Overview

Dataset statistics

Number of variables8
Number of observations8183
Missing cells85
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory519.6 KiB
Average record size in memory65.0 B

Variable types

Numeric1
Text6
Categorical1

Dataset

Description한국지식재산전문도서관 IP서지정보입니다
Author한국지식재산연구원
URLhttps://www.data.go.kr/data/15055895/fileData.do

Alerts

순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 03:49:54.815011
Analysis finished2023-12-12 03:49:58.349412
Duration3.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct8183
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4092
Minimum1
Maximum8183
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size72.0 KiB
2023-12-12T12:49:58.439430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile410.1
Q12046.5
median4092
Q36137.5
95-th percentile7773.9
Maximum8183
Range8182
Interquartile range (IQR)4091

Descriptive statistics

Standard deviation2362.373
Coefficient of variation (CV)0.577315
Kurtosis-1.2
Mean4092
Median Absolute Deviation (MAD)2046
Skewness0
Sum33484836
Variance5580806
MonotonicityStrictly increasing
2023-12-12T12:49:58.585473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
5452 1
 
< 0.1%
5465 1
 
< 0.1%
5464 1
 
< 0.1%
5463 1
 
< 0.1%
5462 1
 
< 0.1%
5461 1
 
< 0.1%
5460 1
 
< 0.1%
5459 1
 
< 0.1%
5458 1
 
< 0.1%
Other values (8173) 8173
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
8183 1
< 0.1%
8182 1
< 0.1%
8181 1
< 0.1%
8180 1
< 0.1%
8179 1
< 0.1%
8178 1
< 0.1%
8177 1
< 0.1%
8176 1
< 0.1%
8175 1
< 0.1%
8174 1
< 0.1%

서명
Text

Distinct6026
Distinct (%)73.6%
Missing0
Missing (%)0.0%
Memory size64.1 KiB
2023-12-12T12:49:58.883589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length258
Median length180
Mean length36.605524
Min length3

Characters and Unicode

Total characters299543
Distinct characters1789
Distinct categories17 ?
Distinct scripts6 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4901 ?
Unique (%)59.9%

Sample

1st rowA Patented World?: Privatisation of Life and Knowledge
2nd rowAll You Need to Know About the Music Business
3rd rowAmerican Corporate Identity 2006
4th rowBlackstone's Statutes on Intellectual Property
5th rowCyber Forensics : A Field Manual for Collecting, Examining, and Preserving Evidence of Computer Crimes
ValueCountFrequency (%)
2279
 
4.8%
and 1398
 
2.9%
the 1083
 
2.3%
of 996
 
2.1%
intellectual 758
 
1.6%
property 738
 
1.5%
및 601
 
1.3%
patent 532
 
1.1%
연구 520
 
1.1%
law 499
 
1.0%
Other values (10793) 38306
80.3%
2023-12-12T12:49:59.598935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
47290
 
15.8%
e 14246
 
4.8%
t 12448
 
4.2%
n 11314
 
3.8%
a 11040
 
3.7%
o 9149
 
3.1%
i 8871
 
3.0%
r 8275
 
2.8%
l 6159
 
2.1%
s 6009
 
2.0%
Other values (1779) 164742
55.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 118624
39.6%
Other Letter 97919
32.7%
Space Separator 47316
 
15.8%
Uppercase Letter 16712
 
5.6%
Decimal Number 8148
 
2.7%
Other Punctuation 6164
 
2.1%
Close Punctuation 1396
 
0.5%
Open Punctuation 1391
 
0.5%
Dash Punctuation 1077
 
0.4%
Math Symbol 502
 
0.2%
Other values (7) 294
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 1753
 
1.8%
산 1603
 
1.6%
의 1526
 
1.6%
한 1363
 
1.4%
재 1345
 
1.4%
の 1233
 
1.3%
제 1193
 
1.2%
기 1184
 
1.2%
연 1125
 
1.1%
식 1119
 
1.1%
Other values (1641) 84475
86.3%
Lowercase Letter
ValueCountFrequency (%)
e 14246
12.0%
t 12448
10.5%
n 11314
9.5%
a 11040
9.3%
o 9149
 
7.7%
i 8871
 
7.5%
r 8275
 
7.0%
l 6159
 
5.2%
s 6009
 
5.1%
c 4495
 
3.8%
Other values (26) 26618
22.4%
Uppercase Letter
ValueCountFrequency (%)
P 2588
15.5%
I 2143
12.8%
T 1634
9.8%
C 1426
 
8.5%
A 1053
 
6.3%
S 854
 
5.1%
R 800
 
4.8%
E 765
 
4.6%
D 704
 
4.2%
L 701
 
4.2%
Other values (16) 4044
24.2%
Other Punctuation
ValueCountFrequency (%)
: 2450
39.7%
, 1107
18.0%
. 1104
17.9%
· 575
 
9.3%
& 327
 
5.3%
/ 207
 
3.4%
' 140
 
2.3%
・ 115
 
1.9%
? 38
 
0.6%
! 34
 
0.6%
Other values (9) 67
 
1.1%
Decimal Number
ValueCountFrequency (%)
0 2170
26.6%
2 1986
24.4%
1 1900
23.3%
3 424
 
5.2%
9 399
 
4.9%
5 283
 
3.5%
4 270
 
3.3%
8 265
 
3.3%
7 241
 
3.0%
6 205
 
2.5%
Other values (4) 5
 
0.1%
Letter Number
ValueCountFrequency (%)
Ⅰ 61
34.5%
Ⅱ 50
28.2%
Ⅲ 30
16.9%
Ⅳ 23
 
13.0%
Ⅴ 4
 
2.3%
Ⅵ 4
 
2.3%
Ⅹ 1
 
0.6%
Ⅷ 1
 
0.6%
〇 1
 
0.6%
Ⅶ 1
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 1252
89.7%
] 83
 
5.9%
」 52
 
3.7%
〉 5
 
0.4%
』 2
 
0.1%
） 1
 
0.1%
〕 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
= 422
84.1%
~ 43
 
8.6%
> 11
 
2.2%
< 11
 
2.2%
| 9
 
1.8%
∼ 4
 
0.8%
+ 2
 
0.4%
Open Punctuation
ValueCountFrequency (%)
( 1251
89.9%
[ 80
 
5.8%
「 52
 
3.7%
〈 5
 
0.4%
『 2
 
0.1%
〔 1
 
0.1%
Space Separator
ValueCountFrequency (%)
47290
99.9%
　 25
 
0.1%
  1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 867
80.5%
― 210
 
19.5%
Modifier Letter
ValueCountFrequency (%)
ー 89
98.9%
々 1
 
1.1%
Modifier Symbol
ValueCountFrequency (%)
` 11
100.0%
Control
ValueCountFrequency (%)
10
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%
Other Symbol
ValueCountFrequency (%)
〓 1
100.0%
Final Punctuation
ValueCountFrequency (%)
” 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 135512
45.2%
Hangul 67844
22.6%
Common 66110
22.1%
Han 20944
 
7.0%
Hiragana 4993
 
1.7%
Katakana 4140
 
1.4%

Most frequent character per script

Han
ValueCountFrequency (%)
法 851
 
4.1%
知 717
 
3.4%
特 663
 
3.2%
許 660
 
3.2%
産 655
 
3.1%
的 641
 
3.1%
財 623
 
3.0%
權 408
 
1.9%
業 278
 
1.3%
國 239
 
1.1%
Other values (930) 15209
72.6%
Hangul
ValueCountFrequency (%)
지 1753
 
2.6%
산 1603
 
2.4%
의 1526
 
2.2%
한 1363
 
2.0%
재 1345
 
2.0%
제 1193
 
1.8%
기 1184
 
1.7%
연 1125
 
1.7%
식 1119
 
1.6%
국 1119
 
1.6%
Other values (567) 54514
80.4%
Katakana
ValueCountFrequency (%)
ン 341
 
8.2%
ス 249
 
6.0%
イ 232
 
5.6%
ト 194
 
4.7%
ア 159
 
3.8%
ド 146
 
3.5%
ジ 142
 
3.4%
ネ 129
 
3.1%
ル 124
 
3.0%
ク 115
 
2.8%
Other values (65) 2309
55.8%
Latin
ValueCountFrequency (%)
e 14246
 
10.5%
t 12448
 
9.2%
n 11314
 
8.3%
a 11040
 
8.1%
o 9149
 
6.8%
i 8871
 
6.5%
r 8275
 
6.1%
l 6159
 
4.5%
s 6009
 
4.4%
c 4495
 
3.3%
Other values (62) 43506
32.1%
Common
ValueCountFrequency (%)
47290
71.5%
: 2450
 
3.7%
0 2170
 
3.3%
2 1986
 
3.0%
1 1900
 
2.9%
) 1252
 
1.9%
( 1251
 
1.9%
, 1107
 
1.7%
. 1104
 
1.7%
- 867
 
1.3%
Other values (54) 4733
 
7.2%
Hiragana
ValueCountFrequency (%)
の 1233
24.7%
る 394
 
7.9%
と 387
 
7.8%
に 335
 
6.7%
か 195
 
3.9%
す 175
 
3.5%
た 172
 
3.4%
を 148
 
3.0%
め 126
 
2.5%
て 107
 
2.1%
Other values (51) 1721
34.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 200239
66.8%
Hangul 67836
 
22.6%
CJK 20780
 
6.9%
Hiragana 4993
 
1.7%
Katakana 4344
 
1.5%
None 789
 
0.3%
Punctuation 212
 
0.1%
Number Forms 176
 
0.1%
CJK Compat Ideographs 162
 
0.1%
Compat Jamo 8
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
47290
23.6%
e 14246
 
7.1%
t 12448
 
6.2%
n 11314
 
5.7%
a 11040
 
5.5%
o 9149
 
4.6%
i 8871
 
4.4%
r 8275
 
4.1%
l 6159
 
3.1%
s 6009
 
3.0%
Other values (78) 65438
32.7%
Hangul
ValueCountFrequency (%)
지 1753
 
2.6%
산 1603
 
2.4%
의 1526
 
2.2%
한 1363
 
2.0%
재 1345
 
2.0%
제 1193
 
1.8%
기 1184
 
1.7%
연 1125
 
1.7%
식 1119
 
1.6%
국 1119
 
1.6%
Other values (566) 54506
80.3%
Hiragana
ValueCountFrequency (%)
の 1233
24.7%
る 394
 
7.9%
と 387
 
7.8%
に 335
 
6.7%
か 195
 
3.9%
す 175
 
3.5%
た 172
 
3.4%
を 148
 
3.0%
め 126
 
2.5%
て 107
 
2.1%
Other values (51) 1721
34.5%
CJK
ValueCountFrequency (%)
法 851
 
4.1%
知 717
 
3.5%
特 663
 
3.2%
許 660
 
3.2%
産 655
 
3.2%
的 641
 
3.1%
財 623
 
3.0%
權 408
 
2.0%
業 278
 
1.3%
國 239
 
1.2%
Other values (903) 15045
72.4%
None
ValueCountFrequency (%)
· 575
72.9%
」 52
 
6.6%
「 52
 
6.6%
　 25
 
3.2%
é 21
 
2.7%
、 12
 
1.5%
〈 5
 
0.6%
〉 5
 
0.6%
è 4
 
0.5%
！ 4
 
0.5%
Other values (24) 34
 
4.3%
Katakana
ValueCountFrequency (%)
ン 341
 
7.8%
ス 249
 
5.7%
イ 232
 
5.3%
ト 194
 
4.5%
ア 159
 
3.7%
ド 146
 
3.4%
ジ 142
 
3.3%
ネ 129
 
3.0%
ル 124
 
2.9%
・ 115
 
2.6%
Other values (67) 2513
57.8%
Punctuation
ValueCountFrequency (%)
― 210
99.1%
‧ 1
 
0.5%
” 1
 
0.5%
Number Forms
ValueCountFrequency (%)
Ⅰ 61
34.7%
Ⅱ 50
28.4%
Ⅲ 30
17.0%
Ⅳ 23
 
13.1%
Ⅴ 4
 
2.3%
Ⅵ 4
 
2.3%
Ⅹ 1
 
0.6%
Ⅷ 1
 
0.6%
Ⅶ 1
 
0.6%
Ⅸ 1
 
0.6%
CJK Compat Ideographs
ValueCountFrequency (%)
理 41
25.3%
論 15
 
9.3%
連 13
 
8.0%
六 12
 
7.4%
不 12
 
7.4%
利 12
 
7.4%
量 9
 
5.6%
年 8
 
4.9%
立 5
 
3.1%
留 5
 
3.1%
Other values (15) 30
18.5%
Compat Jamo
ValueCountFrequency (%)
ㆍ 8
100.0%
Math Operators
ValueCountFrequency (%)
∼ 4
100.0%

저자
Text

Distinct3165
Distinct (%)38.9%
Missing41
Missing (%)0.5%
Memory size64.1 KiB
2023-12-12T12:49:59.892992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length102
Median length76
Mean length8.9427659
Min length2

Characters and Unicode

Total characters72812
Distinct characters1276
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

Unique2174 ?
Unique (%)26.7%

Sample

1st rowAgostino, Ana
2nd rowPassman, Donald S
3rd rowCarter, David E
4th rowChristie, Andrew
5th rowMarcella, Albert J
ValueCountFrequency (%)
한국지식재산연구원 813
 
6.7%
특허청 725
 
6.0%
특허심판원 174
 
1.4%
united 112
 
0.9%
states 109
 
0.9%
property 108
 
0.9%
intellectual 88
 
0.7%
iip(知的財産硏究所 82
 
0.7%
organization 78
 
0.6%
office 78
 
0.6%
Other values (3947) 9748
80.5%
2023-12-12T12:50:00.460717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3977
 
5.5%
e 3268
 
4.5%
a 2677
 
3.7%
n 2339
 
3.2%
r 2308
 
3.2%
i 2195
 
3.0%
t 2163
 
3.0%
o 2088
 
2.9%
l 1516
 
2.1%
, 1470
 
2.0%
Other values (1266) 48811
67.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 32648
44.8%
Lowercase Letter 26820
36.8%
Uppercase Letter 7014
 
9.6%
Space Separator 3982
 
5.5%
Other Punctuation 1698
 
2.3%
Close Punctuation 246
 
0.3%
Open Punctuation 244
 
0.3%
Dash Punctuation 96
 
0.1%
Modifier Letter 56
 
0.1%
Other Symbol 4
 
< 0.1%
Other values (2) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 1435
 
4.4%
국 1293
 
4.0%
한 1280
 
3.9%
산 1147
 
3.5%
지 1144
 
3.5%
재 1143
 
3.5%
연 1126
 
3.4%
식 1083
 
3.3%
구 1058
 
3.2%
허 1021
 
3.1%
Other values (1188) 20918
64.1%
Lowercase Letter
ValueCountFrequency (%)
e 3268
12.2%
a 2677
10.0%
n 2339
 
8.7%
r 2308
 
8.6%
i 2195
 
8.2%
t 2163
 
8.1%
o 2088
 
7.8%
l 1516
 
5.7%
s 1367
 
5.1%
h 970
 
3.6%
Other values (18) 5929
22.1%
Uppercase Letter
ValueCountFrequency (%)
P 665
 
9.5%
I 609
 
8.7%
S 524
 
7.5%
M 482
 
6.9%
C 482
 
6.9%
A 468
 
6.7%
R 345
 
4.9%
J 317
 
4.5%
D 314
 
4.5%
W 296
 
4.2%
Other values (16) 2512
35.8%
Other Punctuation
ValueCountFrequency (%)
, 1470
86.6%
. 172
 
10.1%
& 39
 
2.3%
' 7
 
0.4%
· 4
 
0.2%
， 2
 
0.1%
: 1
 
0.1%
・ 1
 
0.1%
＆ 1
 
0.1%
/ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
3977
99.9%
　 5
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 243
98.8%
] 3
 
1.2%
Open Punctuation
ValueCountFrequency (%)
( 243
99.6%
[ 1
 
0.4%
Dash Punctuation
ValueCountFrequency (%)
- 54
56.2%
― 42
43.8%
Modifier Letter
ValueCountFrequency (%)
ー 54
96.4%
々 2
 
3.6%
Decimal Number
ValueCountFrequency (%)
3 2
66.7%
5 1
33.3%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 33835
46.5%
Hangul 22846
31.4%
Han 9213
 
12.7%
Common 6323
 
8.7%
Katakana 556
 
0.8%
Hiragana 39
 
0.1%

Most frequent character per script

Han
ValueCountFrequency (%)
産 272
 
3.0%
知 261
 
2.8%
財 253
 
2.7%
的 240
 
2.6%
所 230
 
2.5%
究 222
 
2.4%
會 202
 
2.2%
硏 174
 
1.9%
田 162
 
1.8%
本 159
 
1.7%
Other values (755) 7038
76.4%
Hangul
ValueCountFrequency (%)
원 1435
 
6.3%
국 1293
 
5.7%
한 1280
 
5.6%
산 1147
 
5.0%
지 1144
 
5.0%
재 1143
 
5.0%
연 1126
 
4.9%
식 1083
 
4.7%
구 1058
 
4.6%
허 1021
 
4.5%
Other values (342) 11116
48.7%
Katakana
ValueCountFrequency (%)
ン 66
 
11.9%
タ 33
 
5.9%
セ 31
 
5.6%
イ 21
 
3.8%
ク 21
 
3.8%
リ 21
 
3.8%
ト 20
 
3.6%
ル 20
 
3.6%
グ 16
 
2.9%
ッ 15
 
2.7%
Other values (52) 292
52.5%
Latin
ValueCountFrequency (%)
e 3268
 
9.7%
a 2677
 
7.9%
n 2339
 
6.9%
r 2308
 
6.8%
i 2195
 
6.5%
t 2163
 
6.4%
o 2088
 
6.2%
l 1516
 
4.5%
s 1367
 
4.0%
h 970
 
2.9%
Other values (45) 12944
38.3%
Common
ValueCountFrequency (%)
3977
62.9%
, 1470
 
23.2%
) 243
 
3.8%
( 243
 
3.8%
. 172
 
2.7%
- 54
 
0.9%
ー 54
 
0.9%
― 42
 
0.7%
& 39
 
0.6%
' 7
 
0.1%
Other values (11) 22
 
0.3%
Hiragana
ValueCountFrequency (%)
り 4
 
10.3%
も 4
 
10.3%
へ 4
 
10.3%
か 3
 
7.7%
き 3
 
7.7%
さ 2
 
5.1%
ら 2
 
5.1%
ゆ 2
 
5.1%
ち 2
 
5.1%
い 2
 
5.1%
Other values (11) 11
28.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40042
55.0%
Hangul 22842
31.4%
CJK 9148
 
12.6%
Katakana 611
 
0.8%
CJK Compat Ideographs 63
 
0.1%
Punctuation 42
 
0.1%
Hiragana 39
 
0.1%
None 24
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3977
 
9.9%
e 3268
 
8.2%
a 2677
 
6.7%
n 2339
 
5.8%
r 2308
 
5.8%
i 2195
 
5.5%
t 2163
 
5.4%
o 2088
 
5.2%
l 1516
 
3.8%
, 1470
 
3.7%
Other values (56) 16041
40.1%
Hangul
ValueCountFrequency (%)
원 1435
 
6.3%
국 1293
 
5.7%
한 1280
 
5.6%
산 1147
 
5.0%
지 1144
 
5.0%
재 1143
 
5.0%
연 1126
 
4.9%
식 1083
 
4.7%
구 1058
 
4.6%
허 1021
 
4.5%
Other values (341) 11112
48.6%
CJK
ValueCountFrequency (%)
産 272
 
3.0%
知 261
 
2.9%
財 253
 
2.8%
的 240
 
2.6%
所 230
 
2.5%
究 222
 
2.4%
會 202
 
2.2%
硏 174
 
1.9%
田 162
 
1.8%
本 159
 
1.7%
Other values (737) 6973
76.2%
Katakana
ValueCountFrequency (%)
ン 66
 
10.8%
ー 54
 
8.8%
タ 33
 
5.4%
セ 31
 
5.1%
イ 21
 
3.4%
ク 21
 
3.4%
リ 21
 
3.4%
ト 20
 
3.3%
ル 20
 
3.3%
グ 16
 
2.6%
Other values (54) 308
50.4%
Punctuation
ValueCountFrequency (%)
― 42
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
李 15
23.8%
龍 10
15.9%
奈 6
 
9.5%
盧 5
 
7.9%
郎 5
 
7.9%
論 4
 
6.3%
隆 4
 
6.3%
烈 2
 
3.2%
良 2
 
3.2%
復 2
 
3.2%
Other values (7) 8
12.7%
None
ValueCountFrequency (%)
　 5
20.8%
ü 5
20.8%
㈜ 4
16.7%
· 4
16.7%
， 2
 
8.3%
々 2
 
8.3%
é 1
 
4.2%
＆ 1
 
4.2%
Hiragana
ValueCountFrequency (%)
り 4
 
10.3%
も 4
 
10.3%
へ 4
 
10.3%
か 3
 
7.7%
き 3
 
7.7%
さ 2
 
5.1%
ら 2
 
5.1%
ゆ 2
 
5.1%
ち 2
 
5.1%
い 2
 
5.1%
Other values (11) 11
28.2%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

출판사
Text

Distinct1660
Distinct (%)20.4%
Missing41
Missing (%)0.5%
Memory size64.1 KiB
2023-12-12T12:50:00.919663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length75
Median length46
Mean length8.9948416
Min length2

Characters and Unicode

Total characters73236
Distinct characters801
Distinct categories12 ?
Distinct scripts8 ?
Distinct blocks10 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique951 ?
Unique (%)11.7%

Sample

1st rowIndependent
2nd rowSimon & Schuste
3rd rowHarpercollins
4th rowOxford U.K
5th rowCRC
ValueCountFrequency (%)
특허청 866
 
8.6%
한국지식재산연구원 742
 
7.4%
한국지식재산연구원(kiip 346
 
3.5%
press 229
 
2.3%
대외경제정책연구원(kiep 224
 
2.2%
lexisnexis 172
 
1.7%
특허심판원 169
 
1.7%
wipo 152
 
1.5%
books 144
 
1.4%
oxford 131
 
1.3%
Other values (1446) 6849
68.3%
2023-12-12T12:50:01.537606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5034
 
6.9%
e 2320
 
3.2%
원 2151
 
2.9%
한 1931
 
2.6%
s 1873
 
2.6%
I 1862
 
2.5%
국 1775
 
2.4%
연 1704
 
2.3%
r 1691
 
2.3%
구 1676
 
2.3%
Other values (791) 51219
69.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37884
51.7%
Lowercase Letter 18366
25.1%
Uppercase Letter 9621
 
13.1%
Space Separator 5036
 
6.9%
Open Punctuation 964
 
1.3%
Close Punctuation 964
 
1.3%
Other Punctuation 211
 
0.3%
Dash Punctuation 73
 
0.1%
Modifier Letter 56
 
0.1%
Decimal Number 50
 
0.1%
Other values (2) 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 2151
 
5.7%
한 1931
 
5.1%
국 1775
 
4.7%
연 1704
 
4.5%
구 1676
 
4.4%
지 1398
 
3.7%
산 1377
 
3.6%
재 1252
 
3.3%
식 1246
 
3.3%
허 1113
 
2.9%
Other values (713) 22261
58.8%
Uppercase Letter
ValueCountFrequency (%)
I 1862
19.4%
P 1578
16.4%
K 860
 
8.9%
E 700
 
7.3%
O 481
 
5.0%
W 422
 
4.4%
L 401
 
4.2%
A 383
 
4.0%
N 362
 
3.8%
T 359
 
3.7%
Other values (19) 2213
23.0%
Lowercase Letter
ValueCountFrequency (%)
e 2320
12.6%
s 1873
10.2%
r 1691
 
9.2%
i 1501
 
8.2%
o 1440
 
7.8%
a 1415
 
7.7%
n 1220
 
6.6%
l 961
 
5.2%
t 903
 
4.9%
d 585
 
3.2%
Other values (16) 4457
24.3%
Other Punctuation
ValueCountFrequency (%)
& 86
40.8%
. 61
28.9%
, 32
 
15.2%
・ 15
 
7.1%
' 4
 
1.9%
/ 4
 
1.9%
· 4
 
1.9%
; 2
 
0.9%
: 2
 
0.9%
： 1
 
0.5%
Decimal Number
ValueCountFrequency (%)
1 25
50.0%
2 23
46.0%
0 1
 
2.0%
3 1
 
2.0%
Space Separator
ValueCountFrequency (%)
5034
> 99.9%
　 2
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 53
72.6%
― 20
 
27.4%
Open Punctuation
ValueCountFrequency (%)
( 964
100.0%
Close Punctuation
ValueCountFrequency (%)
) 964
100.0%
Modifier Letter
ValueCountFrequency (%)
ー 56
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 10
100.0%
Nonspacing Mark
ValueCountFrequency (%)
̈ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28537
39.0%
Latin 27987
38.2%
Han 8500
 
11.6%
Common 7354
 
10.0%
Katakana 761
 
1.0%
Hiragana 92
 
0.1%
Arabic 4
 
< 0.1%
Inherited 1
 
< 0.1%

Most frequent character per script

Han
ValueCountFrequency (%)
社 396
 
4.7%
會 377
 
4.4%
協 374
 
4.4%
産 292
 
3.4%
明 263
 
3.1%
日 221
 
2.6%
業 210
 
2.5%
經 210
 
2.5%
財 197
 
2.3%
会 194
 
2.3%
Other values (321) 5766
67.8%
Hangul
ValueCountFrequency (%)
원 2151
 
7.5%
한 1931
 
6.8%
국 1775
 
6.2%
연 1704
 
6.0%
구 1676
 
5.9%
지 1398
 
4.9%
산 1377
 
4.8%
재 1252
 
4.4%
식 1246
 
4.4%
허 1113
 
3.9%
Other values (296) 12914
45.3%
Katakana
ValueCountFrequency (%)
ン 95
 
12.5%
イ 51
 
6.7%
ド 51
 
6.7%
タ 40
 
5.3%
ス 37
 
4.9%
ダ 35
 
4.6%
セ 35
 
4.6%
ヤ 34
 
4.5%
モ 34
 
4.5%
ク 21
 
2.8%
Other values (52) 328
43.1%
Latin
ValueCountFrequency (%)
e 2320
 
8.3%
s 1873
 
6.7%
I 1862
 
6.7%
r 1691
 
6.0%
P 1578
 
5.6%
i 1501
 
5.4%
o 1440
 
5.1%
a 1415
 
5.1%
n 1220
 
4.4%
l 961
 
3.4%
Other values (45) 12126
43.3%
Hiragana
ValueCountFrequency (%)
い 8
 
8.7%
せ 8
 
8.7%
ん 8
 
8.7%
ぎ 8
 
8.7%
う 8
 
8.7%
ょ 8
 
8.7%
か 7
 
7.6%
き 5
 
5.4%
す 4
 
4.3%
る 4
 
4.3%
Other values (14) 24
26.1%
Common
ValueCountFrequency (%)
5034
68.5%
( 964
 
13.1%
) 964
 
13.1%
& 86
 
1.2%
. 61
 
0.8%
ー 56
 
0.8%
- 53
 
0.7%
, 32
 
0.4%
1 25
 
0.3%
2 23
 
0.3%
Other values (11) 56
 
0.8%
Arabic
ValueCountFrequency (%)
ې 4
100.0%
Inherited
ValueCountFrequency (%)
̈ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35237
48.1%
Hangul 28527
39.0%
CJK 8482
 
11.6%
Katakana 832
 
1.1%
Hiragana 92
 
0.1%
None 23
 
< 0.1%
Punctuation 20
 
< 0.1%
CJK Compat Ideographs 18
 
< 0.1%
Arabic 4
 
< 0.1%
Diacriticals 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5034
 
14.3%
e 2320
 
6.6%
s 1873
 
5.3%
I 1862
 
5.3%
r 1691
 
4.8%
P 1578
 
4.5%
i 1501
 
4.3%
o 1440
 
4.1%
a 1415
 
4.0%
n 1220
 
3.5%
Other values (57) 15303
43.4%
Hangul
ValueCountFrequency (%)
원 2151
 
7.5%
한 1931
 
6.8%
국 1775
 
6.2%
연 1704
 
6.0%
구 1676
 
5.9%
지 1398
 
4.9%
산 1377
 
4.8%
재 1252
 
4.4%
식 1246
 
4.4%
허 1113
 
3.9%
Other values (295) 12904
45.2%
CJK
ValueCountFrequency (%)
社 396
 
4.7%
會 377
 
4.4%
協 374
 
4.4%
産 292
 
3.4%
明 263
 
3.1%
日 221
 
2.6%
業 210
 
2.5%
經 210
 
2.5%
財 197
 
2.3%
会 194
 
2.3%
Other values (314) 5748
67.8%
Katakana
ValueCountFrequency (%)
ン 95
 
11.4%
ー 56
 
6.7%
イ 51
 
6.1%
ド 51
 
6.1%
タ 40
 
4.8%
ス 37
 
4.4%
ダ 35
 
4.2%
セ 35
 
4.2%
ヤ 34
 
4.1%
モ 34
 
4.1%
Other values (54) 364
43.8%
Punctuation
ValueCountFrequency (%)
― 20
100.0%
None
ValueCountFrequency (%)
㈜ 10
43.5%
· 4
 
17.4%
　 2
 
8.7%
Ｉ 2
 
8.7%
Ｌ 2
 
8.7%
Ｓ 2
 
8.7%
： 1
 
4.3%
Hiragana
ValueCountFrequency (%)
い 8
 
8.7%
せ 8
 
8.7%
ん 8
 
8.7%
ぎ 8
 
8.7%
う 8
 
8.7%
ょ 8
 
8.7%
か 7
 
7.6%
き 5
 
5.4%
す 4
 
4.3%
る 4
 
4.3%
Other values (14) 24
26.1%
CJK Compat Ideographs
ValueCountFrequency (%)
論 6
33.3%
率 3
16.7%
聯 3
16.7%
龍 2
 
11.1%
連 2
 
11.1%
金 1
 
5.6%
勞 1
 
5.6%
Arabic
ValueCountFrequency (%)
ې 4
100.0%
Diacriticals
ValueCountFrequency (%)
̈ 1
100.0%

출판년
Text

Distinct54
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size64.1 KiB
2023-12-12T12:50:01.776393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters32732
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)0.1%

Sample

1st row2006
2nd row2006
3rd row2005
4th row2006
5th row2002
ValueCountFrequency (%)
2011 938
11.5%
2012 842
10.3%
2010 762
9.4%
2013 756
9.3%
2008 688
 
8.5%
2009 636
 
7.8%
2007 605
 
7.4%
2003 493
 
6.1%
2006 382
 
4.7%
2005 312
 
3.8%
Other values (43) 1727
21.2%
2023-12-12T12:50:02.204488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12396
37.9%
2 8539
26.1%
1 5287
16.2%
9 2066
 
6.3%
3 1290
 
3.9%
8 971
 
3.0%
7 735
 
2.2%
6 486
 
1.5%
4 416
 
1.3%
5 378
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32564
99.5%
Space Separator 168
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12396
38.1%
2 8539
26.2%
1 5287
16.2%
9 2066
 
6.3%
3 1290
 
4.0%
8 971
 
3.0%
7 735
 
2.3%
6 486
 
1.5%
4 416
 
1.3%
5 378
 
1.2%
Space Separator
ValueCountFrequency (%)
168
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 32732
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12396
37.9%
2 8539
26.1%
1 5287
16.2%
9 2066
 
6.3%
3 1290
 
3.9%
8 971
 
3.0%
7 735
 
2.2%
6 486
 
1.5%
4 416
 
1.3%
5 378
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32732
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12396
37.9%
2 8539
26.1%
1 5287
16.2%
9 2066
 
6.3%
3 1290
 
3.9%
8 971
 
3.0%
7 735
 
2.2%
6 486
 
1.5%
4 416
 
1.3%
5 378
 
1.2%

별치기호
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size64.1 KiB
전문
4415 
Re
2771 
Ref.
492 
Fo
474 
<NA>
 
31

Length

Max length4
Median length2
Mean length2.127826
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전문
2nd row전문
3rd row전문
4th row전문
5th row전문

Common Values

ValueCountFrequency (%)
전문 4415
54.0%
Re 2771
33.9%
Ref. 492
 
6.0%
Fo 474
 
5.8%
<NA> 31
 
0.4%

Length

2023-12-12T12:50:02.454711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:50:02.635278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전문 4415
54.0%
re 2771
33.9%
ref 492
 
6.0%
fo 474
 
5.8%
na 31
 
0.4%

청구기호
Text

Distinct5041
Distinct (%)61.6%
Missing3
Missing (%)< 0.1%
Memory size64.1 KiB
2023-12-12T12:50:03.038618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length19
Mean length13.57066
Min length5

Characters and Unicode

Total characters111008
Distinct characters315
Distinct categories9 ?
Distinct scripts5 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3626 ?
Unique (%)44.3%

Sample

1st row507.5004 A275p
2nd row507.554204 P288a
3rd row507.53104 C325a
4th row507.50804 C555b
5th row507.56504 M314c
ValueCountFrequency (%)
kiip 1008
 
6.2%
kipo 727
 
4.4%
kiep 250
 
1.5%
seminar 239
 
1.5%
507.518 227
 
1.4%
forum 209
 
1.3%
kipt 174
 
1.1%
507.50803 132
 
0.8%
507.511 115
 
0.7%
507.51804 105
 
0.6%
Other values (4657) 13182
80.5%
2023-12-12T12:50:03.623534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 17695
15.9%
5 13338
12.0%
1 8637
 
7.8%
8190
 
7.4%
2 7319
 
6.6%
7 6725
 
6.1%
. 4941
 
4.5%
3 4505
 
4.1%
4 3795
 
3.4%
I 3790
 
3.4%
Other values (305) 32073
28.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 69654
62.7%
Uppercase Letter 13499
 
12.2%
Space Separator 8191
 
7.4%
Other Letter 7321
 
6.6%
Other Punctuation 4993
 
4.5%
Lowercase Letter 4520
 
4.1%
Dash Punctuation 2696
 
2.4%
Close Punctuation 67
 
0.1%
Open Punctuation 67
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
ㅈ 965
 
13.2%
ㅅ 608
 
8.3%
ㅌ 535
 
7.3%
ㄱ 524
 
7.2%
ㅇ 485
 
6.6%
한 300
 
4.1%
ㅎ 294
 
4.0%
ㄷ 233
 
3.2%
ㅂ 230
 
3.1%
김 153
 
2.1%
Other values (236) 2994
40.9%
Uppercase Letter
ValueCountFrequency (%)
I 3790
28.1%
P 2569
19.0%
K 2429
18.0%
O 886
 
6.6%
E 528
 
3.9%
S 462
 
3.4%
T 436
 
3.2%
C 319
 
2.4%
F 256
 
1.9%
M 203
 
1.5%
Other values (16) 1621
12.0%
Lowercase Letter
ValueCountFrequency (%)
i 729
16.1%
m 549
12.1%
r 497
11.0%
a 357
7.9%
e 350
7.7%
p 306
6.8%
n 289
 
6.4%
u 262
 
5.8%
o 245
 
5.4%
c 219
 
4.8%
Other values (14) 717
15.9%
Decimal Number
ValueCountFrequency (%)
0 17695
25.4%
5 13338
19.1%
1 8637
12.4%
2 7319
10.5%
7 6725
 
9.7%
3 4505
 
6.5%
4 3795
 
5.4%
8 3332
 
4.8%
6 2174
 
3.1%
9 2134
 
3.1%
Other Punctuation
ValueCountFrequency (%)
. 4941
99.0%
& 39
 
0.8%
/ 11
 
0.2%
? 2
 
< 0.1%
Space Separator
ValueCountFrequency (%)
8190
> 99.9%
　 1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 2696
100.0%
Close Punctuation
ValueCountFrequency (%)
) 67
100.0%
Open Punctuation
ValueCountFrequency (%)
( 67
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 85668
77.2%
Latin 18019
 
16.2%
Hangul 7279
 
6.6%
Hiragana 27
 
< 0.1%
Han 15
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
ㅈ 965
 
13.3%
ㅅ 608
 
8.4%
ㅌ 535
 
7.3%
ㄱ 524
 
7.2%
ㅇ 485
 
6.7%
한 300
 
4.1%
ㅎ 294
 
4.0%
ㄷ 233
 
3.2%
ㅂ 230
 
3.2%
김 153
 
2.1%
Other values (213) 2952
40.6%
Latin
ValueCountFrequency (%)
I 3790
21.0%
P 2569
14.3%
K 2429
13.5%
O 886
 
4.9%
i 729
 
4.0%
m 549
 
3.0%
E 528
 
2.9%
r 497
 
2.8%
S 462
 
2.6%
T 436
 
2.4%
Other values (40) 5144
28.5%
Common
ValueCountFrequency (%)
0 17695
20.7%
5 13338
15.6%
1 8637
10.1%
8190
9.6%
2 7319
8.5%
7 6725
 
7.9%
. 4941
 
5.8%
3 4505
 
5.3%
4 3795
 
4.4%
8 3332
 
3.9%
Other values (9) 7191
8.4%
Hiragana
ValueCountFrequency (%)
へ 6
22.2%
り 5
18.5%
い 3
11.1%
ば 2
 
7.4%
れ 2
 
7.4%
ぽ 1
 
3.7%
じ 1
 
3.7%
あ 1
 
3.7%
ほ 1
 
3.7%
さ 1
 
3.7%
Other values (4) 4
14.8%
Han
ValueCountFrequency (%)
発 4
26.7%
塩 2
13.3%
青 2
13.3%
黒 2
13.3%
奥 1
 
6.7%
浅 1
 
6.7%
内 1
 
6.7%
経 1
 
6.7%
渋 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 103686
93.4%
Compat Jamo 4263
 
3.8%
Hangul 3016
 
2.7%
Hiragana 27
 
< 0.1%
CJK 15
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 17695
17.1%
5 13338
12.9%
1 8637
 
8.3%
8190
 
7.9%
2 7319
 
7.1%
7 6725
 
6.5%
. 4941
 
4.8%
3 4505
 
4.3%
4 3795
 
3.7%
I 3790
 
3.7%
Other values (58) 24751
23.9%
Compat Jamo
ValueCountFrequency (%)
ㅈ 965
22.6%
ㅅ 608
14.3%
ㅌ 535
12.5%
ㄱ 524
12.3%
ㅇ 485
11.4%
ㅎ 294
 
6.9%
ㄷ 233
 
5.5%
ㅂ 230
 
5.4%
ㅁ 147
 
3.4%
ㅊ 75
 
1.8%
Other values (5) 167
 
3.9%
Hangul
ValueCountFrequency (%)
한 300
 
9.9%
김 153
 
5.1%
이 140
 
4.6%
특 132
 
4.4%
정 101
 
3.3%
중 82
 
2.7%
박 67
 
2.2%
대 62
 
2.1%
지 58
 
1.9%
저 57
 
1.9%
Other values (198) 1864
61.8%
Hiragana
ValueCountFrequency (%)
へ 6
22.2%
り 5
18.5%
い 3
11.1%
ば 2
 
7.4%
れ 2
 
7.4%
ぽ 1
 
3.7%
じ 1
 
3.7%
あ 1
 
3.7%
ほ 1
 
3.7%
さ 1
 
3.7%
Other values (4) 4
14.8%
CJK
ValueCountFrequency (%)
発 4
26.7%
塩 2
13.3%
青 2
13.3%
黒 2
13.3%
奥 1
 
6.7%
浅 1
 
6.7%
内 1
 
6.7%
経 1
 
6.7%
渋 1
 
6.7%
None
ValueCountFrequency (%)
　 1
100.0%

URL
Text

Distinct6268
Distinct (%)76.6%
Missing0
Missing (%)0.0%
Memory size64.1 KiB
2023-12-12T12:50:04.035249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length54
Mean length54
Min length54

Characters and Unicode

Total characters441882
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5233 ?
Unique (%)63.9%

Sample

1st rowhttp://lib.kiip.re.kr/search/detail/CATTOT000000000445
2nd rowhttp://lib.kiip.re.kr/search/detail/CATTOT000000000447
3rd rowhttp://lib.kiip.re.kr/search/detail/CATTOT000000000448
4th rowhttp://lib.kiip.re.kr/search/detail/CATTOT000000000449
5th rowhttp://lib.kiip.re.kr/search/detail/CATTOT000000000451
ValueCountFrequency (%)
http://lib.kiip.re.kr/search/detail/cattot000000004626 53
 
0.6%
http://lib.kiip.re.kr/search/detail/cattot000000001179 35
 
0.4%
http://lib.kiip.re.kr/search/detail/cattot000000001408 29
 
0.4%
http://lib.kiip.re.kr/search/detail/cattot000000004649 23
 
0.3%
http://lib.kiip.re.kr/search/detail/cattot000000002105 14
 
0.2%
http://lib.kiip.re.kr/search/detail/cattot000000001695 12
 
0.1%
http://lib.kiip.re.kr/search/detail/cattot000000004229 12
 
0.1%
http://lib.kiip.re.kr/search/detail/cattot000000002093 10
 
0.1%
http://lib.kiip.re.kr/search/detail/cattot000000001483 10
 
0.1%
http://lib.kiip.re.kr/search/detail/cattot000000001763 10
 
0.1%
Other values (6258) 7975
97.5%
2023-12-12T12:50:04.566471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 65050
14.7%
/ 40915
 
9.3%
i 32732
 
7.4%
. 24549
 
5.6%
r 24549
 
5.6%
e 24549
 
5.6%
T 24549
 
5.6%
t 24549
 
5.6%
h 16366
 
3.7%
p 16366
 
3.7%
Other values (20) 147708
33.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 220941
50.0%
Decimal Number 98196
22.2%
Other Punctuation 73647
 
16.7%
Uppercase Letter 49098
 
11.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 32732
14.8%
r 24549
11.1%
e 24549
11.1%
t 24549
11.1%
h 16366
7.4%
p 16366
7.4%
l 16366
7.4%
k 16366
7.4%
a 16366
7.4%
d 8183
 
3.7%
Other values (3) 24549
11.1%
Decimal Number
ValueCountFrequency (%)
0 65050
66.2%
1 6579
 
6.7%
5 4049
 
4.1%
6 4035
 
4.1%
4 3813
 
3.9%
2 3364
 
3.4%
8 3009
 
3.1%
7 2994
 
3.0%
3 2743
 
2.8%
9 2560
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
T 24549
50.0%
C 8183
 
16.7%
O 8183
 
16.7%
A 8183
 
16.7%
Other Punctuation
ValueCountFrequency (%)
/ 40915
55.6%
. 24549
33.3%
: 8183
 
11.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 270039
61.1%
Common 171843
38.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 32732
12.1%
r 24549
9.1%
e 24549
9.1%
T 24549
9.1%
t 24549
9.1%
h 16366
 
6.1%
p 16366
 
6.1%
l 16366
 
6.1%
k 16366
 
6.1%
a 16366
 
6.1%
Other values (7) 57281
21.2%
Common
ValueCountFrequency (%)
0 65050
37.9%
/ 40915
23.8%
. 24549
 
14.3%
: 8183
 
4.8%
1 6579
 
3.8%
5 4049
 
2.4%
6 4035
 
2.3%
4 3813
 
2.2%
2 3364
 
2.0%
8 3009
 
1.8%
Other values (3) 8297
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 441882
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 65050
14.7%
/ 40915
 
9.3%
i 32732
 
7.4%
. 24549
 
5.6%
r 24549
 
5.6%
e 24549
 
5.6%
T 24549
 
5.6%
t 24549
 
5.6%
h 16366
 
3.7%
p 16366
 
3.7%
Other values (20) 147708
33.4%

Interactions

2023-12-12T12:49:57.720153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:50:04.685669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번출판년별치기호
순번1.0000.8710.425
출판년0.8711.0000.536
별치기호0.4250.5361.000
2023-12-12T12:50:04.796128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번별치기호
순번1.0000.267
별치기호0.2671.000

Missing values

2023-12-12T12:49:57.898022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:49:58.093344image/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.
2023-12-12T12:49:58.258755image/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

순번서명저자출판사출판년별치기호청구기호URL
01A Patented World?: Privatisation of Life and KnowledgeAgostino, AnaIndependent2006전문507.5004 A275phttp://lib.kiip.re.kr/search/detail/CATTOT000000000445
12All You Need to Know About the Music BusinessPassman, Donald SSimon & Schuste2006전문507.554204 P288ahttp://lib.kiip.re.kr/search/detail/CATTOT000000000447
23American Corporate Identity 2006Carter, David EHarpercollins2005전문507.53104 C325ahttp://lib.kiip.re.kr/search/detail/CATTOT000000000448
34Blackstone's Statutes on Intellectual PropertyChristie, AndrewOxford U.K2006전문507.50804 C555bhttp://lib.kiip.re.kr/search/detail/CATTOT000000000449
45Cyber Forensics : A Field Manual for Collecting, Examining, and Preserving Evidence of Computer CrimesMarcella, Albert JCRC2002전문507.56504 M314chttp://lib.kiip.re.kr/search/detail/CATTOT000000000451
56Information Feudalism : Who Owns the Knowledge Economy?Drahos, PeterNew Press2002전문507.50104 D759ihttp://lib.kiip.re.kr/search/detail/CATTOT000000000456
67International Patent Treaties with CommentaryNelson, JonOxford University2007전문507.518104 N432ihttp://lib.kiip.re.kr/search/detail/CATTOT000000000457
78International Trademarks And CopyrightsMasterson, John TAmer. Bar Assn.2004전문507.54504 M423ihttp://lib.kiip.re.kr/search/detail/CATTOT000000000459
89Introduction to Computer LawBainbridge, DavidPearson2004전문507.56804 B162ihttp://lib.kiip.re.kr/search/detail/CATTOT000000000460
910Law And Economics Of Antitrust And Intellectual PropertyKallay, DinaEdward Elgar2004전문507.50404 K14lhttp://lib.kiip.re.kr/search/detail/CATTOT000000000462
순번서명저자출판사출판년별치기호청구기호URL
817381742013 지식재산 교육통계연보국제지식재산연수원국제지식재산연수원2014ReETC 2014-03ㄱhttp://lib.kiip.re.kr/search/detail/CATTOT000000016629
81748175정당한 직무발명 보상을 위한 산업군별 실시보상액 산정방안 연구 : 최종보고서한남대학교 산학협력단한남대학교 산학협력단2013ReETC 2013-12ㅎhttp://lib.kiip.re.kr/search/detail/CATTOT000000016630
81758176特許廳 訓令例規集 (Ⅰ) = 특허청 훈련예규집 (Ⅰ)特許廳 (특허청)특허청2014ReKIPO 2014-01ㅎhttp://lib.kiip.re.kr/search/detail/CATTOT000000016631
81768177디자인의 국제출원을 위한 국영문 물품명칭집 : The List of Korean-English Products for International Application of Designs특허청특허청2014ReKIPO 2014-03ㄷhttp://lib.kiip.re.kr/search/detail/CATTOT000000016628
81778178特許廳 訓令例規集 (Ⅱ) = 특허청 훈련예규집 (Ⅱ)特許廳 (특허청)특허청2014ReKIPO 2014-01ㅎhttp://lib.kiip.re.kr/search/detail/CATTOT000000016632
81788179국제행사 타당성조사 일반지침 수립을 위한 방법론 연구김흥종대외경제정책연구원(KIEP)2013ReKIEP 2013-12ㄱhttp://lib.kiip.re.kr/search/detail/CATTOT000000016633
81798180한·중·일 3국 IT서비스 산업의 비교 우위 검토: 생산성 분석을 중심으로나승권대외경제정책연구원(KIEP)2013ReKIEP 2013-12ㅎhttp://lib.kiip.re.kr/search/detail/CATTOT000000016634
81808181대외개방이 국내 노동시장의 숙련구조에 미치는 영향배찬권대외경제정책연구원(KIEP)2013ReKIEP 2013-12ㄷhttp://lib.kiip.re.kr/search/detail/CATTOT000000016637
81818182금융통합이 금융위기에 미치는 영향이동은대외경제정책연구원(KIEP)2013ReKIEP 2013-12ㄱhttp://lib.kiip.re.kr/search/detail/CATTOT000000016636
81828183글로벌 유동성 확대가 세계경제에 미치는 영향과 정책 대응이동은대외경제정책연구원(KIEP)2013ReKIEP 2013-12ㄱhttp://lib.kiip.re.kr/search/detail/CATTOT000000016635