Overview

Dataset statistics

Number of variables6
Number of observations480
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory23.1 KiB
Average record size in memory49.3 B

Variable types

Numeric1
Categorical2
Text2
DateTime1

Dataset

Description한국연구재단 등재지로서 지식재산(특허, 상표, 디자인, 저작권 등) 관련 법, 경제·경영,과학·기술 분야를 아우르는 지식재산 융합학술지 입니다.
URLhttps://www.data.go.kr/data/15090821/fileData.do

Alerts

번호 is highly overall correlated with 권High correlation
권 is highly overall correlated with 번호High correlation
번호 has unique valuesUnique
제목 has unique valuesUnique

Reproduction

Analysis started2023-12-12 17:18:37.636658
Analysis finished2023-12-12 17:18:38.467486
Duration0.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct480
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean240.5
Minimum1
Maximum480
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2023-12-13T02:18:38.542575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile24.95
Q1120.75
median240.5
Q3360.25
95-th percentile456.05
Maximum480
Range479
Interquartile range (IQR)239.5

Descriptive statistics

Standard deviation138.70833
Coefficient of variation (CV)0.5767498
Kurtosis-1.2
Mean240.5
Median Absolute Deviation (MAD)120
Skewness0
Sum115440
Variance19240
MonotonicityStrictly increasing
2023-12-13T02:18:38.691202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
242 1
 
0.2%
330 1
 
0.2%
329 1
 
0.2%
328 1
 
0.2%
327 1
 
0.2%
326 1
 
0.2%
325 1
 
0.2%
324 1
 
0.2%
323 1
 
0.2%
Other values (470) 470
97.9%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
480 1
0.2%
479 1
0.2%
478 1
0.2%
477 1
0.2%
476 1
0.2%
475 1
0.2%
474 1
0.2%
473 1
0.2%
472 1
0.2%
471 1
0.2%

권
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
15권
35 
10권
34 
9권
33 
13권
32 
11권
32 
Other values (13)
314 

Length

Max length3
Median length3
Mean length2.5416667
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1권
2nd row1권
3rd row1권
4th row1권
5th row1권

Common Values

ValueCountFrequency (%)
15권 35
 
7.3%
10권 34
 
7.1%
9권 33
 
6.9%
13권 32
 
6.7%
11권 32
 
6.7%
14권 30
 
6.2%
16권 29
 
6.0%
8권 29
 
6.0%
12권 29
 
6.0%
2권 28
 
5.8%
Other values (8) 169
35.2%

Length

2023-12-13T02:18:38.820417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
15권 35
 
7.3%
10권 34
 
7.1%
9권 33
 
6.9%
13권 32
 
6.7%
11권 32
 
6.7%
14권 30
 
6.2%
16권 29
 
6.0%
8권 29
 
6.0%
12권 29
 
6.0%
6권 28
 
5.8%
Other values (8) 169
35.2%

호
Categorical

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
1호
139 
2호
133 
3호
104 
4호
104 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1호
2nd row1호
3rd row1호
4th row1호
5th row1호

Common Values

ValueCountFrequency (%)
1호 139
29.0%
2호 133
27.7%
3호 104
21.7%
4호 104
21.7%

Length

2023-12-13T02:18:38.934414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:18:39.034862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1호 139
29.0%
2호 133
27.7%
3호 104
21.7%
4호 104
21.7%

제목
Text

UNIQUE 

Distinct480
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-12-13T02:18:39.404930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length157
Median length77
Mean length38.354167
Min length8

Characters and Unicode

Total characters18410
Distinct characters639
Distinct categories12 ?
Distinct scripts6 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique480 ?
Unique (%)100.0%

Sample

1st row특허권의 역사적 변화와 자연권적 재산권으로서의 특허권의 변화
2nd row특허권 강화와 지식의 사유화 -미국의 특허개혁을 중심으로-
3rd row인간배아줄기세포와 특허
4th row식물품종의 지적재산권 보호제도
5th row간행물의 반포시기 결정에 관한 연구
ValueCountFrequency (%)
관한 131
 
3.3%
연구 102
 
2.6%
중심으로 92
 
2.4%
대한 84
 
2.1%
70
 
1.8%
고찰 51
 
1.3%
및 46
 
1.2%
분석 39
 
1.0%
위한 31
 
0.8%
특허 30
 
0.8%
Other values (2075) 3236
82.7%
2023-12-13T02:18:40.078856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3522
 
19.1%
의 569
 
3.1%
한 375
 
2.0%
에 352
 
1.9%
특 220
 
1.2%
기 215
 
1.2%
허 210
 
1.1%
법 204
 
1.1%
제 191
 
1.0%
관 187
 
1.0%
Other values (629) 12365
67.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12200
66.3%
Space Separator 3522
 
19.1%
Lowercase Letter 1211
 
6.6%
Uppercase Letter 505
 
2.7%
Decimal Number 438
 
2.4%
Other Punctuation 200
 
1.1%
Dash Punctuation 179
 
1.0%
Open Punctuation 48
 
0.3%
Close Punctuation 48
 
0.3%
Final Punctuation 29
 
0.2%
Other values (2) 30
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 569
 
4.7%
한 375
 
3.1%
에 352
 
2.9%
특 220
 
1.8%
기 215
 
1.8%
허 210
 
1.7%
법 204
 
1.7%
제 191
 
1.6%
관 187
 
1.5%
대 165
 
1.4%
Other values (550) 9512
78.0%
Lowercase Letter
ValueCountFrequency (%)
e 138
11.4%
t 117
9.7%
a 108
 
8.9%
n 106
 
8.8%
i 96
 
7.9%
o 96
 
7.9%
r 82
 
6.8%
s 69
 
5.7%
l 61
 
5.0%
c 50
 
4.1%
Other values (16) 288
23.8%
Uppercase Letter
ValueCountFrequency (%)
P 51
10.1%
A 47
 
9.3%
I 44
 
8.7%
T 44
 
8.7%
C 39
 
7.7%
R 38
 
7.5%
S 35
 
6.9%
D 31
 
6.1%
E 31
 
6.1%
M 20
 
4.0%
Other values (15) 125
24.8%
Decimal Number
ValueCountFrequency (%)
2 113
25.8%
1 92
21.0%
0 70
16.0%
3 30
 
6.8%
5 26
 
5.9%
4 24
 
5.5%
7 22
 
5.0%
8 22
 
5.0%
6 20
 
4.6%
9 19
 
4.3%
Other Punctuation
ValueCountFrequency (%)
. 71
35.5%
: 70
35.0%
, 28
 
14.0%
· 16
 
8.0%
& 11
 
5.5%
/ 4
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 126
70.4%
― 53
29.6%
Open Punctuation
ValueCountFrequency (%)
( 45
93.8%
[ 3
 
6.2%
Close Punctuation
ValueCountFrequency (%)
) 45
93.8%
] 3
 
6.2%
Final Punctuation
ValueCountFrequency (%)
’ 23
79.3%
” 6
 
20.7%
Initial Punctuation
ValueCountFrequency (%)
‘ 22
78.6%
“ 6
 
21.4%
Space Separator
ValueCountFrequency (%)
3522
100.0%
Format
ValueCountFrequency (%)
­ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11934
64.8%
Common 4494
 
24.4%
Latin 1716
 
9.3%
Han 197
 
1.1%
Hiragana 37
 
0.2%
Katakana 32
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 569
 
4.8%
한 375
 
3.1%
에 352
 
2.9%
특 220
 
1.8%
기 215
 
1.8%
허 210
 
1.8%
법 204
 
1.7%
제 191
 
1.6%
관 187
 
1.6%
대 165
 
1.4%
Other values (407) 9246
77.5%
Han
ValueCountFrequency (%)
中 8
 
4.1%
權 8
 
4.1%
商 6
 
3.0%
的 6
 
3.0%
法 6
 
3.0%
標 5
 
2.5%
作 5
 
2.5%
制 4
 
2.0%
度 4
 
2.0%
知 4
 
2.0%
Other values (101) 141
71.6%
Latin
ValueCountFrequency (%)
e 138
 
8.0%
t 117
 
6.8%
a 108
 
6.3%
n 106
 
6.2%
i 96
 
5.6%
o 96
 
5.6%
r 82
 
4.8%
s 69
 
4.0%
l 61
 
3.6%
P 51
 
3.0%
Other values (41) 792
46.2%
Common
ValueCountFrequency (%)
3522
78.4%
- 126
 
2.8%
2 113
 
2.5%
1 92
 
2.0%
. 71
 
1.6%
0 70
 
1.6%
: 70
 
1.6%
― 53
 
1.2%
( 45
 
1.0%
) 45
 
1.0%
Other values (18) 287
 
6.4%
Katakana
ValueCountFrequency (%)
イ 4
12.5%
ク 3
 
9.4%
ラ 2
 
6.2%
フ 2
 
6.2%
ド 2
 
6.2%
ウ 2
 
6.2%
ソ 2
 
6.2%
ス 2
 
6.2%
ア 2
 
6.2%
ル 2
 
6.2%
Other values (8) 9
28.1%
Hiragana
ValueCountFrequency (%)
の 8
21.6%
に 5
13.5%
と 4
10.8%
お 4
10.8%
る 4
10.8%
け 3
 
8.1%
て 2
 
5.4%
を 1
 
2.7%
し 1
 
2.7%
す 1
 
2.7%
Other values (4) 4
10.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11930
64.8%
ASCII 6082
33.0%
CJK 197
 
1.1%
Punctuation 110
 
0.6%
Hiragana 37
 
0.2%
Katakana 32
 
0.2%
None 18
 
0.1%
Compat Jamo 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3522
57.9%
e 138
 
2.3%
- 126
 
2.1%
t 117
 
1.9%
2 113
 
1.9%
a 108
 
1.8%
n 106
 
1.7%
i 96
 
1.6%
o 96
 
1.6%
1 92
 
1.5%
Other values (62) 1568
25.8%
Hangul
ValueCountFrequency (%)
의 569
 
4.8%
한 375
 
3.1%
에 352
 
3.0%
특 220
 
1.8%
기 215
 
1.8%
허 210
 
1.8%
법 204
 
1.7%
제 191
 
1.6%
관 187
 
1.6%
대 165
 
1.4%
Other values (406) 9242
77.5%
Punctuation
ValueCountFrequency (%)
― 53
48.2%
’ 23
20.9%
‘ 22
20.0%
“ 6
 
5.5%
” 6
 
5.5%
None
ValueCountFrequency (%)
· 16
88.9%
­ 2
 
11.1%
CJK
ValueCountFrequency (%)
中 8
 
4.1%
權 8
 
4.1%
商 6
 
3.0%
的 6
 
3.0%
法 6
 
3.0%
標 5
 
2.5%
作 5
 
2.5%
制 4
 
2.0%
度 4
 
2.0%
知 4
 
2.0%
Other values (101) 141
71.6%
Hiragana
ValueCountFrequency (%)
の 8
21.6%
に 5
13.5%
と 4
10.8%
お 4
10.8%
る 4
10.8%
け 3
 
8.1%
て 2
 
5.4%
を 1
 
2.7%
し 1
 
2.7%
す 1
 
2.7%
Other values (4) 4
10.8%
Katakana
ValueCountFrequency (%)
イ 4
12.5%
ク 3
 
9.4%
ラ 2
 
6.2%
フ 2
 
6.2%
ド 2
 
6.2%
ウ 2
 
6.2%
ソ 2
 
6.2%
ス 2
 
6.2%
ア 2
 
6.2%
ル 2
 
6.2%
Other values (8) 9
28.1%
Compat Jamo
ValueCountFrequency (%)
ㆍ 4
100.0%

저자
Text

Distinct349
Distinct (%)72.7%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-12-13T02:18:40.457544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length3
Mean length5.3729167
Min length2

Characters and Unicode

Total characters2579
Distinct characters238
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique278 ?
Unique (%)57.9%

Sample

1st row나종갑
2nd row서환주
3rd row김병일
4th row최근진
5th row정차호
ValueCountFrequency (%)
정차호 11
 
1.6%
이성상 10
 
1.4%
윤장혁 9
 
1.3%
안원모 7
 
1.0%
이주환 7
 
1.0%
윤권순 7
 
1.0%
박윤석 6
 
0.9%
김용길 6
 
0.9%
박성필 6
 
0.9%
김수철 6
 
0.9%
Other values (437) 625
89.3%
2023-12-13T02:18:41.052496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
235
 
9.1%
, 193
 
7.5%
이 106
 
4.1%
김 82
 
3.2%
정 74
 
2.9%
박 68
 
2.6%
영 52
 
2.0%
성 47
 
1.8%
수 45
 
1.7%
호 43
 
1.7%
Other values (228) 1634
63.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2003
77.7%
Space Separator 235
 
9.1%
Other Punctuation 197
 
7.6%
Lowercase Letter 107
 
4.1%
Uppercase Letter 32
 
1.2%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 106
 
5.3%
김 82
 
4.1%
정 74
 
3.7%
박 68
 
3.4%
영 52
 
2.6%
성 47
 
2.3%
수 45
 
2.2%
호 43
 
2.1%
상 41
 
2.0%
재 39
 
1.9%
Other values (185) 1406
70.2%
Lowercase Letter
ValueCountFrequency (%)
a 16
15.0%
n 13
12.1%
i 11
10.3%
e 11
10.3%
u 9
8.4%
o 8
 
7.5%
h 6
 
5.6%
s 5
 
4.7%
t 4
 
3.7%
d 3
 
2.8%
Other values (11) 21
19.6%
Uppercase Letter
ValueCountFrequency (%)
S 5
15.6%
L 4
12.5%
D 3
9.4%
G 3
9.4%
J 3
9.4%
Y 3
9.4%
P 2
 
6.2%
K 2
 
6.2%
N 1
 
3.1%
R 1
 
3.1%
Other values (5) 5
15.6%
Other Punctuation
ValueCountFrequency (%)
, 193
98.0%
. 3
 
1.5%
& 1
 
0.5%
Space Separator
ValueCountFrequency (%)
235
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1959
76.0%
Common 437
 
16.9%
Latin 139
 
5.4%
Han 44
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 106
 
5.4%
김 82
 
4.2%
정 74
 
3.8%
박 68
 
3.5%
영 52
 
2.7%
성 47
 
2.4%
수 45
 
2.3%
호 43
 
2.2%
상 41
 
2.1%
재 39
 
2.0%
Other values (151) 1362
69.5%
Latin
ValueCountFrequency (%)
a 16
 
11.5%
n 13
 
9.4%
i 11
 
7.9%
e 11
 
7.9%
u 9
 
6.5%
o 8
 
5.8%
h 6
 
4.3%
s 5
 
3.6%
S 5
 
3.6%
L 4
 
2.9%
Other values (26) 51
36.7%
Han
ValueCountFrequency (%)
玉 3
 
6.8%
男 3
 
6.8%
晴 3
 
6.8%
兒 2
 
4.5%
喜 2
 
4.5%
李 2
 
4.5%
田 2
 
4.5%
坤 1
 
2.3%
王 1
 
2.3%
村 1
 
2.3%
Other values (24) 24
54.5%
Common
ValueCountFrequency (%)
235
53.8%
, 193
44.2%
. 3
 
0.7%
( 2
 
0.5%
) 2
 
0.5%
& 1
 
0.2%
- 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1959
76.0%
ASCII 576
 
22.3%
CJK 44
 
1.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
235
40.8%
, 193
33.5%
a 16
 
2.8%
n 13
 
2.3%
i 11
 
1.9%
e 11
 
1.9%
u 9
 
1.6%
o 8
 
1.4%
h 6
 
1.0%
s 5
 
0.9%
Other values (33) 69
 
12.0%
Hangul
ValueCountFrequency (%)
이 106
 
5.4%
김 82
 
4.2%
정 74
 
3.8%
박 68
 
3.5%
영 52
 
2.7%
성 47
 
2.4%
수 45
 
2.3%
호 43
 
2.2%
상 41
 
2.1%
재 39
 
2.0%
Other values (151) 1362
69.5%
CJK
ValueCountFrequency (%)
玉 3
 
6.8%
男 3
 
6.8%
晴 3
 
6.8%
兒 2
 
4.5%
喜 2
 
4.5%
李 2
 
4.5%
田 2
 
4.5%
坤 1
 
2.3%
王 1
 
2.3%
村 1
 
2.3%
Other values (24) 24
54.5%

등록일
Date

Distinct67
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
Minimum2005-02-23 00:00:00
Maximum2023-07-07 00:00:00
2023-12-13T02:18:41.211038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:18:41.393352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-13T02:18:38.195533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:18:41.526895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호권호등록일
번호1.0000.9750.3300.996
권0.9751.0000.2670.999
호0.3300.2671.0000.995
등록일0.9960.9990.9951.000
2023-12-13T02:18:41.644495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
호권
호1.0000.146
권0.1461.000
2023-12-13T02:18:41.750392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호권호
번호1.0000.8670.202
권0.8671.0000.146
호0.2020.1461.000

Missing values

2023-12-13T02:18:38.306936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:18:38.418558image/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

번호권호제목저자등록일
011권1호특허권의 역사적 변화와 자연권적 재산권으로서의 특허권의 변화나종갑2005-02-23
121권1호특허권 강화와 지식의 사유화 -미국의 특허개혁을 중심으로-서환주2005-02-23
231권1호인간배아줄기세포와 특허김병일2005-02-23
341권1호식물품종의 지적재산권 보호제도최근진2005-02-23
451권1호간행물의 반포시기 결정에 관한 연구정차호2005-02-23
561권1호국제특허분쟁의 소송절차적 대응전략김용진2005-02-23
671권1호단일색채의 상표등록 여부에 관한 검토 - Qualitex 사건판결을 중심으로 -배대헌2005-02-23
781권1호베니스 특허법 분석을 통한 특허제도 본질에 대한 고찰윤권순2008-11-17
891권1호공유특허권의 실시와 실시허락고영수2008-11-17
9101권1호지식재산의 이전과 주식이성상, 이정동, 류태규2008-11-17
번호권호제목저자등록일
47047118권1호일본의 한정제공데이터 보호 규정 재논의와 데이터에 관한 우리 부정경쟁방지법의 개정 방안김시열2023-04-11
47147218권1호텍스트데이터 마이닝 과정의 저작물 이용 면책 규정 신설안에 대한 소고 적대적 생성신경망에의 적용김성원, 최상민, 이수원2023-04-11
47247318권1호저작권법상 데이터베이스 보호 규정의 재검토 대법원 2022. 5. 12. 선고 2021도1533 판결에 대한 평가를 겸하여류시원2023-04-11
47347418권1호특허-상표 연계 데이터를 활용한 기술기반 기업의 비즈니스 기회 발굴 방법이지호, 고남욱, 김철한, 윤장혁2023-04-11
47447518권2호지식재산 거래시장의 활성화를 위한 NFT 규제정책 연구나황영, 김용길, 박성필2023-04-11
47547618권2호직무발명 보상금 산정 법리의 개선방안 모색이주환2023-07-07
47647718권2호데이터마이닝(TDM)과 특허권의 효력제한권지현2023-07-07
47747818권2호메타버스에서의 디자인보호 개정 화상디자인 제도의 공백을 감안하여조영선2023-07-07
47847918권2호국가연구개발사업의 질적 성과지표 영향요인 비교연구 삼극특허 및 SMART5를 중심으로조용희, 안수용2023-07-07
47948018권2호부정경쟁방지법상 상품형태모방규제에 있어서 “타인”의 의미와 청구주체박선하, 양인수2023-07-07