Overview

Dataset statistics

Number of variables13
Number of observations53
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.6 KiB
Average record size in memory108.5 B

Variable types

Numeric2
Categorical3
Text4
DateTime4

Dataset

Description우리 기관이 보유하고 있는 농림식품R&D 중분류 중 2020년 수산자원생산 R&D 과제정보 공개 농림식품RnD 관련 연구성과로 창출된 데이터를 제공합니다.
Author농림식품기술기획평가원
URLhttps://www.data.go.kr/data/15075434/fileData.do

Alerts

분류 has constant value ""Constant
번호 is highly overall correlated with 총괄과제번호High correlation
사업명 is highly overall correlated with 총괄과제번호High correlation
총괄과제번호 is highly overall correlated with 번호 and 1 other fieldsHigh correlation
번호 has unique valuesUnique
세부과제번호 has unique valuesUnique
과제명 has unique valuesUnique

Reproduction

Analysis started2023-12-11 22:51:46.667577
Analysis finished2023-12-11 22:51:47.880901
Duration1.21 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27
Minimum1
Maximum53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2023-12-12T07:51:47.964637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.6
Q114
median27
Q340
95-th percentile50.4
Maximum53
Range52
Interquartile range (IQR)26

Descriptive statistics

Standard deviation15.443445
Coefficient of variation (CV)0.57197945
Kurtosis-1.2
Mean27
Median Absolute Deviation (MAD)13
Skewness0
Sum1431
Variance238.5
MonotonicityStrictly increasing
2023-12-12T07:51:48.101272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.9%
41 1
 
1.9%
30 1
 
1.9%
31 1
 
1.9%
32 1
 
1.9%
33 1
 
1.9%
34 1
 
1.9%
35 1
 
1.9%
36 1
 
1.9%
37 1
 
1.9%
Other values (43) 43
81.1%
ValueCountFrequency (%)
1 1
1.9%
2 1
1.9%
3 1
1.9%
4 1
1.9%
5 1
1.9%
6 1
1.9%
7 1
1.9%
8 1
1.9%
9 1
1.9%
10 1
1.9%
ValueCountFrequency (%)
53 1
1.9%
52 1
1.9%
51 1
1.9%
50 1
1.9%
49 1
1.9%
48 1
1.9%
47 1
1.9%
46 1
1.9%
45 1
1.9%
44 1
1.9%

분류
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size556.0 B
수산자원/생산
53 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row수산자원/생산
2nd row수산자원/생산
3rd row수산자원/생산
4th row수산자원/생산
5th row수산자원/생산

Common Values

ValueCountFrequency (%)
수산자원/생산 53
100.0%

Length

2023-12-12T07:51:48.223326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:51:48.316760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수산자원/생산 53
100.0%

사업명
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Memory size556.0 B
Golden Seed 프로젝트
39 
농업용수 및 기반시설 관리 효율화 기술
1세대 스마트 애니멀팜 산업화
 
2
1세대 스마트플랜트팜 고도화 및 실증
 
2
1세대 스마트애니멀팜 고도화 및 실증
 
2

Length

Max length21
Median length16
Mean length16.867925
Min length16

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row농업용수 및 기반시설 관리 효율화 기술
2nd row농업용수 및 기반시설 관리 효율화 기술
3rd row농업용수 및 기반시설 관리 효율화 기술
4th rowGolden Seed 프로젝트
5th rowGolden Seed 프로젝트

Common Values

ValueCountFrequency (%)
Golden Seed 프로젝트 39
73.6%
농업용수 및 기반시설 관리 효율화 기술 6
 
11.3%
1세대 스마트 애니멀팜 산업화 2
 
3.8%
1세대 스마트플랜트팜 고도화 및 실증 2
 
3.8%
1세대 스마트애니멀팜 고도화 및 실증 2
 
3.8%
1세대 스마트 플랜트팜 산업화 2
 
3.8%

Length

2023-12-12T07:51:48.405465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:51:48.496396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
golden 39
20.6%
프로젝트 39
20.6%
seed 39
20.6%
10
 
5.3%
1세대 8
 
4.2%
기반시설 6
 
3.2%
관리 6
 
3.2%
효율화 6
 
3.2%
기술 6
 
3.2%
농업용수 6
 
3.2%
Other values (8) 24
12.7%

총괄과제번호
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size556.0 B
213008-5
22 
213009-5
17 
320112-1
320004-1

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row320004-1
2nd row320004-1
3rd row320004-1
4th row213008-5
5th row213008-5

Common Values

ValueCountFrequency (%)
213008-5 22
41.5%
213009-5 17
32.1%
320112-1 8
 
15.1%
320004-1 6
 
11.3%

Length

2023-12-12T07:51:48.622612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:51:48.726330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
213008-5 22
41.5%
213009-5 17
32.1%
320112-1 8
 
15.1%
320004-1 6
 
11.3%

세부과제번호
Text

UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size556.0 B
2023-12-12T07:51:48.883291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters742
Distinct characters15
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

Unique53 ?
Unique (%)100.0%

Sample

1st row320004011HD060
2nd row320004011HD050
3rd row320004011SB010
4th row213008054SB510
5th row213008054SB920
ValueCountFrequency (%)
320004011hd060 1
 
1.9%
213008054sb420 1
 
1.9%
213009054sb220 1
 
1.9%
213009054sb810 1
 
1.9%
213008054sb810 1
 
1.9%
213009054sb310 1
 
1.9%
213008054sb430 1
 
1.9%
213008054sb820 1
 
1.9%
213009054sb820 1
 
1.9%
213008054sb830 1
 
1.9%
Other values (43) 43
81.1%
2023-12-12T07:51:49.165845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 216
29.1%
1 113
15.2%
2 89
12.0%
3 63
 
8.5%
4 52
 
7.0%
S 48
 
6.5%
B 48
 
6.5%
5 44
 
5.9%
8 27
 
3.6%
9 20
 
2.7%
Other values (5) 22
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 635
85.6%
Uppercase Letter 107
 
14.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 216
34.0%
1 113
17.8%
2 89
14.0%
3 63
 
9.9%
4 52
 
8.2%
5 44
 
6.9%
8 27
 
4.3%
9 20
 
3.1%
7 6
 
0.9%
6 5
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
S 48
44.9%
B 48
44.9%
H 5
 
4.7%
D 5
 
4.7%
A 1
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
Common 635
85.6%
Latin 107
 
14.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 216
34.0%
1 113
17.8%
2 89
14.0%
3 63
 
9.9%
4 52
 
8.2%
5 44
 
6.9%
8 27
 
4.3%
9 20
 
3.1%
7 6
 
0.9%
6 5
 
0.8%
Latin
ValueCountFrequency (%)
S 48
44.9%
B 48
44.9%
H 5
 
4.7%
D 5
 
4.7%
A 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 742
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 216
29.1%
1 113
15.2%
2 89
12.0%
3 63
 
8.5%
4 52
 
7.0%
S 48
 
6.5%
B 48
 
6.5%
5 44
 
5.9%
8 27
 
3.6%
9 20
 
2.7%
Other values (5) 22
 
3.0%

과제명
Text

UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size556.0 B
2023-12-12T07:51:49.466516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length31
Mean length25.528302
Min length11

Characters and Unicode

Total characters1353
Distinct characters207
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)100.0%

Sample

1st row저수율 예측 알고리즘 개발
2nd row데이터 기반 최적 관개공급 알고리즘 개발
3rd row농업생산기반시설 선능개선 및 자율학습 물관리 기술개발
4th row붉바리 우량종자 개발과 국내외 산업화
5th row기능성 김 계통주 선발 및 시험양식 연구
ValueCountFrequency (%)
34
 
9.4%
개발 21
 
5.8%
수출용 12
 
3.3%
시스템 8
 
2.2%
종자 6
 
1.7%
스마트팜 6
 
1.7%
기술개발 5
 
1.4%
옥수수 5
 
1.4%
품종 5
 
1.4%
개척 5
 
1.4%
Other values (168) 255
70.4%
2023-12-12T07:51:49.917892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
309
22.8%
51
 
3.8%
48
 
3.5%
42
 
3.1%
37
 
2.7%
34
 
2.5%
31
 
2.3%
28
 
2.1%
24
 
1.8%
23
 
1.7%
Other values (197) 726
53.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1011
74.7%
Space Separator 309
 
22.8%
Uppercase Letter 16
 
1.2%
Other Punctuation 9
 
0.7%
Close Punctuation 4
 
0.3%
Open Punctuation 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
51
 
5.0%
48
 
4.7%
42
 
4.2%
37
 
3.7%
34
 
3.4%
31
 
3.1%
28
 
2.8%
24
 
2.4%
23
 
2.3%
23
 
2.3%
Other values (184) 670
66.3%
Uppercase Letter
ValueCountFrequency (%)
D 4
25.0%
R 4
25.0%
P 2
12.5%
S 2
12.5%
G 2
12.5%
A 1
 
6.2%
I 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
& 4
44.4%
, 3
33.3%
/ 2
22.2%
Space Separator
ValueCountFrequency (%)
309
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1011
74.7%
Common 326
 
24.1%
Latin 16
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
51
 
5.0%
48
 
4.7%
42
 
4.2%
37
 
3.7%
34
 
3.4%
31
 
3.1%
28
 
2.8%
24
 
2.4%
23
 
2.3%
23
 
2.3%
Other values (184) 670
66.3%
Latin
ValueCountFrequency (%)
D 4
25.0%
R 4
25.0%
P 2
12.5%
S 2
12.5%
G 2
12.5%
A 1
 
6.2%
I 1
 
6.2%
Common
ValueCountFrequency (%)
309
94.8%
& 4
 
1.2%
) 4
 
1.2%
( 4
 
1.2%
, 3
 
0.9%
/ 2
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1011
74.7%
ASCII 342
 
25.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
309
90.4%
D 4
 
1.2%
& 4
 
1.2%
R 4
 
1.2%
) 4
 
1.2%
( 4
 
1.2%
, 3
 
0.9%
/ 2
 
0.6%
P 2
 
0.6%
S 2
 
0.6%
Other values (3) 4
 
1.2%
Hangul
ValueCountFrequency (%)
51
 
5.0%
48
 
4.7%
42
 
4.2%
37
 
3.7%
34
 
3.4%
31
 
3.1%
28
 
2.8%
24
 
2.4%
23
 
2.3%
23
 
2.3%
Other values (184) 670
66.3%
Distinct39
Distinct (%)73.6%
Missing0
Missing (%)0.0%
Memory size556.0 B
2023-12-12T07:51:50.162305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length10.169811
Min length4

Characters and Unicode

Total characters539
Distinct characters116
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)52.8%

Sample

1st row네이버시스템(주)
2nd row충남대학교 산학협력단
3rd row한국농어촌공사 농어촌연구원
4th row제주대학교 산학협력단
5th row국립수산과학원 해조류바이오연구센터
ValueCountFrequency (%)
산학협력단 11
 
13.6%
국립식량과학원 7
 
8.6%
국립수산과학원 4
 
4.9%
전남대학교 3
 
3.7%
한국어류육종연구소 2
 
2.5%
코리아 2
 
2.5%
불루젠 2
 
2.5%
2
 
2.5%
고령지농업연구소 2
 
2.5%
주)농우바이오 2
 
2.5%
Other values (38) 44
54.3%
2023-12-12T07:51:50.554661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37
 
6.9%
28
 
5.2%
24
 
4.5%
( 18
 
3.3%
18
 
3.3%
) 18
 
3.3%
17
 
3.2%
16
 
3.0%
12
 
2.2%
12
 
2.2%
Other values (106) 339
62.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 475
88.1%
Space Separator 28
 
5.2%
Open Punctuation 18
 
3.3%
Close Punctuation 18
 
3.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
37
 
7.8%
24
 
5.1%
18
 
3.8%
17
 
3.6%
16
 
3.4%
12
 
2.5%
12
 
2.5%
12
 
2.5%
12
 
2.5%
12
 
2.5%
Other values (103) 303
63.8%
Space Separator
ValueCountFrequency (%)
28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 475
88.1%
Common 64
 
11.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
37
 
7.8%
24
 
5.1%
18
 
3.8%
17
 
3.6%
16
 
3.4%
12
 
2.5%
12
 
2.5%
12
 
2.5%
12
 
2.5%
12
 
2.5%
Other values (103) 303
63.8%
Common
ValueCountFrequency (%)
28
43.8%
( 18
28.1%
) 18
28.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 475
88.1%
ASCII 64
 
11.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
37
 
7.8%
24
 
5.1%
18
 
3.8%
17
 
3.6%
16
 
3.4%
12
 
2.5%
12
 
2.5%
12
 
2.5%
12
 
2.5%
12
 
2.5%
Other values (103) 303
63.8%
ASCII
ValueCountFrequency (%)
28
43.8%
( 18
28.1%
) 18
28.1%
Distinct39
Distinct (%)73.6%
Missing0
Missing (%)0.0%
Memory size556.0 B
2023-12-12T07:51:50.775612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length10.169811
Min length4

Characters and Unicode

Total characters539
Distinct characters116
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)52.8%

Sample

1st row네이버시스템(주)
2nd row충남대학교 산학협력단
3rd row한국농어촌공사 농어촌연구원
4th row제주대학교 산학협력단
5th row국립수산과학원 해조류바이오연구센터
ValueCountFrequency (%)
산학협력단 11
 
13.6%
국립식량과학원 7
 
8.6%
국립수산과학원 4
 
4.9%
전남대학교 3
 
3.7%
한국어류육종연구소 2
 
2.5%
코리아 2
 
2.5%
불루젠 2
 
2.5%
2
 
2.5%
고령지농업연구소 2
 
2.5%
주)농우바이오 2
 
2.5%
Other values (38) 44
54.3%
2023-12-12T07:51:51.156602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37
 
6.9%
28
 
5.2%
24
 
4.5%
( 18
 
3.3%
18
 
3.3%
) 18
 
3.3%
17
 
3.2%
16
 
3.0%
12
 
2.2%
12
 
2.2%
Other values (106) 339
62.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 475
88.1%
Space Separator 28
 
5.2%
Open Punctuation 18
 
3.3%
Close Punctuation 18
 
3.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
37
 
7.8%
24
 
5.1%
18
 
3.8%
17
 
3.6%
16
 
3.4%
12
 
2.5%
12
 
2.5%
12
 
2.5%
12
 
2.5%
12
 
2.5%
Other values (103) 303
63.8%
Space Separator
ValueCountFrequency (%)
28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 475
88.1%
Common 64
 
11.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
37
 
7.8%
24
 
5.1%
18
 
3.8%
17
 
3.6%
16
 
3.4%
12
 
2.5%
12
 
2.5%
12
 
2.5%
12
 
2.5%
12
 
2.5%
Other values (103) 303
63.8%
Common
ValueCountFrequency (%)
28
43.8%
( 18
28.1%
) 18
28.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 475
88.1%
ASCII 64
 
11.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
37
 
7.8%
24
 
5.1%
18
 
3.8%
17
 
3.6%
16
 
3.4%
12
 
2.5%
12
 
2.5%
12
 
2.5%
12
 
2.5%
12
 
2.5%
Other values (103) 303
63.8%
ASCII
ValueCountFrequency (%)
28
43.8%
( 18
28.1%
) 18
28.1%
Distinct5
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Memory size556.0 B
Minimum2017-01-01 00:00:00
Maximum2020-11-13 00:00:00
2023-12-12T07:51:51.259340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:51.352039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
Distinct3
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size556.0 B
Minimum2020-12-31 00:00:00
Maximum2021-12-31 00:00:00
2023-12-12T07:51:51.445128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:51.546591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)
Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size556.0 B
Minimum2020-01-01 00:00:00
Maximum2020-11-13 00:00:00
2023-12-12T07:51:51.633623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:51.713970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size556.0 B
Minimum2020-12-31 00:00:00
Maximum2021-11-12 00:00:00
2023-12-12T07:51:51.793042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:51.924258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

총연구비
Real number (ℝ)

Distinct46
Distinct (%)86.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1450258 × 108
Minimum45000000
Maximum2.168 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2023-12-12T07:51:52.104923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum45000000
5-th percentile80000000
Q11.52 × 108
median2.34 × 108
Q33.6 × 108
95-th percentile6.558 × 108
Maximum2.168 × 109
Range2.123 × 109
Interquartile range (IQR)2.08 × 108

Descriptive statistics

Standard deviation3.1229411 × 108
Coefficient of variation (CV)0.99297789
Kurtosis23.90045
Mean3.1450258 × 108
Median Absolute Deviation (MAD)1.16667 × 108
Skewness4.2501804
Sum1.6668637 × 1010
Variance9.7527613 × 1016
MonotonicityNot monotonic
2023-12-12T07:51:52.238780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
200000000 3
 
5.7%
80000000 3
 
5.7%
97000000 2
 
3.8%
150000000 2
 
3.8%
360000000 2
 
3.8%
424000000 1
 
1.9%
289000000 1
 
1.9%
269000000 1
 
1.9%
494000000 1
 
1.9%
113334000 1
 
1.9%
Other values (36) 36
67.9%
ValueCountFrequency (%)
45000000 1
 
1.9%
80000000 3
5.7%
97000000 2
3.8%
102000000 1
 
1.9%
107000000 1
 
1.9%
110000000 1
 
1.9%
113334000 1
 
1.9%
140000000 1
 
1.9%
150000000 2
3.8%
152000000 1
 
1.9%
ValueCountFrequency (%)
2168000000 1
1.9%
794000000 1
1.9%
658500000 1
1.9%
654000000 1
1.9%
624000000 1
1.9%
570000000 1
1.9%
550667000 1
1.9%
494000000 1
1.9%
480000000 1
1.9%
466667000 1
1.9%

Interactions

2023-12-12T07:51:47.432358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:47.269877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:47.520059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:47.343006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T07:51:52.354952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호사업명총괄과제번호세부과제번호과제명연구수행기관주관기관총연구기관 시작일총연구기간 종료일당해년연구기간 시작일당해년연구기간 종료일총연구비
번호1.0000.5820.7491.0001.0000.5800.5800.8350.8160.9830.9830.000
사업명0.5821.0000.9091.0001.0000.9600.9600.7861.0001.0001.0000.621
총괄과제번호0.7490.9091.0001.0001.0001.0001.0000.8401.0001.0001.0000.318
세부과제번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
과제명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
연구수행기관0.5800.9601.0001.0001.0001.0001.0001.0001.0001.0001.0000.678
주관기관0.5800.9601.0001.0001.0001.0001.0001.0001.0001.0001.0000.678
총연구기관 시작일0.8350.7860.8401.0001.0001.0001.0001.0001.0001.0001.0000.371
총연구기간 종료일0.8161.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.403
당해년연구기간 시작일0.9831.0001.0001.0001.0001.0001.0001.0001.0001.0000.9930.402
당해년연구기간 종료일0.9831.0001.0001.0001.0001.0001.0001.0001.0000.9931.0000.402
총연구비0.0000.6210.3181.0001.0000.6780.6780.3710.4030.4020.4021.000
2023-12-12T07:51:52.507728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
총괄과제번호사업명
총괄과제번호1.0000.778
사업명0.7781.000
2023-12-12T07:51:52.594816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호총연구비사업명총괄과제번호
번호1.0000.2190.3340.527
총연구비0.2191.0000.4790.269
사업명0.3340.4791.0000.778
총괄과제번호0.5270.2690.7781.000

Missing values

2023-12-12T07:51:47.618742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T07:51:47.798482image/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

번호분류사업명총괄과제번호세부과제번호과제명연구수행기관주관기관총연구기관 시작일총연구기간 종료일당해년연구기간 시작일당해년연구기간 종료일총연구비
01수산자원/생산농업용수 및 기반시설 관리 효율화 기술320004-1320004011HD060저수율 예측 알고리즘 개발네이버시스템(주)네이버시스템(주)2020-01-012020-12-312020-01-012020-12-3197000000
12수산자원/생산농업용수 및 기반시설 관리 효율화 기술320004-1320004011HD050데이터 기반 최적 관개공급 알고리즘 개발충남대학교 산학협력단충남대학교 산학협력단2020-01-012020-12-312020-01-012020-12-3145000000
23수산자원/생산농업용수 및 기반시설 관리 효율화 기술320004-1320004011SB010농업생산기반시설 선능개선 및 자율학습 물관리 기술개발한국농어촌공사 농어촌연구원한국농어촌공사 농어촌연구원2020-01-012020-12-312020-01-012020-12-31175000000
34수산자원/생산Golden Seed 프로젝트213008-5213008054SB510붉바리 우량종자 개발과 국내외 산업화제주대학교 산학협력단제주대학교 산학협력단2017-01-012021-12-312020-01-012020-12-31249334000
45수산자원/생산Golden Seed 프로젝트213008-5213008054SB920기능성 김 계통주 선발 및 시험양식 연구국립수산과학원 해조류바이오연구센터국립수산과학원 해조류바이오연구센터2017-01-012021-12-312020-01-012020-12-31150000000
56수산자원/생산Golden Seed 프로젝트213008-5213008054SB710교잡 신종자(속성장, 수온내성) 최적 생산기술 개발 및 표준화목포대학교산학협력단목포대학교산학협력단2017-01-012021-12-312020-01-012020-12-31550667000
67수산자원/생산Golden Seed 프로젝트213009-5213009054SB420수출용 감자 신품종 종자시장 개척 및 병해진단기술 수출기반 조성(주)오리온(주)오리온2017-01-012021-12-312020-01-012020-12-31570000000
78수산자원/생산Golden Seed 프로젝트213008-5213008054SBA10GSP 수산종자사업단 운영비국립수산과학원국립수산과학원2017-01-012021-12-312020-01-012020-12-31230000000
89수산자원/생산농업용수 및 기반시설 관리 효율화 기술320004-1320004011HD030저수지 성능개선 투자우선순위 의사결정 모델 기술개발유니콘스(주)유니콘스(주)2020-01-012020-12-312020-01-012020-12-31174000000
910수산자원/생산Golden Seed 프로젝트213009-5213009054SB510수출용 감자 신품종 종자시장 개척 및 씨감자 생산기술 수출기반 조성홍익바이오홍익바이오2017-01-012021-12-312020-01-012020-12-31658500000
번호분류사업명총괄과제번호세부과제번호과제명연구수행기관주관기관총연구기관 시작일총연구기간 종료일당해년연구기간 시작일당해년연구기간 종료일총연구비
4344수산자원/생산농업용수 및 기반시설 관리 효율화 기술320004-1320004011HD020농업용 저수지의 이수안전도 평가기법 개발아주대학교 산학협력단아주대학교 산학협력단2020-01-012020-12-312020-01-012020-12-3180000000
4445수산자원/생산농업용수 및 기반시설 관리 효율화 기술320004-1320004011HD070계측 네트워크 및 파일럿 시스템 구축(주)수리이엔씨(주)수리이엔씨2020-01-012020-12-312020-01-012020-12-3197000000
4546수산자원/생산1세대 스마트 애니멀팜 산업화320112-1320112011SB310스마트팜 R&D 산출물 관리 및 공유 시스템 개발(주)아트피큐(주)아트피큐2020-11-132021-11-122020-11-132021-11-12624000000
4647수산자원/생산1세대 스마트플랜트팜 고도화 및 실증320112-1320112011SB120스마트팜 빅데이터 플랫폼 운영 및 추진체계 관리(주)씨씨미디어서비스(주)씨씨미디어서비스2020-11-132021-11-122020-11-132021-11-12352000000
4748수산자원/생산1세대 스마트애니멀팜 고도화 및 실증320112-1320112011SB210스마트팜 R&D 데이터 표준화 및 정보수집 연계 시스템 개발(주)호현에프앤씨(주)호현에프앤씨2020-11-132021-11-122020-11-132021-11-12794000000
4849수산자원/생산1세대 스마트 플랜트팜 산업화320112-1320112011SB420스마트팜 연구자 커뮤니티 지원 시스템 분석,설계 지원올앤리치올앤리치2020-11-132021-11-122020-11-132021-11-12235000000
4950수산자원/생산1세대 스마트 플랜트팜 산업화320112-1320112011SB410스마트팜 연구자 커뮤니티 지원 시스템 개발(주)아이콘루프(주)아이콘루프2020-11-132021-11-122020-11-132021-11-12289000000
5051수산자원/생산1세대 스마트 애니멀팜 산업화320112-1320112011SB320민간공유 서비스 기반 스마트팜 R&D 산출물 관리 및 공유 시스템 개발(주)아이콘루프(주)아이콘루프2020-11-132021-11-122020-11-132021-11-12424000000
5152수산자원/생산1세대 스마트애니멀팜 고도화 및 실증320112-1320112011SB220스마트 플랜트팜 R&D 데이터 표준화 및 정보수집 연계 시스템 개발(주)유비엔(주)유비엔2020-11-132021-11-122020-11-132021-11-12654000000
5253수산자원/생산1세대 스마트플랜트팜 고도화 및 실증320112-1320112011SB110빅데이터/AI 분석 지원 시스템 및 클라우드 환경 개발(주)씨씨미디어서비스(주)씨씨미디어서비스2020-11-132021-11-122020-11-132021-11-122168000000