Overview

Dataset statistics

Number of variables9
Number of observations21
Missing cells3
Missing cells (%)1.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 KiB
Average record size in memory80.3 B

Variable types

Numeric1
Categorical2
Text5
DateTime1

Dataset

Description농림식품 관련 RnD 과제 성과로 창출된 정보 제공. 우리원이이 보유하고 있는 농림식품R&D 중분류 중 2020년 수의 R&D 사업화정보 공개
Author농림식품기술기획평가원
URLhttps://www.data.go.kr/data/15075510/fileData.do

Alerts

분류 has constant value ""Constant
사업화년도 has constant value ""Constant
제품명 has 3 (14.3%) missing valuesMissing
번호 has unique valuesUnique
사업화명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:48:02.542742
Analysis finished2023-12-12 09:48:03.280011
Duration0.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11
Minimum1
Maximum21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T18:48:03.334434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median11
Q316
95-th percentile20
Maximum21
Range20
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.2048368
Coefficient of variation (CV)0.56407607
Kurtosis-1.2
Mean11
Median Absolute Deviation (MAD)5
Skewness0
Sum231
Variance38.5
MonotonicityStrictly increasing
2023-12-12T18:48:03.449969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 1
 
4.8%
2 1
 
4.8%
21 1
 
4.8%
20 1
 
4.8%
19 1
 
4.8%
18 1
 
4.8%
17 1
 
4.8%
16 1
 
4.8%
15 1
 
4.8%
14 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
1 1
4.8%
2 1
4.8%
3 1
4.8%
4 1
4.8%
5 1
4.8%
6 1
4.8%
7 1
4.8%
8 1
4.8%
9 1
4.8%
10 1
4.8%
ValueCountFrequency (%)
21 1
4.8%
20 1
4.8%
19 1
4.8%
18 1
4.8%
17 1
4.8%
16 1
4.8%
15 1
4.8%
14 1
4.8%
13 1
4.8%
12 1
4.8%

분류
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
수의
21 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수의 21
100.0%

Length

2023-12-12T18:48:03.570163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:48:03.686403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수의 21
100.0%

과제관리번호
Text

Distinct18
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-12T18:48:03.850772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters168
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

Unique16 ?
Unique (%)76.2%

Sample

1st row116125-3
2nd row117031-3
3rd row117031-3
4th row118024-3
5th row118096-3
ValueCountFrequency (%)
311011-5 3
 
14.3%
117031-3 2
 
9.5%
116125-3 1
 
4.8%
318038-2 1
 
4.8%
716002-7 1
 
4.8%
320064-2 1
 
4.8%
320060-2 1
 
4.8%
318067-3 1
 
4.8%
318052-2 1
 
4.8%
318048-2 1
 
4.8%
Other values (8) 8
38.1%
2023-12-12T18:48:04.148281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 38
22.6%
3 27
16.1%
0 25
14.9%
- 21
12.5%
2 17
10.1%
8 12
 
7.1%
5 8
 
4.8%
7 8
 
4.8%
6 6
 
3.6%
4 3
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147
87.5%
Dash Punctuation 21
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 38
25.9%
3 27
18.4%
0 25
17.0%
2 17
11.6%
8 12
 
8.2%
5 8
 
5.4%
7 8
 
5.4%
6 6
 
4.1%
4 3
 
2.0%
9 3
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 168
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 38
22.6%
3 27
16.1%
0 25
14.9%
- 21
12.5%
2 17
10.1%
8 12
 
7.1%
5 8
 
4.8%
7 8
 
4.8%
6 6
 
3.6%
4 3
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 168
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 38
22.6%
3 27
16.1%
0 25
14.9%
- 21
12.5%
2 17
10.1%
8 12
 
7.1%
5 8
 
4.8%
7 8
 
4.8%
6 6
 
3.6%
4 3
 
1.8%

과제명
Text

Distinct18
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-12T18:48:04.425620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length43
Mean length33.52381
Min length18

Characters and Unicode

Total characters704
Distinct characters185
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

Unique16 ?
Unique (%)76.2%

Sample

1st row조류 인플루엔자 현장, 현시 진단용 초고감도 TD-NMR (Time-Domain 핵자기공명) Kit 개발 및 상용화
2nd row독소 산생 병원성 세균 예방 백신 개발 과 안전성 및 효능 평가
3rd row독소 산생 병원성 세균 예방 백신 개발 과 안전성 및 효능 평가
4th row국내 환경을 고려한 친환경 방제제 개발 및 상용화
5th row질소 거품 안락사 및 알칼리가수분해를 활용한 가축살처분 융합시스템 개발
ValueCountFrequency (%)
개발 18
 
9.8%
및 11
 
6.0%
위한 6
 
3.3%
적용 4
 
2.2%
현장 4
 
2.2%
백신 4
 
2.2%
예방 3
 
1.6%
이용한 3
 
1.6%
기술 3
 
1.6%
인체질병 3
 
1.6%
Other values (105) 124
67.8%
2023-12-12T18:48:04.808459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
162
 
23.0%
발 22
 
3.1%
개 21
 
3.0%
기 14
 
2.0%
용 13
 
1.8%
병 12
 
1.7%
제 11
 
1.6%
및 11
 
1.6%
한 11
 
1.6%
방 10
 
1.4%
Other values (175) 417
59.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 487
69.2%
Space Separator 162
 
23.0%
Uppercase Letter 23
 
3.3%
Lowercase Letter 16
 
2.3%
Close Punctuation 4
 
0.6%
Open Punctuation 4
 
0.6%
Other Punctuation 4
 
0.6%
Dash Punctuation 3
 
0.4%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
발 22
 
4.5%
개 21
 
4.3%
기 14
 
2.9%
용 13
 
2.7%
병 12
 
2.5%
제 11
 
2.3%
및 11
 
2.3%
한 11
 
2.3%
방 10
 
2.1%
가 9
 
1.8%
Other values (148) 353
72.5%
Uppercase Letter
ValueCountFrequency (%)
P 4
17.4%
I 3
13.0%
D 3
13.0%
R 3
13.0%
C 2
8.7%
M 2
8.7%
T 2
8.7%
L 1
 
4.3%
K 1
 
4.3%
N 1
 
4.3%
Lowercase Letter
ValueCountFrequency (%)
i 4
25.0%
e 3
18.8%
m 2
12.5%
n 2
12.5%
d 1
 
6.2%
s 1
 
6.2%
t 1
 
6.2%
a 1
 
6.2%
o 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 3
75.0%
· 1
 
25.0%
Space Separator
ValueCountFrequency (%)
162
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 487
69.2%
Common 178
 
25.3%
Latin 39
 
5.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
발 22
 
4.5%
개 21
 
4.3%
기 14
 
2.9%
용 13
 
2.7%
병 12
 
2.5%
제 11
 
2.3%
및 11
 
2.3%
한 11
 
2.3%
방 10
 
2.1%
가 9
 
1.8%
Other values (148) 353
72.5%
Latin
ValueCountFrequency (%)
P 4
 
10.3%
i 4
 
10.3%
I 3
 
7.7%
e 3
 
7.7%
D 3
 
7.7%
R 3
 
7.7%
C 2
 
5.1%
M 2
 
5.1%
m 2
 
5.1%
n 2
 
5.1%
Other values (10) 11
28.2%
Common
ValueCountFrequency (%)
162
91.0%
) 4
 
2.2%
( 4
 
2.2%
- 3
 
1.7%
, 3
 
1.7%
2 1
 
0.6%
· 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 487
69.2%
ASCII 216
30.7%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
162
75.0%
P 4
 
1.9%
) 4
 
1.9%
i 4
 
1.9%
( 4
 
1.9%
- 3
 
1.4%
I 3
 
1.4%
e 3
 
1.4%
D 3
 
1.4%
, 3
 
1.4%
Other values (16) 23
 
10.6%
Hangul
ValueCountFrequency (%)
발 22
 
4.5%
개 21
 
4.3%
기 14
 
2.9%
용 13
 
2.7%
병 12
 
2.5%
제 11
 
2.3%
및 11
 
2.3%
한 11
 
2.3%
방 10
 
2.1%
가 9
 
1.8%
Other values (148) 353
72.5%
None
ValueCountFrequency (%)
· 1
100.0%

연구책임자
Text

Distinct18
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-12T18:48:04.991048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9047619
Min length2

Characters and Unicode

Total characters61
Distinct characters43
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)76.2%

Sample

1st row조정혁
2nd row허진
3rd row허진
4th row최춘환
5th row윤석훈
ValueCountFrequency (%)
이병천 3
 
14.3%
허진 2
 
9.5%
조정혁 1
 
4.8%
엄재구 1
 
4.8%
장형관 1
 
4.8%
최보화 1
 
4.8%
한재익 1
 
4.8%
장홍희 1
 
4.8%
최창원 1
 
4.8%
유종철 1
 
4.8%
Other values (8) 8
38.1%
2023-12-12T18:48:05.286176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 3
 
4.9%
천 3
 
4.9%
병 3
 
4.9%
최 3
 
4.9%
원 3
 
4.9%
정 3
 
4.9%
박 2
 
3.3%
재 2
 
3.3%
은 2
 
3.3%
장 2
 
3.3%
Other values (33) 35
57.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 61
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 3
 
4.9%
천 3
 
4.9%
병 3
 
4.9%
최 3
 
4.9%
원 3
 
4.9%
정 3
 
4.9%
박 2
 
3.3%
재 2
 
3.3%
은 2
 
3.3%
장 2
 
3.3%
Other values (33) 35
57.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 61
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 3
 
4.9%
천 3
 
4.9%
병 3
 
4.9%
최 3
 
4.9%
원 3
 
4.9%
정 3
 
4.9%
박 2
 
3.3%
재 2
 
3.3%
은 2
 
3.3%
장 2
 
3.3%
Other values (33) 35
57.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 61
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 3
 
4.9%
천 3
 
4.9%
병 3
 
4.9%
최 3
 
4.9%
원 3
 
4.9%
정 3
 
4.9%
박 2
 
3.3%
재 2
 
3.3%
은 2
 
3.3%
장 2
 
3.3%
Other values (33) 35
57.4%

사업화명
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-12T18:48:05.561266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length23
Mean length20.095238
Min length8

Characters and Unicode

Total characters422
Distinct characters160
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row조류 인플루엔자 진단용 TD-NMR 상용화
2nd row부종병 독소 시험백신
3rd row부종병 고스트 시럼백신
4th row조협 복합 추출물을 이용한 시제품 생산
5th row폐사가축 이송시스템
ValueCountFrequency (%)
hetero 2
 
2.2%
이용한 2
 
2.2%
knockout 2
 
2.2%
닭진드기 2
 
2.2%
park2 2
 
2.2%
사업화 2
 
2.2%
연구 2
 
2.2%
pd 2
 
2.2%
모델 2
 
2.2%
2
 
2.2%
Other values (72) 73
78.5%
2023-12-12T18:48:06.008090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
72
 
17.1%
사 8
 
1.9%
o 8
 
1.9%
r 7
 
1.7%
P 7
 
1.7%
e 7
 
1.7%
제 7
 
1.7%
이 7
 
1.7%
용 7
 
1.7%
지 6
 
1.4%
Other values (150) 286
67.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 231
54.7%
Space Separator 72
 
17.1%
Lowercase Letter 61
 
14.5%
Uppercase Letter 36
 
8.5%
Decimal Number 5
 
1.2%
Dash Punctuation 4
 
0.9%
Other Punctuation 4
 
0.9%
Close Punctuation 3
 
0.7%
Open Punctuation 3
 
0.7%
Math Symbol 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 8
 
3.5%
제 7
 
3.0%
이 7
 
3.0%
용 7
 
3.0%
지 6
 
2.6%
기 6
 
2.6%
화 5
 
2.2%
시 5
 
2.2%
소 4
 
1.7%
업 4
 
1.7%
Other values (108) 172
74.5%
Lowercase Letter
ValueCountFrequency (%)
o 8
13.1%
r 7
11.5%
e 7
11.5%
k 6
9.8%
t 5
8.2%
l 4
 
6.6%
c 3
 
4.9%
n 3
 
4.9%
b 3
 
4.9%
i 3
 
4.9%
Other values (8) 12
19.7%
Uppercase Letter
ValueCountFrequency (%)
P 7
19.4%
D 5
13.9%
N 4
11.1%
A 3
8.3%
T 3
8.3%
C 2
 
5.6%
V 2
 
5.6%
S 2
 
5.6%
E 2
 
5.6%
M 2
 
5.6%
Other values (4) 4
11.1%
Decimal Number
ValueCountFrequency (%)
2 4
80.0%
0 1
 
20.0%
Other Punctuation
ValueCountFrequency (%)
. 2
50.0%
/ 2
50.0%
Space Separator
ValueCountFrequency (%)
72
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 231
54.7%
Latin 97
23.0%
Common 94
22.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 8
 
3.5%
제 7
 
3.0%
이 7
 
3.0%
용 7
 
3.0%
지 6
 
2.6%
기 6
 
2.6%
화 5
 
2.2%
시 5
 
2.2%
소 4
 
1.7%
업 4
 
1.7%
Other values (108) 172
74.5%
Latin
ValueCountFrequency (%)
o 8
 
8.2%
r 7
 
7.2%
P 7
 
7.2%
e 7
 
7.2%
k 6
 
6.2%
D 5
 
5.2%
t 5
 
5.2%
l 4
 
4.1%
N 4
 
4.1%
A 3
 
3.1%
Other values (22) 41
42.3%
Common
ValueCountFrequency (%)
72
76.6%
- 4
 
4.3%
2 4
 
4.3%
) 3
 
3.2%
( 3
 
3.2%
. 2
 
2.1%
/ 2
 
2.1%
+ 2
 
2.1%
0 1
 
1.1%
_ 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 231
54.7%
ASCII 191
45.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
72
37.7%
o 8
 
4.2%
r 7
 
3.7%
P 7
 
3.7%
e 7
 
3.7%
k 6
 
3.1%
D 5
 
2.6%
t 5
 
2.6%
l 4
 
2.1%
- 4
 
2.1%
Other values (32) 66
34.6%
Hangul
ValueCountFrequency (%)
사 8
 
3.5%
제 7
 
3.0%
이 7
 
3.0%
용 7
 
3.0%
지 6
 
2.6%
기 6
 
2.6%
화 5
 
2.2%
시 5
 
2.2%
소 4
 
1.7%
업 4
 
1.7%
Other values (108) 172
74.5%

사업화년도
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
2020
21 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2020 21
100.0%

Length

2023-12-12T18:48:06.159833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:48:06.249552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 21
100.0%

제품명
Text

MISSING 

Distinct18
Distinct (%)100.0%
Missing3
Missing (%)14.3%
Memory size300.0 B
2023-12-12T18:48:06.436816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length13
Mean length10.055556
Min length3

Characters and Unicode

Total characters181
Distinct characters85
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)100.0%

Sample

1st rowHMR20
2nd row부종병 독소 시험 백신
3rd row부종병 고스트 시험 백신
4th row에코와구
5th row폐사가축 이송시스템
ValueCountFrequency (%)
백신 3
 
6.5%
허바백 2
 
4.3%
돼지열병 2
 
4.3%
부종병 2
 
4.3%
시험 2
 
4.3%
폐사가축 2
 
4.3%
충아웃 1
 
2.2%
수출용 1
 
2.2%
hmr20 1
 
2.2%
블루독 1
 
2.2%
Other values (29) 29
63.0%
2023-12-12T18:48:06.739331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
28
 
15.5%
백 5
 
2.8%
D 5
 
2.8%
P 4
 
2.2%
주 4
 
2.2%
병 4
 
2.2%
사 3
 
1.7%
- 3
 
1.7%
2 3
 
1.7%
신 3
 
1.7%
Other values (75) 119
65.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 107
59.1%
Space Separator 28
 
15.5%
Uppercase Letter 27
 
14.9%
Decimal Number 8
 
4.4%
Lowercase Letter 6
 
3.3%
Dash Punctuation 3
 
1.7%
Other Punctuation 2
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
백 5
 
4.7%
주 4
 
3.7%
병 4
 
3.7%
사 3
 
2.8%
신 3
 
2.8%
시 3
 
2.8%
독 3
 
2.8%
이 3
 
2.8%
마 3
 
2.8%
제 3
 
2.8%
Other values (48) 73
68.2%
Uppercase Letter
ValueCountFrequency (%)
D 5
18.5%
P 4
14.8%
M 3
11.1%
A 2
 
7.4%
V 2
 
7.4%
R 1
 
3.7%
H 1
 
3.7%
F 1
 
3.7%
T 1
 
3.7%
K 1
 
3.7%
Other values (6) 6
22.2%
Lowercase Letter
ValueCountFrequency (%)
r 2
33.3%
e 1
16.7%
o 1
16.7%
b 1
16.7%
v 1
16.7%
Decimal Number
ValueCountFrequency (%)
2 3
37.5%
0 3
37.5%
1 2
25.0%
Space Separator
ValueCountFrequency (%)
28
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 107
59.1%
Common 41
 
22.7%
Latin 33
 
18.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
백 5
 
4.7%
주 4
 
3.7%
병 4
 
3.7%
사 3
 
2.8%
신 3
 
2.8%
시 3
 
2.8%
독 3
 
2.8%
이 3
 
2.8%
마 3
 
2.8%
제 3
 
2.8%
Other values (48) 73
68.2%
Latin
ValueCountFrequency (%)
D 5
15.2%
P 4
 
12.1%
M 3
 
9.1%
A 2
 
6.1%
r 2
 
6.1%
V 2
 
6.1%
R 1
 
3.0%
H 1
 
3.0%
F 1
 
3.0%
e 1
 
3.0%
Other values (11) 11
33.3%
Common
ValueCountFrequency (%)
28
68.3%
- 3
 
7.3%
2 3
 
7.3%
0 3
 
7.3%
. 2
 
4.9%
1 2
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 107
59.1%
ASCII 74
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
28
37.8%
D 5
 
6.8%
P 4
 
5.4%
- 3
 
4.1%
2 3
 
4.1%
0 3
 
4.1%
M 3
 
4.1%
A 2
 
2.7%
r 2
 
2.7%
V 2
 
2.7%
Other values (17) 19
25.7%
Hangul
ValueCountFrequency (%)
백 5
 
4.7%
주 4
 
3.7%
병 4
 
3.7%
사 3
 
2.8%
신 3
 
2.8%
시 3
 
2.8%
독 3
 
2.8%
이 3
 
2.8%
마 3
 
2.8%
제 3
 
2.8%
Other values (48) 73
68.2%

제품출시일
Date

Distinct17
Distinct (%)81.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
Minimum2015-07-01 00:00:00
Maximum2020-12-31 00:00:00
2023-12-12T18:48:06.855573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:48:06.961164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)

Interactions

2023-12-12T18:48:02.970497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:48:07.044935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호과제관리번호과제명연구책임자사업화명제품명제품출시일
번호1.0000.8650.8650.8651.0001.0000.564
과제관리번호0.8651.0001.0001.0001.0001.0000.977
과제명0.8651.0001.0001.0001.0001.0000.977
연구책임자0.8651.0001.0001.0001.0001.0000.977
사업화명1.0001.0001.0001.0001.0001.0001.000
제품명1.0001.0001.0001.0001.0001.0001.000
제품출시일0.5640.9770.9770.9771.0001.0001.000

Missing values

2023-12-12T18:48:03.103478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:48:03.231601image/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

번호분류과제관리번호과제명연구책임자사업화명사업화년도제품명제품출시일
01수의116125-3조류 인플루엔자 현장, 현시 진단용 초고감도 TD-NMR (Time-Domain 핵자기공명) Kit 개발 및 상용화조정혁조류 인플루엔자 진단용 TD-NMR 상용화2020HMR202020-01-28
12수의117031-3독소 산생 병원성 세균 예방 백신 개발 과 안전성 및 효능 평가허진부종병 독소 시험백신2020부종병 독소 시험 백신2020-02-13
23수의117031-3독소 산생 병원성 세균 예방 백신 개발 과 안전성 및 효능 평가허진부종병 고스트 시럼백신2020부종병 고스트 시험 백신2020-02-13
34수의118024-3국내 환경을 고려한 친환경 방제제 개발 및 상용화최춘환조협 복합 추출물을 이용한 시제품 생산2020에코와구2020-11-02
45수의118096-3질소 거품 안락사 및 알칼리가수분해를 활용한 가축살처분 융합시스템 개발윤석훈폐사가축 이송시스템2020폐사가축 이송시스템2020-12-31
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67수의311011-5인체질병 적용 실험동물 모델 개발이병천Park2 hetero knockout (+/-) pig fibroblast cell line (TGEN_CPP2)2020PD KO 세포주2015-07-01
78수의311011-5인체질병 적용 실험동물 모델 개발이병천Park2 hetero knockout (+/-) PD 모델 미니피그2020PDM-112016-10-05
89수의311011-5인체질병 적용 실험동물 모델 개발이병천SNCA 발현 PD 모델 미니돼지2020PDF-202016-10-05
910수의315028-3돼지열병 그린 마커백신 개발 및 상용화 기술 개발손은주허바백 TM 돼지열병 그린마커 주2020허바백 TM 돼지열병 그린마커 주2020-06-15
번호분류과제관리번호과제명연구책임자사업화명사업화년도제품명제품출시일
1112수의317010-3주요 닭 호흡기질병(뉴캣슬병, 닭 전염성 기관지염 등) 표준 모니터링 기술 개발정광면인수공통전염병면역검사시약 VDPro NDV Ab ELISA ver 2.0. 수출용2020VDPro NDV Ab ELISA ver 2.0. 수출용2020-01-23
1213수의318033-2AI·구제역 소독제 유효성, 환경독성 기준 재정립전태원고용량 발포형 소독제를 이용한 사업화2020블루독2020-08-10
1314수의318038-2구제역 백신 접종용 간편 무침주사기 개발 연구엄재구구제역 백신 접종용 간편 무침 주사기 개발 연구2020구제역 백신 전용 무침주사기2020-12-31
1415수의318048-2종합방제전략(IPM) 개념을 이용한 현장방제기술 개발과 농가보급유종철닭진드기 공동방제 지원사업 참여2020<NA>2020-01-02
1516수의318052-2친환경적인 닭진드기 방제를 위한 곤충병원성 진균을 이용한 현장 적용 기술 개발최창원친환경 닭진드기 살비제2020충아웃2020-07-31
1617수의318067-3매몰지내 가축 부패현황 조사 및 효과적 제거를 위한 기술개발장홍희퍠사가축 처리기2020폐사가축 처리기2020-10-30
1718수의320060-2농장 및 도축장 신속 현장 질병진단을 위한 Pen-side PCR 및 진단결과 자동 전송 시스템 개발한재익수송배지의 다양한 바이러스 감염역 유지능 평가 연구2020<NA>2020-12-31
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