Overview

Dataset statistics

Number of variables5
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory488.3 KiB
Average record size in memory50.0 B

Variable types

Numeric2
Text2
Categorical1

Dataset

Description지식재산관련 논문, 기고 등 관련 학술정보와 지식재산관련 동향/학술/인력정보에 관한 분석보고서 자료입니다.(지식재산학술정보DB)
URLhttps://www.data.go.kr/data/15090792/fileData.do

Alerts

번호 is highly overall correlated with 발행년도High correlation
발행년도 is highly overall correlated with 번호High correlation
번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 11:41:10.700019
Analysis finished2023-12-12 11:41:14.769609
Duration4.07 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39753.946
Minimum5
Maximum80236
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T20:41:14.933251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile4148.4
Q119247.5
median39490
Q360093.5
95-th percentile76159.2
Maximum80236
Range80231
Interquartile range (IQR)40846

Descriptive statistics

Standard deviation23187.142
Coefficient of variation (CV)0.58326642
Kurtosis-1.2080603
Mean39753.946
Median Absolute Deviation (MAD)20423.5
Skewness0.026740024
Sum3.9753946 × 108
Variance5.3764354 × 108
MonotonicityNot monotonic
2023-12-12T20:41:15.239747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
68873 1
 
< 0.1%
12281 1
 
< 0.1%
36891 1
 
< 0.1%
57980 1
 
< 0.1%
68514 1
 
< 0.1%
63784 1
 
< 0.1%
74075 1
 
< 0.1%
64590 1
 
< 0.1%
4410 1
 
< 0.1%
9988 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
5 1
< 0.1%
16 1
< 0.1%
20 1
< 0.1%
23 1
< 0.1%
37 1
< 0.1%
53 1
< 0.1%
66 1
< 0.1%
83 1
< 0.1%
89 1
< 0.1%
93 1
< 0.1%
ValueCountFrequency (%)
80236 1
< 0.1%
80233 1
< 0.1%
80204 1
< 0.1%
80202 1
< 0.1%
80195 1
< 0.1%
80180 1
< 0.1%
80179 1
< 0.1%
80171 1
< 0.1%
80162 1
< 0.1%
80159 1
< 0.1%

제목
Text

Distinct9874
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T20:41:15.797035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length679
Median length214
Mean length61.2048
Min length4

Characters and Unicode

Total characters612048
Distinct characters2233
Distinct categories18 ?
Distinct scripts8 ?
Distinct blocks17 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9760 ?
Unique (%)97.6%

Sample

1st rowTRIBAL SOVEREIGN IMMUNITY AS A DEFENSE AT THE PATENT TRIAL AND APPEAL BOARD OR A VIOLATION OF U.S. ANTITRUST LAWS
2nd rowJapanese companies' intellectual property strategies to China
3rd row기술적 보호조치의 범위 설정 :대법원 2004도2743 컴퓨터프로그램보호법위반
4th row브랜드변경 전략의 기업가치 유발 요인 및 개선효과 분석
5th rowEXHIBIT FACEBOOK: THE DISCOVERABILITY AND ADMISSIBILITY OF SOCIAL MEDIA EVIDENCE
ValueCountFrequency (%)
the 3456
 
4.0%
of 2966
 
3.4%
and 2356
 
2.7%
in 1671
 
1.9%
1490
 
1.7%
patent 1136
 
1.3%
a 1121
 
1.3%
for 913
 
1.1%
to 863
 
1.0%
property 712
 
0.8%
Other values (21917) 70063
80.8%
2023-12-12T20:41:16.636745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
77479
 
12.7%
E 24449
 
4.0%
T 22092
 
3.6%
I 19786
 
3.2%
A 19228
 
3.1%
N 18716
 
3.1%
e 16012
 
2.6%
O 15943
 
2.6%
R 15631
 
2.6%
t 13499
 
2.2%
Other values (2223) 369213
60.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 227555
37.2%
Lowercase Letter 139649
22.8%
Other Letter 137915
22.5%
Space Separator 77480
 
12.7%
Other Punctuation 11494
 
1.9%
Decimal Number 8970
 
1.5%
Close Punctuation 3012
 
0.5%
Open Punctuation 2998
 
0.5%
Dash Punctuation 2441
 
0.4%
Math Symbol 176
 
< 0.1%
Other values (8) 358
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
の 3893
 
2.8%
의 2281
 
1.7%
に 1852
 
1.3%
한 1685
 
1.2%
る 1598
 
1.2%
에 1475
 
1.1%
特 1329
 
1.0%
と 1323
 
1.0%
知 1237
 
0.9%
財 1154
 
0.8%
Other values (2063) 120088
87.1%
Uppercase Letter
ValueCountFrequency (%)
E 24449
10.7%
T 22092
 
9.7%
I 19786
 
8.7%
A 19228
 
8.4%
N 18716
 
8.2%
O 15943
 
7.0%
R 15631
 
6.9%
S 13164
 
5.8%
C 10479
 
4.6%
L 9410
 
4.1%
Other values (39) 58657
25.8%
Lowercase Letter
ValueCountFrequency (%)
e 16012
11.5%
t 13499
9.7%
n 13058
 
9.4%
i 12041
 
8.6%
a 11578
 
8.3%
o 11320
 
8.1%
r 9587
 
6.9%
s 7699
 
5.5%
l 5764
 
4.1%
c 5716
 
4.1%
Other values (16) 33375
23.9%
Other Punctuation
ValueCountFrequency (%)
. 4031
35.1%
: 3686
32.1%
, 1638
14.3%
' 660
 
5.7%
" 404
 
3.5%
、 289
 
2.5%
& 264
 
2.3%
· 124
 
1.1%
/ 115
 
1.0%
! 89
 
0.8%
Other values (12) 194
 
1.7%
Decimal Number
ValueCountFrequency (%)
1 1966
21.9%
2 1888
21.0%
0 1308
14.6%
3 762
 
8.5%
4 594
 
6.6%
7 539
 
6.0%
5 514
 
5.7%
9 491
 
5.5%
8 452
 
5.0%
6 446
 
5.0%
Other values (5) 10
 
0.1%
Math Symbol
ValueCountFrequency (%)
= 57
32.4%
> 45
25.6%
< 44
25.0%
× 13
 
7.4%
~ 7
 
4.0%
+ 7
 
4.0%
| 1
 
0.6%
∼ 1
 
0.6%
→ 1
 
0.6%
Open Punctuation
ValueCountFrequency (%)
( 2286
76.3%
[ 358
 
11.9%
「 299
 
10.0%
『 22
 
0.7%
〔 18
 
0.6%
（ 10
 
0.3%
〈 5
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 2282
75.8%
] 377
 
12.5%
」 299
 
9.9%
』 22
 
0.7%
〕 18
 
0.6%
） 10
 
0.3%
〉 4
 
0.1%
Other Symbol
ValueCountFrequency (%)
® 22
64.7%
™ 4
 
11.8%
○ 4
 
11.8%
♪ 4
 
11.8%
Letter Number
ValueCountFrequency (%)
Ⅱ 7
58.3%
Ⅸ 2
 
16.7%
Ⅰ 2
 
16.7%
Ⅲ 1
 
8.3%
Dash Punctuation
ValueCountFrequency (%)
- 2400
98.3%
― 30
 
1.2%
－ 11
 
0.5%
Currency Symbol
ValueCountFrequency (%)
$ 5
71.4%
￠ 1
 
14.3%
￡ 1
 
14.3%
Space Separator
ValueCountFrequency (%)
77479
> 99.9%
　 1
 
< 0.1%
Final Punctuation
ValueCountFrequency (%)
” 93
60.8%
’ 60
39.2%
Initial Punctuation
ValueCountFrequency (%)
“ 91
64.1%
‘ 51
35.9%
Other Number
ValueCountFrequency (%)
② 2
66.7%
④ 1
33.3%
Modifier Symbol
ValueCountFrequency (%)
` 1
50.0%
¨ 1
50.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 367139
60.0%
Common 106917
 
17.5%
Hangul 62368
 
10.2%
Han 46591
 
7.6%
Hiragana 18819
 
3.1%
Katakana 10137
 
1.7%
Cyrillic 76
 
< 0.1%
Greek 1
 
< 0.1%

Most frequent character per script

Han
ValueCountFrequency (%)
特 1329
 
2.9%
知 1237
 
2.7%
財 1154
 
2.5%
的 1050
 
2.3%
許 993
 
2.1%
産 958
 
2.1%
判 918
 
2.0%
法 900
 
1.9%
事 536
 
1.2%
作 524
 
1.1%
Other values (1199) 36992
79.4%
Hangul
ValueCountFrequency (%)
의 2281
 
3.7%
한 1685
 
2.7%
에 1475
 
2.4%
기 1154
 
1.9%
구 1028
 
1.6%
연 980
 
1.6%
관 895
 
1.4%
제 875
 
1.4%
과 868
 
1.4%
지 852
 
1.4%
Other values (705) 50275
80.6%
Common
ValueCountFrequency (%)
77479
72.5%
. 4031
 
3.8%
: 3686
 
3.4%
- 2400
 
2.2%
( 2286
 
2.1%
) 2282
 
2.1%
1 1966
 
1.8%
2 1888
 
1.8%
, 1638
 
1.5%
0 1308
 
1.2%
Other values (71) 7953
 
7.4%
Katakana
ValueCountFrequency (%)
ン 899
 
8.9%
イ 570
 
5.6%
ス 513
 
5.1%
ト 442
 
4.4%
ル 349
 
3.4%
シ 317
 
3.1%
ラ 314
 
3.1%
ア 284
 
2.8%
ク 262
 
2.6%
ジ 257
 
2.5%
Other values (70) 5930
58.5%
Hiragana
ValueCountFrequency (%)
の 3893
20.7%
に 1852
 
9.8%
る 1598
 
8.5%
と 1323
 
7.0%
を 821
 
4.4%
た 647
 
3.4%
て 612
 
3.3%
け 595
 
3.2%
い 593
 
3.2%
お 583
 
3.1%
Other values (59) 6302
33.5%
Latin
ValueCountFrequency (%)
E 24449
 
6.7%
T 22092
 
6.0%
I 19786
 
5.4%
A 19228
 
5.2%
N 18716
 
5.1%
e 16012
 
4.4%
O 15943
 
4.3%
R 15631
 
4.3%
t 13499
 
3.7%
S 13164
 
3.6%
Other values (47) 188619
51.4%
Cyrillic
ValueCountFrequency (%)
Н 10
13.2%
Т 7
 
9.2%
В 6
 
7.9%
А 6
 
7.9%
С 6
 
7.9%
Е 5
 
6.6%
И 4
 
5.3%
Л 4
 
5.3%
К 4
 
5.3%
О 4
 
5.3%
Other values (11) 20
26.3%
Greek
ValueCountFrequency (%)
Α 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 472437
77.2%
Hangul 62359
 
10.2%
CJK 46584
 
7.6%
Hiragana 18819
 
3.1%
Katakana 10137
 
1.7%
None 1236
 
0.2%
Punctuation 355
 
0.1%
Cyrillic 76
 
< 0.1%
Number Forms 12
 
< 0.1%
Compat Jamo 9
 
< 0.1%
Other values (7) 24
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
77479
 
16.4%
E 24449
 
5.2%
T 22092
 
4.7%
I 19786
 
4.2%
A 19228
 
4.1%
N 18716
 
4.0%
e 16012
 
3.4%
O 15943
 
3.4%
R 15631
 
3.3%
t 13499
 
2.9%
Other values (80) 229602
48.6%
Hiragana
ValueCountFrequency (%)
の 3893
20.7%
に 1852
 
9.8%
る 1598
 
8.5%
と 1323
 
7.0%
を 821
 
4.4%
た 647
 
3.4%
て 612
 
3.3%
け 595
 
3.2%
い 593
 
3.2%
お 583
 
3.1%
Other values (59) 6302
33.5%
Hangul
ValueCountFrequency (%)
의 2281
 
3.7%
한 1685
 
2.7%
에 1475
 
2.4%
기 1154
 
1.9%
구 1028
 
1.6%
연 980
 
1.6%
관 895
 
1.4%
제 875
 
1.4%
과 868
 
1.4%
지 852
 
1.4%
Other values (704) 50266
80.6%
CJK
ValueCountFrequency (%)
特 1329
 
2.9%
知 1237
 
2.7%
財 1154
 
2.5%
的 1050
 
2.3%
許 993
 
2.1%
産 958
 
2.1%
判 918
 
2.0%
法 900
 
1.9%
事 536
 
1.2%
作 524
 
1.1%
Other values (1195) 36985
79.4%
Katakana
ValueCountFrequency (%)
ン 899
 
8.9%
イ 570
 
5.6%
ス 513
 
5.1%
ト 442
 
4.4%
ル 349
 
3.4%
シ 317
 
3.1%
ラ 314
 
3.1%
ア 284
 
2.8%
ク 262
 
2.6%
ジ 257
 
2.5%
Other values (70) 5930
58.5%
None
ValueCountFrequency (%)
」 299
24.2%
「 299
24.2%
、 289
23.4%
· 124
10.0%
¡ 23
 
1.9%
® 22
 
1.8%
』 22
 
1.8%
『 22
 
1.8%
〕 18
 
1.5%
〔 18
 
1.5%
Other values (22) 100
 
8.1%
Punctuation
ValueCountFrequency (%)
” 93
26.2%
“ 91
25.6%
’ 60
16.9%
‘ 51
14.4%
― 30
 
8.5%
… 30
 
8.5%
Cyrillic
ValueCountFrequency (%)
Н 10
13.2%
Т 7
 
9.2%
В 6
 
7.9%
А 6
 
7.9%
С 6
 
7.9%
Е 5
 
6.6%
И 4
 
5.3%
Л 4
 
5.3%
К 4
 
5.3%
О 4
 
5.3%
Other values (11) 20
26.3%
Compat Jamo
ValueCountFrequency (%)
ㆍ 9
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 7
58.3%
Ⅸ 2
 
16.7%
Ⅰ 2
 
16.7%
Ⅲ 1
 
8.3%
Letterlike Symbols
ValueCountFrequency (%)
™ 4
100.0%
Geometric Shapes
ValueCountFrequency (%)
○ 4
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
論 4
57.1%
不 1
 
14.3%
立 1
 
14.3%
女 1
 
14.3%
Misc Symbols
ValueCountFrequency (%)
♪ 4
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
② 2
66.7%
④ 1
33.3%
Math Operators
ValueCountFrequency (%)
∼ 1
100.0%
Arrows
ValueCountFrequency (%)
→ 1
100.0%

저자
Text

Distinct8330
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T20:41:17.367500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1024
Median length173
Mean length15.3536
Min length1

Characters and Unicode

Total characters153536
Distinct characters1460
Distinct categories14 ?
Distinct scripts7 ?
Distinct blocks10 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7642 ?
Unique (%)76.4%

Sample

1st rowSamantha Roth
2nd row安井 あい,平塚 政宏,中島 一
3rd row이대희
4th row오희장
5th rowEmma W. Sholl
ValueCountFrequency (%)
추후등록예정 337
 
1.2%
m 336
 
1.2%
a 314
 
1.2%
and 297
 
1.1%
j 265
 
1.0%
s 242
 
0.9%
214
 
0.8%
r 198
 
0.7%
l 182
 
0.7%
d 171
 
0.6%
Other values (13153) 24737
90.6%
2023-12-12T20:41:18.330788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18317
 
11.9%
a 9131
 
5.9%
e 7890
 
5.1%
n 6774
 
4.4%
, 6526
 
4.3%
. 6230
 
4.1%
i 6103
 
4.0%
r 5607
 
3.7%
o 5034
 
3.3%
l 3851
 
2.5%
Other values (1450) 78073
50.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 69574
45.3%
Other Letter 27427
 
17.9%
Uppercase Letter 23557
 
15.3%
Space Separator 18317
 
11.9%
Other Punctuation 13370
 
8.7%
Dash Punctuation 514
 
0.3%
Open Punctuation 259
 
0.2%
Close Punctuation 259
 
0.2%
Decimal Number 235
 
0.2%
Connector Punctuation 10
 
< 0.1%
Other values (4) 14
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 757
 
2.8%
김 647
 
2.4%
이 539
 
2.0%
田 401
 
1.5%
추 348
 
1.3%
예 348
 
1.3%
록 342
 
1.2%
등 341
 
1.2%
후 340
 
1.2%
영 312
 
1.1%
Other values (1349) 23052
84.0%
Uppercase Letter
ValueCountFrequency (%)
S 1922
 
8.2%
M 1919
 
8.1%
A 1839
 
7.8%
C 1410
 
6.0%
J 1340
 
5.7%
R 1252
 
5.3%
L 1224
 
5.2%
B 1117
 
4.7%
H 1081
 
4.6%
K 1069
 
4.5%
Other values (25) 9384
39.8%
Lowercase Letter
ValueCountFrequency (%)
a 9131
13.1%
e 7890
11.3%
n 6774
9.7%
i 6103
 
8.8%
r 5607
 
8.1%
o 5034
 
7.2%
l 3851
 
5.5%
h 3175
 
4.6%
s 3099
 
4.5%
t 3044
 
4.4%
Other values (18) 15866
22.8%
Other Punctuation
ValueCountFrequency (%)
, 6526
48.8%
. 6230
46.6%
; 508
 
3.8%
' 43
 
0.3%
& 39
 
0.3%
/ 10
 
0.1%
: 4
 
< 0.1%
¡ 4
 
< 0.1%
@ 2
 
< 0.1%
" 1
 
< 0.1%
Other values (3) 3
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 123
52.3%
2 52
22.1%
3 20
 
8.5%
0 16
 
6.8%
4 10
 
4.3%
5 9
 
3.8%
9 2
 
0.9%
6 1
 
0.4%
7 1
 
0.4%
8 1
 
0.4%
Open Punctuation
ValueCountFrequency (%)
( 147
56.8%
[ 111
42.9%
「 1
 
0.4%
Close Punctuation
ValueCountFrequency (%)
) 147
56.8%
] 111
42.9%
」 1
 
0.4%
Math Symbol
ValueCountFrequency (%)
| 4
66.7%
× 1
 
16.7%
= 1
 
16.7%
Space Separator
ValueCountFrequency (%)
18317
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 514
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 10
100.0%
Modifier Symbol
ValueCountFrequency (%)
¨ 3
100.0%
Other Symbol
ValueCountFrequency (%)
® 3
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 93121
60.7%
Common 32978
 
21.5%
Hangul 13961
 
9.1%
Han 12427
 
8.1%
Katakana 924
 
0.6%
Hiragana 115
 
0.1%
Cyrillic 10
 
< 0.1%

Most frequent character per script

Han
ValueCountFrequency (%)
田 401
 
3.2%
一 231
 
1.9%
子 197
 
1.6%
本 191
 
1.5%
山 189
 
1.5%
野 178
 
1.4%
小 173
 
1.4%
村 163
 
1.3%
大 151
 
1.2%
井 135
 
1.1%
Other values (891) 10418
83.8%
Hangul
ValueCountFrequency (%)
정 757
 
5.4%
김 647
 
4.6%
이 539
 
3.9%
추 348
 
2.5%
예 348
 
2.5%
록 342
 
2.4%
등 341
 
2.4%
후 340
 
2.4%
영 312
 
2.2%
박 297
 
2.1%
Other values (343) 9690
69.4%
Katakana
ValueCountFrequency (%)
ン 74
 
8.0%
ト 46
 
5.0%
ル 44
 
4.8%
イ 39
 
4.2%
リ 33
 
3.6%
ラ 31
 
3.4%
ジ 30
 
3.2%
ス 29
 
3.1%
マ 28
 
3.0%
ド 23
 
2.5%
Other values (63) 547
59.2%
Latin
ValueCountFrequency (%)
a 9131
 
9.8%
e 7890
 
8.5%
n 6774
 
7.3%
i 6103
 
6.6%
r 5607
 
6.0%
o 5034
 
5.4%
l 3851
 
4.1%
h 3175
 
3.4%
s 3099
 
3.3%
t 3044
 
3.3%
Other values (45) 39413
42.3%
Common
ValueCountFrequency (%)
18317
55.5%
, 6526
 
19.8%
. 6230
 
18.9%
- 514
 
1.6%
; 508
 
1.5%
( 147
 
0.4%
) 147
 
0.4%
1 123
 
0.4%
[ 111
 
0.3%
] 111
 
0.3%
Other values (28) 244
 
0.7%
Hiragana
ValueCountFrequency (%)
み 14
 
12.2%
り 9
 
7.8%
お 9
 
7.8%
か 7
 
6.1%
に 7
 
6.1%
る 7
 
6.1%
の 6
 
5.2%
き 5
 
4.3%
ゆ 5
 
4.3%
す 4
 
3.5%
Other values (22) 42
36.5%
Cyrillic
ValueCountFrequency (%)
В 2
20.0%
Е 2
20.0%
Г 1
10.0%
А 1
10.0%
О 1
10.0%
Н 1
10.0%
М 1
10.0%
С 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 126075
82.1%
Hangul 13960
 
9.1%
CJK 12418
 
8.1%
Katakana 924
 
0.6%
Hiragana 115
 
0.1%
None 22
 
< 0.1%
Cyrillic 10
 
< 0.1%
CJK Compat Ideographs 9
 
< 0.1%
Punctuation 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18317
 
14.5%
a 9131
 
7.2%
e 7890
 
6.3%
n 6774
 
5.4%
, 6526
 
5.2%
. 6230
 
4.9%
i 6103
 
4.8%
r 5607
 
4.4%
o 5034
 
4.0%
l 3851
 
3.1%
Other values (70) 50612
40.1%
Hangul
ValueCountFrequency (%)
정 757
 
5.4%
김 647
 
4.6%
이 539
 
3.9%
추 348
 
2.5%
예 348
 
2.5%
록 342
 
2.4%
등 341
 
2.4%
후 340
 
2.4%
영 312
 
2.2%
박 297
 
2.1%
Other values (342) 9689
69.4%
CJK
ValueCountFrequency (%)
田 401
 
3.2%
一 231
 
1.9%
子 197
 
1.6%
本 191
 
1.5%
山 189
 
1.5%
野 178
 
1.4%
小 173
 
1.4%
村 163
 
1.3%
大 151
 
1.2%
井 135
 
1.1%
Other values (887) 10409
83.8%
Katakana
ValueCountFrequency (%)
ン 74
 
8.0%
ト 46
 
5.0%
ル 44
 
4.8%
イ 39
 
4.2%
リ 33
 
3.6%
ラ 31
 
3.4%
ジ 30
 
3.2%
ス 29
 
3.1%
マ 28
 
3.0%
ド 23
 
2.5%
Other values (63) 547
59.2%
Hiragana
ValueCountFrequency (%)
み 14
 
12.2%
り 9
 
7.8%
お 9
 
7.8%
か 7
 
6.1%
に 7
 
6.1%
る 7
 
6.1%
の 6
 
5.2%
き 5
 
4.3%
ゆ 5
 
4.3%
す 4
 
3.5%
Other values (22) 42
36.5%
CJK Compat Ideographs
ValueCountFrequency (%)
李 6
66.7%
北 1
 
11.1%
烈 1
 
11.1%
隆 1
 
11.1%
None
ValueCountFrequency (%)
¡ 4
18.2%
¨ 3
13.6%
ı 3
13.6%
® 3
13.6%
ł 2
9.1%
× 1
 
4.5%
¿ 1
 
4.5%
」 1
 
4.5%
「 1
 
4.5%
＆ 1
 
4.5%
Other values (2) 2
9.1%
Cyrillic
ValueCountFrequency (%)
В 2
20.0%
Е 2
20.0%
Г 1
10.0%
А 1
10.0%
О 1
10.0%
Н 1
10.0%
М 1
10.0%
С 1
10.0%
Punctuation
ValueCountFrequency (%)
’ 2
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅇ 1
100.0%

발행년도
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2013.108
Minimum1999
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T20:41:18.546255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1999
5-th percentile2006
Q12009
median2013
Q32017
95-th percentile2020
Maximum2021
Range22
Interquartile range (IQR)8

Descriptive statistics

Standard deviation4.4831179
Coefficient of variation (CV)0.0022269634
Kurtosis-1.1308341
Mean2013.108
Median Absolute Deviation (MAD)4
Skewness0.034050355
Sum20131080
Variance20.098346
MonotonicityNot monotonic
2023-12-12T20:41:18.777200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
2018 831
 
8.3%
2012 808
 
8.1%
2009 717
 
7.2%
2017 712
 
7.1%
2007 699
 
7.0%
2008 680
 
6.8%
2011 653
 
6.5%
2015 619
 
6.2%
2010 610
 
6.1%
2014 605
 
6.0%
Other values (13) 3066
30.7%
ValueCountFrequency (%)
1999 2
 
< 0.1%
2000 9
 
0.1%
2001 2
 
< 0.1%
2002 2
 
< 0.1%
2003 1
 
< 0.1%
2004 1
 
< 0.1%
2005 3
 
< 0.1%
2006 598
6.0%
2007 699
7.0%
2008 680
6.8%
ValueCountFrequency (%)
2021 396
4.0%
2020 422
4.2%
2019 574
5.7%
2018 831
8.3%
2017 712
7.1%
2016 498
5.0%
2015 619
6.2%
2014 605
6.0%
2013 558
5.6%
2012 808
8.1%

원문디비
Categorical

Distinct33
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
CiNii
1779 
Westlaw
1678 
Scopus
986 
일본국회도서관
936 
RISS
821 
Other values (28)
3800 

Length

Max length20
Median length10
Mean length5.5323
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowwestlaw
2nd rowCiNii
3rd row국회
4th rowRISS
5th rowWestlaw

Common Values

ValueCountFrequency (%)
CiNii 1779
17.8%
Westlaw 1678
16.8%
Scopus 986
9.9%
일본국회도서관 936
9.4%
RISS 821
8.2%
westlaw 748
7.5%
BSC 747
7.5%
국회 521
 
5.2%
국회도서관 326
 
3.3%
DBpia 268
 
2.7%
Other values (23) 1190
11.9%

Length

2023-12-12T20:41:19.031606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
westlaw 2601
25.6%
cinii 1779
17.5%
scopus 1199
11.8%
일본국회도서관 936
 
9.2%
riss 821
 
8.1%
bsc 747
 
7.3%
국회 521
 
5.1%
dbpia 397
 
3.9%
국회도서관 326
 
3.2%
kiss 221
 
2.2%
Other values (21) 623
 
6.1%

Interactions

2023-12-12T20:41:14.113538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:41:13.707469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:41:14.300143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:41:13.933424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:41:19.215060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호발행년도원문디비
번호1.0000.9720.773
발행년도0.9721.0000.802
원문디비0.7730.8021.000
2023-12-12T20:41:19.377384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호발행년도원문디비
번호1.0000.9930.402
발행년도0.9931.0000.431
원문디비0.4020.4311.000

Missing values

2023-12-12T20:41:14.507280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:41:14.678690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

번호제목저자발행년도원문디비
6765968873TRIBAL SOVEREIGN IMMUNITY AS A DEFENSE AT THE PATENT TRIAL AND APPEAL BOARD OR A VIOLATION OF U.S. ANTITRUST LAWSSamantha Roth2019westlaw
80358036Japanese companies' intellectual property strategies to China安井 あい,平塚 政宏,中島 一2007CiNii
40874088기술적 보호조치의 범위 설정 :대법원 2004도2743 컴퓨터프로그램보호법위반이대희2006국회
6630767513브랜드변경 전략의 기업가치 유발 요인 및 개선효과 분석오희장2018RISS
3779737807EXHIBIT FACEBOOK: THE DISCOVERABILITY AND ADMISSIBILITY OF SOCIAL MEDIA EVIDENCEEmma W. Sholl2013Westlaw
5724558282Ensuring Protection of Trade Secrets and Intellectual Property in IndiaAtul Gupta, Parvathy Tharamel, Trilegal, Bangalore2017westlaw
5779158896Origin matters: The differential impact of import competition on innovationLi X, Zhou Y.M.2017Scopus
4576945813국제지적재산소송원칙의 개요와 활용방안에 대한 연구이규호2014국회도서관
1384213843の新しい風 目指せ知財立! 龍神際特許事務所 日本が待ち望んでいた知財交のプロ龍神 嘉彦2008CiNii
2993329938Study on the Determination of Design Similarity in China : Analysis of administrative dispute over invalidation trial for Honda CR-V design registration張 雨2011CiNii
번호제목저자발행년도원문디비
4667346739한국형 지식재산서비스 비즈니스 모델 도입을 위한 정부 지원 방안 연구임소진,류태규,강경남,임효정,진경미,조국훈,정영근2013한국지식재산연구원
5053050621화웨이의 PCT 특허 출원 동향분석김진환, 한유진2015Dbpia
3693136941상표판결에서 유사 여부 판단사례에 관한 세부 분류 연구배상철2012프리즘
3261132618Database and copyright infringement: Sportradar case.Adam Rendle.2012Westlaw
2524525247Digital Britain 실시 현황 및 시사점 :디지털 경제법안 중 저작권보호 관련 규정을 중심으로권혜선2010국회
3490334913ASEANの知財をめぐる況と「東南アジア知財ネットワク」の設立大熊, 靖夫2012CiNii
5060650708패션 콜라보레이션의 저작권법적 쟁점 : 그래피티 아트를 중심으로고재윤, 남형두, 고은주2015국회도서관
3192031927911 EXECUTIVE TRADE SECRETSTom C.W. Lin [FNa1]2012Westlaw
4332843369The optimal time path of clean energy R&D policy when patents have finite lifetimeGerlagh, R., Kverndokk, S., Rosendahl, K.E.2014Scopus
41224123도메인이름의 法的 性質과 登錄人의 權利保護에 관한 硏究최진이2006국회