Overview

Dataset statistics

Number of variables13
Number of observations195
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory20.3 KiB
Average record size in memory106.7 B

Variable types

Numeric2
Categorical2
Text5
DateTime4

Dataset

Description우리 기관이 보유하고 있는 농림식품R&D 중분류 중 융복합 R&D 과제정보 공개 분류,사업명,총괄과제번호,세부과제번호,과제명,연구수행기관,주관기관,총연구기간 시작일,총연구기간 종료일,당해년도연구 시작일,당해년도연구 종료일,총연구비,연구내용요약 으로 구성
Author농림식품기술기획평가원
URLhttps://www.data.go.kr/data/15089677/fileData.do

Alerts

분류 has constant value ""Constant
번호 is highly overall correlated with 사업명High correlation
사업명 is highly overall correlated with 번호High correlation
번호 has unique valuesUnique
세부과제번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 01:22:14.931148
Analysis finished2023-12-12 01:22:16.318796
Duration1.39 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct195
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean98
Minimum1
Maximum195
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-12T10:22:16.406924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.7
Q149.5
median98
Q3146.5
95-th percentile185.3
Maximum195
Range194
Interquartile range (IQR)97

Descriptive statistics

Standard deviation56.435804
Coefficient of variation (CV)0.57587555
Kurtosis-1.2
Mean98
Median Absolute Deviation (MAD)49
Skewness0
Sum19110
Variance3185
MonotonicityStrictly increasing
2023-12-12T10:22:16.613714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
124 1
 
0.5%
126 1
 
0.5%
127 1
 
0.5%
128 1
 
0.5%
129 1
 
0.5%
130 1
 
0.5%
131 1
 
0.5%
132 1
 
0.5%
133 1
 
0.5%
Other values (185) 185
94.9%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
195 1
0.5%
194 1
0.5%
193 1
0.5%
192 1
0.5%
191 1
0.5%
190 1
0.5%
189 1
0.5%
188 1
0.5%
187 1
0.5%
186 1
0.5%

분류
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
농림식품 융복합
195 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row농림식품 융복합
2nd row농림식품 융복합
3rd row농림식품 융복합
4th row농림식품 융복합
5th row농림식품 융복합

Common Values

ValueCountFrequency (%)
농림식품 융복합 195
100.0%

Length

2023-12-12T10:22:16.831707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:22:16.990145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
농림식품 195
50.0%
융복합 195
50.0%

사업명
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
내역사업명없음
57 
유용 농생명자원 산업화 기술개발
30 
공공기술 사업화 촉진
15 
에너지자립형생산기술개발
14 
산업화미생물유전체전략연구
13 
Other values (16)
66 

Length

Max length17
Median length14
Mean length10.620513
Min length6

Unique

Unique3 ?
Unique (%)1.5%

Sample

1st rowICT융복합시스템
2nd rowICT융복합시스템
3rd rowICT융복합시스템
4th rowICT융복합시스템
5th row공공기술 사업화 촉진

Common Values

ValueCountFrequency (%)
내역사업명없음 57
29.2%
유용 농생명자원 산업화 기술개발 30
15.4%
공공기술 사업화 촉진 15
 
7.7%
에너지자립형생산기술개발 14
 
7.2%
산업화미생물유전체전략연구 13
 
6.7%
민간중심 R&D 사업화 지원 9
 
4.6%
천연안심소재 산업화 7
 
3.6%
미래대응식품 기술개발 7
 
3.6%
에너지저장관리기술개발 6
 
3.1%
산업기반연구 6
 
3.1%
Other values (11) 31
15.9%

Length

2023-12-12T10:22:17.143585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
내역사업명없음 57
15.4%
산업화 37
 
10.0%
기술개발 37
 
10.0%
농생명자원 30
 
8.1%
유용 30
 
8.1%
사업화 24
 
6.5%
공공기술 15
 
4.0%
촉진 15
 
4.0%
에너지자립형생산기술개발 14
 
3.8%
산업화미생물유전체전략연구 13
 
3.5%
Other values (24) 99
26.7%

총괄과제번호
Text

Distinct79
Distinct (%)40.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-12T10:22:17.469336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters1560
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

Unique19 ?
Unique (%)9.7%

Sample

1st row119079-4
2nd row119079-4
3rd row317015-6
4th row317018-5
5th row821008-3
ValueCountFrequency (%)
617071-5 6
 
3.1%
421009-4 6
 
3.1%
421027-4 5
 
2.6%
319089-3 5
 
2.6%
421002-4 5
 
2.6%
421021-3 4
 
2.1%
821064-3 4
 
2.1%
421028-3 4
 
2.1%
421029-4 4
 
2.1%
120094-3 4
 
2.1%
Other values (69) 148
75.9%
2023-12-12T10:22:18.023986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 291
18.7%
0 264
16.9%
2 255
16.3%
- 195
12.5%
4 154
9.9%
3 153
9.8%
9 75
 
4.8%
8 59
 
3.8%
7 51
 
3.3%
5 34
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1365
87.5%
Dash Punctuation 195
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 291
21.3%
0 264
19.3%
2 255
18.7%
4 154
11.3%
3 153
11.2%
9 75
 
5.5%
8 59
 
4.3%
7 51
 
3.7%
5 34
 
2.5%
6 29
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 195
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1560
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 291
18.7%
0 264
16.9%
2 255
16.3%
- 195
12.5%
4 154
9.9%
3 153
9.8%
9 75
 
4.8%
8 59
 
3.8%
7 51
 
3.3%
5 34
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1560
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 291
18.7%
0 264
16.9%
2 255
16.3%
- 195
12.5%
4 154
9.9%
3 153
9.8%
9 75
 
4.8%
8 59
 
3.8%
7 51
 
3.3%
5 34
 
2.2%

세부과제번호
Text

UNIQUE 

Distinct195
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-12T10:22:18.324228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters2730
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique195 ?
Unique (%)100.0%

Sample

1st row119079043SB010
2nd row119079043HD020
3rd row317015065SB010
4th row317018055SB010
5th row821008031SB010
ValueCountFrequency (%)
119079043sb010 1
 
0.5%
821068031hd020 1
 
0.5%
120095032hd020 1
 
0.5%
617071055sb110 1
 
0.5%
617071055hd320 1
 
0.5%
617071055hd330 1
 
0.5%
617071055hd130 1
 
0.5%
120094032sb010 1
 
0.5%
120094032hd040 1
 
0.5%
120094032hd020 1
 
0.5%
Other values (185) 185
94.9%
2023-12-12T10:22:19.087040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 843
30.9%
1 492
18.0%
2 337
 
12.3%
3 214
 
7.8%
4 183
 
6.7%
H 116
 
4.2%
D 116
 
4.2%
S 79
 
2.9%
B 79
 
2.9%
9 76
 
2.8%
Other values (6) 195
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2338
85.6%
Uppercase Letter 390
 
14.3%
Lowercase Letter 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 843
36.1%
1 492
21.0%
2 337
 
14.4%
3 214
 
9.2%
4 183
 
7.8%
9 76
 
3.3%
8 60
 
2.6%
7 53
 
2.3%
5 51
 
2.2%
6 29
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
H 116
29.7%
D 116
29.7%
S 79
20.3%
B 79
20.3%
Lowercase Letter
ValueCountFrequency (%)
a 1
50.0%
b 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2338
85.6%
Latin 392
 
14.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 843
36.1%
1 492
21.0%
2 337
 
14.4%
3 214
 
9.2%
4 183
 
7.8%
9 76
 
3.3%
8 60
 
2.6%
7 53
 
2.3%
5 51
 
2.2%
6 29
 
1.2%
Latin
ValueCountFrequency (%)
H 116
29.6%
D 116
29.6%
S 79
20.2%
B 79
20.2%
a 1
 
0.3%
b 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2730
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 843
30.9%
1 492
18.0%
2 337
 
12.3%
3 214
 
7.8%
4 183
 
6.7%
H 116
 
4.2%
D 116
 
4.2%
S 79
 
2.9%
B 79
 
2.9%
9 76
 
2.8%
Other values (6) 195
 
7.1%

과제명
Text

Distinct178
Distinct (%)91.3%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-12T10:22:19.466825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length46
Mean length32.687179
Min length12

Characters and Unicode

Total characters6374
Distinct characters411
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique166 ?
Unique (%)85.1%

Sample

1st row가축 스마트 진료를 위한 데이터 수집 시스템 구축
2nd row빅데이터 기반 가축 스마트 진료 시스템 개발
3rd row농축산 ICT 기자재 표준 기술 개발
4th row인삼의 최적 생육환경 조성을 위한 ICT 융복합 첨단 재배관리시스템 개발
5th row글로벌 선도 국내자생 금불초복합추출물의 체지방 감소 소재 및 건강기능식품 산업화
ValueCountFrequency (%)
개발 110
 
6.7%
및 106
 
6.5%
위한 26
 
1.6%
활용한 24
 
1.5%
시스템 23
 
1.4%
기반 19
 
1.2%
스마트 18
 
1.1%
소재 17
 
1.0%
구축 16
 
1.0%
기능성 15
 
0.9%
Other values (702) 1266
77.2%
2023-12-12T10:22:20.116707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1449
 
22.7%
발 145
 
2.3%
개 138
 
2.2%
기 107
 
1.7%
및 106
 
1.7%
스 96
 
1.5%
용 91
 
1.4%
한 80
 
1.3%
물 80
 
1.3%
생 73
 
1.1%
Other values (401) 4009
62.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4694
73.6%
Space Separator 1449
 
22.7%
Lowercase Letter 91
 
1.4%
Uppercase Letter 74
 
1.2%
Decimal Number 18
 
0.3%
Other Punctuation 16
 
0.3%
Dash Punctuation 12
 
0.2%
Open Punctuation 9
 
0.1%
Close Punctuation 9
 
0.1%
Initial Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
발 145
 
3.1%
개 138
 
2.9%
기 107
 
2.3%
및 106
 
2.3%
스 96
 
2.0%
용 91
 
1.9%
한 80
 
1.7%
물 80
 
1.7%
생 73
 
1.6%
성 70
 
1.5%
Other values (353) 3708
79.0%
Lowercase Letter
ValueCountFrequency (%)
a 13
14.3%
t 8
 
8.8%
i 8
 
8.8%
n 8
 
8.8%
e 8
 
8.8%
o 7
 
7.7%
c 5
 
5.5%
l 5
 
5.5%
s 4
 
4.4%
m 3
 
3.3%
Other values (10) 22
24.2%
Uppercase Letter
ValueCountFrequency (%)
C 12
16.2%
S 9
12.2%
I 8
10.8%
D 6
8.1%
T 6
8.1%
W 5
6.8%
M 5
6.8%
F 5
6.8%
B 4
 
5.4%
O 4
 
5.4%
Other values (4) 10
13.5%
Decimal Number
ValueCountFrequency (%)
0 6
33.3%
4 4
22.2%
2 4
22.2%
1 2
 
11.1%
3 1
 
5.6%
9 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
/ 9
56.2%
. 7
43.8%
Space Separator
ValueCountFrequency (%)
1449
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4694
73.6%
Common 1515
 
23.8%
Latin 165
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
발 145
 
3.1%
개 138
 
2.9%
기 107
 
2.3%
및 106
 
2.3%
스 96
 
2.0%
용 91
 
1.9%
한 80
 
1.7%
물 80
 
1.7%
생 73
 
1.6%
성 70
 
1.5%
Other values (353) 3708
79.0%
Latin
ValueCountFrequency (%)
a 13
 
7.9%
C 12
 
7.3%
S 9
 
5.5%
t 8
 
4.8%
i 8
 
4.8%
n 8
 
4.8%
e 8
 
4.8%
I 8
 
4.8%
o 7
 
4.2%
D 6
 
3.6%
Other values (24) 78
47.3%
Common
ValueCountFrequency (%)
1449
95.6%
- 12
 
0.8%
( 9
 
0.6%
/ 9
 
0.6%
) 9
 
0.6%
. 7
 
0.5%
0 6
 
0.4%
4 4
 
0.3%
2 4
 
0.3%
1 2
 
0.1%
Other values (4) 4
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4694
73.6%
ASCII 1678
 
26.3%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1449
86.4%
a 13
 
0.8%
C 12
 
0.7%
- 12
 
0.7%
( 9
 
0.5%
/ 9
 
0.5%
S 9
 
0.5%
) 9
 
0.5%
t 8
 
0.5%
i 8
 
0.5%
Other values (36) 140
 
8.3%
Hangul
ValueCountFrequency (%)
발 145
 
3.1%
개 138
 
2.9%
기 107
 
2.3%
및 106
 
2.3%
스 96
 
2.0%
용 91
 
1.9%
한 80
 
1.7%
물 80
 
1.7%
생 73
 
1.6%
성 70
 
1.5%
Other values (353) 3708
79.0%
Punctuation
ValueCountFrequency (%)
‘ 1
50.0%
’ 1
50.0%

연구수행기관
Text

Distinct154
Distinct (%)79.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-12T10:22:20.481891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length10.005128
Min length4

Characters and Unicode

Total characters1951
Distinct characters226
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique129 ?
Unique (%)66.2%

Sample

1st row주식회사 리얼팜
2nd row고려동물병원
3rd row한국전자통신연구원
4th row농업회사법인 원스베리
5th row코스맥스바이오(주)
ValueCountFrequency (%)
산학협력단 49
 
17.1%
주식회사 22
 
7.7%
농업회사법인 7
 
2.4%
경북대학교 5
 
1.7%
서울대학교 5
 
1.7%
연세대학교 5
 
1.7%
전남대학교 4
 
1.4%
건국대학교 3
 
1.0%
한국전자통신연구원 3
 
1.0%
순천대학교 3
 
1.0%
Other values (159) 181
63.1%
2023-12-12T10:22:21.031542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 140
 
7.2%
92
 
4.7%
산 77
 
3.9%
주 77
 
3.9%
협 67
 
3.4%
대 66
 
3.4%
단 66
 
3.4%
력 63
 
3.2%
교 63
 
3.2%
( 54
 
2.8%
Other values (216) 1186
60.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1749
89.6%
Space Separator 92
 
4.7%
Open Punctuation 54
 
2.8%
Close Punctuation 54
 
2.8%
Other Symbol 1
 
0.1%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 140
 
8.0%
산 77
 
4.4%
주 77
 
4.4%
협 67
 
3.8%
대 66
 
3.8%
단 66
 
3.8%
력 63
 
3.6%
교 63
 
3.6%
원 53
 
3.0%
사 44
 
2.5%
Other values (211) 1033
59.1%
Space Separator
ValueCountFrequency (%)
92
100.0%
Open Punctuation
ValueCountFrequency (%)
( 54
100.0%
Close Punctuation
ValueCountFrequency (%)
) 54
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1750
89.7%
Common 201
 
10.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 140
 
8.0%
산 77
 
4.4%
주 77
 
4.4%
협 67
 
3.8%
대 66
 
3.8%
단 66
 
3.8%
력 63
 
3.6%
교 63
 
3.6%
원 53
 
3.0%
사 44
 
2.5%
Other values (212) 1034
59.1%
Common
ValueCountFrequency (%)
92
45.8%
( 54
26.9%
) 54
26.9%
2 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1749
89.6%
ASCII 201
 
10.3%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 140
 
8.0%
산 77
 
4.4%
주 77
 
4.4%
협 67
 
3.8%
대 66
 
3.8%
단 66
 
3.8%
력 63
 
3.6%
교 63
 
3.6%
원 53
 
3.0%
사 44
 
2.5%
Other values (211) 1033
59.1%
ASCII
ValueCountFrequency (%)
92
45.8%
( 54
26.9%
) 54
26.9%
2 1
 
0.5%
None
ValueCountFrequency (%)
㈜ 1
100.0%

주관기관
Text

Distinct154
Distinct (%)79.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-12T10:22:21.333233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length10.005128
Min length4

Characters and Unicode

Total characters1951
Distinct characters226
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique129 ?
Unique (%)66.2%

Sample

1st row주식회사 리얼팜
2nd row고려동물병원
3rd row한국전자통신연구원
4th row농업회사법인 원스베리
5th row코스맥스바이오(주)
ValueCountFrequency (%)
산학협력단 49
 
17.1%
주식회사 22
 
7.7%
농업회사법인 7
 
2.4%
경북대학교 5
 
1.7%
서울대학교 5
 
1.7%
연세대학교 5
 
1.7%
전남대학교 4
 
1.4%
건국대학교 3
 
1.0%
한국전자통신연구원 3
 
1.0%
순천대학교 3
 
1.0%
Other values (159) 181
63.1%
2023-12-12T10:22:21.849446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 140
 
7.2%
92
 
4.7%
산 77
 
3.9%
주 77
 
3.9%
협 67
 
3.4%
대 66
 
3.4%
단 66
 
3.4%
력 63
 
3.2%
교 63
 
3.2%
( 54
 
2.8%
Other values (216) 1186
60.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1749
89.6%
Space Separator 92
 
4.7%
Open Punctuation 54
 
2.8%
Close Punctuation 54
 
2.8%
Other Symbol 1
 
0.1%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 140
 
8.0%
산 77
 
4.4%
주 77
 
4.4%
협 67
 
3.8%
대 66
 
3.8%
단 66
 
3.8%
력 63
 
3.6%
교 63
 
3.6%
원 53
 
3.0%
사 44
 
2.5%
Other values (211) 1033
59.1%
Space Separator
ValueCountFrequency (%)
92
100.0%
Open Punctuation
ValueCountFrequency (%)
( 54
100.0%
Close Punctuation
ValueCountFrequency (%)
) 54
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1750
89.7%
Common 201
 
10.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 140
 
8.0%
산 77
 
4.4%
주 77
 
4.4%
협 67
 
3.8%
대 66
 
3.8%
단 66
 
3.8%
력 63
 
3.6%
교 63
 
3.6%
원 53
 
3.0%
사 44
 
2.5%
Other values (212) 1034
59.1%
Common
ValueCountFrequency (%)
92
45.8%
( 54
26.9%
) 54
26.9%
2 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1749
89.6%
ASCII 201
 
10.3%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 140
 
8.0%
산 77
 
4.4%
주 77
 
4.4%
협 67
 
3.8%
대 66
 
3.8%
단 66
 
3.8%
력 63
 
3.6%
교 63
 
3.6%
원 53
 
3.0%
사 44
 
2.5%
Other values (211) 1033
59.1%
ASCII
ValueCountFrequency (%)
92
45.8%
( 54
26.9%
) 54
26.9%
2 1
 
0.5%
None
ValueCountFrequency (%)
㈜ 1
100.0%

총연구기관 시작일
Date

Distinct15
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
Minimum2017-04-21 00:00:00
Maximum2021-04-07 00:00:00
2023-12-12T10:22:21.993605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:22:22.147475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)

총연구기간 종료일
Date

Distinct10
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
Minimum2021-12-31 00:00:00
Maximum2024-12-31 00:00:00
2023-12-12T10:22:22.316246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:22:22.523628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)

당해년연구기간 시작일
Date

Distinct8
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
Minimum2021-01-01 00:00:00
Maximum2021-07-01 00:00:00
2023-12-12T10:22:22.670508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:22:22.863067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)

당해년연구기간 종료일
Date

Distinct9
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
Minimum2021-12-31 00:00:00
Maximum2023-12-31 00:00:00
2023-12-12T10:22:23.042468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:22:23.202201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)

총연구비
Real number (ℝ)

Distinct119
Distinct (%)61.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7369181 × 108
Minimum26700000
Maximum8.716 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-12T10:22:23.376745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum26700000
5-th percentile45805000
Q184875000
median1.333 × 108
Q32 × 108
95-th percentile4.63656 × 108
Maximum8.716 × 108
Range8.449 × 108
Interquartile range (IQR)1.15125 × 108

Descriptive statistics

Standard deviation1.4506747 × 108
Coefficient of variation (CV)0.83520041
Kurtosis6.758038
Mean1.7369181 × 108
Median Absolute Deviation (MAD)57300000
Skewness2.3579652
Sum3.3869903 × 1010
Variance2.1044571 × 1016
MonotonicityNot monotonic
2023-12-12T10:22:23.559764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100000000 16
 
8.2%
200000000 10
 
5.1%
50000000 8
 
4.1%
120000000 5
 
2.6%
80000000 5
 
2.6%
70000000 4
 
2.1%
300000000 4
 
2.1%
150000000 4
 
2.1%
60000000 4
 
2.1%
90000000 4
 
2.1%
Other values (109) 131
67.2%
ValueCountFrequency (%)
26700000 1
 
0.5%
30000000 1
 
0.5%
33500000 1
 
0.5%
40000000 2
 
1.0%
42700000 1
 
0.5%
45000000 3
 
1.5%
45350000 1
 
0.5%
46000000 1
 
0.5%
50000000 8
4.1%
54750000 1
 
0.5%
ValueCountFrequency (%)
871600000 1
0.5%
867000000 1
0.5%
750000000 1
0.5%
685000000 1
0.5%
600000000 1
0.5%
562500000 1
0.5%
560000000 1
0.5%
555000000 1
0.5%
546667000 1
0.5%
500000000 1
0.5%

Interactions

2023-12-12T10:22:15.825103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:22:15.640192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:22:15.924283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:22:15.738890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:22:23.712792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호사업명총괄과제번호총연구기관 시작일총연구기간 종료일당해년연구기간 시작일당해년연구기간 종료일총연구비
번호1.0000.9520.9970.8670.8700.7440.5560.470
사업명0.9521.0000.9990.9710.9620.9430.8770.223
총괄과제번호0.9970.9991.0001.0001.0000.9960.9590.000
총연구기관 시작일0.8670.9711.0001.0000.9760.9850.9230.457
총연구기간 종료일0.8700.9621.0000.9761.0000.9680.9360.498
당해년연구기간 시작일0.7440.9430.9960.9850.9681.0000.9360.305
당해년연구기간 종료일0.5560.8770.9590.9230.9360.9361.0000.282
총연구비0.4700.2230.0000.4570.4980.3050.2821.000
2023-12-12T10:22:23.892449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호총연구비사업명
번호1.000-0.2070.746
총연구비-0.2071.0000.077
사업명0.7460.0771.000

Missing values

2023-12-12T10:22:16.048623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:22:16.243405image/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
01농림식품 융복합ICT융복합시스템119079-4119079043SB010가축 스마트 진료를 위한 데이터 수집 시스템 구축주식회사 리얼팜주식회사 리얼팜2019-08-302022-12-312021-01-012021-12-31122004000
12농림식품 융복합ICT융복합시스템119079-4119079043HD020빅데이터 기반 가축 스마트 진료 시스템 개발고려동물병원고려동물병원2019-08-302022-12-312021-01-012021-12-3164663000
23농림식품 융복합ICT융복합시스템317015-6317015065SB010농축산 ICT 기자재 표준 기술 개발한국전자통신연구원한국전자통신연구원2017-04-212022-12-312021-01-012021-12-31300000000
34농림식품 융복합ICT융복합시스템317018-5317018055SB010인삼의 최적 생육환경 조성을 위한 ICT 융복합 첨단 재배관리시스템 개발농업회사법인 원스베리농업회사법인 원스베리2017-04-212021-12-312021-01-012021-12-31210000000
45농림식품 융복합공공기술 사업화 촉진821008-3821008031SB010글로벌 선도 국내자생 금불초복합추출물의 체지방 감소 소재 및 건강기능식품 산업화코스맥스바이오(주)코스맥스바이오(주)2021-04-012023-12-312021-04-012021-12-31305000000
56농림식품 융복합공공기술 사업화 촉진821008-3821008031HD020금불초복합추출물의 체지방감소 기전 및 표준화 연구경희대학교산학협력단경희대학교산학협력단2021-04-012023-12-312021-04-012021-12-31120000000
67농림식품 융복합공공기술 사업화 촉진821021-3821021031HD020국내 야생 돌콩을 활용한 근육노화 및 노화 억제 건강기능식품 기능성 원료 및 제품 개발(주)유니베라(주)유니베라2021-04-012023-12-312021-04-012021-12-31135000000
78농림식품 융복합공공기술 사업화 촉진821021-3821021031SB010국내 야생 돌콩을 활용한 근육노화 및 노화 억제 건강기능성제품 사업화한국한의학연구원한국한의학연구원2021-04-012023-12-312021-04-012021-12-31165000000
89농림식품 융복합공공기술 사업화 촉진821023-3821023031HD020매실 기능성분 함량증가 고부가가치 원료 및 제품 사업화바이오파마바이오파마2021-04-012023-12-312021-04-012021-12-31156000000
910농림식품 융복합공공기술 사업화 촉진821023-3821023031SB010매실 기능성분 함량증가 가공기술 활용 고부가가치 원료 및 제품 사업화한국한의학연구원한국한의학연구원2021-04-012023-12-312021-04-012021-12-3168000000
번호분류사업명총괄과제번호세부과제번호과제명연구수행기관주관기관총연구기관 시작일총연구기간 종료일당해년연구기간 시작일당해년연구기간 종료일총연구비
185186농림식품 융복합진단기술산업화321104-3321104031HD020바이오센서 기반 식물 바이러스 검출을 위한 정밀 현장진단용 기기 개발(주)넥스바이오(주)넥스바이오2021-04-012023-12-312021-04-012021-12-31120000000
186187농림식품 융복합천연안심소재 산업화119023-3119023033SB010자근 복합 추출물을 이용한 천연 보존료 개발세명대학교 산학협력단세명대학교 산학협력단2019-05-202021-12-312021-01-012021-12-3145000000
187188농림식품 융복합천연안심소재 산업화119023-3119023033HD040안정성 시험 및 제조공정 최적화(주)다정(주)다정2019-05-202021-12-312021-01-012021-12-31213000000
188189농림식품 융복합천연안심소재 산업화119034-3119034033SB010곤충 오일의 기능성 탐색 및 고부가가치 제품개발(주)글로벌허브(주)글로벌허브2019-05-202021-12-312021-01-012021-12-31133300000
189190농림식품 융복합천연안심소재 산업화119034-3119034033HD030곤충오일의 항균효능평가 및 제품규격 개발영남대학교산학협력단영남대학교산학협력단2019-05-202021-12-312021-01-012021-12-3176000000
190191농림식품 융복합천연안심소재 산업화319047-3319047033HD020버섯을 활용한 천연 비타민 D 소재 개발경성대학교 산학협력단경성대학교 산학협력단2019-05-202022-06-302021-07-012022-06-3080000000
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