Overview

Dataset statistics

Number of variables9
Number of observations577
Missing cells13
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory41.3 KiB
Average record size in memory73.2 B

Variable types

Text5
Categorical3
Numeric1

Dataset

Description2021년 2월 기준 ICTBAY 특허클러스트 분류별 특허 정보입니다.
Author한국연구재단 정보통신기획평가원
URLhttps://www.data.go.kr/data/15077403/fileData.do

Alerts

생성사용자 is highly imbalanced (95.3%)Imbalance
국가 is highly imbalanced (53.5%)Imbalance
상태 is highly imbalanced (58.3%)Imbalance
출원번호 has 12 (2.1%) missing valuesMissing
특허 has unique valuesUnique

Reproduction

Analysis started2023-12-12 03:52:52.751583
Analysis finished2023-12-12 03:52:54.317800
Duration1.57 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

특허
Text

UNIQUE 

Distinct577
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
2023-12-12T12:52:54.570524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters10386
Distinct characters36
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique577 ?
Unique (%)100.0%

Sample

1st row75EFMNGKP04WQ1N000
2nd row75EE21SU804VURU000
3rd row75EE224TG04VUX1000
4th row75EE2261A04VUXR000
5th row75EE21Y1J04VUU7000
ValueCountFrequency (%)
75efmngkp04wq1n000 1
 
0.2%
75edwqctq04vm6h000 1
 
0.2%
75efq7ewr04wusd000 1
 
0.2%
75efmndss04wq05000 1
 
0.2%
75efmndss04wq06000 1
 
0.2%
75efmndss04wq07000 1
 
0.2%
75efmndss04wq08000 1
 
0.2%
75efmndss04wq09000 1
 
0.2%
75efmndss04wq0a000 1
 
0.2%
75efq7ewr04wusg000 1
 
0.2%
Other values (567) 567
98.3%
2023-12-12T12:52:55.102359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2541
24.5%
E 845
 
8.1%
5 745
 
7.2%
7 646
 
6.2%
4 635
 
6.1%
V 382
 
3.7%
X 335
 
3.2%
F 291
 
2.8%
A 275
 
2.6%
Z 252
 
2.4%
Other values (26) 3439
33.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5244
50.5%
Uppercase Letter 5142
49.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 845
16.4%
V 382
 
7.4%
X 335
 
6.5%
F 291
 
5.7%
A 275
 
5.3%
Z 252
 
4.9%
H 246
 
4.8%
W 232
 
4.5%
Y 200
 
3.9%
R 194
 
3.8%
Other values (16) 1890
36.8%
Decimal Number
ValueCountFrequency (%)
0 2541
48.5%
5 745
 
14.2%
7 646
 
12.3%
4 635
 
12.1%
8 186
 
3.5%
2 133
 
2.5%
6 102
 
1.9%
9 93
 
1.8%
1 88
 
1.7%
3 75
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
Common 5244
50.5%
Latin 5142
49.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 845
16.4%
V 382
 
7.4%
X 335
 
6.5%
F 291
 
5.7%
A 275
 
5.3%
Z 252
 
4.9%
H 246
 
4.8%
W 232
 
4.5%
Y 200
 
3.9%
R 194
 
3.8%
Other values (16) 1890
36.8%
Common
ValueCountFrequency (%)
0 2541
48.5%
5 745
 
14.2%
7 646
 
12.3%
4 635
 
12.1%
8 186
 
3.5%
2 133
 
2.5%
6 102
 
1.9%
9 93
 
1.8%
1 88
 
1.7%
3 75
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10386
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2541
24.5%
E 845
 
8.1%
5 745
 
7.2%
7 646
 
6.2%
4 635
 
6.1%
V 382
 
3.7%
X 335
 
3.2%
F 291
 
2.8%
A 275
 
2.6%
Z 252
 
2.4%
Other values (26) 3439
33.1%

생성사용자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
000000000000000UU0
574 
759PD9UEM04KGWN000
 
3

Length

Max length18
Median length18
Mean length18
Min length18

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row000000000000000UU0
2nd row000000000000000UU0
3rd row000000000000000UU0
4th row000000000000000UU0
5th row000000000000000UU0

Common Values

ValueCountFrequency (%)
000000000000000UU0 574
99.5%
759PD9UEM04KGWN000 3
 
0.5%

Length

2023-12-12T12:52:55.311297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:52:55.457971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
000000000000000uu0 574
99.5%
759pd9uem04kgwn000 3
 
0.5%

생성일시
Text

Distinct155
Distinct (%)26.9%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
2023-12-12T12:52:55.814553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length21.39688
Min length21

Characters and Unicode

Total characters12346
Distinct characters16
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)8.8%

Sample

1st row2017-10-10 오후 4:41:37
2nd row2017-09-15 오전 9:51:04
3rd row2017-09-15 오전 11:06:28
4th row2017-09-15 오전 11:22:06
5th row2017-09-15 오전 10:18:47
ValueCountFrequency (%)
오후 308
17.8%
오전 269
 
15.5%
2017-09-12 85
 
4.9%
2017-11-10 81
 
4.7%
2017-11-08 75
 
4.3%
2017-09-15 53
 
3.1%
2017-10-30 50
 
2.9%
2017-10-12 45
 
2.6%
1:33:59 30
 
1.7%
11:01:38 30
 
1.7%
Other values (173) 705
40.7%
2023-12-12T12:52:56.480321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2102
17.0%
0 1773
14.4%
- 1154
9.3%
1154
9.3%
: 1154
9.3%
2 1017
8.2%
7 678
 
5.5%
오 577
 
4.7%
4 469
 
3.8%
3 457
 
3.7%
Other values (6) 1811
14.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7730
62.6%
Dash Punctuation 1154
 
9.3%
Space Separator 1154
 
9.3%
Other Punctuation 1154
 
9.3%
Other Letter 1154
 
9.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2102
27.2%
0 1773
22.9%
2 1017
13.2%
7 678
 
8.8%
4 469
 
6.1%
3 457
 
5.9%
9 423
 
5.5%
5 397
 
5.1%
8 279
 
3.6%
6 135
 
1.7%
Other Letter
ValueCountFrequency (%)
오 577
50.0%
후 308
26.7%
전 269
23.3%
Dash Punctuation
ValueCountFrequency (%)
- 1154
100.0%
Space Separator
ValueCountFrequency (%)
1154
100.0%
Other Punctuation
ValueCountFrequency (%)
: 1154
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11192
90.7%
Hangul 1154
 
9.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2102
18.8%
0 1773
15.8%
- 1154
10.3%
1154
10.3%
: 1154
10.3%
2 1017
9.1%
7 678
 
6.1%
4 469
 
4.2%
3 457
 
4.1%
9 423
 
3.8%
Other values (3) 811
 
7.2%
Hangul
ValueCountFrequency (%)
오 577
50.0%
후 308
26.7%
전 269
23.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11192
90.7%
Hangul 1154
 
9.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2102
18.8%
0 1773
15.8%
- 1154
10.3%
1154
10.3%
: 1154
10.3%
2 1017
9.1%
7 678
 
6.1%
4 469
 
4.2%
3 457
 
4.1%
9 423
 
3.8%
Other values (3) 811
 
7.2%
Hangul
ValueCountFrequency (%)
오 577
50.0%
후 308
26.7%
전 269
23.3%

국가
Categorical

IMBALANCE 

Distinct22
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
대한민국
292 
한국
164 
미국
62 
PCT
 
14
미국
 
7
Other values (17)
38 

Length

Max length10
Median length4
Mean length3.1455806
Min length2

Unique

Unique9 ?
Unique (%)1.6%

Sample

1st row대한민국
2nd row유럽
3rd row대한민국
4th row대한민국
5th row대한민국

Common Values

ValueCountFrequency (%)
대한민국 292
50.6%
한국 164
28.4%
미국 62
 
10.7%
PCT 14
 
2.4%
미국 7
 
1.2%
한국 6
 
1.0%
대한민국 5
 
0.9%
중국 4
 
0.7%
국내 4
 
0.7%
전세계 3
 
0.5%
Other values (12) 16
 
2.8%

Length

2023-12-12T12:52:56.729990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대한민국 298
51.5%
한국 170
29.4%
미국 69
 
11.9%
pct 16
 
2.8%
중국 4
 
0.7%
국내 4
 
0.7%
전세계 3
 
0.5%
한국/미국 3
 
0.5%
korea 2
 
0.3%
us 2
 
0.3%
Other values (7) 8
 
1.4%

출원번호
Text

MISSING 

Distinct541
Distinct (%)95.8%
Missing12
Missing (%)2.1%
Memory size4.6 KiB
2023-12-12T12:52:57.071205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length26
Mean length20.500885
Min length1

Characters and Unicode

Total characters11583
Distinct characters60
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique525 ?
Unique (%)92.9%

Sample

1st row10-2016-0104905 (2016-08-18)
2nd row90121294
3rd row1020150191029 (2015.12.31)
4th row10-2016-057329
5th row10-2015-0165598(2015.11.25)
ValueCountFrequency (%)
1.02e+12 9
 
1.3%
us 9
 
1.3%
2016.08.31 4
 
0.6%
2016 4
 
0.6%
2017 4
 
0.6%
10-2014-0010948/2 3
 
0.4%
10 2
 
0.3%
2017.01.25 2
 
0.3%
2016.10.19 2
 
0.3%
2016-0129678 2
 
0.3%
Other values (649) 673
94.3%
2023-12-12T12:52:57.657210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2441
21.1%
1 2010
17.4%
2 1303
11.2%
- 855
 
7.4%
6 737
 
6.4%
7 547
 
4.7%
. 491
 
4.2%
5 478
 
4.1%
3 437
 
3.8%
4 384
 
3.3%
Other values (50) 1900
16.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8988
77.6%
Dash Punctuation 855
 
7.4%
Other Punctuation 679
 
5.9%
Open Punctuation 347
 
3.0%
Close Punctuation 345
 
3.0%
Space Separator 192
 
1.7%
Uppercase Letter 124
 
1.1%
Other Letter 27
 
0.2%
Lowercase Letter 17
 
0.1%
Math Symbol 9
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
년 5
18.5%
건 3
11.1%
원 3
11.1%
출 3
11.1%
월 2
 
7.4%
진 1
 
3.7%
행 1
 
3.7%
국 1
 
3.7%
정 1
 
3.7%
예 1
 
3.7%
Other values (6) 6
22.2%
Uppercase Letter
ValueCountFrequency (%)
R 19
15.3%
P 18
14.5%
K 17
13.7%
C 16
12.9%
T 15
12.1%
U 10
8.1%
S 10
8.1%
E 9
7.3%
X 2
 
1.6%
A 2
 
1.6%
Other values (5) 6
 
4.8%
Decimal Number
ValueCountFrequency (%)
0 2441
27.2%
1 2010
22.4%
2 1303
14.5%
6 737
 
8.2%
7 547
 
6.1%
5 478
 
5.3%
3 437
 
4.9%
4 384
 
4.3%
9 339
 
3.8%
8 312
 
3.5%
Lowercase Letter
ValueCountFrequency (%)
u 3
17.6%
e 3
17.6%
a 2
11.8%
t 2
11.8%
n 2
11.8%
b 1
 
5.9%
r 1
 
5.9%
g 1
 
5.9%
l 1
 
5.9%
y 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 491
72.3%
/ 161
 
23.7%
, 26
 
3.8%
: 1
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 855
100.0%
Open Punctuation
ValueCountFrequency (%)
( 347
100.0%
Close Punctuation
ValueCountFrequency (%)
) 345
100.0%
Space Separator
ValueCountFrequency (%)
192
100.0%
Math Symbol
ValueCountFrequency (%)
+ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11415
98.5%
Latin 141
 
1.2%
Hangul 27
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
R 19
13.5%
P 18
12.8%
K 17
12.1%
C 16
11.3%
T 15
10.6%
U 10
7.1%
S 10
7.1%
E 9
6.4%
u 3
 
2.1%
e 3
 
2.1%
Other values (15) 21
14.9%
Common
ValueCountFrequency (%)
0 2441
21.4%
1 2010
17.6%
2 1303
11.4%
- 855
 
7.5%
6 737
 
6.5%
7 547
 
4.8%
. 491
 
4.3%
5 478
 
4.2%
3 437
 
3.8%
4 384
 
3.4%
Other values (9) 1732
15.2%
Hangul
ValueCountFrequency (%)
년 5
18.5%
건 3
11.1%
원 3
11.1%
출 3
11.1%
월 2
 
7.4%
진 1
 
3.7%
행 1
 
3.7%
국 1
 
3.7%
정 1
 
3.7%
예 1
 
3.7%
Other values (6) 6
22.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11556
99.8%
Hangul 27
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2441
21.1%
1 2010
17.4%
2 1303
11.3%
- 855
 
7.4%
6 737
 
6.4%
7 547
 
4.7%
. 491
 
4.2%
5 478
 
4.1%
3 437
 
3.8%
4 384
 
3.3%
Other values (34) 1873
16.2%
Hangul
ValueCountFrequency (%)
년 5
18.5%
건 3
11.1%
원 3
11.1%
출 3
11.1%
월 2
 
7.4%
진 1
 
3.7%
행 1
 
3.7%
국 1
 
3.7%
정 1
 
3.7%
예 1
 
3.7%
Other values (6) 6
22.2%

상태
Categorical

IMBALANCE 

Distinct30
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
출원
332 
등록
155 
출원완료
 
13
출원
 
12
<NA>
 
10
Other values (25)
55 

Length

Max length8
Median length2
Mean length2.339688
Min length2

Unique

Unique13 ?
Unique (%)2.3%

Sample

1st row등록진행중
2nd row등록
3rd row출원
4th row출원
5th row출원

Common Values

ValueCountFrequency (%)
출원 332
57.5%
등록 155
26.9%
출원완료 13
 
2.3%
출원 12
 
2.1%
<NA> 10
 
1.7%
출원 완료 6
 
1.0%
출원 5
 
0.9%
등록 5
 
0.9%
출원 진행 중 4
 
0.7%
등록완료 4
 
0.7%
Other values (20) 31
 
5.4%

Length

2023-12-12T12:52:57.901707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
출원 368
60.2%
등록 161
26.4%
출원완료 13
 
2.1%
na 10
 
1.6%
완료 7
 
1.1%
중 7
 
1.1%
진행 4
 
0.7%
등록완료 4
 
0.7%
예정 4
 
0.7%
출 3
 
0.5%
Other values (19) 30
 
4.9%

명칭
Text

Distinct528
Distinct (%)91.7%
Missing1
Missing (%)0.2%
Memory size4.6 KiB
2023-12-12T12:52:58.401604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length144
Median length78
Mean length34.03125
Min length3

Characters and Unicode

Total characters19602
Distinct characters530
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique485 ?
Unique (%)84.2%

Sample

1st row스마트 환경에서의 강화 학습을 이용한 태스크 중심의 서비스 개인화 기법
2nd rowPET-MRI 융합시스템
3rd row사물 인터넷（ＩｏＴ）네트워크의 보안을 유지 및 강화하기 위한 시스템
4th row비연속적으로 확률 뉴런을 가지는 딥러닝 모델 및 지식 전파에 기반한 학습 방법 및 그 시스템
5th row비콘 단말기의 위치 추정 장치 및 그 방법
ValueCountFrequency (%)
및 298
 
6.6%
방법 285
 
6.3%
장치 183
 
4.1%
시스템 96
 
2.1%
이용한 93
 
2.1%
위한 85
 
1.9%
그 69
 
1.5%
안테나 51
 
1.1%
and 49
 
1.1%
method 44
 
1.0%
Other values (1656) 3259
72.2%
2023-12-12T12:52:59.043470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4035
 
20.6%
방 371
 
1.9%
법 346
 
1.8%
이 322
 
1.6%
및 313
 
1.6%
A 265
 
1.4%
장 258
 
1.3%
치 258
 
1.3%
스 254
 
1.3%
한 250
 
1.3%
Other values (520) 12930
66.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10375
52.9%
Space Separator 4035
 
20.6%
Uppercase Letter 2825
 
14.4%
Lowercase Letter 2179
 
11.1%
Dash Punctuation 59
 
0.3%
Decimal Number 44
 
0.2%
Other Punctuation 39
 
0.2%
Close Punctuation 23
 
0.1%
Open Punctuation 23
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
방 371
 
3.6%
법 346
 
3.3%
이 322
 
3.1%
및 313
 
3.0%
장 258
 
2.5%
치 258
 
2.5%
스 254
 
2.4%
한 250
 
2.4%
기 218
 
2.1%
시 210
 
2.0%
Other values (447) 7575
73.0%
Uppercase Letter
ValueCountFrequency (%)
A 265
 
9.4%
E 234
 
8.3%
N 225
 
8.0%
T 224
 
7.9%
O 206
 
7.3%
I 183
 
6.5%
M 179
 
6.3%
S 174
 
6.2%
R 156
 
5.5%
C 153
 
5.4%
Other values (22) 826
29.2%
Lowercase Letter
ValueCountFrequency (%)
e 224
10.3%
t 210
 
9.6%
o 205
 
9.4%
a 195
 
8.9%
n 187
 
8.6%
i 159
 
7.3%
r 154
 
7.1%
s 113
 
5.2%
d 98
 
4.5%
l 75
 
3.4%
Other values (17) 559
25.7%
Other Punctuation
ValueCountFrequency (%)
, 27
69.2%
/ 8
 
20.5%
' 3
 
7.7%
. 1
 
2.6%
Decimal Number
ValueCountFrequency (%)
3 21
47.7%
2 18
40.9%
1 3
 
6.8%
0 2
 
4.5%
Close Punctuation
ValueCountFrequency (%)
) 22
95.7%
） 1
 
4.3%
Open Punctuation
ValueCountFrequency (%)
( 22
95.7%
（ 1
 
4.3%
Space Separator
ValueCountFrequency (%)
4035
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 59
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10375
52.9%
Latin 5004
25.5%
Common 4223
21.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
방 371
 
3.6%
법 346
 
3.3%
이 322
 
3.1%
및 313
 
3.0%
장 258
 
2.5%
치 258
 
2.5%
스 254
 
2.4%
한 250
 
2.4%
기 218
 
2.1%
시 210
 
2.0%
Other values (447) 7575
73.0%
Latin
ValueCountFrequency (%)
A 265
 
5.3%
E 234
 
4.7%
N 225
 
4.5%
e 224
 
4.5%
T 224
 
4.5%
t 210
 
4.2%
O 206
 
4.1%
o 205
 
4.1%
a 195
 
3.9%
n 187
 
3.7%
Other values (49) 2829
56.5%
Common
ValueCountFrequency (%)
4035
95.5%
- 59
 
1.4%
, 27
 
0.6%
) 22
 
0.5%
( 22
 
0.5%
3 21
 
0.5%
2 18
 
0.4%
/ 8
 
0.2%
1 3
 
0.1%
' 3
 
0.1%
Other values (4) 5
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10375
52.9%
ASCII 9202
46.9%
None 25
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4035
43.8%
A 265
 
2.9%
E 234
 
2.5%
N 225
 
2.4%
e 224
 
2.4%
T 224
 
2.4%
t 210
 
2.3%
O 206
 
2.2%
o 205
 
2.2%
a 195
 
2.1%
Other values (52) 3179
34.5%
Hangul
ValueCountFrequency (%)
방 371
 
3.6%
법 346
 
3.3%
이 322
 
3.1%
및 313
 
3.0%
장 258
 
2.5%
치 258
 
2.5%
스 254
 
2.4%
한 250
 
2.4%
기 218
 
2.1%
시 210
 
2.0%
Other values (447) 7575
73.0%
None
ValueCountFrequency (%)
Ｄ 6
24.0%
Ｅ 5
20.0%
Ｌ 5
20.0%
Ｉ 2
 
8.0%
（ 1
 
4.0%
ｏ 1
 
4.0%
Ｎ 1
 
4.0%
Ｆ 1
 
4.0%
Ｃ 1
 
4.0%
Ｔ 1
 
4.0%

특허순번
Real number (ℝ)

Distinct49
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.7677643
Minimum1
Maximum49
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2023-12-12T12:52:59.235254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q36
95-th percentile33
Maximum49
Range48
Interquartile range (IQR)5

Descriptive statistics

Standard deviation9.7625347
Coefficient of variation (CV)1.4425051
Kurtosis5.9022074
Mean6.7677643
Median Absolute Deviation (MAD)2
Skewness2.5386924
Sum3905
Variance95.307084
MonotonicityNot monotonic
2023-12-12T12:52:59.393795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
1 151
26.2%
2 100
17.3%
3 67
11.6%
4 47
 
8.1%
5 41
 
7.1%
6 27
 
4.7%
7 20
 
3.5%
8 14
 
2.4%
9 11
 
1.9%
10 8
 
1.4%
Other values (39) 91
15.8%
ValueCountFrequency (%)
1 151
26.2%
2 100
17.3%
3 67
11.6%
4 47
 
8.1%
5 41
 
7.1%
6 27
 
4.7%
7 20
 
3.5%
8 14
 
2.4%
9 11
 
1.9%
10 8
 
1.4%
ValueCountFrequency (%)
49 1
0.2%
48 1
0.2%
47 1
0.2%
46 1
0.2%
45 2
0.3%
44 2
0.3%
43 2
0.3%
42 2
0.3%
41 2
0.3%
40 2
0.3%

기술
Text

Distinct151
Distinct (%)26.2%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
2023-12-12T12:52:59.681239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters10386
Distinct characters36
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)8.8%

Sample

1st row75EE9QTRK04WJUT000
2nd row75ECNGE0B04VD3G000
3rd row75ECNGBEK04VD1C000
4th row75ECO3GQR04VFK1000
5th row75ECMVLW604VC0Z000
ValueCountFrequency (%)
75edtqxad04vghh000 49
 
8.5%
75ecnh19p04vdaf000 45
 
7.8%
75eco45cf04vfqd000 16
 
2.8%
75eeafdmp04wlf7000 14
 
2.4%
75ee2310k04vvw2000 14
 
2.4%
75eckh4rq04v8k0000 13
 
2.3%
75edwpw8h04vlxz000 10
 
1.7%
75edwp3wp04vlrm000 10
 
1.7%
75eeaf5bl04wl7x000 9
 
1.6%
75eco2mvk04vewr000 9
 
1.6%
Other values (141) 388
67.2%
2023-12-12T12:53:00.150384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2410
23.2%
E 788
 
7.6%
5 703
 
6.8%
7 697
 
6.7%
4 668
 
6.4%
V 630
 
6.1%
C 471
 
4.5%
D 336
 
3.2%
H 258
 
2.5%
A 250
 
2.4%
Other values (26) 3175
30.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 5240
50.5%
Decimal Number 5146
49.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 788
15.0%
V 630
 
12.0%
C 471
 
9.0%
D 336
 
6.4%
H 258
 
4.9%
A 250
 
4.8%
W 226
 
4.3%
F 221
 
4.2%
N 189
 
3.6%
G 147
 
2.8%
Other values (16) 1724
32.9%
Decimal Number
ValueCountFrequency (%)
0 2410
46.8%
5 703
 
13.7%
7 697
 
13.5%
4 668
 
13.0%
1 141
 
2.7%
6 114
 
2.2%
3 109
 
2.1%
2 107
 
2.1%
9 105
 
2.0%
8 92
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 5240
50.5%
Common 5146
49.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 788
15.0%
V 630
 
12.0%
C 471
 
9.0%
D 336
 
6.4%
H 258
 
4.9%
A 250
 
4.8%
W 226
 
4.3%
F 221
 
4.2%
N 189
 
3.6%
G 147
 
2.8%
Other values (16) 1724
32.9%
Common
ValueCountFrequency (%)
0 2410
46.8%
5 703
 
13.7%
7 697
 
13.5%
4 668
 
13.0%
1 141
 
2.7%
6 114
 
2.2%
3 109
 
2.1%
2 107
 
2.1%
9 105
 
2.0%
8 92
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10386
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2410
23.2%
E 788
 
7.6%
5 703
 
6.8%
7 697
 
6.7%
4 668
 
6.4%
V 630
 
6.1%
C 471
 
4.5%
D 336
 
3.2%
H 258
 
2.5%
A 250
 
2.4%
Other values (26) 3175
30.6%

Interactions

2023-12-12T12:52:53.614295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:53:00.278873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
생성사용자국가상태특허순번
생성사용자1.0000.0000.0000.000
국가0.0001.0000.8900.098
상태0.0000.8901.0000.000
특허순번0.0000.0980.0001.000
2023-12-12T12:53:00.438226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상태국가생성사용자
상태1.0000.4570.000
국가0.4571.0000.000
생성사용자0.0000.0001.000
2023-12-12T12:53:00.658874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
특허순번생성사용자국가상태
특허순번1.0000.0000.0390.000
생성사용자0.0001.0000.0000.000
국가0.0390.0001.0000.457
상태0.0000.0000.4571.000

Missing values

2023-12-12T12:52:53.824389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:52:54.055800image/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.
2023-12-12T12:52:54.228353image/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

특허생성사용자생성일시국가출원번호상태명칭특허순번기술
075EFMNGKP04WQ1N000000000000000000UU02017-10-10 오후 4:41:37대한민국10-2016-0104905 (2016-08-18)등록진행중스마트 환경에서의 강화 학습을 이용한 태스크 중심의 서비스 개인화 기법175EE9QTRK04WJUT000
175EE21SU804VURU000000000000000000UU02017-09-15 오전 9:51:04유럽90121294등록PET-MRI 융합시스템175ECNGE0B04VD3G000
275EE224TG04VUX1000000000000000000UU02017-09-15 오전 11:06:28대한민국1020150191029 (2015.12.31)출원사물 인터넷（ＩｏＴ）네트워크의 보안을 유지 및 강화하기 위한 시스템175ECNGBEK04VD1C000
375EE2261A04VUXR000000000000000000UU02017-09-15 오전 11:22:06대한민국10-2016-057329출원비연속적으로 확률 뉴런을 가지는 딥러닝 모델 및 지식 전파에 기반한 학습 방법 및 그 시스템175ECO3GQR04VFK1000
475EE21Y1J04VUU7000000000000000000UU02017-09-15 오전 10:18:47대한민국10-2015-0165598(2015.11.25)출원비콘 단말기의 위치 추정 장치 및 그 방법175ECMVLW604VC0Z000
575EE21Y1J04VUU8000000000000000000UU02017-09-15 오전 10:18:47대한민국10-2016-0145737(2016.11.03)출원이동 비콘의 위치 추정 시스템 및 그 방법275ECMVLW604VC0Z000
675EE1GD0U04VTGB000000000000000000UU02017-09-14 오전 9:48:30미국9,542,559등록Detecting exploitable bugs in binary code275ECO1C4404VE96000
775EE21X5Y04VUT2000000000000000000UU02017-09-15 오전 10:07:10대한민국10-0866617등록차량 운행정보 관리 시스템 및 그 방법275ECMVRC604VC2Z000
875EE21Y1J04VUU9000000000000000000UU02017-09-15 오전 10:18:47대한민국10-2016-0150145(2016.11.11)출원이동 비콘의 실내 위치 추정 시스템 및 그 방법375ECMVLW604VC0Z000
975EE22S9Z04VVOR000000000000000000UU02017-09-15 오후 2:10:31한국10-2016-0050545(2016/04/26)출원소프트웨어의 코드 클론 탐지 장치 및 방법175ECO2WLM04VF8S000
특허생성사용자생성일시국가출원번호상태명칭특허순번기술
56775EH902F204XFXD000000000000000000UU02017-11-08 오후 5:00:46미국14/973795등록결정밀리미터파 멀티 핫 스팟 빔 셀룰러 환경에서의 시스템 운용 방법375EDTPWJN04VG48000
56875EH902PU04XFXZ000000000000000000UU02017-11-08 오후 5:04:34한국2016-0027245 (2016-03-07)출원 중가상 물리 시스템의 라이브러리 구축방법 및 장치175ECI4I4W04V51G000
56975EH902PU04XFY0000000000000000000UU02017-11-08 오후 5:04:34한국10-2017-0031151 (2017.03.13)출원 중제어 대상의 상태 예측 방법 및 장치275ECI4I4W04V51G000
57075EHA5FZF04XGTE000000000000000000UU02017-11-10 오전 10:05:23미국15/194013(2016.05.02.)출원SYSTEM AND METHOD FOR AUTOMATICALLY RECREATING PERSONAL MEDIA THROUGH FUSION OF MULTIMODAL FEATURES175ECJBD5L04V6VC000
57175EHA5FZF04XGTF000000000000000000UU02017-11-10 오전 10:05:23한국2016-0003779(2016.01.08.)출원다중-모달리티 특징 융합을 통한 퍼스널 미디어 자동 재창작 시스템 및 그 동작 방법275ECJBD5L04V6VC000
57275EHA5FZF04XGTG000000000000000000UU02017-11-10 오전 10:05:23한국2015-0178477(2015.12.10.)출원영상 간 이질성이 최소화된 조각 영상 추천장치 및 그 방법375ECJBD5L04V6VC000
57375EHA5FZF04XGTH000000000000000000UU02017-11-10 오전 10:05:23한국2016-0129678 (2016.09.30.)출원조합 미디어 콘텐츠 생성 방법 및 장치475ECJBD5L04V6VC000
57475EHA5FZF04XGTI000000000000000000UU02017-11-10 오전 10:05:23한국2017-0009875 (2017.01.19.)출원영상 처리 장치 및 방법575ECJBD5L04V6VC000
57575IMFUZD104ZTYI000000000000000000UU02018-01-29 오후 3:03:42한국<NA>출원준비중다중 사용자 기반 실외환경 증강현실 콘텐츠 제공 장치 및 방법175ECI4X6P04V56A000
57675IPLJIRV052A81000000000000000000UU02018-03-20 오전 9:18:51대한민국2007-052305(2017.5.17.)등록중견인 수단에 대한 모니터링 장치 및 견인 수단에 대한 모니터링 방법175ECJAX6C04V6NW000