19.6%
: 588
 
8.2%
o 409
 
5.7%
a 344
 
4.8%
e 312
 
4.4%
i 299
 
4.2%
s 293
 
4.1%
( 264
 
3.7%
) 264
 
3.7%
r 250
 
3.5%
Other values (64) 2722
38.1%
Hangul
ValueCountFrequency (%)
스 723
 
4.8%
이 617
 
4.1%
사 588
 
3.9%
북 524
 
3.5%
아 348
 
2.3%
어 264
 
1.8%
문 263
 
1.7%
미 256
 
1.7%
판 240
 
1.6%
출 232
 
1.5%
Other values (520) 11016
73.1%
None
ValueCountFrequency (%)
× 11
100.0%
CJK
ValueCountFrequency (%)
社 5
 
10.0%
出 5
 
10.0%
版 4
 
8.0%
法 3
 
6.0%
文 3
 
6.0%
公 2
 
4.0%
司 2
 
4.0%
大 2
 
4.0%
夏 2
 
4.0%
雨 2
 
4.0%
Other values (20) 20
40.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
25.0%
ㅊ 1
25.0%
ㅁ 1
25.0%
ㅇ 1
25.0%

발행년도
Categorical

HIGH CORRELATION 

Distinct37
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
2023
860 
2022
350 
2021
277 
2019
208 
2020
196 
Other values (32)
1109 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique8 ?
Unique (%)0.3%

Sample

1st row2019
2nd row2014
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2023 860
28.7%
2022 350
11.7%
2021 277
 
9.2%
2019 208
 
6.9%
2020 196
 
6.5%
2024 185
 
6.2%
2018 163
 
5.4%
2017 129
 
4.3%
2016 123
 
4.1%
2015 92
 
3.1%
Other values (27) 417
13.9%

Length

2024-05-10T23:51:54.498569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2023 860
28.7%
2022 350
11.7%
2021 277
 
9.2%
2019 208
 
6.9%
2020 196
 
6.5%
2024 185
 
6.2%
2018 163
 
5.4%
2017 129
 
4.3%
2016 123
 
4.1%
2015 92
 
3.1%
Other values (26) 416
13.9%

ISBN번호
Text

Distinct2950
Distinct (%)99.3%
Missing28
Missing (%)0.9%
Memory size23.6 KiB
2024-05-10T23:51:55.321436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length13
Mean length12.974428
Min length10

Characters and Unicode

Total characters38560
Distinct characters11
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

Unique2930 ?
Unique (%)98.6%

Sample

1st row9788954655972
2nd row9788936434120
3rd row9788954681155
4th row9791191056556
5th row9791191824001
ValueCountFrequency (%)
9791189683801 3
 
0.1%
9791193031377 3
 
0.1%
9788954430074 2
 
0.1%
9791130635712 2
 
0.1%
9791157747214 2
 
0.1%
9788986836240 2
 
0.1%
9791160506228 2
 
0.1%
9788992394949 2
 
0.1%
9791193231043 2
 
0.1%
9791155816592 2
 
0.1%
Other values (2940) 2950
99.3%
2024-05-10T23:51:56.623024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 8453
21.9%
1 5466
14.2%
7 5224
13.5%
8 5098
13.2%
6 2676
 
6.9%
5 2395
 
6.2%
0 2369
 
6.1%
4 2319
 
6.0%
3 2280
 
5.9%
2 2277
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38557
> 99.9%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 8453
21.9%
1 5466
14.2%
7 5224
13.5%
8 5098
13.2%
6 2676
 
6.9%
5 2395
 
6.2%
0 2369
 
6.1%
4 2319
 
6.0%
3 2280
 
5.9%
2 2277
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
x 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 38557
> 99.9%
Latin 3
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
9 8453
21.9%
1 5466
14.2%
7 5224
13.5%
8 5098
13.2%
6 2676
 
6.9%
5 2395
 
6.2%
0 2369
 
6.1%
4 2319
 
6.0%
3 2280
 
5.9%
2 2277
 
5.9%
Latin
ValueCountFrequency (%)
x 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38560
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 8453
21.9%
1 5466
14.2%
7 5224
13.5%
8 5098
13.2%
6 2676
 
6.9%
5 2395
 
6.2%
0 2369
 
6.1%
4 2319
 
6.0%
3 2280
 
5.9%
2 2277
 
5.9%

분류기호
Real number (ℝ)

ZEROS 

Distinct10
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.0553333
Minimum0
Maximum9
Zeros154
Zeros (%)5.1%
Negative0
Negative (%)0.0%
Memory size26.5 KiB
2024-05-10T23:51:57.148642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median5
Q38
95-th percentile9
Maximum9
Range9
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.7786409
Coefficient of variation (CV)0.54964543
Kurtosis-1.1902558
Mean5.0553333
Median Absolute Deviation (MAD)2
Skewness-0.17898786
Sum15166
Variance7.7208452
MonotonicityNot monotonic
2024-05-10T23:51:57.473344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
8 603
20.1%
3 432
14.4%
5 322
10.7%
4 315
10.5%
9 309
10.3%
1 300
10.0%
6 255
8.5%
7 189
 
6.3%
0 154
 
5.1%
2 121
 
4.0%
ValueCountFrequency (%)
0 154
 
5.1%
1 300
10.0%
2 121
 
4.0%
3 432
14.4%
4 315
10.5%
5 322
10.7%
6 255
8.5%
7 189
 
6.3%
8 603
20.1%
9 309
10.3%
ValueCountFrequency (%)
9 309
10.3%
8 603
20.1%
7 189
 
6.3%
6 255
8.5%
5 322
10.7%
4 315
10.5%
3 432
14.4%
2 121
 
4.0%
1 300
10.0%
0 154
 
5.1%

대출횟수
Real number (ℝ)

Distinct19
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.5256667
Minimum2
Maximum28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.5 KiB
2024-05-10T23:51:57.846810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q13
median3
Q34
95-th percentile7
Maximum28
Range26
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.8034482
Coefficient of variation (CV)0.51151977
Kurtosis24.232687
Mean3.5256667
Median Absolute Deviation (MAD)1
Skewness3.6034247
Sum10577
Variance3.2524254
MonotonicityDecreasing
2024-05-10T23:51:58.354111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
3 1174
39.1%
2 743
24.8%
4 608
20.3%
5 211
 
7.0%
6 109
 
3.6%
7 57
 
1.9%
8 30
 
1.0%
9 20
 
0.7%
10 12
 
0.4%
11 11
 
0.4%
Other values (9) 25
 
0.8%
ValueCountFrequency (%)
2 743
24.8%
3 1174
39.1%
4 608
20.3%
5 211
 
7.0%
6 109
 
3.6%
7 57
 
1.9%
8 30
 
1.0%
9 20
 
0.7%
10 12
 
0.4%
11 11
 
0.4%
ValueCountFrequency (%)
28 1
 
< 0.1%
20 1
 
< 0.1%
19 1
 
< 0.1%
17 2
 
0.1%
16 1
 
< 0.1%
15 3
 
0.1%
14 4
 
0.1%
13 6
0.2%
12 6
0.2%
11 11
0.4%

Interactions

2024-05-10T23:51:44.384609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:51:41.497576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:51:43.425579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:51:44.710957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:51:42.493321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:51:43.844460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:51:45.063499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:51:42.867725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:51:44.124032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-10T23:51:58.665284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
제어번호발행년도분류기호대출횟수
제어번호1.0000.9220.2770.080
발행년도0.9221.0000.2460.000
분류기호0.2770.2461.0000.246
대출횟수0.0800.0000.2461.000
2024-05-10T23:51:59.048385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
제어번호분류기호대출횟수발행년도
제어번호1.000-0.0720.0570.645
분류기호-0.0721.0000.0910.088
대출횟수0.0570.0911.0000.000
발행년도0.6450.0880.0001.000

Missing values

2024-05-10T23:51:45.534447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-10T23:51:46.137443image/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.
2024-05-10T23:51:46.433741image/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

제어번호제목저자발행처발행년도ISBN번호분류기호대출횟수
01297078여행의 이유 :김영하 산문김영하 지음문학동네20199788954655972828
1541851소년이 온다 :한강 장편소설한강 지음창비20149788936434120820
21509082홍학의 자리 :정해연 장편소설정해연 지음엘릭시르 : 문학동네20219788954681155819
31481845미드나잇 라이브러리매트 헤이그 지음인플루엔셜20219791191056556817
41508624지구 끝의 온실 :김초엽 장편소설김초엽 지음Giant Books(자이언트북스)20219791191824001817
51563918하얼빈 :김훈 장편소설김훈 지음문학동네20229788954699914816
61220440부자 아빠 가난한 아빠 :부자들이 들려주는 '돈'과 '투자'의 비밀 : 20주년 특별 기념판로버트 기요사키 지음민음인20189791158883591315
71485420불편한 편의점 :김호연 장편소설김호연 지음나무옆의자20219791161571188815
81058983파친코 :이민진 장편소설 .1이민진 지음문학사상20189788970129815815
91543223도파민네이션 :쾌락 과잉 시대에서 균형 찾기애나 렘키 지음흐름출판20229788965965046514
제어번호제목저자발행처발행년도ISBN번호분류기호대출횟수
299017736군 리더십 :이론과 사례를 중심으로 =Military leadership최병순 지음북코리아2010978896324072532
29911642212굶주린 마흔의 생존 독서 :인생이 변하는 독서일기변한다 지음느린서재2023979119819442802
29921672560굿 하는 날안덕자봄봄(봄봄출판사)2022979116863011632
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