Overview

Dataset statistics

Number of variables8
Number of observations628
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory40.0 KiB
Average record size in memory65.2 B

Variable types

Numeric1
Text4
Categorical2
DateTime1

Dataset

Description국토교통R&D과제별 특허출원 현황으로 과제명, 출원국, 출원구분, 특허명, 출원일, 출원번호, 출원기관 정보 제공
Author국토교통과학기술진흥원
URLhttps://www.data.go.kr/data/15054529/fileData.do

Alerts

출원구분 has constant value ""Constant
출원국 is highly imbalanced (90.1%)Imbalance
번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 08:23:20.002545
Analysis finished2023-12-12 08:23:21.141784
Duration1.14 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct628
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean314.5
Minimum1
Maximum628
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-12T17:23:21.215005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile32.35
Q1157.75
median314.5
Q3471.25
95-th percentile596.65
Maximum628
Range627
Interquartile range (IQR)313.5

Descriptive statistics

Standard deviation181.43226
Coefficient of variation (CV)0.57689114
Kurtosis-1.2
Mean314.5
Median Absolute Deviation (MAD)157
Skewness0
Sum197506
Variance32917.667
MonotonicityStrictly increasing
2023-12-12T17:23:21.380237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
424 1
 
0.2%
417 1
 
0.2%
418 1
 
0.2%
419 1
 
0.2%
420 1
 
0.2%
421 1
 
0.2%
422 1
 
0.2%
423 1
 
0.2%
425 1
 
0.2%
Other values (618) 618
98.4%
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 (%)
628 1
0.2%
627 1
0.2%
626 1
0.2%
625 1
0.2%
624 1
0.2%
623 1
0.2%
622 1
0.2%
621 1
0.2%
620 1
0.2%
619 1
0.2%
Distinct447
Distinct (%)71.2%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2023-12-12T17:23:21.772130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length82
Median length63
Mean length34.971338
Min length11

Characters and Unicode

Total characters21962
Distinct characters544
Distinct categories12 ?
Distinct scripts5 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique322 ?
Unique (%)51.3%

Sample

1st rowAI 기반 건전성 예지진단 데이터베이스 구축
2nd row공정 효율화 의사결정 기술 및 동적 위험성 진단 평가 기술 개발
3rd row플랜트 핵심설비 하드웨어 기반 시뮬레이션 시스템 설계, 가상화 플랫폼 연계 및 검증
4th row플랜트 핵심설비 하드웨어 기반 시뮬레이션 시스템 설계, 가상화 플랫폼 연계 및 검증
5th rowAI·데이터 기반 스마트시티 통합플랫폼 모델 개발 및 실증연구 사업 시행 공고
ValueCountFrequency (%)
개발 451
 
8.4%
340
 
6.3%
기술 176
 
3.3%
기반 114
 
2.1%
위한 90
 
1.7%
시스템 83
 
1.5%
플랫폼 42
 
0.8%
기술개발 40
 
0.7%
스마트 40
 
0.7%
설계 38
 
0.7%
Other values (1739) 3981
73.8%
2023-12-12T17:23:22.398093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4784
 
21.8%
629
 
2.9%
549
 
2.5%
544
 
2.5%
354
 
1.6%
340
 
1.5%
315
 
1.4%
308
 
1.4%
244
 
1.1%
226
 
1.0%
Other values (534) 13669
62.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15386
70.1%
Space Separator 4784
 
21.8%
Uppercase Letter 711
 
3.2%
Lowercase Letter 417
 
1.9%
Other Punctuation 218
 
1.0%
Decimal Number 211
 
1.0%
Open Punctuation 82
 
0.4%
Close Punctuation 82
 
0.4%
Dash Punctuation 48
 
0.2%
Math Symbol 10
 
< 0.1%
Other values (2) 13
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
629
 
4.1%
549
 
3.6%
544
 
3.5%
354
 
2.3%
340
 
2.2%
315
 
2.0%
308
 
2.0%
244
 
1.6%
226
 
1.5%
214
 
1.4%
Other values (455) 11663
75.8%
Lowercase Letter
ValueCountFrequency (%)
e 40
 
9.6%
i 38
 
9.1%
m 36
 
8.6%
a 34
 
8.2%
t 32
 
7.7%
o 31
 
7.4%
n 29
 
7.0%
g 20
 
4.8%
l 19
 
4.6%
r 18
 
4.3%
Other values (15) 120
28.8%
Uppercase Letter
ValueCountFrequency (%)
I 76
 
10.7%
S 74
 
10.4%
C 71
 
10.0%
M 61
 
8.6%
T 60
 
8.4%
A 45
 
6.3%
D 36
 
5.1%
P 32
 
4.5%
B 32
 
4.5%
W 28
 
3.9%
Other values (14) 196
27.6%
Decimal Number
ValueCountFrequency (%)
3 41
19.4%
0 39
18.5%
2 35
16.6%
5 26
12.3%
4 24
11.4%
1 23
10.9%
7 7
 
3.3%
6 6
 
2.8%
9 5
 
2.4%
8 5
 
2.4%
Other Punctuation
ValueCountFrequency (%)
/ 84
38.5%
, 45
20.6%
· 44
20.2%
% 17
 
7.8%
. 13
 
6.0%
# 5
 
2.3%
: 4
 
1.8%
& 3
 
1.4%
; 3
 
1.4%
Math Symbol
ValueCountFrequency (%)
+ 6
60.0%
± 3
30.0%
~ 1
 
10.0%
Other Symbol
ValueCountFrequency (%)
° 4
50.0%
2
25.0%
2
25.0%
Space Separator
ValueCountFrequency (%)
4784
100.0%
Open Punctuation
ValueCountFrequency (%)
( 82
100.0%
Close Punctuation
ValueCountFrequency (%)
) 82
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15385
70.1%
Common 5448
 
24.8%
Latin 1127
 
5.1%
Han 1
 
< 0.1%
Greek 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
629
 
4.1%
549
 
3.6%
544
 
3.5%
354
 
2.3%
340
 
2.2%
315
 
2.0%
308
 
2.0%
244
 
1.6%
226
 
1.5%
214
 
1.4%
Other values (454) 11662
75.8%
Latin
ValueCountFrequency (%)
I 76
 
6.7%
S 74
 
6.6%
C 71
 
6.3%
M 61
 
5.4%
T 60
 
5.3%
A 45
 
4.0%
e 40
 
3.5%
i 38
 
3.4%
m 36
 
3.2%
D 36
 
3.2%
Other values (38) 590
52.4%
Common
ValueCountFrequency (%)
4784
87.8%
/ 84
 
1.5%
( 82
 
1.5%
) 82
 
1.5%
- 48
 
0.9%
, 45
 
0.8%
· 44
 
0.8%
3 41
 
0.8%
0 39
 
0.7%
2 35
 
0.6%
Other values (20) 164
 
3.0%
Han
ValueCountFrequency (%)
1
100.0%
Greek
ValueCountFrequency (%)
μ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15378
70.0%
ASCII 6520
29.7%
None 52
 
0.2%
Compat Jamo 7
 
< 0.1%
Letterlike Symbols 2
 
< 0.1%
CJK Compat 2
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4784
73.4%
/ 84
 
1.3%
( 82
 
1.3%
) 82
 
1.3%
I 76
 
1.2%
S 74
 
1.1%
C 71
 
1.1%
M 61
 
0.9%
T 60
 
0.9%
- 48
 
0.7%
Other values (63) 1098
 
16.8%
Hangul
ValueCountFrequency (%)
629
 
4.1%
549
 
3.6%
544
 
3.5%
354
 
2.3%
340
 
2.2%
315
 
2.0%
308
 
2.0%
244
 
1.6%
226
 
1.5%
214
 
1.4%
Other values (453) 11655
75.8%
None
ValueCountFrequency (%)
· 44
84.6%
° 4
 
7.7%
± 3
 
5.8%
μ 1
 
1.9%
Compat Jamo
ValueCountFrequency (%)
7
100.0%
Letterlike Symbols
ValueCountFrequency (%)
2
100.0%
CJK Compat
ValueCountFrequency (%)
2
100.0%
CJK
ValueCountFrequency (%)
1
100.0%

출원국
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
대한민국
608 
PCT
 
11
미국
 
6
독일
 
1
싱가포르
 
1

Length

Max length4
Median length4
Mean length3.9585987
Min length2

Unique

Unique3 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
대한민국 608
96.8%
PCT 11
 
1.8%
미국 6
 
1.0%
독일 1
 
0.2%
싱가포르 1
 
0.2%
베트남 1
 
0.2%

Length

2023-12-12T17:23:22.567139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:23:22.706450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대한민국 608
96.8%
pct 11
 
1.8%
미국 6
 
1.0%
독일 1
 
0.2%
싱가포르 1
 
0.2%
베트남 1
 
0.2%

출원구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
출원
628 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
출원 628
100.0%

Length

2023-12-12T17:23:22.849102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:23:22.967916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
출원 628
100.0%
Distinct612
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2023-12-12T17:23:23.386475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length116
Median length62
Mean length30.807325
Min length4

Characters and Unicode

Total characters19347
Distinct characters586
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique598 ?
Unique (%)95.2%

Sample

1st row인공지능 기반의 오일가스 플랜트 설비 고장 예측 및 진단시스템
2nd row비선형 최적 제어 방법
3rd row인공지능 모델을 위한 학습 데이터 생성 장치 및 방법
4th row플랜트 설비 관리 시스템 및 방법
5th row개인정보 보호 처리가 가능한 CCTV 영상 관리 시스템,장치, 및 방법
ValueCountFrequency (%)
334
 
6.6%
방법 245
 
4.9%
시스템 170
 
3.4%
이용한 128
 
2.5%
장치 113
 
2.2%
위한 90
 
1.8%
이를 54
 
1.1%
52
 
1.0%
콘크리트 41
 
0.8%
기반 32
 
0.6%
Other values (2220) 3770
75.0%
2023-12-12T17:23:24.016261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4428
 
22.9%
446
 
2.3%
389
 
2.0%
372
 
1.9%
367
 
1.9%
358
 
1.9%
338
 
1.7%
334
 
1.7%
275
 
1.4%
254
 
1.3%
Other values (576) 11786
60.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14074
72.7%
Space Separator 4428
 
22.9%
Uppercase Letter 620
 
3.2%
Lowercase Letter 117
 
0.6%
Decimal Number 35
 
0.2%
Other Punctuation 34
 
0.2%
Dash Punctuation 25
 
0.1%
Close Punctuation 7
 
< 0.1%
Open Punctuation 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
446
 
3.2%
389
 
2.8%
372
 
2.6%
367
 
2.6%
358
 
2.5%
338
 
2.4%
334
 
2.4%
275
 
2.0%
254
 
1.8%
241
 
1.7%
Other values (519) 10700
76.0%
Uppercase Letter
ValueCountFrequency (%)
I 55
 
8.9%
A 48
 
7.7%
T 47
 
7.6%
C 42
 
6.8%
M 42
 
6.8%
E 40
 
6.5%
R 39
 
6.3%
N 39
 
6.3%
S 38
 
6.1%
O 34
 
5.5%
Other values (14) 196
31.6%
Lowercase Letter
ValueCountFrequency (%)
o 20
17.1%
e 13
11.1%
t 13
11.1%
r 9
 
7.7%
n 9
 
7.7%
i 8
 
6.8%
c 7
 
6.0%
a 6
 
5.1%
s 5
 
4.3%
u 4
 
3.4%
Other values (10) 23
19.7%
Decimal Number
ValueCountFrequency (%)
3 18
51.4%
2 11
31.4%
4 3
 
8.6%
1 2
 
5.7%
6 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
, 31
91.2%
/ 3
 
8.8%
Close Punctuation
ValueCountFrequency (%)
) 5
71.4%
} 2
 
28.6%
Open Punctuation
ValueCountFrequency (%)
( 5
71.4%
{ 2
 
28.6%
Space Separator
ValueCountFrequency (%)
4428
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14074
72.7%
Common 4536
 
23.4%
Latin 737
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
446
 
3.2%
389
 
2.8%
372
 
2.6%
367
 
2.6%
358
 
2.5%
338
 
2.4%
334
 
2.4%
275
 
2.0%
254
 
1.8%
241
 
1.7%
Other values (519) 10700
76.0%
Latin
ValueCountFrequency (%)
I 55
 
7.5%
A 48
 
6.5%
T 47
 
6.4%
C 42
 
5.7%
M 42
 
5.7%
E 40
 
5.4%
R 39
 
5.3%
N 39
 
5.3%
S 38
 
5.2%
O 34
 
4.6%
Other values (34) 313
42.5%
Common
ValueCountFrequency (%)
4428
97.6%
, 31
 
0.7%
- 25
 
0.6%
3 18
 
0.4%
2 11
 
0.2%
) 5
 
0.1%
( 5
 
0.1%
/ 3
 
0.1%
4 3
 
0.1%
} 2
 
< 0.1%
Other values (3) 5
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14074
72.7%
ASCII 5273
 
27.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4428
84.0%
I 55
 
1.0%
A 48
 
0.9%
T 47
 
0.9%
C 42
 
0.8%
M 42
 
0.8%
E 40
 
0.8%
R 39
 
0.7%
N 39
 
0.7%
S 38
 
0.7%
Other values (47) 455
 
8.6%
Hangul
ValueCountFrequency (%)
446
 
3.2%
389
 
2.8%
372
 
2.6%
367
 
2.6%
358
 
2.5%
338
 
2.4%
334
 
2.4%
275
 
2.0%
254
 
1.8%
241
 
1.7%
Other values (519) 10700
76.0%
Distinct121
Distinct (%)19.3%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
Minimum2021-08-03 00:00:00
Maximum2022-06-15 00:00:00
2023-12-12T17:23:24.198354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:23:24.382606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct626
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2023-12-12T17:23:24.712939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length15.022293
Min length9

Characters and Unicode

Total characters9434
Distinct characters18
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

Unique624 ?
Unique (%)99.4%

Sample

1st row10-2021-0192548
2nd row10-2021-0158500
3rd row10-2021-0161479
4th row10-2021-0161480
5th row10-2021-0179581
ValueCountFrequency (%)
10-2021-0172119 2
 
0.3%
10-2021-0101869 2
 
0.3%
10-2021-0159575 1
 
0.2%
10-2021-0135663 1
 
0.2%
10-2021-0146426 1
 
0.2%
10-2021-0161042 1
 
0.2%
10-2021-0152727 1
 
0.2%
10-2021-0120745 1
 
0.2%
10-2021-0138340 1
 
0.2%
10-2021-0147208 1
 
0.2%
Other values (616) 616
98.1%
2023-12-12T17:23:25.222933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2192
23.2%
1 2104
22.3%
2 1606
17.0%
- 1218
12.9%
6 363
 
3.8%
5 359
 
3.8%
4 328
 
3.5%
7 301
 
3.2%
3 298
 
3.2%
8 298
 
3.2%
Other values (8) 367
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8101
85.9%
Dash Punctuation 1218
 
12.9%
Uppercase Letter 81
 
0.9%
Other Punctuation 34
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2192
27.1%
1 2104
26.0%
2 1606
19.8%
6 363
 
4.5%
5 359
 
4.4%
4 328
 
4.0%
7 301
 
3.7%
3 298
 
3.7%
8 298
 
3.7%
9 252
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
P 16
19.8%
C 16
19.8%
T 16
19.8%
K 16
19.8%
R 16
19.8%
W 1
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 1218
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9353
99.1%
Latin 81
 
0.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2192
23.4%
1 2104
22.5%
2 1606
17.2%
- 1218
13.0%
6 363
 
3.9%
5 359
 
3.8%
4 328
 
3.5%
7 301
 
3.2%
3 298
 
3.2%
8 298
 
3.2%
Other values (2) 286
 
3.1%
Latin
ValueCountFrequency (%)
P 16
19.8%
C 16
19.8%
T 16
19.8%
K 16
19.8%
R 16
19.8%
W 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9434
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2192
23.2%
1 2104
22.3%
2 1606
17.0%
- 1218
12.9%
6 363
 
3.8%
5 359
 
3.8%
4 328
 
3.5%
7 301
 
3.2%
3 298
 
3.2%
8 298
 
3.2%
Other values (8) 367
 
3.9%
Distinct345
Distinct (%)54.9%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2023-12-12T17:23:25.472275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length39
Mean length10.851911
Min length3

Characters and Unicode

Total characters6815
Distinct characters304
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

Unique219 ?
Unique (%)34.9%

Sample

1st row앤츠이엔씨(주)
2nd row광운대학교 산학협력단
3rd row한국건설기술연구원
4th row한국건설기술연구원
5th row(주)마크애니;(주)와이드큐브
ValueCountFrequency (%)
주식회사 126
 
13.2%
산학협력단 117
 
12.3%
한국철도기술연구원 30
 
3.1%
한국건설기술연구원 21
 
2.2%
한국교통대학교 10
 
1.0%
한국전자기술연구원 9
 
0.9%
연세대학교 9
 
0.9%
한국생산기술연구원 8
 
0.8%
한국전자통신연구원 8
 
0.8%
금오공과대학교 8
 
0.8%
Other values (357) 608
63.7%
2023-12-12T17:23:25.873645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
350
 
5.1%
347
 
5.1%
333
 
4.9%
( 222
 
3.3%
) 222
 
3.3%
192
 
2.8%
191
 
2.8%
190
 
2.8%
190
 
2.8%
188
 
2.8%
Other values (294) 4390
64.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5890
86.4%
Space Separator 333
 
4.9%
Open Punctuation 222
 
3.3%
Close Punctuation 222
 
3.3%
Other Punctuation 81
 
1.2%
Decimal Number 40
 
0.6%
Uppercase Letter 12
 
0.2%
Dash Punctuation 8
 
0.1%
Other Symbol 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
350
 
5.9%
347
 
5.9%
192
 
3.3%
191
 
3.2%
190
 
3.2%
190
 
3.2%
188
 
3.2%
177
 
3.0%
177
 
3.0%
164
 
2.8%
Other values (269) 3724
63.2%
Decimal Number
ValueCountFrequency (%)
0 12
30.0%
2 6
15.0%
3 5
12.5%
1 5
12.5%
8 4
 
10.0%
4 3
 
7.5%
7 2
 
5.0%
9 2
 
5.0%
5 1
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
L 3
25.0%
T 2
16.7%
X 2
16.7%
E 1
 
8.3%
D 1
 
8.3%
K 1
 
8.3%
R 1
 
8.3%
I 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
; 76
93.8%
% 3
 
3.7%
, 2
 
2.5%
Space Separator
ValueCountFrequency (%)
333
100.0%
Open Punctuation
ValueCountFrequency (%)
( 222
100.0%
Close Punctuation
ValueCountFrequency (%)
) 222
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Other Symbol
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5897
86.5%
Common 906
 
13.3%
Latin 12
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
350
 
5.9%
347
 
5.9%
192
 
3.3%
191
 
3.2%
190
 
3.2%
190
 
3.2%
188
 
3.2%
177
 
3.0%
177
 
3.0%
164
 
2.8%
Other values (270) 3731
63.3%
Common
ValueCountFrequency (%)
333
36.8%
( 222
24.5%
) 222
24.5%
; 76
 
8.4%
0 12
 
1.3%
- 8
 
0.9%
2 6
 
0.7%
3 5
 
0.6%
1 5
 
0.6%
8 4
 
0.4%
Other values (6) 13
 
1.4%
Latin
ValueCountFrequency (%)
L 3
25.0%
T 2
16.7%
X 2
16.7%
E 1
 
8.3%
D 1
 
8.3%
K 1
 
8.3%
R 1
 
8.3%
I 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5890
86.4%
ASCII 918
 
13.5%
None 7
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
350
 
5.9%
347
 
5.9%
192
 
3.3%
191
 
3.2%
190
 
3.2%
190
 
3.2%
188
 
3.2%
177
 
3.0%
177
 
3.0%
164
 
2.8%
Other values (269) 3724
63.2%
ASCII
ValueCountFrequency (%)
333
36.3%
( 222
24.2%
) 222
24.2%
; 76
 
8.3%
0 12
 
1.3%
- 8
 
0.9%
2 6
 
0.7%
3 5
 
0.5%
1 5
 
0.5%
8 4
 
0.4%
Other values (14) 25
 
2.7%
None
ValueCountFrequency (%)
7
100.0%

Interactions

2023-12-12T17:23:20.810147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:23:25.978937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호출원국
번호1.0000.091
출원국0.0911.000
2023-12-12T17:23:26.064747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호출원국
번호1.0000.047
출원국0.0471.000

Missing values

2023-12-12T17:23:20.967590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:23:21.096156image/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

번호과제명출원국출원구분특허명칭출원일자출원번호출원기관명
01AI 기반 건전성 예지진단 데이터베이스 구축대한민국출원인공지능 기반의 오일가스 플랜트 설비 고장 예측 및 진단시스템2021-12-3010-2021-0192548앤츠이엔씨(주)
12공정 효율화 의사결정 기술 및 동적 위험성 진단 평가 기술 개발대한민국출원비선형 최적 제어 방법2021-11-1710-2021-0158500광운대학교 산학협력단
23플랜트 핵심설비 하드웨어 기반 시뮬레이션 시스템 설계, 가상화 플랫폼 연계 및 검증대한민국출원인공지능 모델을 위한 학습 데이터 생성 장치 및 방법2021-11-2210-2021-0161479한국건설기술연구원
34플랜트 핵심설비 하드웨어 기반 시뮬레이션 시스템 설계, 가상화 플랫폼 연계 및 검증대한민국출원플랜트 설비 관리 시스템 및 방법2021-11-2210-2021-0161480한국건설기술연구원
45AI·데이터 기반 스마트시티 통합플랫폼 모델 개발 및 실증연구 사업 시행 공고대한민국출원개인정보 보호 처리가 가능한 CCTV 영상 관리 시스템,장치, 및 방법2021-12-1510-2021-0179581(주)마크애니;(주)와이드큐브
56AI기반 ICT융합 위험 예방 및 실시간 대응 기술대한민국출원이상행동검출을수행하기위한딥러닝모델을이용하여태스크를수행하는방법및장치2021-11-0110-2021-0148116퍼스트마일 주식회사
67AI기반 ICT융합 위험 예방 및 실시간 대응 기술대한민국출원다양한이상행동검출을수행하는다중태스크네트워크모델2021-10-2810-2021-0145713퍼스트마일 주식회사
78AI기반 ICT융합 위험 예방 및 실시간 대응 기술대한민국출원영상에서이상행동검출을위한딥러닝모델을이용하여태스크를수행하는방법및장치2021-11-0110-2021-0148138퍼스트마일 주식회사
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910AI기반 통합 화재안전 알고리즘 및 인필 시스템 개발대한민국출원적어도 하나의 건축물의 화재를 종합적으로 관리하는 통합형 게이트웨이 및 시스템2021-09-2410-2021-0126237한국건설기술연구원
번호과제명출원국출원구분특허명칭출원일자출원번호출원기관명
618619수력플랜트 성능시험 및 평가기술대한민국출원모델수차의 케이싱2021-08-0510-2021-0103254(주)금성이앤씨
619620Hybrid 방향 추진시스템 및 MWD 개발, 현장 실증대한민국출원머드 모터의 동력 전달 유닛2021-10-1210-2021-0135008산동금속공업(주)
620621나노기반 전이금속황화물(TMD) 이수 제조 기술 개발대한민국출원나노 점토광물 기반의 시추이수 및 그 제조방법2021-11-0510-2012-0151005고려대학교 산학협력단; 경상국립대학교산학협력단; 한국지질자원연구원
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627628차세대 여객 휴대수하물 보안검색 기술개발PCT출원전산단층촬영장치, 이의 제조 방법 및 구동 방법2021-10-12PCT/KR2021/013980주식회사 에스에스티랩