Overview

Dataset statistics

Number of variables9
Number of observations10000
Missing cells7250
Missing cells (%)8.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory800.8 KiB
Average record size in memory82.0 B

Variable types

Numeric2
Text6
Categorical1

Dataset

Description한국생명공학연구원 도서관에서 소장중인 도서 리스트
Author한국생명공학연구원
URLhttps://www.data.go.kr/data/3034126/fileData.do

Alerts

등록번호 is highly overall correlated with 출판년High correlation
출판년 is highly overall correlated with 등록번호High correlation
복본 is highly imbalanced (82.5%)Imbalance
저자 has 194 (1.9%) missing valuesMissing
도서 has 181 (1.8%) missing valuesMissing
권년차 has 6862 (68.6%) missing valuesMissing
등록번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 18:25:11.812118
Analysis finished2023-12-12 18:25:15.445858
Duration3.63 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

등록번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9921.3135
Minimum1
Maximum18822
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T03:25:15.548443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile788.9
Q15560.5
median9975
Q314748.25
95-th percentile17996.15
Maximum18822
Range18821
Interquartile range (IQR)9187.75

Descriptive statistics

Standard deviation5442.2651
Coefficient of variation (CV)0.5485428
Kurtosis-1.1542962
Mean9921.3135
Median Absolute Deviation (MAD)4560.5
Skewness-0.13318522
Sum99213135
Variance29618250
MonotonicityNot monotonic
2023-12-13T03:25:15.747038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2583 1
 
< 0.1%
8876 1
 
< 0.1%
691 1
 
< 0.1%
9725 1
 
< 0.1%
9390 1
 
< 0.1%
15350 1
 
< 0.1%
11495 1
 
< 0.1%
9883 1
 
< 0.1%
2952 1
 
< 0.1%
18498 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
14 1
< 0.1%
15 1
< 0.1%
16 1
< 0.1%
ValueCountFrequency (%)
18822 1
< 0.1%
18821 1
< 0.1%
18820 1
< 0.1%
18819 1
< 0.1%
18818 1
< 0.1%
18816 1
< 0.1%
18814 1
< 0.1%
18813 1
< 0.1%
18812 1
< 0.1%
18811 1
< 0.1%

서명
Text

Distinct7714
Distinct (%)77.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T03:25:16.107917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length200
Median length160
Mean length37.6851
Min length1

Characters and Unicode

Total characters376851
Distinct characters1972
Distinct categories17 ?
Distinct scripts7 ?
Distinct blocks15 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6683 ?
Unique (%)66.8%

Sample

1st rowBioinformatics : from nucleic acids and proteins to cell metabolism ; from nucleic acids and proteins to cell metabolism ; contributions to the conference on "Bioinformatics", October 9 to 11, 1995, B
2nd row장류의 과학과 건강기능성
3rd rowEcologically based pest management : new solutions for a new century
4th row(앨빈 토플러)부의 미래
5th row進化の謎をゲノムで解く
ValueCountFrequency (%)
6021
 
9.8%
of 2150
 
3.5%
and 2079
 
3.4%
the 1247
 
2.0%
in 1058
 
1.7%
a 670
 
1.1%
biology 464
 
0.8%
molecular 436
 
0.7%
for 404
 
0.7%
to 357
 
0.6%
Other values (14859) 46733
75.8%
2023-12-13T03:25:16.809321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
51654
 
13.7%
e 22698
 
6.0%
o 22440
 
6.0%
i 20207
 
5.4%
a 19898
 
5.3%
n 18785
 
5.0%
t 16029
 
4.3%
r 14617
 
3.9%
s 13945
 
3.7%
c 12833
 
3.4%
Other values (1962) 163745
43.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 229536
60.9%
Other Letter 66850
 
17.7%
Space Separator 51657
 
13.7%
Uppercase Letter 11870
 
3.1%
Other Punctuation 8463
 
2.2%
Decimal Number 4111
 
1.1%
Math Symbol 1076
 
0.3%
Dash Punctuation 1027
 
0.3%
Open Punctuation 988
 
0.3%
Close Punctuation 980
 
0.3%
Other values (7) 293
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 1824
 
2.7%
이 1301
 
1.9%
학 1094
 
1.6%
기 1059
 
1.6%
한 1016
 
1.5%
과 913
 
1.4%
는 778
 
1.2%
물 762
 
1.1%
생 740
 
1.1%
지 705
 
1.1%
Other values (1832) 56658
84.8%
Lowercase Letter
ValueCountFrequency (%)
e 22698
9.9%
o 22440
9.8%
i 20207
 
8.8%
a 19898
 
8.7%
n 18785
 
8.2%
t 16029
 
7.0%
r 14617
 
6.4%
s 13945
 
6.1%
c 12833
 
5.6%
l 12674
 
5.5%
Other values (18) 55410
24.1%
Uppercase Letter
ValueCountFrequency (%)
A 1174
 
9.9%
P 1030
 
8.7%
C 1004
 
8.5%
M 881
 
7.4%
I 846
 
7.1%
B 831
 
7.0%
T 794
 
6.7%
S 747
 
6.3%
E 550
 
4.6%
N 525
 
4.4%
Other values (18) 3488
29.4%
Other Punctuation
ValueCountFrequency (%)
: 4758
56.2%
, 2077
24.5%
. 564
 
6.7%
· 308
 
3.6%
' 215
 
2.5%
/ 212
 
2.5%
& 145
 
1.7%
! 74
 
0.9%
， 41
 
0.5%
; 33
 
0.4%
Other values (8) 36
 
0.4%
Decimal Number
ValueCountFrequency (%)
1 1145
27.9%
0 775
18.9%
2 768
18.7%
9 361
 
8.8%
3 304
 
7.4%
4 197
 
4.8%
5 193
 
4.7%
8 149
 
3.6%
6 125
 
3.0%
7 90
 
2.2%
Other values (3) 4
 
0.1%
Math Symbol
ValueCountFrequency (%)
= 999
92.8%
+ 30
 
2.8%
~ 28
 
2.6%
| 6
 
0.6%
｜ 6
 
0.6%
∼ 3
 
0.3%
< 1
 
0.1%
> 1
 
0.1%
～ 1
 
0.1%
＋ 1
 
0.1%
Letter Number
ValueCountFrequency (%)
Ⅰ 39
34.2%
Ⅱ 34
29.8%
Ⅲ 29
25.4%
Ⅳ 6
 
5.3%
Ⅴ 4
 
3.5%
Ⅵ 2
 
1.8%
Open Punctuation
ValueCountFrequency (%)
( 968
98.0%
[ 16
 
1.6%
『 2
 
0.2%
《 1
 
0.1%
「 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 961
98.1%
] 15
 
1.5%
』 2
 
0.2%
》 1
 
0.1%
」 1
 
0.1%
Other Number
ValueCountFrequency (%)
¹ 4
44.4%
³ 3
33.3%
③ 1
 
11.1%
² 1
 
11.1%
Other Symbol
ValueCountFrequency (%)
▼ 14
73.7%
™ 4
 
21.1%
℃ 1
 
5.3%
Space Separator
ValueCountFrequency (%)
51654
> 99.9%
　 3
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 969
94.4%
― 58
 
5.6%
Control
ValueCountFrequency (%)
 125
99.2%
 1
 
0.8%
Modifier Symbol
ValueCountFrequency (%)
˙ 7
87.5%
´ 1
 
12.5%
Final Punctuation
ValueCountFrequency (%)
’ 15
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 241515
64.1%
Common 68481
 
18.2%
Hangul 56510
 
15.0%
Han 6917
 
1.8%
Katakana 2094
 
0.6%
Hiragana 1329
 
0.4%
Greek 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 1824
 
3.2%
이 1301
 
2.3%
학 1094
 
1.9%
기 1059
 
1.9%
한 1016
 
1.8%
과 913
 
1.6%
는 778
 
1.4%
물 762
 
1.3%
생 740
 
1.3%
지 705
 
1.2%
Other values (993) 46318
82.0%
Han
ValueCountFrequency (%)
物 222
 
3.2%
學 205
 
3.0%
生 187
 
2.7%
大 120
 
1.7%
國 107
 
1.5%
鑑 104
 
1.5%
植 100
 
1.4%
術 92
 
1.3%
技 91
 
1.3%
科 85
 
1.2%
Other values (695) 5604
81.0%
Katakana
ValueCountFrequency (%)
イ 168
 
8.0%
ン 121
 
5.8%
ス 107
 
5.1%
ク 107
 
5.1%
オ 91
 
4.3%
ト 75
 
3.6%
バ 74
 
3.5%
テ 72
 
3.4%
ロ 67
 
3.2%
ル 62
 
3.0%
Other values (66) 1150
54.9%
Common
ValueCountFrequency (%)
51654
75.4%
: 4758
 
6.9%
, 2077
 
3.0%
1 1145
 
1.7%
= 999
 
1.5%
- 969
 
1.4%
( 968
 
1.4%
) 961
 
1.4%
0 775
 
1.1%
2 768
 
1.1%
Other values (58) 3407
 
5.0%
Latin
ValueCountFrequency (%)
e 22698
 
9.4%
o 22440
 
9.3%
i 20207
 
8.4%
a 19898
 
8.2%
n 18785
 
7.8%
t 16029
 
6.6%
r 14617
 
6.1%
s 13945
 
5.8%
c 12833
 
5.3%
l 12674
 
5.2%
Other values (50) 67389
27.9%
Hiragana
ValueCountFrequency (%)
の 327
24.6%
と 161
 
12.1%
る 79
 
5.9%
か 68
 
5.1%
を 54
 
4.1%
ら 54
 
4.1%
で 40
 
3.0%
に 38
 
2.9%
た 36
 
2.7%
す 31
 
2.3%
Other values (48) 441
33.2%
Greek
ValueCountFrequency (%)
β 4
80.0%
α 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 309376
82.1%
Hangul 56402
 
15.0%
CJK 6831
 
1.8%
Katakana 2094
 
0.6%
Hiragana 1329
 
0.4%
None 408
 
0.1%
Number Forms 114
 
< 0.1%
Compat Jamo 108
 
< 0.1%
CJK Compat Ideographs 86
 
< 0.1%
Punctuation 73
 
< 0.1%
Other values (5) 30
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
51654
16.7%
e 22698
 
7.3%
o 22440
 
7.3%
i 20207
 
6.5%
a 19898
 
6.4%
n 18785
 
6.1%
t 16029
 
5.2%
r 14617
 
4.7%
s 13945
 
4.5%
c 12833
 
4.1%
Other values (78) 96270
31.1%
Hangul
ValueCountFrequency (%)
의 1824
 
3.2%
이 1301
 
2.3%
학 1094
 
1.9%
기 1059
 
1.9%
한 1016
 
1.8%
과 913
 
1.6%
는 778
 
1.4%
물 762
 
1.4%
생 740
 
1.3%
지 705
 
1.2%
Other values (991) 46210
81.9%
Hiragana
ValueCountFrequency (%)
の 327
24.6%
と 161
 
12.1%
る 79
 
5.9%
か 68
 
5.1%
を 54
 
4.1%
ら 54
 
4.1%
で 40
 
3.0%
に 38
 
2.9%
た 36
 
2.7%
す 31
 
2.3%
Other values (48) 441
33.2%
None
ValueCountFrequency (%)
· 308
75.5%
， 41
 
10.0%
、 9
 
2.2%
＆ 6
 
1.5%
｜ 6
 
1.5%
β 4
 
1.0%
¹ 4
 
1.0%
！ 3
 
0.7%
　 3
 
0.7%
³ 3
 
0.7%
Other values (18) 21
 
5.1%
CJK
ValueCountFrequency (%)
物 222
 
3.2%
學 205
 
3.0%
生 187
 
2.7%
大 120
 
1.8%
國 107
 
1.6%
鑑 104
 
1.5%
植 100
 
1.5%
術 92
 
1.3%
技 91
 
1.3%
科 85
 
1.2%
Other values (675) 5518
80.8%
Katakana
ValueCountFrequency (%)
イ 168
 
8.0%
ン 121
 
5.8%
ス 107
 
5.1%
ク 107
 
5.1%
オ 91
 
4.3%
ト 75
 
3.6%
バ 74
 
3.5%
テ 72
 
3.4%
ロ 67
 
3.2%
ル 62
 
3.0%
Other values (66) 1150
54.9%
Compat Jamo
ValueCountFrequency (%)
ㆍ 101
93.5%
ㅡ 7
 
6.5%
Punctuation
ValueCountFrequency (%)
― 58
79.5%
’ 15
 
20.5%
Number Forms
ValueCountFrequency (%)
Ⅰ 39
34.2%
Ⅱ 34
29.8%
Ⅲ 29
25.4%
Ⅳ 6
 
5.3%
Ⅴ 4
 
3.5%
Ⅵ 2
 
1.8%
CJK Compat Ideographs
ValueCountFrequency (%)
歷 25
29.1%
年 25
29.1%
利 10
 
11.6%
理 3
 
3.5%
不 2
 
2.3%
勞 2
 
2.3%
臨 2
 
2.3%
女 2
 
2.3%
茶 2
 
2.3%
裂 2
 
2.3%
Other values (10) 11
12.8%
Geometric Shapes
ValueCountFrequency (%)
▼ 14
100.0%
Modifier Letters
ValueCountFrequency (%)
˙ 7
100.0%
Letterlike Symbols
ValueCountFrequency (%)
™ 4
80.0%
℃ 1
 
20.0%
Math Operators
ValueCountFrequency (%)
∼ 3
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
③ 1
100.0%

저자
Text

MISSING 

Distinct6297
Distinct (%)64.2%
Missing194
Missing (%)1.9%
Memory size156.2 KiB
2023-12-13T03:25:17.254282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length100
Median length89
Mean length11.866204
Min length2

Characters and Unicode

Total characters116360
Distinct characters1149
Distinct categories13 ?
Distinct scripts6 ?
Distinct blocks10 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4889 ?
Unique (%)49.9%

Sample

1st rowSchomburg, Dietmar
2nd row박건영
3rd rowNational Research Council (U.S.)
4th row토플러, 앨빈
5th row長谷部, 光泰
ValueCountFrequency (%)
j 438
 
2.1%
m 333
 
1.6%
a 314
 
1.5%
r 268
 
1.3%
l 212
 
1.0%
e 202
 
1.0%
d 196
 
0.9%
h 177
 
0.8%
david 171
 
0.8%
w 169
 
0.8%
Other values (7747) 18706
88.3%
2023-12-13T03:25:18.204247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11387
 
9.8%
e 7440
 
6.4%
a 6463
 
5.6%
n 5851
 
5.0%
, 5813
 
5.0%
r 5439
 
4.7%
o 5334
 
4.6%
i 4910
 
4.2%
l 3606
 
3.1%
t 3220
 
2.8%
Other values (1139) 56897
48.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 61895
53.2%
Other Letter 19876
 
17.1%
Uppercase Letter 15802
 
13.6%
Space Separator 11392
 
9.8%
Other Punctuation 6919
 
5.9%
Dash Punctuation 229
 
0.2%
Open Punctuation 66
 
0.1%
Close Punctuation 63
 
0.1%
Control 58
 
< 0.1%
Decimal Number 42
 
< 0.1%
Other values (3) 18
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 676
 
3.4%
김 395
 
2.0%
정 338
 
1.7%
학 308
 
1.5%
스 292
 
1.5%
한 292
 
1.5%
국 276
 
1.4%
기 239
 
1.2%
연 233
 
1.2%
회 225
 
1.1%
Other values (1049) 16602
83.5%
Uppercase Letter
ValueCountFrequency (%)
S 1188
 
7.5%
M 1179
 
7.5%
J 1176
 
7.4%
A 1050
 
6.6%
R 1048
 
6.6%
C 1005
 
6.4%
D 953
 
6.0%
B 944
 
6.0%
H 810
 
5.1%
G 783
 
5.0%
Other values (17) 5666
35.9%
Lowercase Letter
ValueCountFrequency (%)
e 7440
12.0%
a 6463
10.4%
n 5851
9.5%
r 5439
 
8.8%
o 5334
 
8.6%
i 4910
 
7.9%
l 3606
 
5.8%
t 3220
 
5.2%
s 2901
 
4.7%
h 2329
 
3.8%
Other values (16) 14402
23.3%
Other Punctuation
ValueCountFrequency (%)
, 5813
84.0%
. 981
 
14.2%
& 55
 
0.8%
' 28
 
0.4%
/ 17
 
0.2%
: 11
 
0.2%
· 7
 
0.1%
" 5
 
0.1%
! 1
 
< 0.1%
！ 1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
9 16
38.1%
1 9
21.4%
4 9
21.4%
2 2
 
4.8%
6 2
 
4.8%
0 2
 
4.8%
5 1
 
2.4%
3 1
 
2.4%
Math Symbol
ValueCountFrequency (%)
| 4
36.4%
< 3
27.3%
> 3
27.3%
+ 1
 
9.1%
Control
ValueCountFrequency (%)
 54
93.1%
 3
 
5.2%
 1
 
1.7%
Modifier Symbol
ValueCountFrequency (%)
´ 4
66.7%
¨ 1
 
16.7%
^ 1
 
16.7%
Space Separator
ValueCountFrequency (%)
11387
> 99.9%
　 5
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 225
98.3%
― 4
 
1.7%
Open Punctuation
ValueCountFrequency (%)
( 65
98.5%
[ 1
 
1.5%
Close Punctuation
ValueCountFrequency (%)
) 62
98.4%
] 1
 
1.6%
Other Symbol
ValueCountFrequency (%)
▼ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 77697
66.8%
Common 18787
 
16.1%
Hangul 18054
 
15.5%
Han 1632
 
1.4%
Katakana 183
 
0.2%
Hiragana 7
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 676
 
3.7%
김 395
 
2.2%
정 338
 
1.9%
학 308
 
1.7%
스 292
 
1.6%
한 292
 
1.6%
국 276
 
1.5%
기 239
 
1.3%
연 233
 
1.3%
회 225
 
1.2%
Other values (600) 14780
81.9%
Han
ValueCountFrequency (%)
中 77
 
4.7%
國 61
 
3.7%
會 47
 
2.9%
學 44
 
2.7%
編 35
 
2.1%
田 34
 
2.1%
科 33
 
2.0%
植 33
 
2.0%
物 32
 
2.0%
志 31
 
1.9%
Other values (389) 1205
73.8%
Latin
ValueCountFrequency (%)
e 7440
 
9.6%
a 6463
 
8.3%
n 5851
 
7.5%
r 5439
 
7.0%
o 5334
 
6.9%
i 4910
 
6.3%
l 3606
 
4.6%
t 3220
 
4.1%
s 2901
 
3.7%
h 2329
 
3.0%
Other values (43) 30204
38.9%
Katakana
ValueCountFrequency (%)
シ 18
 
9.8%
イ 16
 
8.7%
ン 16
 
8.7%
ス 12
 
6.6%
ム 11
 
6.0%
エ 10
 
5.5%
オ 9
 
4.9%
バ 9
 
4.9%
ト 6
 
3.3%
リ 6
 
3.3%
Other values (34) 70
38.3%
Common
ValueCountFrequency (%)
11387
60.6%
, 5813
30.9%
. 981
 
5.2%
- 225
 
1.2%
( 65
 
0.3%
) 62
 
0.3%
& 55
 
0.3%
 54
 
0.3%
' 28
 
0.1%
/ 17
 
0.1%
Other values (27) 100
 
0.5%
Hiragana
ValueCountFrequency (%)
い 2
28.6%
と 1
14.3%
な 1
14.3%
ら 1
14.3%
え 1
14.3%
み 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 96460
82.9%
Hangul 18052
 
15.5%
CJK 1618
 
1.4%
Katakana 183
 
0.2%
None 19
 
< 0.1%
CJK Compat Ideographs 14
 
< 0.1%
Hiragana 7
 
< 0.1%
Punctuation 4
 
< 0.1%
Compat Jamo 2
 
< 0.1%
Geometric Shapes 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11387
 
11.8%
e 7440
 
7.7%
a 6463
 
6.7%
n 5851
 
6.1%
, 5813
 
6.0%
r 5439
 
5.6%
o 5334
 
5.5%
i 4910
 
5.1%
l 3606
 
3.7%
t 3220
 
3.3%
Other values (72) 36997
38.4%
Hangul
ValueCountFrequency (%)
이 676
 
3.7%
김 395
 
2.2%
정 338
 
1.9%
학 308
 
1.7%
스 292
 
1.6%
한 292
 
1.6%
국 276
 
1.5%
기 239
 
1.3%
연 233
 
1.3%
회 225
 
1.2%
Other values (598) 14778
81.9%
CJK
ValueCountFrequency (%)
中 77
 
4.8%
國 61
 
3.8%
會 47
 
2.9%
學 44
 
2.7%
編 35
 
2.2%
田 34
 
2.1%
科 33
 
2.0%
植 33
 
2.0%
物 32
 
2.0%
志 31
 
1.9%
Other values (382) 1191
73.6%
Katakana
ValueCountFrequency (%)
シ 18
 
9.8%
イ 16
 
8.7%
ン 16
 
8.7%
ス 12
 
6.6%
ム 11
 
6.0%
エ 10
 
5.5%
オ 9
 
4.9%
バ 9
 
4.9%
ト 6
 
3.3%
リ 6
 
3.3%
Other values (34) 70
38.3%
None
ValueCountFrequency (%)
· 7
36.8%
　 5
26.3%
´ 4
21.1%
¨ 1
 
5.3%
Ø 1
 
5.3%
！ 1
 
5.3%
CJK Compat Ideographs
ValueCountFrequency (%)
利 5
35.7%
隆 4
28.6%
林 1
 
7.1%
立 1
 
7.1%
不 1
 
7.1%
良 1
 
7.1%
女 1
 
7.1%
Punctuation
ValueCountFrequency (%)
― 4
100.0%
Hiragana
ValueCountFrequency (%)
い 2
28.6%
と 1
14.3%
な 1
14.3%
ら 1
14.3%
え 1
14.3%
み 1
14.3%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
50.0%
ㅡ 1
50.0%
Geometric Shapes
ValueCountFrequency (%)
▼ 1
100.0%

출판사
Text

Distinct2427
Distinct (%)24.3%
Missing10
Missing (%)0.1%
Memory size156.2 KiB
2023-12-13T03:25:18.565651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length100
Median length94
Mean length12.13003
Min length1

Characters and Unicode

Total characters121179
Distinct characters846
Distinct categories12 ?
Distinct scripts6 ?
Distinct blocks9 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1421 ?
Unique (%)14.2%

Sample

1st rowVCH
2nd row한국장류협동조합
3rd rowNational Academy Press
4th row청림출판
5th row學硏メディカル秀潤社
ValueCountFrequency (%)
press 2160
 
11.7%
academic 875
 
4.7%
university 400
 
2.2%
379
 
2.0%
wiley 297
 
1.6%
humana 251
 
1.4%
oxford 251
 
1.4%
of 250
 
1.4%
publishers 203
 
1.1%
springer 198
 
1.1%
Other values (2382) 13253
71.6%
2023-12-13T03:25:19.056019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 9270
 
7.6%
8527
 
7.0%
s 7478
 
6.2%
r 7374
 
6.1%
i 6838
 
5.6%
a 5373
 
4.4%
n 4593
 
3.8%
o 4392
 
3.6%
c 4316
 
3.6%
l 3757
 
3.1%
Other values (836) 59261
48.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 71207
58.8%
Other Letter 23940
 
19.8%
Uppercase Letter 14917
 
12.3%
Space Separator 8527
 
7.0%
Other Punctuation 1356
 
1.1%
Dash Punctuation 510
 
0.4%
Control 374
 
0.3%
Close Punctuation 119
 
0.1%
Open Punctuation 118
 
0.1%
Decimal Number 104
 
0.1%
Other values (2) 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 1166
 
4.9%
스 796
 
3.3%
이 682
 
2.8%
학 511
 
2.1%
국 477
 
2.0%
한 460
 
1.9%
원 456
 
1.9%
판 419
 
1.8%
출 418
 
1.7%
문 384
 
1.6%
Other values (757) 18171
75.9%
Lowercase Letter
ValueCountFrequency (%)
e 9270
13.0%
s 7478
10.5%
r 7374
10.4%
i 6838
9.6%
a 5373
 
7.5%
n 4593
 
6.5%
o 4392
 
6.2%
c 4316
 
6.1%
l 3757
 
5.3%
t 2859
 
4.0%
Other values (16) 14957
21.0%
Uppercase Letter
ValueCountFrequency (%)
P 2952
19.8%
A 1493
10.0%
S 1429
9.6%
C 1306
 
8.8%
H 927
 
6.2%
B 763
 
5.1%
W 713
 
4.8%
I 667
 
4.5%
R 575
 
3.9%
L 545
 
3.7%
Other values (15) 3547
23.8%
Other Punctuation
ValueCountFrequency (%)
. 422
31.1%
& 353
26.0%
, 344
25.4%
/ 141
 
10.4%
' 39
 
2.9%
: 22
 
1.6%
; 16
 
1.2%
* 12
 
0.9%
· 4
 
0.3%
@ 2
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 49
47.1%
2 45
43.3%
9 5
 
4.8%
8 2
 
1.9%
3 1
 
1.0%
0 1
 
1.0%
5 1
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 497
97.5%
― 13
 
2.5%
Open Punctuation
ValueCountFrequency (%)
( 106
89.8%
[ 12
 
10.2%
Close Punctuation
ValueCountFrequency (%)
) 106
89.1%
] 13
 
10.9%
Space Separator
ValueCountFrequency (%)
8527
100.0%
Control
ValueCountFrequency (%)
 374
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 5
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 86124
71.1%
Hangul 21477
 
17.7%
Common 11115
 
9.2%
Han 2119
 
1.7%
Katakana 339
 
0.3%
Hiragana 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 1166
 
5.4%
스 796
 
3.7%
이 682
 
3.2%
학 511
 
2.4%
국 477
 
2.2%
한 460
 
2.1%
원 456
 
2.1%
판 419
 
2.0%
출 418
 
1.9%
문 384
 
1.8%
Other values (469) 15708
73.1%
Han
ValueCountFrequency (%)
社 272
 
12.8%
出 120
 
5.7%
版 120
 
5.7%
學 84
 
4.0%
會 78
 
3.7%
羊 72
 
3.4%
土 72
 
3.4%
書 50
 
2.4%
日 40
 
1.9%
業 32
 
1.5%
Other values (225) 1179
55.6%
Latin
ValueCountFrequency (%)
e 9270
 
10.8%
s 7478
 
8.7%
r 7374
 
8.6%
i 6838
 
7.9%
a 5373
 
6.2%
n 4593
 
5.3%
o 4392
 
5.1%
c 4316
 
5.0%
l 3757
 
4.4%
P 2952
 
3.4%
Other values (41) 29781
34.6%
Katakana
ValueCountFrequency (%)
シ 47
 
13.9%
ン 29
 
8.6%
エ 26
 
7.7%
ム 26
 
7.7%
ス 14
 
4.1%
イ 14
 
4.1%
タ 13
 
3.8%
セ 11
 
3.2%
フ 11
 
3.2%
ラ 11
 
3.2%
Other values (38) 137
40.4%
Common
ValueCountFrequency (%)
8527
76.7%
- 497
 
4.5%
. 422
 
3.8%
 374
 
3.4%
& 353
 
3.2%
, 344
 
3.1%
/ 141
 
1.3%
( 106
 
1.0%
) 106
 
1.0%
1 49
 
0.4%
Other values (18) 196
 
1.8%
Hiragana
ValueCountFrequency (%)
む 1
20.0%
く 1
20.0%
す 1
20.0%
あ 1
20.0%
と 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 97217
80.2%
Hangul 21476
 
17.7%
CJK 2111
 
1.7%
Katakana 339
 
0.3%
Punctuation 18
 
< 0.1%
CJK Compat Ideographs 8
 
< 0.1%
Hiragana 5
 
< 0.1%
None 4
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 9270
 
9.5%
8527
 
8.8%
s 7478
 
7.7%
r 7374
 
7.6%
i 6838
 
7.0%
a 5373
 
5.5%
n 4593
 
4.7%
o 4392
 
4.5%
c 4316
 
4.4%
l 3757
 
3.9%
Other values (66) 35299
36.3%
Hangul
ValueCountFrequency (%)
사 1166
 
5.4%
스 796
 
3.7%
이 682
 
3.2%
학 511
 
2.4%
국 477
 
2.2%
한 460
 
2.1%
원 456
 
2.1%
판 419
 
2.0%
출 418
 
1.9%
문 384
 
1.8%
Other values (468) 15707
73.1%
CJK
ValueCountFrequency (%)
社 272
 
12.9%
出 120
 
5.7%
版 120
 
5.7%
學 84
 
4.0%
會 78
 
3.7%
羊 72
 
3.4%
土 72
 
3.4%
書 50
 
2.4%
日 40
 
1.9%
業 32
 
1.5%
Other values (219) 1171
55.5%
Katakana
ValueCountFrequency (%)
シ 47
 
13.9%
ン 29
 
8.6%
エ 26
 
7.7%
ム 26
 
7.7%
ス 14
 
4.1%
イ 14
 
4.1%
タ 13
 
3.8%
セ 11
 
3.2%
フ 11
 
3.2%
ラ 11
 
3.2%
Other values (38) 137
40.4%
Punctuation
ValueCountFrequency (%)
― 13
72.2%
’ 5
 
27.8%
None
ValueCountFrequency (%)
· 4
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
率 2
25.0%
勞 2
25.0%
林 1
12.5%
栗 1
12.5%
阮 1
12.5%
金 1
12.5%
Hiragana
ValueCountFrequency (%)
む 1
20.0%
く 1
20.0%
す 1
20.0%
あ 1
20.0%
と 1
20.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

출판년
Real number (ℝ)

HIGH CORRELATION 

Distinct84
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2000.2735
Minimum1905
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T03:25:19.242979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1905
5-th percentile1975
Q11994
median2003
Q32010
95-th percentile2017
Maximum2020
Range115
Interquartile range (IQR)16

Descriptive statistics

Standard deviation13.730177
Coefficient of variation (CV)0.0068641496
Kurtosis3.9439247
Mean2000.2735
Median Absolute Deviation (MAD)8
Skewness-1.5999817
Sum20002735
Variance188.51775
MonotonicityNot monotonic
2023-12-13T03:25:19.425575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2003 446
 
4.5%
1994 411
 
4.1%
2004 406
 
4.1%
2005 390
 
3.9%
2002 383
 
3.8%
2007 342
 
3.4%
1995 334
 
3.3%
2011 330
 
3.3%
2006 317
 
3.2%
2013 310
 
3.1%
Other values (74) 6331
63.3%
ValueCountFrequency (%)
1905 1
 
< 0.1%
1916 1
 
< 0.1%
1921 1
 
< 0.1%
1922 1
 
< 0.1%
1934 1
 
< 0.1%
1938 1
 
< 0.1%
1940 1
 
< 0.1%
1941 39
0.4%
1943 13
 
0.1%
1944 27
0.3%
ValueCountFrequency (%)
2020 54
 
0.5%
2019 147
1.5%
2018 217
2.2%
2017 187
1.9%
2016 202
2.0%
2015 273
2.7%
2014 304
3.0%
2013 310
3.1%
2012 300
3.0%
2011 330
3.3%

분류
Text

Distinct2969
Distinct (%)29.7%
Missing3
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-13T03:25:19.775451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length6.6145844
Min length2

Characters and Unicode

Total characters66126
Distinct characters45
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1767 ?
Unique (%)17.7%

Sample

1st rowQP517.C45
2nd rowTX560.F47
3rd rowSB950
4th rowHB3730
5th rowQH431
ValueCountFrequency (%)
qp601 336
 
3.2%
qh506 322
 
3.1%
qh301 207
 
2.0%
md 155
 
1.5%
g154.7 138
 
1.3%
qp551 124
 
1.2%
qh324.2 84
 
0.8%
tp248.2 81
 
0.8%
qk355 76
 
0.7%
tp248.3 73
 
0.7%
Other values (2877) 8773
84.6%
2023-12-13T03:25:20.227560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 5668
 
8.6%
. 5561
 
8.4%
Q 5341
 
8.1%
1 5149
 
7.8%
6 4227
 
6.4%
4 4181
 
6.3%
2 4059
 
6.1%
3 3868
 
5.8%
9 2876
 
4.3%
0 2871
 
4.3%
Other values (35) 22325
33.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38515
58.2%
Uppercase Letter 21496
32.5%
Other Punctuation 5561
 
8.4%
Space Separator 372
 
0.6%
Dash Punctuation 176
 
0.3%
Other Letter 5
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Q 5341
24.8%
H 2566
11.9%
P 2478
11.5%
R 1839
 
8.6%
D 1194
 
5.6%
K 986
 
4.6%
T 886
 
4.1%
S 859
 
4.0%
B 855
 
4.0%
L 753
 
3.5%
Other values (16) 3739
17.4%
Decimal Number
ValueCountFrequency (%)
5 5668
14.7%
1 5149
13.4%
6 4227
11.0%
4 4181
10.9%
2 4059
10.5%
3 3868
10.0%
9 2876
7.5%
0 2871
7.5%
7 2836
7.4%
8 2780
7.2%
Other Letter
ValueCountFrequency (%)
김 1
20.0%
홍 1
20.0%
피 1
20.0%
황 1
20.0%
박 1
20.0%
Other Punctuation
ValueCountFrequency (%)
. 5561
100.0%
Space Separator
ValueCountFrequency (%)
372
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 176
100.0%
Lowercase Letter
ValueCountFrequency (%)
l 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 44624
67.5%
Latin 21497
32.5%
Hangul 5
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
Q 5341
24.8%
H 2566
11.9%
P 2478
11.5%
R 1839
 
8.6%
D 1194
 
5.6%
K 986
 
4.6%
T 886
 
4.1%
S 859
 
4.0%
B 855
 
4.0%
L 753
 
3.5%
Other values (17) 3740
17.4%
Common
ValueCountFrequency (%)
5 5668
12.7%
. 5561
12.5%
1 5149
11.5%
6 4227
9.5%
4 4181
9.4%
2 4059
9.1%
3 3868
8.7%
9 2876
6.4%
0 2871
6.4%
7 2836
6.4%
Other values (3) 3328
7.5%
Hangul
ValueCountFrequency (%)
김 1
20.0%
홍 1
20.0%
피 1
20.0%
황 1
20.0%
박 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66121
> 99.9%
Hangul 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 5668
 
8.6%
. 5561
 
8.4%
Q 5341
 
8.1%
1 5149
 
7.8%
6 4227
 
6.4%
4 4181
 
6.3%
2 4059
 
6.1%
3 3868
 
5.8%
9 2876
 
4.3%
0 2871
 
4.3%
Other values (30) 22320
33.8%
Hangul
ValueCountFrequency (%)
김 1
20.0%
홍 1
20.0%
피 1
20.0%
황 1
20.0%
박 1
20.0%

도서
Text

MISSING 

Distinct6733
Distinct (%)68.6%
Missing181
Missing (%)1.8%
Memory size156.2 KiB
2023-12-13T03:25:20.612325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length8.7515022
Min length3

Characters and Unicode

Total characters85931
Distinct characters496
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5530 ?
Unique (%)56.3%

Sample

1st row.B55 1995
2nd row박13 2009
3rd row.E365 1996
4th row토798 2006
5th row장295 2015
ValueCountFrequency (%)
2 577
 
2.9%
2003 406
 
2.0%
2005 376
 
1.9%
2004 374
 
1.9%
1994 363
 
1.8%
2002 357
 
1.8%
2007 339
 
1.7%
1995 318
 
1.6%
3 313
 
1.6%
2011 313
 
1.6%
Other values (3972) 16431
81.5%
2023-12-13T03:25:21.195548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10350
12.0%
0 9839
11.4%
2 8822
10.3%
9 8335
9.7%
1 8067
9.4%
. 5281
 
6.1%
4 4304
 
5.0%
5 4197
 
4.9%
6 4069
 
4.7%
3 3817
 
4.4%
Other values (486) 18850
21.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58845
68.5%
Space Separator 10350
 
12.0%
Uppercase Letter 5289
 
6.2%
Other Punctuation 5281
 
6.1%
Other Letter 4578
 
5.3%
Dash Punctuation 1532
 
1.8%
Lowercase Letter 56
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 233
 
5.1%
한 230
 
5.0%
김 209
 
4.6%
박 109
 
2.4%
세 104
 
2.3%
유 83
 
1.8%
생 75
 
1.6%
조 70
 
1.5%
정 70
 
1.5%
중 65
 
1.4%
Other values (441) 3330
72.7%
Uppercase Letter
ValueCountFrequency (%)
M 898
17.0%
A 489
 
9.2%
C 461
 
8.7%
B 373
 
7.1%
S 366
 
6.9%
P 353
 
6.7%
E 235
 
4.4%
I 228
 
4.3%
F 218
 
4.1%
H 211
 
4.0%
Other values (16) 1457
27.5%
Decimal Number
ValueCountFrequency (%)
0 9839
16.7%
2 8822
15.0%
9 8335
14.2%
1 8067
13.7%
4 4304
7.3%
5 4197
7.1%
6 4069
6.9%
3 3817
 
6.5%
7 3786
 
6.4%
8 3609
 
6.1%
Lowercase Letter
ValueCountFrequency (%)
t 47
83.9%
p 4
 
7.1%
u 2
 
3.6%
x 1
 
1.8%
s 1
 
1.8%
l 1
 
1.8%
Space Separator
ValueCountFrequency (%)
10350
100.0%
Other Punctuation
ValueCountFrequency (%)
. 5281
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1532
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 76008
88.5%
Latin 5345
 
6.2%
Hangul 4578
 
5.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 233
 
5.1%
한 230
 
5.0%
김 209
 
4.6%
박 109
 
2.4%
세 104
 
2.3%
유 83
 
1.8%
생 75
 
1.6%
조 70
 
1.5%
정 70
 
1.5%
중 65
 
1.4%
Other values (441) 3330
72.7%
Latin
ValueCountFrequency (%)
M 898
16.8%
A 489
 
9.1%
C 461
 
8.6%
B 373
 
7.0%
S 366
 
6.8%
P 353
 
6.6%
E 235
 
4.4%
I 228
 
4.3%
F 218
 
4.1%
H 211
 
3.9%
Other values (22) 1513
28.3%
Common
ValueCountFrequency (%)
10350
13.6%
0 9839
12.9%
2 8822
11.6%
9 8335
11.0%
1 8067
10.6%
. 5281
6.9%
4 4304
5.7%
5 4197
5.5%
6 4069
 
5.4%
3 3817
 
5.0%
Other values (3) 8927
11.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 81353
94.7%
Hangul 4543
 
5.3%
Compat Jamo 35
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10350
12.7%
0 9839
12.1%
2 8822
10.8%
9 8335
10.2%
1 8067
9.9%
. 5281
 
6.5%
4 4304
 
5.3%
5 4197
 
5.2%
6 4069
 
5.0%
3 3817
 
4.7%
Other values (35) 14272
17.5%
Hangul
ValueCountFrequency (%)
이 233
 
5.1%
한 230
 
5.1%
김 209
 
4.6%
박 109
 
2.4%
세 104
 
2.3%
유 83
 
1.8%
생 75
 
1.7%
조 70
 
1.5%
정 70
 
1.5%
중 65
 
1.4%
Other values (430) 3295
72.5%
Compat Jamo
ValueCountFrequency (%)
ㅎ 7
20.0%
ㅇ 6
17.1%
ㅅ 5
14.3%
ㄱ 4
11.4%
ㅈ 4
11.4%
ㅁ 2
 
5.7%
ㅂ 2
 
5.7%
ㄴ 2
 
5.7%
ㅍ 1
 
2.9%
ㄷ 1
 
2.9%

권년차
Text

MISSING 

Distinct633
Distinct (%)20.2%
Missing6862
Missing (%)68.6%
Memory size156.2 KiB
2023-12-13T03:25:21.611167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.8540472
Min length2

Characters and Unicode

Total characters12094
Distinct characters35
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

Unique330 ?
Unique (%)10.5%

Sample

1st rowv.1
2nd rowv.12
3rd rowv.1
4th rowv.2
5th rowv.21-2
ValueCountFrequency (%)
v.1 450
 
14.3%
v.2 436
 
13.9%
v.3 180
 
5.7%
v.4 108
 
3.4%
v.5 86
 
2.7%
v.6 62
 
2.0%
v.7 59
 
1.9%
v.8 45
 
1.4%
v.10 36
 
1.1%
v.9 35
 
1.1%
Other values (620) 1644
52.3%
2023-12-13T03:25:22.156028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 2906
24.0%
v 2890
23.9%
1 1419
11.7%
2 1288
10.6%
3 623
 
5.2%
0 537
 
4.4%
4 420
 
3.5%
5 367
 
3.0%
6 358
 
3.0%
9 330
 
2.7%
Other values (25) 956
 
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5905
48.8%
Lowercase Letter 2931
24.2%
Other Punctuation 2924
24.2%
Dash Punctuation 215
 
1.8%
Uppercase Letter 65
 
0.5%
Close Punctuation 24
 
0.2%
Open Punctuation 24
 
0.2%
Space Separator 3
 
< 0.1%
Other Letter 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1419
24.0%
2 1288
21.8%
3 623
10.6%
0 537
 
9.1%
4 420
 
7.1%
5 367
 
6.2%
6 358
 
6.1%
9 330
 
5.6%
7 285
 
4.8%
8 278
 
4.7%
Lowercase Letter
ValueCountFrequency (%)
v 2890
98.6%
p 17
 
0.6%
t 15
 
0.5%
a 3
 
0.1%
c 2
 
0.1%
s 1
 
< 0.1%
u 1
 
< 0.1%
e 1
 
< 0.1%
b 1
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
B 22
33.8%
A 21
32.3%
I 17
26.2%
P 2
 
3.1%
C 2
 
3.1%
F 1
 
1.5%
Other Punctuation
ValueCountFrequency (%)
. 2906
99.4%
/ 17
 
0.6%
, 1
 
< 0.1%
Other Letter
ValueCountFrequency (%)
해 1
33.3%
설 1
33.3%
서 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 215
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9095
75.2%
Latin 2996
 
24.8%
Hangul 3
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 2906
32.0%
1 1419
15.6%
2 1288
14.2%
3 623
 
6.8%
0 537
 
5.9%
4 420
 
4.6%
5 367
 
4.0%
6 358
 
3.9%
9 330
 
3.6%
7 285
 
3.1%
Other values (7) 562
 
6.2%
Latin
ValueCountFrequency (%)
v 2890
96.5%
B 22
 
0.7%
A 21
 
0.7%
p 17
 
0.6%
I 17
 
0.6%
t 15
 
0.5%
a 3
 
0.1%
P 2
 
0.1%
c 2
 
0.1%
C 2
 
0.1%
Other values (5) 5
 
0.2%
Hangul
ValueCountFrequency (%)
해 1
33.3%
설 1
33.3%
서 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12091
> 99.9%
Hangul 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 2906
24.0%
v 2890
23.9%
1 1419
11.7%
2 1288
10.7%
3 623
 
5.2%
0 537
 
4.4%
4 420
 
3.5%
5 367
 
3.0%
6 358
 
3.0%
9 330
 
2.7%
Other values (22) 953
 
7.9%
Hangul
ValueCountFrequency (%)
해 1
33.3%
설 1
33.3%
서 1
33.3%

복본
Categorical

IMBALANCE 

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8813 
c.2
 
877
c.3
 
227
c.4
 
53
c.5
 
12
Other values (9)
 
18

Length

Max length4
Median length4
Mean length3.8815
Min length3

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8813
88.1%
c.2 877
 
8.8%
c.3 227
 
2.3%
c.4 53
 
0.5%
c.5 12
 
0.1%
v.1 4
 
< 0.1%
c.7 3
 
< 0.1%
c.6 3
 
< 0.1%
v.3 2
 
< 0.1%
v.2 2
 
< 0.1%
Other values (4) 4
 
< 0.1%

Length

2023-12-13T03:25:22.292306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8813
88.1%
c.2 877
 
8.8%
c.3 227
 
2.3%
c.4 53
 
0.5%
c.5 12
 
0.1%
v.1 4
 
< 0.1%
c.7 3
 
< 0.1%
c.6 3
 
< 0.1%
v.3 2
 
< 0.1%
v.2 2
 
< 0.1%
Other values (4) 4
 
< 0.1%

Interactions

2023-12-13T03:25:14.679897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:25:14.474956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:25:14.806270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:25:14.578069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:25:22.380616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록번호출판년복본
등록번호1.0000.8450.197
출판년0.8451.0000.163
복본0.1970.1631.000
2023-12-13T03:25:22.474040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록번호출판년복본
등록번호1.0000.8960.082
출판년0.8961.0000.081
복본0.0820.0811.000

Missing values

2023-12-13T03:25:15.007553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:25:15.197868image/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.
2023-12-13T03:25:15.355181image/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

등록번호서명저자출판사출판년분류도서권년차복본
18762583Bioinformatics : from nucleic acids and proteins to cell metabolism ; from nucleic acids and proteins to cell metabolism ; contributions to the conference on "Bioinformatics", October 9 to 11, 1995, BSchomburg, DietmarVCH1995QP517.C45.B55 1995<NA><NA>
1013112979장류의 과학과 건강기능성박건영한국장류협동조합2009TX560.F47박13 2009<NA><NA>
57187763Ecologically based pest management : new solutions for a new centuryNational Research Council (U.S.)National Academy Press1996SB950.E365 1996<NA><NA>
880411551(앨빈 토플러)부의 미래토플러, 앨빈청림출판2006HB3730토798 2006<NA><NA>
1367516909進化の謎をゲノムで解く長谷部, 光泰學硏メディカル秀潤社2015QH431장295 2015<NA><NA>
1358916823바이오센서 응용분야별 R&D현황 및 나노바이오융합 기술/시장분석R&D정보센터지식산업정보원2015MD 2015 -14<NA><NA><NA>
13901919The model leader : a fully functioning personHitt, William DBattelle Press1993HD57.7.H58 1993<NA><NA>
952112299커피조윤정대원사2007TX415조37 2007<NA><NA>
1386017122웃으면서 죽음을 이야기하는 방법최세희다산북스2016PR6052.A6657웃68 2016<NA><NA>
12021429EDI通信과 保安임승택컴퓨터월드 출판사업부1994TK3226임57 1994<NA><NA>
등록번호서명저자출판사출판년분류도서권년차복본
1491618215바이오의약품 산업분석보고서비피기술거래비티타임즈2018MD 2018 -10<NA><NA><NA>
68068946Microbes : an invisible universeGest, HowardASM Press2003QR41.2.G468 2003<NA><NA>
37015266Integrin protocolsHowlett, AnthonyHumana Press1999QH506.M48 1999v.129<NA>
749761Vitamins and hormones<NA>Academic Press1943QP801.V5.V5v.26<NA>
647653Progress in nucleic acid research and molecular biologyDavidson, J. NAcademic Press1963QP551.P695v.18<NA>
188192Aqueous two-phase systemsWalter, HarryAcademic Press1994QP601.M49 1994v.228<NA>
63768493정부지원제도총람한국산업정보원한국산업정보원2003HD62.5정462003<NA>
23673337Nuclear magnetic resonance and nucleic acidsJames, Thomas LAcademic Press1995QP601.M49 1995v.261<NA>
60918171Marek's diseaseHirai, KanjiSpringer2001QR1.C9 2001v.255<NA>
1044513338바우돌리노 : 움베르토 에코 장편소설 상-하에코, 움베르토열린책들2002PQ4865.C65바67 2002v.1<NA>